International Journal of Euro-Mediterranean Studies issn 1855-3362 (printed) issn 2232-6022 (online) The aim of the International Journal of Euro-Mediterranean Studies is to promote intercultural dialogue and exchanges between societies, develop human resources, and to assure greater mutual understanding in the Euro-Mediterranean region. L’objectif de la revue internationale d’etudes Euro-Méditerranéennes est de promouvoir le dialogue interculturel et les échanges entre les sociétés, développer les ressources humaines et assurer une compréhension mutuelle de qualité au sein de la région euro-méditerranéenne. Namen Mednarodne revije za evro­mediteranske študije je spodbujanje medkulturnega dialoga in izmenjav, razvoj cloveških virov in zagotavljanje boljšega medsebojnega razumevanja v evro-mediteranski regiji. ijems is indexed in Scopus, International Bibliography of the Social Sciences, Directory of Open Access Journals, Index Islamicus, oclc, and Summon by Serial Solutions. editor-in-chief Jaka Vadnjal, Euro-Mediterranean University, Slovenia, editor.ijems@emuni.si associate editors Barbara Gornik, Science and Research Centre Koper, Slovenia Karim Moustagh.r, Al Akhawayn University, Morocco Chahir Zaki, Cairo University, Egypt editorial advisory board Abeer Refky, Arab Academy for Science, Technology and Maritime Transport, Egypt Francesco Martinico, University of Catania, Italy Mona Esam Othman Fayed, University of Cairo, Egypt Claudio Cressati, University of Udine, Italy Lola Bañon Castellón, University of Valencia, Spain Nataša Uroševic, Juraj Dobrila University of Pula, Croatia Boštjan Udovic, University of Ljubljana, Slovenia Maysoun Ibrahim, Palestinian Syndicate for Information Sciences and Technology, Palestine Péter Kacziba, University of Pécs, Hungary Lot. Ben Romdhane, University of Sousse, Tunisia Mejjad Nezha, UniversityHassan ii of Casablanca, Morocco International Journal of Euro-Mediterranean Studies Table of Contents 5 Interdisciplinary Perspectives on Sustainability, Development, and Culture in the Mediterranean and Beyond Jaka Vadnjal 9 Musicians, as an Important Building Block of Mediterranean Rural Tourism Aleksandra Govedarica, Nataša Kraljevic, Darko Lacmanovic, Urša Lamut, Predrag Ljubotina, Andrej Raspor, Bojan Rojko, and Ajda Srdic 31 How Do Serbian Gymnastics Coaches Make Decisions? Edvard Kolar, Saša Velickovic, Rado Pišot, Marijo Možnik, and Matej Tušak 53 Knowledge Management Index for Better Climate Change Management: A Case Study in the Egyptian Petroleum Sector Aly A. Ahmed, Mohamed Shaltout, Mohamed Salaheldin, and Ahmed Elshazly 83 Post-Crisis Analysis of Media Consumption and Perceptions of the covid-19 Pandemic: A Study of Moroccan Youth in Urban Areas Anoire El Attari, Hind Belaziz, Abderrahman Tenkoul, and Nouhaila Bourass 103 Economic Integration of Mediterranean States Janez Fabijan, Jaka Vadnjal, and Draško Veselinovic 129 Résumés 133 Povzetki 137 ã information for authors Manuscripts are accepted on the understanding that they are original and not under simultaneous consideration by any other publication. Submitted manuscripts may be subject to checks in order to detect instances of plagiarism. All manuscripts are double-blind peer reviewed. Manuscripts should be prepared following The Chicago Manual of Style. For submissions and detailed instructions about the style and content of papers, please see https://ijems.emuni.si. copyright notice The International Journal of Euro-Mediterranean Studies is an Open Access Journal distributed under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License. Copyright for all articles published in ijems is held by individual authors. No author fees are charged. published by Euro-Mediterranean University Trevisini Palace Kidricevo nabrežje 2 si-6330 Piran, Slovenia https://ijems.emuni.si ijems@emuni.si Print run: 200. Printed in Slovenia by Gra.ka 3000, Dob Mednarodna revija za evro-mediteranske študije je namenjena mednarodni znanstveni in strokovni javnosti; izhaja v anglešcini s povzetki v slovenšcini, francošcini in arabšcini. Izid je .nancno podprla Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije iz sredstev državnega proracuna iz naslova razpisa za so.nanciranje domacih znanstvenih periodicnih publikacij. Revija je brezplacna. ijems | editorial Interdisciplinary Perspectives on Sustainability, Development, and Culture in the Mediterranean and Beyond jaka vadnjal Euro-Mediterranean University, Slovenia jaka.vadnjal@emuni.si © 2024 Jaka Vadnjal https://doi.org/10.70908/2232-6022/18.5-7 The Mediterranean region, with its rich cultural tapestry and diverse socio-economic dynamics, continues to provide fertile ground for inter­disciplinary academic inquiry. In this issue of our International Jour­nal of Euro-Mediterranean Studies, we are pleased to present a collec­tion of six papers that each contribute unique insights into the press­ing challenges and opportunities facing Mediterranean societies today. Ranging from rural tourism and climate change to urban .ood man­agement and post-pandemic media consumption, these articles re.ect the breadth of inquiry necessary to understand and shape the region’s future. culture and tourism: music as a rural catalyst The paper by Govedarica et al. explores an overlooked dimension of ru­ral tourism: the role of musicians as cultural agents and drivers of re­gional development. By positioning musicians not just as entertainers but as integral parts of local identity and economic revitalization, this research stimulates the discourse on cultural tourism. In the context of Mediterranean rural areas, where depopulation and economic stagna­tion are common, this paper reveals how music and local cultural assets can become important tools for community building and sustainable tourism. The authors advocate for strategic integration of musicians into tourism development plans, urging policymakers to harness their cultural capital more e.ectively. sports decision-making: insights from serbian gymnastics From cultural tourism to athletic cognition, Kolar et al. delve into the realm of decision-making in sports, speci.cally analyzing how gymnas­ [6] tics coaches in Serbia navigate complex choices. This study provides critical insights into the cognitive and contextual factors that in.uence coaching strategies. It combines elements of psychology, pedagogy, and sports science to construct a picture of how high-stakes decisions are made in elite sport settings. Given the increasing professionalization of sports across the Mediterranean region, the paper contributes to an understanding of how knowledge, intuition, and experience intersect in high-performance environments. climate change and knowledge management in the petroleum sector The work of Ahmed Aly et al. shifts our attention to the industrial and environmental sphere, examining the Egyptian petroleum sector’s capacity for climate change management through a knowledge man­ agement lens. The authors develop a valuable framework for evalu­ ating how e.ectively organizations collect, share, and apply climate- related knowledge. By focusing on a high-emissions industry within a vulnerable region, the study presents both a diagnostic tool and a call to action. The .ndings emphasize the importance of embedding knowledge-driven sustainability strategies in corporate and govern­ mental frameworks, particularly in sectors with signi.cant environ­ mental footprints. youth, media, and post-pandemic recovery in morocco The Covid-19 pandemic has left deep psychological and societal im­ prints, particularly among the youth. In their paper, El Attari et al. examine how Moroccan youth consumed media during and after the pandemic, o.ering a critical post-crisis analysis. Through surveys and behavioral data, the study highlights the change in media habits, per­ ceptions of information credibility, and broader societal anxieties. This work not only contributes to the global literature on after pandemic times but also highlights the unique cultural and informational land­ scape of North Africa. Policymakers and educators can draw from this research to develop more e.ective youth engagement and media liter­acy programs in the wake of future crises. economic integration:a mediterranean imperative [7] Finally, Fabian et al. tackle one of the most enduring challenges in the region: economic integration. The authors provide a thorough exami­nation of the barriers and opportunities for greater economic cooper­ation among Mediterranean states. From trade and infrastructure to regulatory harmonization, the paper argues that deeper economic in­tegration is not just bene.cial but essential for the region’s stability and prosperity. By comparing di.erent integration models and examining case studies, the authors present a persuasive case for renewed political commitment to regional cooperation in an era marked by geopolitical uncertainty and economic fragmentation. conclusion: toward a holistic vision Collectively, these papers underscore the importance of interdisci­plinary approaches in addressing the Mediterranean region’s complex challenges. They invite us to consider how cultural identity, scienti.c innovation, governance, and regional solidarity intersect in shaping resilient futures. As editors, we are proud to host these important con­tributions and hope they inspire further research and collaboration across disciplinary and national borders. ijems | scientific article Musicians, as an Important Building Block of Mediterranean Rural Tourism aleksandra govedarica Mediterranean University, Montenegro alexgovedarica@gmail.com nataša kraljevi. Mediterranean University, Montenegro natasa.kraljevic@unimediteran.net darko lacmanovi. Mediterranean University, Montenegro darko.lacmanovic@unimediteran.net urša lamut Rudolfovo – Science and Technology Centre Novo mesto, Slovenia lamut.ursa@gmail.com predrag ljubotina School of Advanced Social Studies in Nova Gorica, Slovenia predrag.ljubotina@gmail.com andrej raspor School of Advanced Social Studies in Nova Gorica, Slovenia andrej.raspor@fuds.si bojan rojko School of Advanced Social Studies in Nova Gorica, Slovenia bojan.rojko@agencija-antonov.si ajda srdi. School of Advanced Social Studies in Nova Gorica, Slovenia ajda.srdic@gmail.com This paper looks into the signi.cant role of musicians in improving rural tourism o.erings. Rural tourism is one of the main pillars of economic development and cultural preservation as it is a tool that provides jobs, improves the local quality of life, and supports the ren­ovation of historic sites. Through their creativity, musicians safeguard and spread intangible cultural heritage, such as traditional music and dance, which positively in.uences the .nancial performance of ru­ral tourism entrepreneurs. Music festivals and events in the country­side are also a great source of rural tourism. They bring in substantial revenue and help form a favorable image of the destination. Events in less-favored areas have attracted visitors by diversifying tourism o.erings and encouraging regional development. Despite this, their success is contingent upon good planning and proper organisation. This study investigates the in.uences of factors such as state support, proactivity, job satisfaction, luck, and personality traits on the success and development of musicians in Mediterranean countries, speci.­cally in Slovenia and Montenegro. It has been revealed that includ­ing cultural resources into tourism strategies makes rural areas more attractive and competitive. Empirical studies on rural tourism indi­cate that musicians contribute signi.cantly to cultural tourism by at­tracting visitors, preserving local heritage, and stimulating economic growth, thereby supporting the sustainable development of rural areas. [10] Key Words: musicians, rural tourism, Mediterranean region, state support, self-con.dence © 2024 Aleksandra Govedarica, Nataša Kraljevic, Darko Lacmanovic, Urša Lamut, Predrag Ljubotina, Andrej Raspor, Bojan Rojko, and Ajda Srdic https://doi.org/10.70908/2232-6022/18.9-29 introduction This paper aims to determine the importance of the musician’s role in building the o.er in a rural tourism destination. Rural tourism has become essential for economic growth and cultural preservation in many areas. It generates employment, improves the quality of life for local population and fosters the restoration and surveillance of historic places. Among the various factors that make rural places attractive, mu­ sicians and folk music deserve a unique position. They play a critical role in de.ning the identity of rural areas, which become more appealing to tourists in search of authentic and immersive experiences. Musicians, in fact, by their art and performances, contribute to both preserving and propagating intangible cultural heritage, such as tradi­tional music or dance. This cultural diversity can dramatically impact the .nancial performance of rural tourism entrepreneurs by attracting a broader variety of tourists. Traditional music is an important start in rural tourism development, as it provides creative and engaging ser­vices that fundamentally improve the competitive advantage of rural areas. This is why music festivals and events play a signi.cant role in rural tourism. Not only do they comprise a large portion of revenue through tourists spending on accommodation, food, and transportation, but they also help to create a good image of the destination. They are also e.ective instruments for regional development, attracting tourists to otherwise less popular regions and adding to tourism product variety. However, the outcome of such events depends on musician’s readiness to cooperate and their level of proactivity. Therefore, musicians are one of the essential backbones of rural tourism o.erings. They provide a rich cultural experience that makes a di.erence in providing tourism products and, therefore, helps the sus­tainable development of rural areas. Their contribution to rural tourism draws attention to the need to embed cultural assets into tourism plans to increase the attractiveness and competitiveness of rural destina­tions. [11] theoretical background Tourism has emerged as one of the largest and fastest-growing eco­nomic sectors globally, contributing signi.cantly to international trade and employment (Croce 2018; Lew 2011; Agbola et al. 2020). Despite its economic importance, tourism faces challenges related to sustainabil­ity, inclusivity, and climate change (Croce 2018; Moreno de la Santa 2020; Scott et al. 2012). The industry’s growth has led to increased recognition of its potential to foster economic development and al­leviate poverty, particularly in developing countries (Saarinen et al. 2011). However, tourism’s vulnerability to external factors, such as the covid-19 pandemic, highlights the need to understand demand drivers and practical strategies better (Agbola et al. 2020). As the sector continues to expand, there is a growing emphasis on mitigating nega­tive impacts and promoting sustainable practices (Croce 2018; Willson 2015). Researchers caution against overgeneralising tourism’s bene.ts and impacts, emphasizing the need for more nuanced approaches to address its complex challenges (Sharpley 2012). Rural tourism o.ers signi.cant economic development and cultural preservation opportunities in rural areas. It can create jobs, improve the local quality of life, and support the restoration of historic sites (Corina 2018). Musicians and traditional music play a crucial role in rural tourism o.erings, contributing to the distinctiveness of desti­nations (Rudan and Stipanovic 2021). Intangible cultural heritage, in­cluding music and dance, can positively in.uence the .nancial results for rural tourism entrepreneurs (Starcevic et al. 2022). Tradition, en­compassing music, dance, and local cuisine, is a key initiator of rural tourism development (Antic et al. 2015). Rural tourism can strengthen the competitive position of destinations through creative o.erings and private-sector involvement (Gannon 1994). It has the potential to build economic independence for rural communities, as evidenced by the suc­cess of tourist villagesinother regions(Maretetal. 2018; Triyantoet al. 2018). The inclusion of music industry o.erings can be leveraged to design cultural experiences for demanding tourists (Vaz et al. 2017). In both developed and developing countries, tourism is frequently supposed to be a viable means of raising the economic activity of re­gions. Additionally, developing a tourism industry has been noted to promote the destination’s image, enabling the region to achieve other [12] objectives, such as business recruitment and retention. Music festivals and events signi.cantly impact tourism, particularly in rural and lesser-known destinations. This is especially typical for re­gions with a rich cultural tradition, which certainly includes Mediter­ranean countries. Music events can boost local economies by generat­ing revenue through tourist expenditure on accommodation, food, and transportation (Baldi et al. 2022; Cekrlija and Milic 2024). They also contribute to destination image formation and place-making (Duarte et al. 2018). Music tourism can lead to cultural changes, a.ecting local musicians and traditions (Basu and Imara 2014; Stipanovic et al. 2023). Festivals serve as key tools for regional development, attracting visi­tors to less-favoured areas and diversifying tourism o.erings (Ribeiro et al. 2006). These events not only have economic impacts, but also bring social, cultural, and political implications for host communities (Dujmovic and Vitasovic 2012). However, the success of music events in promoting tourism depends on strategic planning, organization and the willingness of musicians to contribute (Cekrlija and Milic 2024). Based on the introduction provided, the following research question could be formulated: How do factors such as state support, job satis­faction, luck, and personality traits (self-con.dence, subjective norms, internal locus of control) in.uence the proactivity of musicians and, consequently, their readiness to be involved in the growth of rural mu­sic tourism in Mediterranean countries like Slovenia and Montenegro? hypotheses development Rural tourism has become an increasingly important regional develop­ ment and re-imaging strategy in Mediterranean countries, particularly as they face global rural restructuring challenges (Hall and Mitchell 2000). Previous research has mentioned music as one of the traditional elements that can attract tourists to rural areas, alongside dance, cloth­ ing, and culinary specialties (Antic et al. 2015). Integrating cultural re­ sources, including traditional music, into rural tourism o.erings can enhance the appeal of destinations and contribute to rural revitaliza­ tion (Wang 2023). However, rural tourism development still involves a complex interplay of various factors, including natural beauty, lo­ cal traditions, and government policies (Antic et al. 2015; Wang 2023). It’s important to recognize that while rural tourism can provide op­portunities for economic development and job creation in rural areas, also it also presents challenges and potential adverse impacts (Boz et al. 2018; Saarinen 2007). Sustainable rural tourism development requires [13] careful planning and consideration of economic, social, and environ­mental factors (Boz et al. 2018; Fun et al. 2014). The interplay between state support, proactivity, luck, and work sat­isfaction creates a complex environment for Mediterranean musicians. While state support provides opportunities and resources, individual proactivity remains crucial for career advancement. The cultural un­derstanding of luck and fortune adds another layer to this dynamic, potentially in.uencing how musicians perceive and pursue opportu­nities. Job satisfaction, especially when combined with a supportive work-family culture, can help sustain proactive behaviors and commit­ment to one’s musical career despite challenges and uncertainties. State support for the music industry varies across Mediterranean countries, with some nations recognizing its potential as both cultural and economic asset. A recent study in Kosovo found that the art and music sector has shown considerable growth potential, contributing to the country’s cultural and economic environment by providing employ­ment opportunities (Breznica et al. 2024). The Kosovan music scene encompasses various genres, from traditional folk music to modern styles, catering to both local and global preferences. Slovenia and Mon­tenegro share a recent past with Kosovo, so we derived hypotheses h1 and h2 based on these .ndings. h1 The level of perceived state support di.ers between the ob­served regions h1a Ahigherlevelofperceivedstatesupportleadstoahigherlevel of proactivity Proactivity plays a signi.cant role in the success of musicians in Mediterranean countries. Research by Smale et al. (2019) has shown that proactive career behaviours, such as self-promotion, network­ing, and continuous skill development, positively correlate with mu­sicians’ subjective .nancial success, as measured by income stability, career satisfaction, and professional opportunities (Smale et al. 2019). Proactivity emerges as a crucial trait for musicians and entrepreneurs in Mediterranean countries, particularly during economic crises, as it enables adaptability, opportunity recognition, and .nancial resilience (Toubes et al. 2019). However, the relationship between proactivity and work-life balance is more complex. Interestingly, the bene.ts of career proactivity may vary across cultures, with factors such as in-group col­ [14] lectivism, power distance, and uncertainty avoidance in.uencing the outcomes (Smale et al. 2019). The concept of luck and fortune also plays a role in the social imagination of Mediterranean musicians. Anthro­pological studies have highlighted how idioms of luck and fortune can connect humans, potentially in.uencing the perceived success of mu­sicians (da Col 2012). This understanding of luck may interact with proactive behaviours, shaping how musicians approach their careers and interpret their successes or failures. On this basis, we set our hy­potheses h2, h3 and h4. h2 The percentage of income from the music industry di.ers be­tween the observed regions h2a A higher percentage of income from the music industry leads to a higher level of proactivity h3 The level of perceived luck di.ers across the observed regions h3a Ahigherlevelofperceivedluckisassociatedwithahigherlevel of proactivity Work satisfaction is another crucial factor that in.uences musi­cians. Research has shown that job satisfaction can be a motivational resource for maintaining high levels of proactivity over time (Strauss et al. 2015). Additionally, a supportive work-family culture has been associated with less work-family con.ict, greater job satisfaction, and greater a.ective commitment (de Janasz et al. 2013). Balancing their artistic pursuits with family responsibilities may be particularly im­portant for musicians in the Mediterranean region, given the cultural emphasis on family in many of these countries. On this basis, we set our hypothesis h5. h4 The level of work satisfaction di.ers between the observed re­gions h4a A higher level of work satisfaction leads to a higher level of proactivity Research on musicians’ personalities and cognitive pro.les has re­vealed interesting di.erences both among various groups of musicians and between musicians and non-musicians. These di.erences extend factors such as subjective norms, self-con.dence, and locus of control, which can vary based on factors such as musical training, instrument type, and cultural background. Subjective norms among musicians are also in.uenced by the type of musical training they receive. For in­stance, Rose et al. (2018) suggest that formal music learning is asso-[15] ciated with higher levels of conscientiousness, while musicians, in gen­eral, tend to have higher levels of openness to experience compared to population norms. Research also indicates that the close environment may shape musicians’ perceptions of what is expected or valued within their musical community (Rose et al. 2019). Self-con.dence among musicians seems to be closely tied to their performance abilities and their perception of control over their skills. Hanton and Connaughton (2002) highlight that perceived control is a crucial moderating factor in how musicians interpret anxiety symp­toms and their impact on performance. When musicians feel in con­trol of their symptoms, they tend to interpret them as facilitative for performance, leading to increased self-con.dence. Conversely, a lack of perceived control can result in debilitative e.ects on performance and lower self-con.dence (Hanton and Connaughton 2002). The locus of control among musicians may di.er based on their musical back­ground, expertise and cultural environment. Agres et al. (2022) suggest that musicians are more sensitive to the dynamic and schematic prop­erties of musical stimuli than non-musicians. This heightened sensi­tivity could indicate a more internal locus of control, as musicians may feel more capable of understanding and manipulating musical elements (Agres et al. 2022). Additionally, Por.itt and Rosas (2020) reveal that di.erent types of musicians (rhythmic, melodic, and harmonic) exhibit varying cognitive performances, which could in.uence their perception of control over their musical abilities (Por.itt and Rosas 2020). While the available research does not explicitly address regional di.erences in these aspects, it is reasonable to assume that cultural factors and lo­cal environment may contribute to variations in subjective norms, self-con.dence, and locus of control among musicians in di.erent regions. On this basis, we believe it makes sense to include personality fac­tors into our research model and to explore these potential regional di.erences and their implications. h5 The level of perceived self-con.dence di.ers between the ob­served regions h5a A higher level of perceived self-con.dence leads to a higher level of proactivity h6 The level of perceived subjective norms di.ers between the ob­served regions [16] h6a A higher level of perceived subjective norms leads to a higher level of proactivity h7 The level of internal locus of control di.ers between the ob­served regions h7a A higher-level internal locus of control is associated with a higher level of proactivity methodology and results To test the hypotheses, we collected data in Slovenia and Montenegro in 2023. In both cases, the population consists of musicians in the ob­served region, which was in 2023. The data were collected using an on-line survey questionnaire and with the help of regional musicians’ as­sociations. The values of the variables were compared using the t-test between independent samples. To test the assumed dependence relations, we set up a linear regression model for each region separately to test the hypotheses in each region. In this way, we also enabled the comparison of regression coe.cients between the observed regions. The gender composition of the sample is comparable in both re­gions. in both cases, the sample is approximately two-thirds male and 1/3 female. Table 1 also shows the regional composition of the sample, namely by age, years of activity in the music industry and the percent­age of personal revenue that comes from the music industry. The sam­ple size is appropriate if we note that the Montenegro sample is small but still su.cient to meet the minimum requirements for carrying out the planned analyses (Louangrath 2017). The dependent variable in our linear regression model is the indi­vidual’s proactivity level. We collected data using a 10-item Likert scale, which has been used and validated in previous research. Items are cap­tured on 7-step scale (Bateman and Crant 1993). For all independent variables, we also used previously used and validated scales. To measure the perceived level of state support, a 5­point six-item scale was used. The scale originates from the research on the perceived organizational support (Eisenberger et al. 2001). Self­ Musicians, as an Important Building Block table 1 Sample Frequencies Country Male Female Total n . n . n . Slovenia ... .... .. .... ... ..... Montenegro .. .... .. .... .. ..... [17] Total ... .... .. .... ... ..... Country Item n Mean sd Slovenia Age Years in music Percent of income ... ... ... ..... ..... ..... ..... ..... ..... Montenegro Age Years in music Percent of income .. .. .. ..... ..... ..... .... ..... ..... table 2 t-Test Results Item t Sig. Mean* Percent of incom from music ..... ..... ....... State support ..... ..... ....... Self con.dence –..... ..... –....... Proactivity –..... ..... –....... Subjective norms ..... ..... ....... Luck –..... ..... –....... Internal locus of control ..... ..... ....... Work satisfaction ..... ..... ....... notes *Slovenia-Montenegro. con.dence was measured with nine items on 5-point Likert scale previ­ously used in a study of private and public self-consciousness (Vleem­ingand Engelse1981).Subjectivenorms were captured with threeitems on 7-point scale based on a previous study of entrepreneurial programs in relation to students entrepreneurial intention after graduation (Lev­enson 1973; Souitaris et al. 2007). From the same study, we also used 4 items for measuring the inter­nal locus of control level which we supplemented with four additional items used in the research of multidimensional locus of control (Lev­enson 1973). Work satisfaction was captured with 5 item scale (Oyler 2007). To compare the two observed regions by individual variables, we Aleksandra Govedarica et al. table 3 Country-Level Variable Comparison: Hypotheses Con.rmation h Observed variable Con.rmed h. The level of perceived state support Yes h. The percentage of income from the music industry No [18] h. The level of perceived luck Yes h. The level of work satisfaction Yes h. The level of perceived self-con.dence Yes h. The level of perceived subjective norms No h. The level of internal locus of control No used the t-test of means of independent samples to test the hypothe­ses. The results of the t-test are summarized in table 2. We detected a statistically signi.cant di.erence between the two groups in perceived state support. Inthiscase, we detected avery highsigni.cance level (p = 0.000). Slovenian musicians perceive a higher level of state sup­port compared to their colleagues from Montenegro. Interestingly, in the case of self-con.dence, we detected an equally high statistically sig­ni.cant di.erence (p = 0.012), but in favour of Montenegrin musicians. Montenegrin musicians also attach greater importance to the lucky cir­cumstances necessary for successful operation in the music industry (p =0.040). Regarding job satisfaction, the detected statistically signi.cant dif­ference (p = 0.003) showed higher satisfaction among Slovenian mu­sicians. We did not detect statistically signi.cant di.erences between the two groups for the other observed factors. An overview of the con­.rmed hypotheses is given in table 3. We used a regression model to test the causal relationships between the independent variables presented in the introduction of this para­graph and musicians’ proactivity, which is the model’s dependent vari­able. We developed a regression model for each region separately to compare the two regions. The regression coe.cients are given in ta­ble 4. The results of the models show that only a few of the factors in­cluded a.ect the proactivity of music industry stakeholders. This is es­pecially true for Montenegro, where we detected a statistically signif­icant causal relationship only in the case of self-assessed level of self-con.dence (p = 0.043). All other factors do not have a statistically sig­ni.cant e.ect on the proactivity of Montenegrin musicians. The model Musicians, as an Important Building Block table 4 Regression Models Coe.cients Country Item B ß t Sig. Slovenia (Constant) ...... ..... ..... Percent of incom from music –..... –..... –..... ..... State –..... –..... –..... ..... [19] Self_con.dence ..... ..... ..... ..... Subj_norms –..... –..... –..... ..... Luck ..... ..... ..... ..... Locus ..... ..... ..... ..... Work_satisf ..... ..... ..... ..... Gend_F ..... ..... ..... ..... Montenegro (Constant) ...... ..... ..... Percent of incom from music –..... –..... –..... ..... State –..... –..... –..... ..... Self_con.dence ..... ..... ..... ..... Subj_norms ..... ..... ..... ..... Luck –..... –..... –..... ..... Locus ..... ..... ..... ..... Work_satisf ..... ..... ..... ..... Gend_F –..... –..... –..... ..... notes Dependent variable: proactivity. is quite good at the sample level, explaining 45.9. of the variance in proactivity in Slovenia and 53.5. in Montenegro. In Slovenia, proac­tivity is statistically signi.cantly a.ected by perceived state support (p = 0.049), level of self-con.dence (p = 0.000) and the level of internal locus of control of behaviour (p =0.004). It is worth mentioning that a higher level of perceived state sup­port leads to a lower level of individual proactivity. We believe such a result would require an in-depth analysis to explain the reasons. In any case, the result represents a good motive for future research. In both observed countries, self-con.dence stands out as the most potent fac­tor (slo ß =0.467 and mne ß =0.386). In addition to the independent variables, we included the respon­dent’s gender in the model as a control variable. The analysis showed that in Slovenia, female musicians are statistically signi.cantly more proactive than their male counterparts (p = 0.001). However, in Mon­tenegro, we did not detect statistically signi.cant di.erences between the genders. Table 5 gives an overview of the tested hypotheses. Aleksandra Govedarica et al. table 5 Country-Level Hypotheses Con.rmation h Independent variable Slovenia Montenegro h.a The level of perceived state support Yes No [20] h.a The percentage of income from the music industry h.a The level of perceived luck h.a The level of work satisfaction No No No No No No h.a The level of perceived self-con.dence h.a The level of perceived subjective norms Yes No Yes No h.a The level of internal locus of control Yes No notes Dependent variable: proactivity. discussion The research results show a strong connection with general theoretical positions, which can be summarized through a few facts. As a globally growing economic sector, rural tourism can strongly contribute to eco­nomic development and the preservation of cultural heritage in rural areas. Within these frameworks, the basis is formed by activities such as traditional music, dance, clothing, and culinary specialities (Guo et al. 2023). These activities signi.cantly contribute to the attractiveness of destinations and the revitalization of rural areas. Rural tourism also plays a key role in preserving cultural heritage, promoting sustainable development, and increasing economic oppor­tunities in rural areas. In this context, musicians represent an essential factor in developing tourism in rural areas. Mediterranean countries can undoubtedly use their rich cultural heritage to develop tourism in rural regions. Of course, the willingness of music industry stake­holders to participate in this project is of key importance for success­fully implementing this idea. Musicians are an essential part of the ru­ral tourism o.er, attracting visitors with their artistry and Mediter­ranean authenticity, and creating unique experiences. Branding that connects rural tourism and musical tradition strengthens the recogni­tion of regions and builds an emotional bond with visitors, encouraging tourism’s long-term development (Damnjanovic et al. 2009). To ensure readiness for cooperation, state support is needed. In this context, we found that Slovenian musicians recognize state support for their activity as an essential factor that encourages a higher level of proactivity. On the other hand, their Montenegrin colleagues on the other side of the Mediterranean do not perceive state support as an important factor. The perceived di.erence is worth in-depth consider­ation and analysis to uncover the underlying causes. The reason may lie in the possibly too low level of support for the music industry from the state so far. From this perspective, it would be bene.cial for state bodies responsible for developing rural tourism to place greater empha­sis on supporting the music industry and its participants. In doing so, [21] it is necessary to focus on the visibility of this support, as the musi­cians themselves must positively recognise it. Only in this case can we rightly expect a greater willingness for active cooperation among musi­cians. This conclusion is in line with the existing theory, as sustainable rural development can be achieved mainly through the integration of tourism and local cultural practices (Coros, et al. 2021; Kim and Jamal 2015). In addition to the above, previous studies emphasise the impor­tance of better governance for more successful tourism development in rural regions (Lane and Kastenholz 2015). Of course, we should not overlook the critical fact that the research found a negative correlation between the level of proactivity and per­ceived state support. This means that higher perceived support can also lead to lower stakeholder proactivity. From this perspective, we also be­lieve that further research is needed to identify the reasons for such results. This is consistent with the theoretical argument that proactiv­ity is essential for achieving success, even though there is limited sup­port. This result is consistent with research indicating that state sup­port can provide resources and opportunities, but individual proactiv­ity remains key to career advancement (Hall and Mitchell 2000; Wang 2023). The observation that proactivity was better predicted by self-con.­dence in both countries provides theoretical support to the assumption that self-con.dence is a crucial determinant of proactive behaviour. Several studies report that self-con.dence is related to perceptions of control over ability and performance, which, in turn, should facilitate proactiveness (Hanton and Connaughton 2002; Agres et al. 2022), and thus con.rms the speci.city of this within this body of research. When comparing the two observed Mediterranean regions, we detected a higher level of self-con.dence among Montenegrin musicians, which may also be a consequence of the previous .nding that they receive less support from the state and are thus more dependent on their abilities. The research results show that musicians in Montenegro attach greater importance to luck, which can shape their approach to their ca­reers and proactivity. This is an interesting .nding related to theoretical claims about the role of luck in the social imagination of musicians. Da Col, in his study, discovered that the cultural perception of the notion of luck is a potential explanatory factor in success and proactivity per­ception (da Col 2012). In light of this .nding, it is worth mentioning the [22] possibility that musicians in Montenegro attach greater signi.cance to luck than their Slovenian counterparts, possibly due to the lower level of state support for their activity. The research additionally found that musicians in Slovenia are more satis.ed with their jobs, which can contribute to their proactivity. How­ever, this factor was signi.cant only in Slovenia when tested with a re­gression model. Owing to the results of the studies, many authors have formulated in their research the conclusion that job satisfaction can be a motivational resource to sustain high levels of proactivity (Strauss et al. 2015; de Janasz et al. 2013), which emphasizes the signi.cance of the results obtained, since it is in agreement with the previously estab­lished relationship between job satisfaction and high levels of proactiv­ity in the music industry. Music plays a crucial role in enhancing rural tourism o.erings, par­ticularly through the valorisation of traditional and local music her­itage (Rudan and Stipanovic 2021; Krajnovic and Gortan-Carlin 2007). However, challenges arise from the commercialization of rural spaces and the potential loss of authentic cultural experiences (Wu 2017). Ad­ditional challenges lie in fully exploiting rural tourism potential, includ­ing the need to build trust, rebuild social capital, and integrate local communities into development processes (Demonja 2014; Quaranta et al. 2016a). Accordingly, educating the younger generation can undoubt­edly contribute to the further development of rural music tourism in Slovenia and Montenegro, as it re.ects the speci.c interest of the in­habitants in musical education in these regions. The Mediterranean cultural environment in Slovenia encourages students to join numer­ous musical groups of various genres during and after their studies (Plevnik et al. 2021), enhancing the local music scene and its appeal to visitors. This creates a unique synergy between musical tradition and tourism, supporting the sustainable development of rural areas. conclusion Rural tourism has emerged as an important driving factor in economic growth and cultural protection across the globe. Musicians, using their artistry and performing activities, contribute to rural regions’ distinc­tive cultural identity, which in turn makes regions more attractive to tourists seeking genuine and immersive experiences. This is especially important for regions with a rich cultural tradition, which certainly in­cludes Mediterranean countries. Rural tourism is a key driver of economic development, contribut-[23] ing to income diversi.cation, job creation, and cultural preservation. Studies indicate that it enhances local economies by promoting small businesses, reducing urban migration, and fostering sustainable re­source management (Dimitrijevic et al. 2022; Livandovschi 2022; Sert 2024). Rural tourism supports environmental conservation through ecotourism initiatives and incentivizes the protection of cultural her­itage. It contributes to preserving cultural heritage, natural resources, and traditional crafts (Sert 2024; Tola et al. 2024). Community involve­ment is crucial for successful rural tourism development, as it fosters a deeper understanding of local challenges and promotes innovative solutions (Kuqi et al. 2019). Rural tourism bene.ts both tourists and host communities, improving infrastructure and quality. However, in­adequate infrastructure, seasonal demand .uctuations, and environ­mental degradation require strategic policy interventions life (Slusar­iuc 2018; Tola et al. 2024). Our analysis shows that several determinants, such as state assis­tance, self-e.cacy, job satisfaction, and cultural variations, shape mu­sicians’ proactivity. Although state funding is critical, it should be struc­tured to encourage musicians’ autonomy and creativity without fos­tering excessivedependence on subsidies. Self-con.dence among mu­sicians was identi.ed as one of the main determinants of proactivity in both observed regions. The study also highlights the need to support an understanding of cultural nuances. Rural tourism has become a cornerstone of economic growth and cultural heritage in many Mediterranean areas. Musicians are, moreover, critical actors in the construction of the distinctive cul­tural identity of rural Mediterranean communities via their perfor­mance/artistic practices. Hence, rural communities have become in­creasingly desirable tourist destinations that display authenticity and immersive experiences. This study emphasises the role of managing critical motivational factors, with the goal of raising the musician’s proactivity levels. The research shows that some background variables a.ecting musi­cians’ proactivity are state support, self-e.cacy, job satisfaction, and cultural variability. State aid is, of course, crucial, but it should be de­signed to encourage engagement with the arts by musicians in a way that does lead to excessive dependence on such support. Notably, self-con.dence emerged as the most decisive factor in.uencing proactivity [24] among musicians, underscoring the need for self-con.dence training and professional development workshops. In general, the paper contributes to the sustainable regional devel­opment of Mediterranean rural areas by providing insights into some of the variables driving musicians’ initiative and music tourism de­velopment. The .ndings can be applied to enhance the music indus­try and rural tourism o.erings in Slovenia, Montenegro, and other Mediterranean regions. This would ultimately improve the appeal of rural destinations while promoting economic development, cultural preservation, and the development of proactive skills in musicians through education. In addition, it draws attention to the importance of more sophisticated support structures for musicians and more robust approaches for creating rural music tourism. The study’s limitations include the small sample size in Montene­gro, which may a.ect the general validity of the .ndings, and the geo­graphical limitation to only two Mediterranean countries, which makes it di.cult to generalize to wider regions. Self-reporting scales may in­troduce bias, while the time frame, which is limited to 2023, does not allow for insight into long-term trends. In addition, the study does not include a wider range of factors, such as cultural di.erences or .nancial barriers, limiting the results’ comprehensiveness. For further research, we suggest including a wider geographical area and additional factors such as cultural di.erences, .nancial barriers and the impact of digitalization, which would allow for a more compre­hensive analysis. Additionally, long-term studies and the use of quali­tative methods would contribute to a deeper understanding of the dy­namic factors that in.uence musicians’ proactivity and the develop­ment of music tourism. references Agbola,F.W., T. Dogru, andU. Gunter. 2020a. ‘Tourism Demand: Emerging Theoretical and Empirical Issues.’ Tourism Economics 26 (8): 1307–10. Agres, K.,T.Y.Tay,and M. Pearce.2022. ‘Comparing Musiciansand Non-Musicians’ Expectations in Music and Vision.’ In acm International Conference Proceeding Series, 74–9. Association for Computing Ma­chinery. Antic, A.,A.Vujko, and T. Gajic. 2015. ‘Tradition as an Initiator of Rural Tourism Destinations Development.’ Škola biznisa 2(12): 9–20. Baldi, L., M. Peri, G. Baldi, and M. T. Trentinaglia. 2022. ‘Economic Im­ [25] pact of an International Musical Event in a Small Destination: What Bene.ts for Local and Rural Development?’ Event Management 26 (2): 419–36. Basu,R., andM.Imara.2014. ‘Fromthe PerspectiveofMusicians in Goa: How Has Tourism Changed Music Culture?’ Journal of Tourism and Hospitality Management 2 (9): 343–56. Bateman, T. S., and J. M. Crant. 1993. ‘The Proactive Component of Or­ganizational Behavior: A Measure and Correlates.’ Journal of Organi­zational Behavior 14 (2): 103–18. Boz, I., O. Kilic, and C. Kaynakci. 2018. ‘Rural Tourism Contributions to Rural Development in the Eastern Black Sea Region of Turkey.’ International Journal of Scienti.c Research and Management 6(4): ah­2018. Breznica, R. K., B. Luzha, F. G. Rexhepi, and B. R. Rexhepi. 2024. ‘An Analysis of The Economic Impact Potential of The Art Music Scene in Kosovo: Is It a Burden or An Additional Value for Society?’ Inter­national Journal of Religion 5 (5): 460–74. Cekrlija, S., and Z. Milic. 2024. ‘The Signi.cance of Tourist Consump­tion from the Perspective of Organizing Music Festivals.’ Science In­ternational Journal 3 (1): 133–7. Col, G. da. 2012. ‘Introduction: Natural Philosophies of Fortune-Luck, Vitality, and Uncontrolled Relatedness.’ Social Analysis 56 (1): 1–23. Corina, S. G. 2018. ‘Rural Tourism an Opportunity for Sustenable De­velopment.’ Ovidius University Annals: Economic Sciences Series 18 (2): 349–53. Coros, , M. M., D. Privitera, L. M. Paunescu, A. Nedelcu, C. Lupu, and A. Ganus, ceac. 2021. ‘Marginimea Sibiului Tells Its Story: Sustainabil­ity, Cultural Heritage and Rural Tourism; A Supply-Side Perspective.’ Sustainability (Switzerland) 13 (9): 5309. Croce, V. 2018. ‘With Growth Comes Accountability: Could a Leisure Ac­tivity Turn into a Driver for Sustainable Growth?’ Journal of Tourism Futures 4 (3): 218–32. Damnjanovic, V., M. Kravic, and T. Abdul Razek. 2009. ‘Tourism Brand­ing Strategy of the Mediterranean Region.’ International Journal of Euro-Mediterranean Studies 2 (1): 99–120. Dimitrijevic, M., L. Ristic, and N. Boškovic. 2022. ‘Rural Tourism as a Driver of the Economic and Rural Development in the Republic of [26] Serbia.’ Menadzment u hotelijerstvu i turizmu 10 (1). https://doi.org /10.5937/menhottur2201079d. Demonja, D. 2014. ‘Pregled i analiza stanja ruralnog turizma u hrvatskoj.’ Sociologija i prostor 52 (1): 69–90. Duarte, P., J. A. Folgado-Fernández, and J. M. Hernández-Mogollón. 2018. ‘Measurement of the Impact of Music Festivals on Destina­tion Image: The Case of a Womad Festival.’ Event Management 22 (4): 517–26. Dujmovic,M., andA.Vitasovic.2012. ‘Festivals,Local Communities and Tourism.’ In Soundtracks: Music, Tourism and Travel Conference, 1–8. Leeds Metropolitan University. Eisenberger, R., S. Armeli, B. Rexwinkel, P. D. Lynch, and L. Rhoades. 2001. ‘Reciprocation of Perceived Organizational Support.’ Journal of Applied Psychology 86 (1): 42–51. Fun, F. S.,L.M. Chiun,P.Songan,and V. Nair. 2014. ‘TheImpactofLo­cal Communities’ Involvement and Relationship Quality on Sustain­able Rural Tourism in Rural Area, Sarawak: The Moderating Impact of Self-E.cacy.’ Procedia: Social and Behavioral Sciences 144:60–5. Gannon, A. 1994. ‘Rural Tourism as a Factor in Rural Community Eco­nomic Development for Economies in Transition.’ Journal of Sustain­able Tourism 2 (1–2): 51–60. Guo, B., Y. M. Wang, H. Zhang, C. Liang, Y. Feng, and F. Hu. 2023. ‘Impact of the Digital Economy on High-Quality Urban Economic Development: Evidence from Chinese Cities.’ Economic Modelling 120:106194. Hall, C. M., and R. Mitchell. 2000. ‘Wine Tourism in the Mediterranean: A Tool for Restructuring and Development.’ Thunderbird Interna­tional Business Review 42 (4): 445–65. Hanton, S., and D. Connaughton. 2002. ‘Perceived Control of Anxiety and Its Relationship to Self-Con.dence and Performance.’ Research Quarterly for Exercise and Sport 73 (1): 87–97. Janasz,S.de, S. J. Behson, K.Jonsen, andM.J.Lankau. 2013. ‘Dual Sources of Support for Dual Roles: How Mentoring and Work-Family Culture In.uence Work-Family Con.ict and Job Attitudes.’ Interna­tional Journal of Human Resource Management 24 (7): 1435–53. Kim, S., and T. Jamal. 2015. ‘The Co-Evolution of Rural Tourism and Sustainable Rural Development in Hongdong, Korea: Complexity, Con.ict and Local Response.’ Journal of Sustainable Tourism 23 (8–9): 1363–85. Krajnovic, A., and I. P. Gortan-Carlin. 2007. ‘Possibilities of Music Her­itage Tourist Valorization: An Example of Istria.’ Tourism and Hospi­tality Management 13 (2): 469–82. Kuqi, B., H. Shabani, and P. Hasanaj. 2019. ‘The Role of Community in Rural Tourism Development and Economic Impact.’ Knowledge: In­ternational Journal 34 (1): 229–34. Lane,B., andE.Kastenholz. 2015.‘RuralTourism:TheEvolution of Prac­tice and Research Approaches – towards a New Generation Con­ [27] cept?’ Journal of Sustainable Tourism 23 (8–9): 1133–56. Levenson, H. 1973. ‘Multidimensional Locus of Control in Psychiatric Patients.’ Journal of Consulting and Clinical Psychology 41 (3): 397–404. Lew, A. A. 2011. ‘Tourism’s Role in the Global Economy.’ Tourism Geogra­phies 13 (1): 148–51. Livandovschi, R. 2022. ‘The Role of the Rural Tourism in Developing the Economy of Rural Regions’. In Competitiveness and Innovation in the Knowledge Economy: 26th International Scienti.c Conference. asem. Louangrath, P. 2017. ‘Minimum Sample Size Method Based on Survey Scales.’ International Journal of Research & Methodology in Social Sci­ence 3(3):44–52. Maret, S.,C.G. Iwu,T. B.Musikavanhu, and R. D. Handayani. 2018. ‘Ru­ral Tourism as a Way to Build Economic Independence.’ African Jour­nal of Hospitality, Tourism and Leisure 7 (4): 1–11. Moreno de la Santa, J. G. S. 2020. ‘Tourism as a Lever for a More Inclu­sive Society.’ Worldwide Hospitality and Tourism Themes 12 (6): 731–8. Oyler, J. D. 2007. ‘Core Self-Evaluations And Job Satisfaction: The Role Of Organizational And Community Embeddedness.’ PhD diss., Vir­ginia Polytechnic Institute and State University. Plevnik, M., M.Gerževic, I. Lešnik,I.Babnik, andK.Babnik. 2021. ‘The Mediterranean as a Factor of Enrolment InMusic Programmes of Individual Musical Instruments in Music Schools: A Case Study of Slovenia.’ International Journal of Euro-Mediterranean Studies 14 (2): 91–105. Por.itt, F., and R. Rosas. 2020. ‘Core Music Elements: Rhythmic, Melo­dicand Harmonic MusiciansShowDi.erencesinCognitive Perfor­mance (Elementos Básicos de La Música: Músicos Rítmicos, Melódi­cos y Armónicos Muestran Diferencias de Desempeño Cognitivo).’ Estudios de Psicologia 41 (3): 532–62. Quaranta, G., E. Citro, and R. Salvia. 2016. ‘Economic and Social Sus­tainable Synergies to Promote Innovations in Rural Tourism and Lo­cal Development.’ Sustainability (Switzerland) 8 (7): 668. Ribeiro, J. C.,L.Vareiro, C.P.Fabeiro, and X. Pardellas de Blas. 2006. ‘Importância Da Celebração de Eventos Culturais Parao Turismo Do Minho-Lima: Um Estudo de Caso.’ Revista Portuguesa de Estudos Re­gionais 11: 61–76. Rose,D., A. Jones Bartoli,and P. Heaton.2019. ‘Formal-Informal Musi­ [28] cal Learning, Sex and Musicians’ Personalities.’ Personality and Indi­vidual Di.erences 142:207–13. Rudan, E., and C. Stipanovic. 2021. ‘Music in the Tourism O.ering of Rural Regions (the Case of Eastern Croatia).’ European Countryside 13 (3): 685–96. Saarinen, J. 2007. ‘Contradictions of Rural Tourism Initiatives in Rural Development Contexts: Finnish Rural Tourism Strategy Case Study.’ Current Issues in Tourism 10 (1): 96–105. Saarinen, J., C. Rogerson, and H. Manwa. 2011. ‘Tourism and Millen­nium Development Goals: Tourism for Global Development?’ Cur­rent Issues in Tourism 14 (3): 201–3. Scott, D., S. Gössling, and C. M. Hall. 2012. ‘International Tourism and Climate Change.’ Wiley Interdisciplinary Reviews: Climate Change 3: 213–32. Sert, A. N. 2024. ‘Rural Tourism As Promoter of Rural Development.’ Journal of Management and Economic Studies 6(4):370–9. Sharpley, R. 2012. ‘Tourism and Vulnerability: A Case of Pessimism?’ Tourism Recreation Research 37 (3): 257–60. Slusariuc, G. C. 2018. ‘Rural Tourism an Opportunity for Sustenable De­velopment.’ Ovidius University Annals: Economic Sciences Series 18 (2): 349–53. Smale, A., S. Bagdadli, R. Cotton, S. Dello Russo, M. Dickmann, A. Dysvik, M.Gianecchini,R. Kaše, M. Lazarova, A.Reichel,P.Rozo, M. Verbruggen 2019. ‘Proactive Career Behaviors and Subjective Ca­reer Success: The Moderating Role of National Culture.’ Journal of Organizational Behavior 40 (1): 105–22. Souitaris, V., S. Zerbinati, and A. Al-Laham. 2007. ‘Do Entrepreneur­ship Programmes Raise Entrepreneurial Intention of Science and Engineering Students? The E.ect of Learning, Inspiration and Re­sources.’ Journal of Business Venturing 22 (4): 566–91. Starcevic, K.,Ž.Vojinovic, and J. Glavaš.2022. ‘Intangible Cultural Her­itage and Their In.uence on Financial Results in Rural Tourism.’ Ekonomika poljoprivrede 69 (2): 483–96. Stipanovic, C., E. Rudan, and V. Zubovic. 2023. ‘Enhancing Competitive­ness for Economic and Tourism Growth: Case of Croatia.’ In Tourism in Southern and Eastern Europe 7:397–408. Strauss, K., M. A.Gri.n,S.K. Parker, andC. M.Mason.2015. ‘Building and Sustaining Proactive Behaviors: The Role of Adaptivity and Job Satisfaction.’ Journal of Business and Psychology 30 (1): 63–72. Tola, A., A. Minga, andE.Muca. 2024.‘RuralTourism: Nurturing Pros­perity and Community Resilience.’ Edelweiss Applied Science and Technology 8(3):279–89. Toubes, D. R., J. García del Junco, and M. Abe. 2019. ‘Cross-Cultural Analysis of Japanese and Mediterranean Entrepreneurs during the Global Economic Crisis.’ Journal of International and Global Studies 10 (2): 3. Triyanto,C. G. I., T. B. Musikavanhu, andR.D.Handayani.2018. ‘Rural [29] Tourism as a Way to Build Economic Independence.’ African Journal of Hospitality, Tourism and Leisure 7 (4): 1–11. Vaz, M., A. Dinis, and O. Silva. 2017. ‘New Rurality, Traditional Music and Tourist Experience.’ Journal of Tourism, Heritage & Services Mar­keting 3(1): 25–32. Vleeming,R.G., andJ.A.Engelse.1981. ‘AssessmentofPrivate andPub­lic Self-Consciousness: A Dutch Replication.’ Journal of Personality Assessment 45 (4): 385–9. Wang, H. 2023. ‘Study on the Development of Rural Tourism and Cul­tural Integration in Zhejiang Province.’ Frontiers in Business, Eco­nomics and Management 7(2):74–9. Willson, G. 2015. Taking Responsibility for Tourism. Taylor & Francis. Wu, J. 2017. ‘Ethnic Tourism and the Big Song: Public Pedagogies and the Ambiguity of Environmental Discourse in Southwest China.’ Ed­ucational Philosophy and Theory 49 (5): 480–500. ijems | scientific article How Do Serbian Gymnastics Coaches Make Decisions? edvard kolar marijo možnik Science and Research Centre University of Zagreb, Croatia Koper, Slovenia marijo.moznik@gmail.com edvard.kolar@zrs-kp.si matej tušak saša veli.kovi. University of Ljubljana, Slovenia University of Niš, Serbia matej.tusak@fsp.uni-lj.si v.sale70@gmail.com rado pišot Science and Research Centre Koper, Slovenia rado.pisot@zrs-kp.si Di.erent authors argue that coaching is fundamentally a decision-making (hereinafter: dm) process, while coaches’ dm has been identi.ed as a key element of a coach’s practice. In the present study, we examined the dm behavior of Serbian gymnastics coaches. The sample consisted of 53 coaches (age: 40.96±13.04 years). Manifested dm behavior was measured during the national coaching seminar using the General dm Style Inven­tory, which includes .ve dm styles de.ned as rational, intuitive, depen­dent, spontaneous and avoidant dm. Factor analyses were performed to reveal the dm styles’ structure. Pearson’s correlation coe.cient was used to identify the association between dm styles, demographic and profes­sional characteristics, and anova was used to detect di.erences between more experienced and less experienced coaches. The results showed that coaches use a combination of all .ve dm styles when making decisions, but mostly use rational and dependent dm styles. Based on the discov­ered average structure of the dm styles, we can conclude that Serbian gymnastics coaches are mostly rational decision-makers who increase their rationality by seeking advice, opinions, and knowledge from col­leagues when making decisions. Furthermore, more experienced coaches can make decisions more independently and also faster when the situa­tion is urgent or time-limited. Key Words: Serbian gymnastics coaches, decision-making styles, structure, demographic characteristics, professional characteristics, experience © 2024 Edvard Kolar, Saša Velickovic, Rado Pišot, Marijo Možnik, and Matej Tušak https://doi.org/10.70908/2232-6022/18.31-52 introduction Di.erent authors argue that coaching is essentially a decision-making (hereinafter: dm) process (Abraham and Collins 2011, 367; Lyle and Muir 2020, 1), withcoaches’ dm identi.edasa keyaspectoftheirprac­ [32] tice (Kaya2014, 333; Coutts 2017,717;Tilletal. 2018,14).Itisconsidered the hallmark of an expert coach (Nash and Collins, 2006) and one of the most important skills a coach must possess (Post and van Gelder 2023). dm is a de.ning element of coaching expertise (Harvey et al. 2015). Athletes’ performance is mainly determined by their developed ca­pabilities (knowledge, abilities, characteristics, and motivation) and ef­fective training process management, the long-term goal of which is to transform the athlete’s capabilities to meet the demands of their sport (Kolar et al. 2006, 11). Nash and Collins (2006, 467) view coaches as managers of the training process, responsible for planning, organizing, implementing, and evaluating. They coordinate experts and athletes and delegate tasks to optimize the training process (Kolar et al. 2025, 2). The aforementioned sets of the coach’s managerial tasks within a sports training process represent the substantive aspect of the coach’s role, while the basic method of their work is making decisions (Abraham et al. 2006, 549; Kolar and Tušak 2022, 49; Wilson and Kiely 2023, 2). dm is a process de.ned as a choice between options (Heller and Hindle 2001, 154), in.uenced by the interplay of two cognitive sys­tems: System 1 (intuitive, heuristic) and System 2 (rational, analytical) (Kahneman 2017, 576). System 1 enables quick, creative decisions, es­pecially with domain-speci.c experience (Klein 2015, 164), while Sys­tem 2 is characterized by slower, more deliberate and conscious think­ing used for complex evaluations and long-term planning (Evans and Stanovich 2013; Gonzalez-Loureiro and Vlacic 2016; Kahneman 2017). System 2 also ensures decisions align with strategic goals (Elbanna and Child 2007, 445–6; Bayo and Akintokunbo 2022, 58). dm styles emerge from these fundamental cognitive styles and are in.uenced by person­ality, biases, knowledge, and experience (Harren 1979; Scott and Bruce 1995).Variousauthorshavede.ned dm stylesas(1)hierarchicallysub­ordinate to the fundamental cognitive styles (Spicer and Sadler-Smith 2005, 146; Kozhevnikov 2007, 473; Dewberry et al. 2013, 784; Kolar et al. 2025,2)and(2)manifestingatthedecision-makinglevel. dm stylesare learned responses to speci.c situations, not mutually exclusive, and oc­cur in variouscombinations in individuals (Scott and Bruce 1995). The General Decision-Making Style Inventory (hereinafter: gdms) is the most commonly used questionnaire for assessing these styles (Berisha et al. 2018, 3; Urieta et al. 2021, 2). Coaches are highly trained professionals (experts) with specialized knowledge and experience in their sport (Lyle and Muir 2020, 14). Eric­sson (2018a, 3–4) describes an expert as someone who is highly skilled [33] and knowledgeable in a particular .eld, or someone who is widely rec­ognized as a reliable source of knowledge, techniques, or skills, with their judgments being acknowledged as authoritative both publicly and by theirpeers.Ericsson etal. (1993, 372) argue thatexpertise andex­pert performance are developed through extensive experience in a spe­ci.c domain, which requires long-term involvement (at least 10 years or 10,000 hours) in deliberate practice in that domain. Kolar et al. (2025, 12) argue that a coach’s expertise is de.ned by (1) years of experience (2) within a speci.c domain, and (3) achieving high-level results in inter­national competitions. Only the coach who ful.lls all three criteria can be recognized as an expert, with their decisions – whether long-term or sudden – being highly valid and reliable. Thisstudywillexaminethe dm stylesofSerbiangymnasticscoaches, focusing on (1) the overall dm styles structure and (2) mutual corre­lations of dm styles, (3) their correlations with coaches’ demographic and professional characteristics, and (4) di.erences in the dm styles used between more and less experienced coaches. literature review Despite the growing recognition of the importance of coaches’ dm in the training process, which involves adapting or tailoring the coach’s dm behavior to the speci.c or even unique needs of the athlete and of the chosen sport (Harvey et al. 2015, 152), research in the .eld of sports coaching theory still lacks empirical insights into coaches’ dm styles. There are quite a few studies in which the authors dealt mainly with the leadership styles and behaviors of sports coaches (Chelladurai and Arnott 1985; Côté et al. 1995; Marshall 2006; Kaya 2014; Elderton 2020; Jin et al. 2022; Jawoosh et al. 2022) and applied the .ndings to their dm behavior in various situations and contexts. These studies primar­ily focus on identifying the coach’s leadership style, particularly how it in.uences the level of athlete involvement in decision-making pro­cesses. Abraham and Collins (2015, 1) report that there has recently been an increased interest in using Naturalistic Decision Making (here­inafter: ndm) paradigm and the Recognition Primed Decision Mak­ing (hereinafter: rpd) model to examine and understand the dm of sport coaches in time-limited situations. The ndm approach (Klein 2008;2015)isanalternativetothenormative,rationalistic dm process [34] approach, whose main orientation is that decision-makers in natural settings rely heavily on expert intuition. Bossard et al. (2022, 1), in their study, note that there is an extensive number of studies where di.erent authors use the rpd model to explore the dm behavior of expert coaches (Abraham and Collins 2015; Harvey et al. 2015; Collins et al. 2016; Collins and Collins 2016; Ashford et al. 2020) from di.erent sports in natural settings. Findings suggest that coaches have an ini­tial desire to engage in rpd-type behavior and have the capacity to be ‘experts’ but maynot usethis capacityunlessforcedtodo so(Abraham and Collins 2015, 1). Also, Harvey et al. (2015, 152) stated that ndm can o.er a suitable framework to apply to coaches’ dm behavior and Collins et al. (2016, 5–6) added that there are considerable variations, both between coaches and between sports, in the perceived frequency ofintuitive dm use(rpd model).Theyfoundthat,inallcases,coaches acknowledged the need for careful planning across all elements of their work, where the intuitive aspects of the coaches’ dm emerged di.er­entially across the macro (planning stage) and micro (implementation stage) processes of the training session. Moreover, Richards et al. (2016, 73) argue that the dm process is complex and multifactorial, where a crucial underpinning for the e.cient application of the coach’s tactical knowledge is the use of a slow, deliberate and re.ective examination of the process. In the .eld of the sports training process, there are certainly many situations in which coaches make decisions consistent with the ndm paradigm and the use of the rpd model, but as Kahneman and Klein (2009, 524–5) point out, there are three fundamental conditions for valid intuitive reasoning. The environment within which the reasoning takes place (1) must be orderly, there (2) must be the possibility for the decision-maker to learn the rules of its orderliness, and (3) there must be adequate feedback about their thoughts and actions. Only if all conditions are met at the same time will the associative mem­ory (stored tacit knowledge or experience) be able to recognize the circumstances and produce quick and accurate decisions. Introducing the ndm paradigm and the rpd model into sports coaching has pro­vided a deeper understanding of how coaches handle the complexity, crises, and uncertainty of training. It o.ers a framework for explaining how coaches make decisions in the dynamic, high-pressure moments of coaching. Abraham and Collins (2011), together with Martindale and Collins (2007), argue that, like the ndm paradigm, the classic dm model (nor-[35] mative model, hereafter cdm) also has limitations, and they intro­ducedtheconceptofprofessionaljudgmentand dm (hereafter pjdm) as a comprehensive model for understanding and facilitating the com­plex behavior of dm in sports coaches. By integrating the principles of cdm and ndm into pjdm, the authors suggest that coaches make decisions along a continuum from logical and rational options to in­tuitive, experience-based decision-making. Moreover, Collins et al. (2016,2)alsodescribedtheconceptofnested dm,whichcanbeunder­stood as an application of pjdm to coaching. They argue that higher­order/longer-term (strategic) decisions should be taken in a more con­sidered, deliberative (cdm) fashion, while immediate, in-session (oper­ative) decisions are more short-term and almost intuitive (more re.ec­tive of an ndm approach). This ‘nesting’ of intuitive, short-term de­cisions within more deliberate, long-term decisions is a key feature of the coaching process, helping to align immediate actions with broader, long-term goals. The pjdm model, therefore, assumes that the dm process of coaches, depending on the (1) problem situation and the (2) goal of the decision, occurs both within System 1 (speci.c domain expert intuition) and within System 2 (bounded rational analytical pro­cess). The latent use of di.erent cognitive styles (System 1 and 2) used by coaches in their dm behavior can be detected through manifest dm styles that shape the coach’s dm behavior. Manifested dm behavior was observed and measured with Scott and Bruce’s (1995, 829) gdms inventory by Giske et al. (2013), who investigated soccer coaches’ dm styles in relation to elite and non-elite coaching experience and level of playing history. The results of their study show that soccer coaches mostly use the rational or intuitive dm style and almost no avoidant dm style, and that coaches with more expertise in a speci.c-domain of coaching statistically signi.cantly use more rational and intuitive dm styles than non-experts. Additionally, coaches with elite-level player ex­perience also show statistically signi.cantly greater use of intuitive and rational dm styles than coaches without that experience (Giske et al. 2013, 695). The second study, conducted by Noh et al. (2018) explored the relationship between soccer club coaches ‘dm style, basic psycho­logical needs and intention to continue exercising. This study’s results showed that coaches’ rational and intuitive dm styles have a positive e.ect on the participants’ basic psychological needs, while coaches’ de­ [36] pendent and avoidant styles have a negative e.ect on their basic psy­chological needs. Furthermore, this study also revealed that coaches’ rational and intuitive dm styles have a positive e.ect on sport partic­ipants’ intention to continue exercising, while coaches’ avoidant style has a negative e.ect on their intention to continue to exercise (Noh et al. 2018, 10). In both studies, the structure of decision-making styles within all formed samples (entire, experts, non-experts ...) was the same. Coaches demonstrate the highest proportion of use of both func­tional dm styles (1) rational and (2) intuitive, followed in order by the so-called non-functional dm styles, (3) dependent, (4) spontaneous, and (5) avoidant dm style. The use of functional dm styles in dm pro­cesses generally leads to correct and e.ective decisions, while the in­creasedpresenceofnon-functionalstylesintheoverall dm stylestruc­ture of coaches could indicate the risk that their dm behavior often leads to negative results and inconsistent decisions (Mitchell et al. 2011, 693–4; Faletic and Avsec 2013, 133). Kolar et al. (2025, 8) in their study developed a conceptual frame­work for coaches’ decision making in conventional sport (e.g. gymnas­tics, .gure skating) which encompass a wide range of situations that may arise during training and the potential approaches for addressing them. This should result in di.erent types of decisions and character­istic of coaches’ decision-making behavior. The developed conceptual framework foresees three types of decisions (strategic, tactical and op­erational), each of which should have a di.erent role in the compre­hensive process of sports training. To de.ne the types of decisions, the (1) expected time frame of validity, (2) time impact, and (3) level of ur­gency of decisions made were primarily used. The authors point out that these three types of decisions should have a (1) distinct role in the comprehensive process of sports training, should be (2) carried out on the basis of di.erent cognitive processes, (3) be manifested in the forms of di.erent dm style structures and (4) be enforced by using di.erent leadership styles. From this perspective, therefore, each type of deci­sion identi.ed has its own unique role, signi.cance, and meaning in managing comprehensive sport training process. As the authors note, if we areaware of thelevel of knowledge and theamountofexperience of the coaches and we .nd out (measure) their dm style structure, the conceptual framework provides clear guidance on which coach should be entrusted with managing athletes during training and competitions (Kolar et al. 2025, 11). [37] methods Participants The sample consisted of 53 Serbian gymnastics coaches (age: 40.96± 13.04 years), which represents nearly the entire population of Serbian gymnastics coaches and exceeds the minimum requirement for con­ducting factor analysis (de Winter et al. 2009). The upper age limit was 79 years, while the lower age limit was 20 years. The most experienced coach had 38 years of experience, and the least experienced had 2 years (12.91±9.21 years). The sample included 17 men (32.1.) and 36 women (67.9.). Participants completed the questionnaire during the national coaching seminar in Kostolac (Serbia, August 2023). All subjects partic­ipated in the study voluntarily and without any compensation. Instrument The dm style was measured using the gdms (Scott and Bruce 1995), which was translated into Serbian. The gdms questionnaire measures .ve di.erent dm styles: rational, intuitive, dependent, avoidant, and spontaneous. The questionnaire consists of 25 items (5 for each dm style) ranging on a .ve-point Likert scale, ranging from strongly dis­agree (1) to strongly agree (5). A total score for each of the .ve dm styles was obtained by summing the item scores that measured each dm style, with scores ranging from 5 to 25. The gdms scales have pre­viously demonstrated good psychometric characteristics across di.er­ent samples (managers, students, the general population, military o.­cers, sport managers, sport coaches and others) from various countries (Scott and Bruce 1995; Thunholm 2004; Spicer and Sadler-Smith 2005; Gambetti et al. 2008; Curseu and Schruijer; 2012; Avsec 2012; Giske et al. 2013; Bavolár and Orosová 2015; Noh et al. 2018; Alacreu-Crespo et. al 2019; Kolar and Tušak 2022). In this study, the alpha coe.cients of the scales ranged between 0.472 (spontaneous) to 0.870 (avoidant) (ta­ble 1). The Cronbach’s alpha for the entire gdms is 0.726, which is a good indicator of internal consistency. The reliability coe.cient for the spontaneous style was deemed adequate, while other coe.cients indi­cated moderate to strong internal consistency (Taber 2018, 1278). Gen-eral information questions about gender, age, experience, level of edu­cation, status, and success of the coach were also added. Statistical Analysis [38] Statistical data processing was carried out using the Statistical Pack­age for the Social Sciences 29 (ibm spss). The factor analysis method – Principal Component Factoring (pcf) and varimax rotation of fac­tors – was used to test the assumption about the structure of dm styles. Factor extraction was carried out using Kaiser-Guttman’s cri­terion (Eigenvalue > 1) and the scree plot diagram (Cattell’s Scree Test) (Cattell 1966). Before applying the factor analysis (hereinafter: fa), the data adequacy was tested with the Keiser-Meyer-Olkin Measure of Sampling Adequacy (kmo) and Bartlett’s test of sphericity. Values of the kmo test above 0.6 indicate that the analyzed data is suitable for the use of fa (Tabachnick and Fidell 2007). Bartlett’s test must show signi.cant di.erences at a risk level of less than 5. (p < 0.05), indicating that the correlation matrix is not uniform and that the observed vari­ables are related to some extent. The internal consistency of the overall scale and subscales was measured using Cronbach’s alpha coe.cient. Pearson’s correlation coe.cient was used to identify the association between dm styles, demographic and professional characteristics of the sample, and anova was used to detect di.erences between more experienced and less experienced coaches. results Table 1 shows descriptive statistics for .ve dm styles. The average values of the individual dm style use (Mean/Value) were calculated from the scores dedicated to items assigned to an individual dm style (Scott and Bruce 1995). The average share of the individual dm style use (Mean/. of maximum) in relation to the maximum possible total value of the sum of items of the individual dm style (maximum = 25) was also calculated for each dm style. Thestructureofthe dm styles(table1)revealedthatSerbiancoaches, onaverage,mostoftenusetherationalanddependent dm styles.These are followed by the intuitive and spontaneous dm styles, whereas coaches are least likely to use the avoidant dm style. Similar results on the structure of dm styles in di.erent samples were also found by other authors (Scott and Bruce 1995; Giske et al. 2013; Ghazi and Hu 2016; Krasniqi et al. 2019; Noh et al. 2018; Kolar and Tušak 2022). How Do Serbian Gymnastics Coaches Make Decisions? table 1 Descriptive Statistics and Internal Consistency of dm Styles dm Styles N Min Max Mean sd Skew. Kurt. a Value . dmsr .. .. .. ..... .... ..... –..... ..... ..... dmsi .. .. .. ..... .... ..... ..... ..... ..... [39] dmsd .. . .. ..... .... ..... –..... ..... ..... dmsa .. . .. .... .... ..... ..... ..... ..... dmss .. . .. ..... .... ..... ..... –..... ..... notes dmsr –rationalstyle,dmsi –intuitivestyle,dmsd –dependentstyle,dmsa –avoidant style, dmss – spontaneous style. table 2 The Kaiser-Meyer-Olkin (kmo) Test and Bartlett’s Test of Sphericity Kaiser-Meyer-Olkin Measure of Sampling Adequacy Bartlett’s Test of Sphericity Approx. .2 df ..... ....... ....... Sig. ..... The average structure of dm styles also reveals that Serbian coaches achieve a signi.cantly high proportion of use of the rational dm style (87.3.), as well as high proportions of use of the dependent (71.2.) and intuitive (65.8.) dm styles, while the spontaneous style is used occasionally (51.2.) and the avoidant style is mostly not used (38.1.) in the training process. Before applying fa, the Kaiser-Meyer-Olkin (kmo) test and Bart­lett’s test of sphericity (table 2) were carried out to evaluate the factora­bility. The kmo measure ofsamplingadequacy was 0.639(therequired minimum is above 0.6) and the signi.cance of Bartlett’s test of spheric­ity was 0.000 (p < 0.01). The results of both tests show that the studied sample is suitable for performing fa. The structure of the decision-making styles of Serbian gymnastics coaches was veri.ed by fa using the method of principal components with varimax rotation (table 3). The fa procedure based on Kaiser­Guttman’s criterion extracted six (6) factors, which cumulatively ex­plain 67.820. of the total variance. Table 3 also shows a scree plot dia­gram with the factor eigenvalue curve bending at the .fth factor, indi­cating that a .ve-factor solution corresponds to the gdms model and couldalsobeconsideredavalidresultofthe fa (Scott and Bruce 1995; Spicer and Sadler-Smith 2005). Thus, the rotated solution with .ve fac­tors explains 62.957. of the total variance of the observed variables. Edvard Kolar et al. table 3 fa of the gdms Inventory and Scree Plot Diagram (a) (b) (c) (d) (.) (.) (.) (.) (.) (.) (.) (.) (.) . ..... ...... ...... ..... ...... ...... ..... ...... ...... [40] . ..... ...... ...... ..... ...... ...... ..... ...... ...... . ..... ...... ...... ..... ...... ...... ..... ...... ...... . ..... ..... ...... ..... ..... ...... ..... ...... ...... . ..... ..... ...... ..... ..... ...... ..... ..... ...... . ..... ..... ...... ..... ..... ...... ..... ..... ...... . ..... ..... ...... . ..... ..... ...... ... . ..... ..... ...... ... .. ..... ..... ...... .. ..... ..... ...... ... .. ..... ..... ...... ... .. ..... ..... ...... ... .. ..... ..... ...... .. ..... ..... ...... ... .. ..... ..... ...... ... .. ..... ..... ...... ... .. ..... ..... ...... .. ..... ..... ...... ... .. ..... ..... ...... ... .. ..... ..... ...... .. ..... ..... ...... ... .. ..... ..... ...... ... .. ..... ..... ...... ... .. ..... ..... ....... notes Column headings are as follows: (a) component, (b) initial eigenvalues, (c) extraction sums of squared loadings, (d) rotation sums of squared loadings, (1) total, (2) percentage of variance, (3) cumulative percentage. Table 4 shows the factor structure and factor loadings of the items included in the gdms inventory. The .rst factor is associated with all .ve items measuring the avoidant style and two items from the spon­taneous dm style (dmss4 and dmss2). The projections of avoidant style items on the .rst factor are high (factor loadings from 0.700 to 0.816), while the projection of the spontaneous dm style items on the same factor is very low (0.472, 0.382). Therefore, the .rst factor can be table 4 Factor Structure and Factor Loadings of the 25 Items of the gdms Inventory Items Component ...... dmsa. ..... [41] dmsa. ..... dmsa. ..... dmsa. ..... dmsa. ..... dmss. ..... dmss. ..... dmsr. ..... dmsr. ..... dmsr. ..... dmsr. ..... dmsr. ..... dmsd. ..... dmsd. ..... dmsd. ..... dmsd. ..... dmsd. ..... dmsi. ..... dmsi. ..... dmsi. ..... dmsi. ..... dmss. ..... dmss. ..... dmss. ..... dmsi. ..... notes dmsa1–5 – avoidant style items, dmsr1–5 – rational style items, dmsd1–5 – dependent style items, dmsi1–5 – intuitive style items, dmss1–5 – spontaneous style items. named the ‘avoidant style’, explaining 16.499. of the total variance of the rotated solution (table 3). It can be observed that all the items mea­suringarational dm style(dmsr1 to dmsr5)arerelatedtothesecond factor (factor loadings from 0.413 to 0.837). This factor explains 13.726. of the total variance of the rotated solution (table 3) and can be named the‘rationalstyle’. Thethirdfactorisexplainedwith.vedependent dm style variables (dmsd1 to dmsd5) with factor loadings from 0.531 to 0.818. The third factor explains 12.113. of the total variance (table 3) and can be named the ‘dependent style’. The fourth factor (table 4) is explained by four items measuring the intuitive dm style (dmsi1, 2, 4 and 5) with factor loadings from 0.730 to 0.783. The fourth factor ex­ [42] plains 11.549. of the total variance of the rotated solution (table 3) and can be named the ‘intuitive style’. The .fth factor is explained by only threeitems,belonging to thespontaneous dm style(dmss1, 3 and5) with factor loadings 0.518 and 0.779. The .fth factor explains 9.070. of the total variance of the rotated solution (table 3) and can be named the ‘spontaneous style’. The sixth factor of the rotated solution is ex­plainedbyonlyonevariable from theintuitive dm style(dmsi3),with a factor loading of 0.643, explaining 4.862. of the total variance (table 3). This variable was distributed outside the predicted dm styles. Since the scree plot diagram suggests a .ve-factor solution (table 3) and the sixth factor is de.ned by only one variable (table 4), we will exclude this factor from further analysis. Regardless of the clarity of the .ve-factor structure model, which is consistent with the original gdms model from Scott and Bruce (1995), some variables are nevertheless distributed outside the pre­dicted dm styles. The obtained factor model shows a good stability for the avoidant, rational and dependent dm styles in terms of the included items. The stability of intuitive dm style is relatively good, while the spontaneous style scale proved to be very unstable and prob­lematic. However, it should be noted that, even in the original paper by Scott and Bruce (1995), the spontaneous style was added at a later stage, and the items and questions are somehow ambiguous. The items, which in the presented study (table 4) were not projected onto the fac­tors in accordance with the original model, are dmss2 (‘I often make decisions on the spur of the moment’), dmss4 (‘I often make impul­sive decisions’), and dmsi3 (‘I generally make decisions that feel right to me’). Some other authors have also faced a similar problem with the same variables on di.erent samples (Baiocco et al. 2009; Reyna et al. 2014; Fischer et al. 2015; del Campo et al. 2016; Kolar and Tušak 2022). The variables that were not distributed among the factors in accordance with the intended model were named ‘problematic items’ and due to missing content validity or ambiguity, they were excluded from future considerations in their research. Based on that, we will also, in the con­tinuation of the present study, remove the mentioned variables from the structure of the dm styles of Serbian gymnastics coaches and con­sider the dm style structure with 22 items. In the continuation of the investigation of the characteristics of the dm behavior of Serbian coaches, we examined the connections between the extracted dm styles and also the connections of these styles with [43] some demographic and professional characteristics of the selected sam­ple. Table 5 shows that rational and avoidant dm styles are negatively statistically correlated at a 1. level risk, which is in line with the .nd­ings of other authors (Scott in Bruce 1995, 830; Spicer and Sadler-Smith 2005, 141; Baiocco et al. 2009, 968; Faletic and Avsec 2013, 138; Hariri et al. 2014, 293). This type of connection between these two styles was also expected, since the rational dm style depends on the decision-makers fully following the rules and procedures in the judgment process, with the aim of making the best possible decision, while the avoidant dm style is characterized by the fact that the decision maker avoids the de­cision, is not capable of relevant judgment and manifests itself mainly in indecisive behavior. A statistically signi.cant positive association at a 1. risk level was also found between the intuitive and sponta­neous dm styles. Similar conclusions were also reached by other au­thors (Scott and Bruce 1995; Thunholm 2004; Spicer and Sadler-Smith 2005; Baiocco et al. 2009; Curseu and Schruijer 2012; Faletic and Avsec 2013; Reyna et. al. 2014; Hariri et al. 2014; Bavolár and Orosová 2015; Berisha et al. 2018). These .ndings align with our expectations, as both intuitive and spontaneous decision-making styles are linked at a latent level to the intuitive-experiential cognitive style (Alacreu-Crespo et al. 2019), which de.nes the manifestation of these styles. The analysis of associations between individual styles also showed a statistically sig­ni.cant positive correlation at a 5. risk level between dependent and avoidant dm styles, which requires caution and is addressed and ex­plained in the discussion section. Table 5 also shows that the age, experience, status, and success of coaches are all positively correlated at a 1. signi.cance level. This sug­gests that more experienced coaches are also older, achieve better re­sults with their athletes, and hold higher positions within the national coaching hierarchy. This fact may also indicate a positive human re­source strategy within the coaching organization in Serbian gymnas­tics. An examination of statistically signi.cant associations at di.erent risk levels (table 5) of demographic and professional characteristics of coaches with dm styles shows that female coaches (Faletic and Avsec table 5 Correlations between the dm Styles, Demographics and Professional Characteristics Item ........... .Gender [44] . Age . Exper. ..... ..... .....*** . Educat. ..... ..... ..... . Status ..... .....** .....***..... . Success ..... ..... .....** ..... .....*** . dmsr ..... ..... ..... ..... ..... ..... . dmsi ..... ..... ..... ..... ..... ..... ..... . dmsd ..... ..... .....** ..... ..... ..... ..... ..... .. dmsa ..... ..... ..... ..... ..... ..... .....*** ..... .....** .. dmss .....** .....* .....** ..... ..... ..... ..... .....***..... ..... notes *Correlationissigni.cantatthe0.10level(2-tailed), **correlationissigni.cantatthe0.05 level (2-tailed), *** correlation is signi.cant at the 0.01 level (2-tailed). 2013, 139; Bayram and Aydemir 2017, 911), older (Faletic and Avsec 2013, 139; Bulog 2016, 399) and more experienced coaches are on average more spontaneous in dm, while younger coaches tend to be more de­pendent decision-makers. The analysis of the connections between the measured variables re­vealed that the experience of the coaches is the parameter that forms the largest number of statistically signi.cant connections with the other measured parameters. We can also assume that experience is the statistical source of some other connections. For this reason, we divided the sample of coaches into two groups based on the number of years of coaching experience and analyzed whether there are any dif­ferences between the groups formed in this way in the other measured parameters. Thus, coaches with ten (10) or fewer years of experience were included in the group of less experienced coaches, while those with more than 10 years of experience were classi.ed as more experi­enced coaches (Ericsson 2018b, 746, Kolar et al. 2025, 12). Analysis of the di.erences between more and less experienced coach­es (.gure 1) shows that more experienced coaches are statistically sig­ni.cantly older (p = 0.000) and have a statistically signi.cantly higher coaching status (p = 0.022). An examination of the di.erences in the structure of dm stylesbetweenthe twogroups revealsthatmoreexpe­rienced coaches are statistically more likely to be spontaneous decision-makers (p = 0.083) while less experienced coaches tend to be more de­pendent decision-makers (p = 0.006). Similar results were also obtained .... Gender (p = .....) .... ..... Age (p = .....***) ..... .... Education (p = .....) .... [45] .... Status (p = .....**) .... .... Success (p = .....) .... ..... dmsr (p = .....) ..... ..... dmsi (p = .....) ..... ..... dmsd (p = .....***) ..... .... dmsa (p = .....) .... .... dmss (p = .....*) ..... f igure 1 Analysis of di.erences between More and Less Experienced Coaches notes Dark –lessexperience,light –moreexperience; *correlationissigni.cantatthe0.10level (2-tailed), ** correlation is signi.cant at the 0.05 level (2-tailed), *** correlation is signi.cant at the 0.01 level (2-tailed). in the research on the decision-making styles of football coaches (Giske et al. 2013), but the di.erences in this study were not signi.cant. discussion The dm style refers to how an individual gathers, interprets, and uses information to make decisions. Thunholm (2004) de.ned it as a re­sponse pattern demonstrated when confronted with a decision. dm styles signi.cantly impact a coach’s performance, which in turn af­fects athlete outcomes (Kolar et al. 2025, 12). As Rowe and Boulgarides (1992)noted, dm stylesareessentialfore.ective dm andshouldbeas­sessed. This study found that Serbian gymnastics coaches employ a com­bination of all .ve dm styles, with rational and dependent styles being the most common, indicating that they are primarily rational decision-makers. Rational decision-makers critically evaluate evidence and follow a structured, time-consuming process before making deci­sions (Fitzgerald et al. 2017). Interestingly, the dependent style, which is less prevalent in other coaching studies (Giske et al. 2013; Noh et al. 2018), was the second most frequently used. Alacreu-Crespo et al. (2019) found that dependent decision-makers seek emotional and in­strumental support (e.g., moral support, advice, help and information [46] from others), relying on others to increase the rationality of their deci­sions (Vroom 2003; Khasawneh et al. 2011). This aligns with the theory of extended rationality (Secchi 2010), where coaches reduce limitations in information processing by consulting others (Simon 1976). However, the correlation analysis (table 5) revealed a signi.cant pos­itiverelationshipbetweenthedependentandavoidant dm styles.This combination,referredtoasadependent-avoidant dm style,canbeseen as dysfunctional (Faletic and Avsec 2013, 133; Fischer et al. 2015, 525), as such individuals are either unable or unwilling to accept responsibility for decisions and tend to avoid dm, shifting responsibility onto others (Scott and Bruce 1995; Harren 1979). Experiencelevelalsoimpacts dm styles(.gure1).Moreexperienced coaches tend to be older, have higher national coaching status, and are less likely to rely on the dependent style compared to their less expe­rienced counterparts. Phillips et al. (1984, 497) found that decision-makers with a dominant dependent style tend to lack con.dence and seek con.rmation from others. Less experienced coaches (.gure 1), of­ten with lower status in the national coaching hierarchies, are more likely to use the dependent style due to their limited authority to make independent decisions and less domain-speci.c knowledge (Kahneman and Klein 2009). Additionally, more experienced coaches tend to be more sponta­neous decision-makers. Kolar et al. (2025, 10) noted that spontaneous decisions typically arise during operational-type decisions in the train­ing process and are often driven by a coach’s gut feeling (System 1), coupled with the urgency to act quickly. These decisions can also be understood in accordance with Thunholm’s (2004, 941) de.nition as a high-speed, intuitive dm style decision, used in dm situations that are under time pressure. These decisions are essential in unpredictable situations and are valid only when made by experienced coaches who possess su.cient tacit knowledge, acquired in a speci.c domain envi­ronment, and have learned the rules of that domain through frequent and accurate feedback (Kahneman and Klein 2009, 524–5). In contrast, novice coaches may rely on guesswork or be in.uenced by cognitive bi­ases, which makes their decisions less reliable (Kolar et al. 2025). There­fore, thefrequentuseofthespontaneous dm styleamongexperienced coaches was both expected and appropriate. conclusion Based on the average structure of the dm styles discovered in this [47] study, we can conclude that Serbian gymnastics coaches are primarily rational decision-makers who enhance their rationality by consulting with colleagues for advice, opinions, and knowledge when making de­ cisions, and that more experienced coaches can make decisions more independently and also faster when the situation is urgent or time- limited. The .ndings of this research support the theoretical frame­ work of coaches’ dm in conventional sports, developed by Kolar et al. (2025), and contribute to a better understanding of the importance of coaches’ dm and knowledge expansion. However, the study has some limitations, mostly related to the relatively small sample drawn from a single cultural environment. Therefore, future research in this .eld is needed. references Abraham, A., and D. Collins. 2011. ‘Taking the Next Step: Ways forward for Coaching Science.’ Quest 63:366–84. Abraham, A., and D. Collins. 2015. ‘Professional Judgement and Deci­sion Making in Sport Coaching: To Jump or Not to Jump.’ Paper presented at the International Conference on Naturalistic Decision Making, 9–12 June, McLean, va. Abraham, A., D. Collins, and R. Martindale. 2006. ‘The Coaching Sche­matic: Validation through Expert Coach Consensus.’ Journal of Sports Sciences 24 (6): 549–64. Alacreu-Crespo, A., M. C. Fuentes, D. Abad-Tortosa, I. Cano-Lopez, E. Gonzalez, and M. A. Serrano. 2019. ‘Spanish Validation of General Decision-Making Style Scale: Sex Invariance, Sex Di.erences and Relationship with Personality and Coping Style.’ Judgment and Deci­sion Making 14(6): 739–51. Ashford, M., A. Abraham, and J. Poolton. 2020. ‘A Communal Language for Decision Making in Team Invasion Sports.’ International Sport Coaching Journal 8(1): 122–9. Avsec, A. 2012. ‘Do Emotionally Intelligent Individuals Use More Adap­tive Decision-Making Styles?’ Studia Psychologica 54 (3): 209–19. Baiocco, R., F. Laghi, and M. D’Alessio. 2009. ‘Decision-Making Style among Adolescents: Relationship with Sensation Seeking and Locus of Control.’ Journal of Adolescence 32:963–76. [48] Bavolár, J., and O. Orosová. 2015. ‘Decision-Making Styles and Their As­sociations with Decision-Making Competencies and Mental Health.’ Judgment and Decision Making 10 (1): 115–22. Bayo,P.L., andO.O.Akintokunbo. 2022. ‘Strategic Decision Making: Process and Aid to Better Decision Making in Organizations: A Liter­ature Review Approach.’ International Journal of Economics and Busi­ness Management 8 (1): 56–62. Bayram, N., and M. Aydemir. 2017. ‘Decision-Making Styles and Per­sonality Traits.’ International Journal of Recent Advances in Organi­zational Behaviour and Decision Sciences 3(1): 905–15. Berisha, G.,J.S.Pula, andB.Krasniqi. 2018.‘Convergent Validity of Two Decision Making Style Measures.’ Journal of Dynamic Decision Mak­ing 4(1):1–8. Bossard,C., T. Kérivel, S. Dugény,P.Bagot, T.Fontaine, andG. Ker­marrec. 2022. ‘Naturalistic Decision-Making in Sport: How Cur­rent Advances into Recognition Primed Decision Model O.er In­sights for Future Research in Sport Settings?’ Frontiers in Psychology 13:936140. Bulog, I. 2016. ‘The In.uence of Top Management Demographic Charac­teristics on Decision Making Approaches.’ Ekonomski vjesnik 29 (2): 393–403. Chelladurai, P., and M. Arnott. 1985. ‘Decision Styles in Coaching: Pref­erences of Basketball Players.’ Research Quarterly for Exercise and Sport 56 (1): 15–24. Cattell, R. 1966. ‘The Scree Test for the Number of Factors.’ Multivariate Behavioral Research 1:245–76. Collins, L., and D. Collins. 2016. ‘Professional Judgement and Decision-Making in Adventure Sports Coaching: The Role of Interaction.’ Journal of Sports Science 34:1231–9. Collins, D., L. Collins, and H. J. Carson. 2016. ‘If It Feels Right, Do It: Intuitive Decision Making in a Sample of High-Level Sport Coaches.’ Frontiers in Psychology 7:504. Côté,J., J. Salmela, P. Trudel, A.Baria, and S. Russell. 1995.‘The Coach­ing Model: A Grounded Assessment of Expert Gymnastics Coaches’ Knowledge.’ Journal of Sport and Exercise Psychology 17:1–17. Coutts,A. J.2017. ‘Challenges in Developing Evidence-Based Practice in High-Performance Sport.’ International Journal of Sports Physiology and Performance 12:717–18. Curseu, P.L., andS.G.L.Schruijer.2012. ‘Decision Style andRatio­nality: An Analysis of Predictive Validity of the General Decision-Making Style Inventory.’ Educational and Psychological Measurement 72 (6): 1053–62. de Winter, J.C.F., D. Dodou, andP.A.Wieringa. 2009. ‘Exploratory Factor Analysis with Small Sample Sizes.’ Multivariate Behavioral Re­search 44 (2): 147–81. delCampo,C., S. Pauser,E.Steiner,and R. Vetschera. 2016. ‘Decision Making Styles and the Use of Heuristics in Decision Making.’ Journal [49] of Business Economics 86 (4): 389–412. Dewberry, C., M. Juanchich and S. Narendran. 2013. ‘Decision-Making Competence in Everyday Life: The Roles of General Cognitive Styles, Decision-Making Styles and Personality.’ Personality and Individual Di.erences 55:783–8. Elbanna, S., and J. Child. 2007. ‘In.uences on Strategic Decision E.ec­tiveness: Development and Test of an Integrative Model.’ Strategic Management Journal 28:431–53. Elderon, W. 2020. ‘Learner-Centred Coaching.’ Acecoach, 21 January. https://acecoach.com/learner-centred-coaching/ Ericsson, A. K. 2018a. ‘An Introduction to the Second Edition of The Cambridge Handbook of Expertise and Expert Performance: Its De­velopment, Organization and Content.’ In The Cambridge Handbook of Expertise and Expert Performance, edited by K. A. Ericsson, R. R. Ho.man, A, Kozbelt, and A. M. Williams. Cambridge University Press. Ericsson, A.K.2018b.‘The Di.erentialIn.uence on Experience,Prac­tice and Deliberate Practice on Development of Superior Individual Performance of Experts.’ In The Cambridge Handbook of Expertise and Expert Performance, edited by K. A. Ericsson, R. R. Ho.man, A, Koz­belt, and A. M. Williams. Cambridge University Press. Ericsson,A.K., R. T. Krampe,and C. Tesch-Romer. 1993. ‘The Role of Deliberate Practice in the Acquisition of Expert Performance.’ Psy­chological Review 100 (3): 363–406. Evans, J. S. B. T., and K. E. Stanovich. 2013. ‘Dual-Process Theories of Higher Cognition: Advancing the Debate.’ Perspectives on Psycholog­ical Science 8(3): 223–41. Faletic, L., and A. Avsec. 2013. ‘Stili odlocanja kot napovedniki psi­hicnega blagostanja.’ Anthropos 45 (3–4): 129–49. Fischer, S., K. Soyez, and S. Gurtner. 2015. ‘Adapting Scott and Bruce’s General Decision-Making Style Inventory to Patient Decision Mak­ing in Provider Choice.’ Medical Decision Making 35 (4): 525–32. Fitzgerald, D. R., S. Mohammed, and G. O. Kremer. 2017. ‘Di.erences in the Way We Decide: The E.ect of Decision Style Diversity on Pro­cess Con.ict in Design Teams.’ Personality and Individual Di.erences 104:339–44. Gambetti, E., M. Fabbri, L. Bensi, and L. Tonetti. 2008. ‘A contribution [50] to the Italian validation of General Decision-Style Inventory.’ Per­sonality and Individual Di.erences 44 (4): 842–52. Ghazi, A. M. A., and W. Hu. 2016. ‘Impact of Individual Decision-Making Styles on Marketing Information System Based Decision-Making: An Empirical Study of Saudi Arabia Manufacturing Firms.’ Journal of International Business Research and Marketing 1 (3): 27–39. Giske, R., B. Benestad, K. Haraldstad, and R. Høigaard. 2013. ‘Decision-Making Styles among Norwegian Soccer Coaches: An Analysis of Decision-Making Style in Relation to Elite and Non-Elite Coaching and Level of Playing History.’ International Journal of Sports Science and Coaching 8(4): 689–701. Gonzalez-Loureiro, M., and B. Vlacic. 2016. ‘International Business De­cisions and Manager’s Cognitive Style: Opening up Research Av­enues from Cognitive Behavioral Strategy.’ Revista Eletrônica Gestão and Sociedade 10 (27): 1501–22. Hariri, H., R. Monypenny, and M. Prideaux. 2014. ‘Leadership Styles and Decision-Making Styles in an Indonesian School Context.’ School Leadership and Management 34 (3): 284–98. Harren, V. A. 1979. ‘A Model of Career Decision-Making for College Stu­dents.’ Journal of Vocational Behavior 14:119–33. Harvey, S., J. Lyle, and B. Muir. 2015. ‘Naturalistic Decision Making in High Performance Team Sport Coaching.’ International Sport Coach­ing Journal 2:152–68. Heller, R., and T. Hindle. 2001. Veliki poslovni prirocnik. Mladinska kn­jiga. Jawoosh, H. N., H.A.Alshukri, M. H. Kzar,M.N.Kizar, M.A. A.Ameer, and M. R. A. Razak. 2022. ‘Analysis of Coaches’ Leadership Style and Its Impact on Athletes’ Satisfaction in University Football Teams.’ International Journal of Human Movement and Sports Sciences 10 (6): 1115–25. Jin, H.,S.Kim,A.Love, Y. Jin, andJ. Zhao. 2022. ‘E.ects of Lead­ership Style on Coach-Athlete Relationship, Athletes’ Motivations, and Athlete Satisfaction.’ Frontiers in Psychology 13:1012953. Kahneman, D. 2017. Razmišljanje, hitro in pocasno. umco. Kahneman, D., and G. Klein. 2009. ‘Condition for Intu6itive Expertise: AFailure to Disagree.’ American Psychologist 64 (6): 515–26. Kaya, A. 2014. ‘Decision Making by Coaches and Athletes in Sport.’ Pro­cedia: Social and Behavioral Sciences 152:333–8. Khasawneh, S., A. Alomati, and A. Abu-Tineh. 2011. ‘Decision-Making Styles of Department Chairs at Public Jordanian Universities: A High-Expectancy Workforce.’ Tertiary Education and Management 17 (4): 309–18. Klein, G. 2008. ‘Naturalistic Decision Making.’ The Journal of the Human Factors and Ergonomics Society 50 (3): 456–60. Klein, G. 2015. ‘A Naturalistic Decision-Making Perspective on Study­ing Intuitive Decision Making.’ Journal of Applied Research in Memory and Cognition 4:164–8. [51] Kolar, E., and M. Tušak. 2022. ‘The Decision-Making Style Structure of Slovenian Sport Managers.’ Annales Kinesiologiae 13 (1): 47–73. Kolar, E., M. Kovac, and S. Piletic. 2006. ‘Ravnanje s športniki v konven­cionalnih športnih panogah.’ In Gimnastika za trenerje in pedagoge 2, edited by E. Kolar and S. Piletic. Gimnasticna zveza Slovenije. Kolar, E., R.Biloslavo, R. Pišot,S. Velickovic, andM.Tušak.2025. ‘Con­ceptual Framework of Coaches’ Decision-Making in Conventional Sports.’ Frontiers in Psychology 15:1498186. Kozhevnikov, M. 2007. ‘Cognitive Styles in the Context of Modern Psy­chology: Toward an Integrated Framework of Cognitive Style.’ Psy­chological Bulletin 133(3): 464–81. Krasniqi,B. A., G. Berisha, andJ. S.Pula. 2019.‘Does Decision-Making Style Predict Managers’ Entrepreneurial Intentions?’ Journal of Global Entrepreneurship Research 9(68): 1–15. Lyle, J.W.B., andB.Muir. 2020. ‘Coaches’ Decision Making.’ In The Routledge International Encyclopedia of Sport and Exercise Psychology. Routledge. Marshall, M. K. 2006. ‘The Critical Factors of Coaching Practice Leading to Successful Coaching Outcomes.’ PhD diss., Antioch University. Martindale, A., and D. Collins. 2007. ‘Enhancing the Evaluation of Ef­fectiveness with Professional Judgement and Decision Making.’ The Sport Psychologist 21:458–74. Mitchell, J. R.,D.A.Shepherd, andM.P.Sharfman. 2011. ‘Erratic Strate­gic Decisions: When and Why Managers are Inconsistent in Strate­gic Decision Making.’ Strategic Management Journal 32:683–704. Nash, C., and D. Collins. 2006. ‘Tacit Knowledge in Expert Coaching: Science or Art?’ Quest 58:464–76. Noh, Y. K., K.Lee,and C. H. Bum. 2018. ‘The Relationship between Soc­cer Club Coaches’ Decision-Making Style, Basic Psychological Needs, and Intention to Continue to Exercise: Based on Amateur Male Soc­cer Club Members in Korea.’ Social Science 7 (1): 200. Phillips, S. D., N. J. Pazienza, and H. H. Ferrin. 1984. ‘Decision-Making Styles and Problem-Solving Appraisal.’ Journal of Counselling Psy­chology 31(4): 497–502. Post, G., and T. van Gelder. 2023. ‘Seven Kinds of Decisions Sports Coaches Make.’ Strategies: A Journal for Physical and Sport Educators 36 (5): 24–36. [52] Reyna, C.,M.V.Ortiz, and R. G. Revilla. 2014. ‘ExploratoryStructural Equation Modelling of General Decision-Making Style Inventory.’ Revista de Psicologia 23 (1): 33–9. Richards, P., D. Collins, and D. R. Mascarenhas. 2016. ‘Developing Team Decision-Making: A Holistic Framework Integrating Both On-Field and O.-Field Pedagogical Coaching Processes.’ Sports Coaching Re­view 6:57–75. Rowe, A. J., and J. D. Boulgarides. 1992. Managerial Decision Making: A Guide to Successful Business Decisions. McMillan. Scott, S. G., and R. A. Bruce. 1995. ‘Decision-Making Style: The Devel­opment and Assessment of a New Measure.’ Educational and Psycho­logical Measurement 55 (5): 818–31. Secchi, D. 2010. Extendable Rationality: Understanding Decision Making in Organizations. Springer. Simon, H. A. 1976. ‘From Substantive to Procedural Rationality.’ In Method and Appraisal in Economics, edited by S. J. Latsis. Cambridge University Press. Spicer, D. P., and E. Sadler-Smith. 2005. ‘An Examination of the General Decision-Making Style Questionnaire in Two uk Samples.’ Journal of Managerial Psychology 20 (2): 137–49. Urieta,P., A. Aluja, L. F. Garcia, F. Balada, and E.Lacomba.2021. ‘Deci­sion-Making and the Alternative Five Factor Personality Model: Ex­ploring the Role of Personality Traits, Age, Sex and Social Position.’ Frontiers in Psychology 12:717705. Tabachnick, B.G., andL.S.Fidell. 2007. Using Multivariate Statistics. 5th ed. Pearson Education. Taber, K. S. 2018. ‘The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education.’ Research in Science Education 48:1273–96. Thunholm, P. 2004. ‘Decision-Making Style: Habit, Style or Both?’ Per­sonality and Individual Di.erences 36:931–44. Till, K. A.,R.Muir, A. Abraham, D. Piggott, andJ. Tee.2019. ‘A Frame­work for Decision-Making within Strength and Conditioning Coach­ing.’ Strength and Conditioning Journal 41 (1): 14–26. Vroom, V. H. 2003. ‘Educating Managers for Decision-Making and Lead­ership.’ Management Decision 41 (10): 968–78. Wilson, P. J., and J. Kiely. 2023. ‘Developing Decision-Making Exper­tise in Professional Sports Sta.: What We Can Learn from the Good Judgement Project.’ Sports Med Open 9 (1): 100. ijems | scientific article Knowledge Management Index for Better Climate Change Management: A Case Study in the Egyptian Petroleum Sector aly a. ahmed mohamed salaheldin Alexandria University, Egypt Sidpec, Egypt aly.ahmed_pg@alexu.edu.eg msalaheldin@sidpec.com mohamed shaltout ahmed elshazly Alexandria University, Egypt Heliopolis University mohamed.shaltot@alexu.edu.eg and Alexandria University, Egypt ahmed.elshazly@hu.edu.eg Climate change presents signi.cant challenges to organizations, re­quiring adaptation and mitigation strategies grounded in climate-related knowledge and technological innovation. The petroleum sec­tor faces increasing regulatory and environmental pressures. In re­sponse, this study introduces the Climate Change Knowledge Man­agement Index (cki), a novel metric designed to assess climate knowl­edge preparedness by integrating energy, environmental, and knowl­edge management systems. The cki provides a standardized frame­work for evaluating how petroleum organizations manage, formalize, and apply climate-relevant knowledge in strategic decision-making. The index was applied to two Egyptian petroleum companies with dif­fering knowledge management approaches, revealing notable di.er­ences in climate resilience. The company with formal knowledge man­agement practices scored 0.283, demonstrating stronger integration, lower emissions, and more informed climate decisions. In contrast, the comparison company scored 0.133. Both scores were benchmarked against an optimal value of 0.606. These .ndings highlight the role of structured knowledge management in strengthening climate re­silience and supporting strategic choices across high-emission sectors. The cki equips decision-makers with a practical tool to evaluate and improve knowledge governance, particularly in developing economies. Its diagnostic capacity o.ers valuable guidance for sectors transition­ing toward sustainable operations. Key Words: climate change management, knowledge management index, strategic decision-making, energy management systems, environmental management systems, petroleum sector © 2024 Aly A. Ahmed, Mohamed Shaltout, Mohamed Salaheldin, and Ahmed Elshazly https://doi.org/10.70908/2232-6022/18.53-82 [54] introduction Applying a Knowledge Management System (kms) is pivotal in enhanc­ing organizational performance, particularly in the petroleum sector, which operates under complex environmental and operational con­straints (Abdelwhab Ali et al. 2019). Organizations in this industry must comply with stringent environmental regulations while main­taining e.cient and uninterrupted operations. To meet these dual demands, a kms is essential for capturing, preserving, and sharing critical institutional knowledge (Orsato et al. 2017). Beyond protecting technicalknow-how,ane.ective kms enhancesadaptabilitybylinking employee expertise with structured organizational systems (Yang et al. 2024). Previous research has emphasized the strategic role of kms in improving climate change management and operational resilience (Ahmed and Elshazly 2021). The Egyptian petroleum sector stands at a critical intersection be­tween economic growth and environmental vulnerability. Beyond its economic signi.cance, the sector’s exposure to climate-induced disrup­tions, ranging from infrastructure damage due to sea-level rise to oper­ational ine.ciencies caused by temperature extremes, poses challenges beyond traditional risk management frameworks (Shaltout et al. 2015; Shaltout 2019). In response, there is a growing emphasis on aligning operational practices with international climate commitments, notably Egypt’s rati.cation of the Paris Agreement (United Nations 2015) and its national e.orts toward achieving Sustainable Development Goals (sdgs) 7 and 13 (United Nations 2015). Addressing these challenges de­mands a strategic shift: organizations must embed knowledge-driven resilience mechanisms that interlink environmental stewardship, en­ergy management, and institutional learning within their core business models. The Egyptian petroleum sector plays a strategic economic role, con­tributingapproximately24.ofthenational gdpwhilesimultaneously facing acute climate risks, such as coastal .ooding and rising sea tem­peratures (Shaltout et al. 2015). This dual vulnerability necessitates the adoption of integrated management systems that balance opera­tional continuity with climate adaptation imperatives. However, exist­ing frameworks often fail to adequately represent these unique sectoral challenges, reinforcing the need for more targeted climate knowledge management initiatives. At the macroeconomic level, the Knowledge Economy Index (kei), developedbythe WorldBankInstitute,providesabenchmarkfor evalu-[55] ating how countries utilize knowledge to drive innovation and sustain­ability (World Bank 2009). However, for industries exposed to climate-related risks, such as the petroleum sector, there is an increasing need tointegrate kms withEnergyManagementSystems(enms)andEnvi­ronmental ManagementSystems (ems).Janus(2016)emphasizesthat embedding kms within environmental strategies is vital for building long-term resilience. The theoretical foundations of Knowledge Management (km) in high-risk industries draw heavily from Nonaka’s (1994) seci model, which identi.es four knowledge conversion processes: socialization, externalization, combination, and internalization. This model explains how frontline operational expertise (e.g., emission reduction tech­niques) becomes institutionalized through documentation and train­ing in climate change contexts. Recent global developments have further accelerated the integra­tion of knowledge systems with sustainability e.orts. The growing reliance on Environmental, Social, and Governance (esg) reporting frameworks, such as those developed by the Global Reporting Initia­tive (2021) and the World Economic Forum’s stakeholder capitalism metrics (World Economic Forum 2020), compels petroleum companies to demonstrate tangible knowledge management practices related to environmental stewardship. Furthermore, international .nancial in­stitutions increasingly link credit ratings and investment decisions to demonstrated climate resilience, emphasizing the strategic importance of formalized climate knowledge systems within corporate governance structures (Global Reporting Initiative 2021; World Economic Forum 2020). International .nancial institutions increasingly link credit rat­ings and investment decisions to demonstrated climate resilience, fur­ther elevating the strategic importance of formalized climate knowl­edge systems within corporate governance structures. This integration has been gaining attention in Egypt. Implement­ing iso 50001 enms has led to measurable improvements in energy e.ciency and reductions in greenhouse gas emissions. (Salaheldin et al. 2015). Complementing this, structured decision-making tools such as the Analytic Hierarchy Process (ahp) and Fuzzy ahp have proven valuable for prioritizing sustainability projects across environmen­tal, economic, and social pillars (Galal and Moneim 2015; Salaheldin 2009; Salaheldin et al. 2015). While kei and ahp-based tools exist, [56] none integrate kms, enms, and ems into a uni.ed framework for sector-speci.c climate resilience assessment, particularly within the petroleumsector. The cki introducedinthisstudyisthe.rstdiagnos­tic tool to combine these management systems into a uni.ed, opera­tionalized framework, enhancing climate resilience. This study addresses this gap by introducing the Climate Change Knowledge Management Index (cki), a novel framework designed to evaluate how organizations manage climate-related knowledge by in­tegrating kms, enms, and ems practices. The cki leverages interna­tional standards and structured methodologies, such as ahp, to pro­vide a multi-criteria evaluation system tailored to the complexities of the petroleum sector. Given its strategic economic role and growing vulnerability to cli­mate-related risks, the Egyptian petroleum sector is a .tting context for this study. Cross-sectoral collaboration is vital in this landscape, as Penca et al. (2024) argue that building transdisciplinary competen­cies is essential for developing actionable solutions to sustainability challenges. Furthermore, the scienti.c contributions of Shaltout et al. (2015) and Shaltout’s (2019) work, particularly on sea-level rise and sea surface temperature trends, underscore the urgent need to translate environmental data into operational strategies. This research also builds upon broader regional initiatives to pro­mote green transformation in industrial sectors across North Africa. Recent national strategies, such as Egypt’s Integrated Sustainable En­ergy Strategy (ises) 2035 (Ministry of Electricity and Renewable En­ergy 2016), emphasize the importance of coupling energy and envi­ronmental management systems with knowledge-based innovation as essential for advancing sustainable development. Thus, the Climate Change Knowledge Management Index (cki) addresses immediate or­ganizational needs and contributes to Egypt’s broader national objec­tives toward achieving a greener, more resilient economy (Ministry of Electricity and Renewable Energy 2016; United Nations 2015). Accordingly, this study aims to develop and validate the cki as a practical, scalable tool for enhancing climate resilience in the Egyptian petroleum sector. literature review: theoretical and methodological foundations While the introduction outlined the rationale for integrating km into climate resilience e.orts, this section comprehensively reviews the the­oreticalandmethodologicalfoundationssupportingthecki’sdevelop-[57] ment. kms has long been recognized as a catalyst for innovation and adaptability, particularly in complex, high-risk industries like the pe­troleum sector (Abdelwhab Ali et al. 2019). The World Bank’s Knowl­edge Economy Index (kei) provides a foundational framework for as­sessing national knowledge infrastructures, highlighting how e.ective knowledge use contributes to long-term sustainability (World Bank 2009). However, the kei lackstheoperationalgranularity necessaryto evaluate km performance within individual organizations or speci.c sectors. Building on this global perspective, national-level studies have in­creasingly emphasized the importance of formalized knowledge sys­tems in speci.c sectors. Previous research emphasized kms’s strategic role in supporting climate change adaptation and operational continu­ity in Egypt’s energy sector. Ahmed and Elshazly (2021) highlight the urgent need to formalize tacit knowledge .ows into structured systems for resilience building. In parallel with knowledge management devel­opment, structured decision-making methodologies have emerged as critical tools for evaluating sustainability priorities. Researchers and practitioners increasingly rely on structured deci­sion-making methods to prioritize and assess complex environmen­taland operationalcriteria. Among these,the Analytic Hierarchy Pro­cess (ahp), developed by Saaty (1980), remains predominant. In the Egyptian context, Galal and Moneim (2015) applied ahpto develop a sustainability index that balances economic, environmental, and social considerations, an approach conceptually aligned with the cki intro­duced in this study. While ahpo.ers a solid foundation for prioritization, emerging hybrid models have further enhanced decision-making under uncer­tainty. However, while ahpprovides a structured prioritization meth­od, its reliance on subjective pairwise comparisons introduces poten­tial bias. This study mitigates such risks by employing expert valida­tion techniques and consistency ratio checks during the matrix devel­opment. Hybrid models such as Fuzzy ahp(Salaheldin 2009) have gained traction in enhancing decision-making under uncertainty. Notably, Salaheldin (2009; Salahedin et al. 2015) applied both ahpand Fuzzy ahpto prioritize energy improvement projects and evaluate the per­formance of energy management systems in Egyptian industrial fa­ [58] cilities. These studies illustrate how integrating kms with structured frameworks such as enms and ems can support more sustainable and e.cient operations. Building on this foundation, the cki extends these tools to evaluate knowledge management maturity in the con­text of climate resilience. However, operationalizing climate knowledge resilience also requires addressing fundamental challenges related to knowledge conversion processes. Knowledge Conversion Challenges in Climate Resilience The theoretical foundations of knowledge management in high-risk sectors, such as the petroleum sector, heavily rely on Nonaka’s (1994) seci model, which outlines four knowledge conversion processes: so­cialization, externalization, combination, and internalization. While socialization (informal tacit knowledge sharing) predominates front-line climate adaptation practices, formalizing this knowledge remains an ongoing challenge. The ‘know-how paradox,’ where critical safety or operational expertise resists documentation (Orsato et al. 2017), along with the knowledge attrition linked to aging workforces (Abdelwhab Ali et al. 2019), presents signi.cant barriers. Empirical studies reinforce this gap: iso 30401-certi.ed kms im­plementations have been shown to improve climate resilience metrics by 18–22. in comparable sectors (Janus 2016). However, Salaheldin et al. (2015) found that approximately 63. of climate-related operational knowledge remains tacit in the Egyptian petrochemical sector, under­scoring the critical need for structured knowledge conversion systems. These insights align with .ndings from Ahmed and Elshazly (2021), which emphasized km maturity gaps in Egyptian energy .rms and highlightedthenecessityofintegrated km benchmarkstosupportsus­tainability transitions. External regulatory frameworks also shape cli­mate knowledge management practices alongside internal knowledge dynamics. Regulatory Context and Sectoral Imperatives Egypt’s national 2030 sustainability agenda mandates the integration of Environmental Management Systems (ems) and Energy Manage­ment Systems (enms) across industrial sectors. However, as noted in Ahmed and Elshazly (2021), no standardized framework for bench­marking Knowledge Management System (kms) maturity exists against these environmental standards. The cki addresses this regulatory gap by o.ering a scalable diagnostic tool that aligns knowledge governance [59] with broader sustainability mandates, enhancing compliance and orga­nizational resilience. Beyond organizational and regulatory considera­tions, integrating ecological knowledge has become increasingly vital for comprehensive climate resilience. Ecological Context for Climate Knowledge Integration Beyond traditional organizational frameworks, recent studies highlight the ecological dimensions of climate knowledge integration. Mangrove ecosystems, for example, play a critical role in carbon sequestration, of­feringnaturalsolutionstorising co2 levels (Awad et al. 2023). Integrat­ing such environmental insights into ckm systems enables petroleum organizations to align operational strategies with environmental sus­tainabilitygoals.The cki encouragesincorporatingecologicaldatainto strategic planning processes, supporting more holistic approaches to climate resilience. In summary, existing literature lacks a sector-speci.c framework to assess how petroleum organizations structure, prioritize, and utilize climate-relatedknowledge.The cki isdesignedto.llthisgapbydraw­ing on existing models like ahp, enms, and ems and aligning them withinauni.ed kms-basedevaluationframework.Thisinnovativetool is both a diagnostic instrument and a strategic guide for organizations striving for knowledge-driven climate resilience. methodology Methodology Description The research methodology primarily relies on analyzing questionnaires using structured techniques. It begins with designing a draft question­nairebased on thestudy objectives. Thedraft wasreviewed through structured interviews with .eld experts to enhance its accuracy. After revisions, the .nalized version was distributed online to reach the maximum number of targeted respondents. Additionally, to ensure the clarity and reliability of the survey, we followed three key validation steps: expert review, cognitive interviewing, and usability testing, as recommended by Beatty et al. (2020). Aly A. Ahmed et al. table 1 Hierarchy of Key Performance Indicators (.) (.) (.) (.) (.) (.) enms ien e. Percentage of employees having Awareness sessions I11 Max of the enms [60] e. Energy intensity I12 Min e. Energy e.ciency midterm target [.] (.–. years) I13 Max ems iev n. Percentage of employees having Awareness sessions I21 Max of ems n . Percentage of direct and indirect ghg emissions from I22 Min sources owned or controlled by the company and from the generation of acquired and consumed electric­ ity, steam, heat, or cooling (collectively referred to as ’electricity’) (Scope . & .) [tons] n. Percentage of all indirect ghg emissions (not in­ I23 Min cluded in Scope .) that occur in the value chain of the reporting company, including both upstream and downstream emissions (Scope .) [tons] kms ikm k. Percentage of employees having Awareness sessions I31 Max of the kms k. The percentage of climate–related ideas collected from I32 Max employees k. Percentage of climate–related converted knowledge I33 Max (implicit to explicit) notes Column headings are as follows: (1) main system, (2) pillar, (3) kpi, (4) kpi descriptions,(5) id foreach kpi,(6)theoptimaldirections. Appreciationof ghg refers to Greenhouse Gases. The structured interviews involved asking all participants the same questions in a .xed order (Rashidi et al. 2014). These questions cover the level of importance of each Key Performance Indicator (kpi) in re­lation to the others in each pillar listed in table 1. Structured interviews were employed to ensure consistency in data collection. This approach allowed for a standardized set of questions, facilitating comparability across responses and reducing potential bi­ases in data interpretation (Rashidi et al. 2014). The methodology was implemented through nine steps: 1 Initial design of the .rst questionnaire. 2 Structured interviews to adjust the .rst questionnaire. 3 Designing the .rst questionnaire and distributing it by using Google Forms. 4 Collect and analyze the results. 5 Calculate the weight of each pillar. 6De.ne three kpis for each pillar. 7 A second structured interview with only decision-makers to cal­ culate the weight of kpis. [61] 8De.ne the formula to calculate cki. 9 Apply this formula to two di.erent companies. The cki was applied to two companies within the Egyptian petro­leum sector. One has implemented a kms in compliance with iso 30401, while the other has not, allowing for a clear comparison of the index’s performance under di.erent km conditions. Both com­panies had previously adopted energy management systems, ensuring a fair basis for comparison. Access to performance data in this sector is typically restricted, which further shapes the scope of the application. Given these constraints, a focused two-company application was con­sideredappropriate fortheinitialvalidationofthe cki.Thegoalatthis stage was not to generalize .ndings, but to assess the index’s practical relevance. Broader applications are recommended in future research to con.rm its robustness across the sector. The questionnaires include quality control questions to measure the respondents’ seriousness and relevance to the .eld of research. The .rst questionnaire was built to measure the weight of the three main pillars using 15 questions, as seen in Appendix 1. Then, a struc­tured interview with six experts was conducted: an operations man­ager in a petrochemicals company, a quality manager of an oil re.ning company, an energy e.ciency manager in a petrochemicals company, the exploration manager in an upstream company, and the head of the oceanography department at Alexandria University. This structured in­terview omits three questions, adds two new questions, and clari.es three of the existing questions. The .nal questionnaire consists of 14 questions, including personal information, nature of work, and techni­cal information (Appendix 2). The adjusted form of the .rst questionnaire was distributed using Google Forms and was valid for two weeks (from January 22, 2023 to February 5, 2023). This questionnaire was only distributed within the Egyptian petroleum sector and was valid for all its categories and dis­ciplines. The quality control strategy accepts only the responses that complete their information and answers. The second survey started with a structured interview technique de­signed only for organizational decision-makers. It was performed to identify the speci.c weight of each kpi inside each main pillar. The questionnaire design strategy involved using the ahp, as de­ scribed by Saaty (1980). This method was employed to calculate the [62] weights of each pillar and all its corresponding kpis. In addition, theInconsistencyIndex (ici)was used as aquality con­trol factor. First, a Consistency Ratio (cr) is used to measure how con­sistent the judgments have been relative to large samples of purely ran­dom judgments. If the cr is over 0.1, then the judgments should be considered untrustworthy, as explained by Salaheldin et al. (2015). Analytical Hierarchy Process (ahp) The ahp,developedbyThomasSaatyin1980,isawidelyuseddecision­making tool based on pairwise comparisons. It assigns relative weights to key factors, in this study, enms, ems, and kms, through a struc­tured comparison process (Saaty 1980). Pairwise comparisons provide numerical values for the relative importance of each factor, helping de­termine the priority vector for further calculations. This study used the .rst survey to evaluate the three main pillars, and the second survey was to assess the kpis across three hierarchical levels. This approach ensures rational decision-making by comparing two elements at a time without external in.uence (Saaty 1990). Weighting Criteria Using ahp ahpwas applied to determine the relative importance of criteria and sub-criteria, using a nine-point scale to rank their signi.cance (Saaty 2008). Six pairwise comparison matrices were created to evaluate the main hierarchy (enms, ems, and kms) (Ramík 2020). This method is furthersupportedbySalaheldin(2009),whoutilized fahpforbideval­uations in petrochemical projects, and Salaheldin et al. (2015), who ap­plied ahpfor energy e.ciency optimization in the petrochemical sec­tor. The evaluation comparison scale used to assess the relative impor­tance between factors follows Saaty’s (1980) nine-point scale in the An­alytic Hierarchy Process (ahp). Experts used Saaty’s scale, where 1 indi­cates equal importance and 9 represents extreme importance. Interme­diate values 3, 5, and 7 correspond to moderate, strong, and very strong importance, respectively. A detailedsummary of theentirecomparison scale is provided in Appendix 2. table 2 Pairwise Comparison Matrix for a hpCalculations a a . b a c a b ./a . ./b c Sum ./a c . [63] The pairwise comparison process adheres to Saaty’s (1980) ahp methodology, wherein criteria are evaluated relative to one another to derive a consistent priority vector. Table 2 presents the structural form of the comparison matrix employed in this study. The decision makers’ judgment may be inconsistent; therefore, it was necessary to analyze the inconsistency of the pairwise compari­son. This was achieved by calculating the ici and Inconsistency Ratio (icr). The preference ratings given by the decision-makers were con­sidered consistent if the icr was less than or equal to 0.1. The ici and icr were calculated using equations (1) and (2), respectively. .max -n icr = , (1) n - 1 icr ici = . (2) ri Where n is the size of the comparison matrix, .max is the eigenvalue, and ri istherandomindexdependingonthematrixsize.Thepairwise comparison is to be conducted by many decision-makers to arrive at the relative weight for each criterion. The weights obtained from the subjective judgment of each decision maker are aggregated using the geometric mean as per equations (3) and (4):  1 n n mw1ij =  mw1ij m=1 For all i and j, (3) 1  n   n mwkl = mwkl For all k and l. (4) m=1 th Where wm 1ij indicates the weight w1ij given by the m decision maker, and n represents the number of decision-makers involved in setting the criteria preferences. In the current study, the geometric mean prioritizes all elements. The advantage of the geometric mean is that it gives equal weight to each number in the set, which can be helpful when calculating growth rates or rates of return. The disadvantage is that it cannot be used with negative numbers (Vogel 2022) which is not considered in our study. The t-test is applied to measure the main di.erences between the ge­ ometric means. The t-test is a statistical test used to identify whether [64] the di.erence between two means is signi.cant or not (Liang et al. 2019). The cki Hierarchy The cki is measured in terms of three main pillars represented: (a) enms,(b) ems,and(c) kms.Toassessthedegreeofconformancecon­cerning each pillar, several kpis consider each pillar’s main aspects. Thus, a hierarchy of kpis is suggested as shown in table 1. The .rst level of the hierarchy includes the three pillars of enms, ems, and kms. ThesecondLevelinthehierarchyrepresentsthe kpis’ identi.cation (id),de.nition,andimprovementdirection,whicharepresented inta­ble1.All theseindicators haveone levelofsubcategories andare thus labelled Ikl. Two su.xes identify each indicator: the .rst (k)indicates the main pillar, and the second (l)indicates the kpis. The following criteria are considered in selecting the relevant indi­cators (Galal and Moneim 2015): • Measurability: This can be measured using quantitative or quali­tative data. • Ease of access to data is based on readily available data in the facility; no extra e.ort is needed for data collection. • Non-dimensionality: This is indicated as a ratio of the same units to facilitate the aggregation of all indicators into a single dimen­sionless value. • Relevancy: relates directly to the dimensions of sustainability. The de.nition and formula of each indicator will be discussed as fol­lows. The enms Pillar (ien) It measures the extent to which the organization controls its energy consumption, including promoting awareness and managing consump­ tion practices. In addition, this pillar evaluates the organization’s eco­ nomic approach to managing its climate change knowledge. The kpis are: • Percentage of employees having awareness sessions of enms: no. of employees have energy management systemawareness sessions I11 = (5) total number of employees • Energy intensity [65] $ value of eneregy consumption I12 = 1 - (6) $ value of total inputs of production • Energy e.ciency midterm target [.] (3–5 years) $ value of eneregy consumption I13 = (7) $value of totalinputsof production The ems Pillar (iev) It measures the extent to which emissions from any organizational pro­cess are controlled. This pillar also measures the number of employees aware of this system and its e.ect. The key performance indicators are: • Percentage of employees having Awareness sessions of ems: no. of employees have environment managementsystem awareness sessions I21 = (8) total number of employees • Percentage of direct and indirect ghg emissions from sources owned or controlled by the company and from the generation of acquired and consumed electricity, steam, heat, or cooling (collectively referred to as ’electricity’) (Scope 1 & 2) [tons]: total direct and indirect emissions (Scope 1 & 2) I22 = 1 - (9) weight of annual emissions quantity produced (All Scopes) • Percentage of indirect ghg emissions (not included in Scope 2) that occur in the value chain of the reporting company, including both upstream and downstream emissions (Scope 3) [tons]: Total indirect emissions (Scope 3) I23 = 1 - (10) weight of annual emisions quantity produced (All Scopes) The kms Pillar (ikm) It measures the value added by sharing knowledge and its e.ciency. This represents the social e.ect of key performance indicators that re­.ect the well-being of the laborers and their development. The key per­formance indicators are: • Percentage of employees having Awareness sessions of kms: no. of employees have knowledge managementsystem awareness sessions I31 = (11) total number of employees [66] • Percentage of climate-related collected ideas from employees annually: no. of climate related ideas I32 = (12) total number of ideas • Percentage of climate-related converted knowledge (implicit to explicit): no. of converted climate related knowledge I33 = (13) totalnumberofconverted knowledge Calculating the cki Thecalculationofthe cki isachievedintwosteps. Firststep,the kpis within each of the three pillars are algebraically added using their re­spective weight to obtain a single measure for each. The three resulting measures are the ien, iev, and ikm, which are obtained using equa­tions (14–16), respectively. 3  Ien = w1iI1i (14) i=1 3  Iev = w2iI2i (15) i=1 3  Ikm = w3iI3i (16) i=1 Second step, the three resulting pillars are considered as three com­ ponentsofavectorinathree-dimensionalspacetoarriveatthe cki as per equation (17):  cki = I2 +I2 +I2 (17) en ev km results The study initially collected 52 responses during the questionnaire’s time frame. However, two responses were removed due to incomplete information, and an additional nine responses were excluded because they were not employed in the petroleum sector. Moreover, .ve re­ sponses were rejected based on the quality control criterion, speci.cally due to a high inconsistency ratio. As a result, 36 valid responses were retained for analysis. First Questionnaire (Target Group Whose Occupation Is Related to [67] the Petroleum Sector) The survey of 36 Egyptian petroleum professionals revealed a signi.­cant operational disparity: downstream operations (oil re.ning, petro­chemicals, gas processing plants) accounted for 86. of responses (n = 31), with representation from oil re.ning (42., n =13),petrochemicals (32., n = 10), natural gas processing (13., n = 4), and service providers in o&m, hse, and maintenance (13., n = 4). In contrast, (Oil & Gas Exploration and Production) represented only 14. (n =5). This distribution highlights the strong representation of process­ing/manufacturing roles and potentially lower engagement in upstream operations with climate change knowledge initiatives. The .ndings sug­gest: • Upstream professionals may be less aware of or engaged with cli­mate initiatives. • Targeted awareness programs are needed for exploration/pro­duction teams. • Further research should investigate speci.c knowledge gaps. Notably, gender analysis showed no signi.cant di.erences in re­sponse patterns across sectors. The Upstream Category The results indicate that, according to industry sectors and the up­stream category, workers in this sector tend to place greater importance on awareness about energy management and climate change knowl­edge than on other drivers (enms, ems, and kms). The upstream category has .ve responses: • All participants are male, as women are rarely represented in up­stream .elds. • 4 outofare 5inthe agerange 35–45, 1out of 5is inthe agerange 45–55. • All participants hold middle management positions. • All participants work in operational .elds. Aly A. Ahmed et al. table 3 The Geometric Mean Values for the Upstream and Downstream Categories Pillar Upstream Downstream Geometric Mean Normalized Geometric Mean Normalized ien ...... ...... ...... ...... [68] iev ...... ...... ...... ...... ikm ...... ...... ...... ...... As shown in table 3, employees working in the upstream segment of the petroleum industry reported that ems had the highest in.u­ence on their knowledge about climate change, with a share of 41.76.. The enms camenext,accountingfor39.24.oftheimpact. Meanwhile, kms wasseenashavingaminorrole,contributingonly19.00.totheir understanding. These results suggest that ems and enms primarily shape climate-related knowledge in upstream operations, while kms practices may still need further attention. The Downstream Category The downstream category is divided into re.ning, petrochemicals, nat­ural gas, and services industries (table 3). The results indicate that work­ers in this sector tend to place greater importance on awareness about environmental management and climate change knowledge than on other drivers (enms, ems, and kms). The downstream category has 31 responses: • 2 out of 31 are female, and 29 out of 31 are male. • 4 outof31 are in theage range25–35,18out of 31 are inthe age range 35–45, 8 out of 31 are in the age range 45–55, and 1 out of 31 is in the age range above 55. • 8 out of 31 are senior-level, 16 out of 31 are middle management level, and 7 out of 31 are top-level management. According to the results presented in table 3, most workers in the downstream segment identi.ed enms as the most in.uential factor in shaping their climate change knowledge, with a score of 45.05.. The ems followedat36.46., while kms hadthe leastreportedimpactat 18.47.. These .ndings highlight the central role of energy and environ­mental systems in promoting climate awareness in downstream oper­ations and suggest an opportunity to improve kms’s contribution in this area. The segmentation of respondents based on their .eld of work, in­ table 4 Fields of Work Pillar (.) (.) (.) (.) (.) (.) (.) ien ...... ...... ...... ...... ...... ...... ...... iev ...... ...... ...... ...... ...... ...... ...... ikm ...... ...... ...... ...... ...... ...... ...... [69] notes Columnheadingsindicatethegeometric.eldofeach.eldasfollows:(1)Op­erations, (2) Maintenance, (3) Energy Management, (4) Quality Assurance, (5) Health, Safety and Environment (hse), (6) Management, and (7) Administration. cluding operations, maintenance, and management, reveals that the majority are from operations (50.), followed by maintenance and con­dition monitoring (8.), quality assurance (8.), health, safety, and en­vironment (hse) (8.), administration (8.), laboratory (3.), energy management (8.), and management (6.). The responses from operations personnel indicate no signi.cant di.erencebetween theimpactof enms and ems onclimate change knowledge, as demonstrated in table 4. Responses from the mainte­nance .eld of work, hse, management, and administration personnel were consistent with expectations, given that their work largely ad­heres to standards, and the only .eld with standardized regulations is environmental management. The responses from energy management professionals aligned with expectations, re.ecting their focus on their specialized .eld. Quality assurance sta. shared a similar perspective, with heightened concern for ems. Regarding the managerial level, middle management positions com­prise 58.33. of the respondents, senior-level roles make up 22.22., and top-level management constitutes 19.44.. Lastly, the geometric mean is normalized for the .ltered data, and the analysis reveals that the ems exertsthemostsigni.cantin.uenceonclimatechangeawareness within the organization (43.92.), followed by the enms (37.43.). The kms exhibits the least impact, contributing 18.64.. Accordingly, the second questionnaire was conducted with decision-makers through a structured interview to determine the weights of in­dicators for each pillar mentioned above. Second Questionnaire (Target Group: Decision-Makers Working in the Egyptian Petroleum Sector) The second questionnaire was a structured interview conducted with 10 decision-makers working in the Egyptian petroleum sector to evaluate ...... ...... . figure 1 . . . kpis of enms . . . . . . .. ...... ...... e. ...... ...... ...... ...... . figure 2 ...... . . ems’s kpis . . . . . . . .. ...... ....... . . . . . . . . ... figure 3 kms’s kpis theweightofthe KeyPerformance Indicators (kpis) thatmay a.ect the knowledge of each pillar in this study (table 1). First,themain kpis andtheirweightsforthe enms arelistedinta­ble6andshown in .gure1.Theresults highlightthe greatersigni.cance of raising employee awareness compared to other kpis. Secondly, for the ems, table 6 lists the selected main kpis and their weights. The results show the importance of raising employee awareness over the other kpis as seen in .gure 2. Finally, the main selected kpis and their weights for the kms, as [71] listed in table 6, show that raising awareness among employees is con­sidered more important than the other kpis, as illustrated in .gure 3. Final Weights The.nalweightsforeach kpi (refertotable1fordescriptions)werede­rived through ahppairwisecomparisons.For enms,employeeaware­ness sessions (e1) received the highest weight (0.63), followed by en­ergy intensity (e2) and midterm targets (e3) at 0.12 and 0.25, respec­tively. A similar weighting pattern emerged for ems (n1 = 0.73) and kms (k1 = 0.67), con.rming the importance of awareness-building in climate knowledge governance (table 6). framework implementation The proposed framework was implemented to evaluate the cki of two petroleum sector companies in Alexandria, Egypt. Both companies are certi.ed with four quality certi.cates: iso 9001, iso 14001, iso 50001, and iso 45001; however, Company 1 also holds iso 30401. The companies employ between 1,000 and 3,000 sta. members. Selecting two companies with varying levels of kms maturity en­abled testing the framework under di.erent real-world conditions. This diversity enhanced the validation process by demonstrating the cki’s ability to assess organizational readiness across di.erent operational contexts. Moreover, this choice balanced methodological rigor with practical constraints, such as data accessibility within the petroleum sector. Data Collection The data required to calculate the various indicators were collected from the two companies and are presented in table 5. Notably, the data needed for calculating the indicators does not require special data collection, as they are part of the standard data recorded for any plant. These align with other information typically required for di.erent qual­ity systems in use, meaning there is no additional burden associated with the sustainability assessment. Data description . . Aly A. Ahmed et al. table 5 Data Collected from the Two Companies Number of employees who attended enms awareness sessions ... ... Total number of employees .... .... [72] Dollar value of energy consumption (.) ... ... Dollar value of total inputs of production (.) .... .... Number of employees who attended ems awareness sessions ... ... Weight of annual emissions quantity produced (All Scopes) ... .... Total direct and indirect emissions (Scope . & .) ... ... Total indirect emissions (Scope .) ... ... Number of employees who attended kms awareness sessions ... .. Total number of ideas collected from employees annually for devel. ... .. Number of climate-related ideas collected from employees annually .. .. Total number of converted knowledge (implicit to explicit) .. .. Number of climate-related knowledge conversions. .. . notes The (Dollar value $) indicates the .nancial value of the data. Calculations Utilizing multiple existing data sources – such as iso 50001 audit re­ports, iso 14001 compliance documentation, and internal training records – enabled e.ective data triangulation. This cross-veri.cation enhanced both the reliability and validity of the collected information, reducing the potential for bias and ensuring that kpi evaluations ac­curately re.ected actual operational practices rather than isolated doc­uments or individual reports. All quantitative indicators (e.g., energy consumption, emissions data) were validated against the companies’ iso 50001 and 14001 audit reports to ensure reliability. For employee awareness metrics (kpis k1, n1, e1), data were cross-checked with training attendance records to ensure consistency. However, Scope 3 (indirect emissions, kpi n3) relies on supplier self-reports, which is a known limitation in the petroleum sector (Galal and Moneim 2015). This potential bias was mitigated by averaging the responses of multiple decision-makers, thereby enhancing data reliability. Despite the structured approach, speci.c challenges were encoun­tered during data collection. Access to detailed operational data was sometimes restricted due to con.dentiality concerns. Additionally, in­consistencies were observed in how di.erent departments documented their environmental or energy-related knowledge practices. These chal­lenges required careful clari.cation through follow-up interviews and reinforced the need to triangulate .ndings across multiple sources. The veri.ed data were systematically mapped to the corresponding kpis. Where discrepancies existed among documents, interviews, and observations, expert judgment and consensus validation techniques [73] were employed to adjust scoring. This ensured that the .nal cki val­ues accurately re.ected documented practices and operational behav­iors within each organization. While the cki framework was successfully applied, several opera­tional challenges emerged that warrant discussion. First, variations in departmental awareness of knowledge management protocols compli­cated the aggregation of accurate data, especially regarding tacit-to­explicit knowledge conversions. Second, resistance to sharing sensitive environmental and energy information delayed parts of the validation process, highlighting an underlying cultural barrier to open knowledge exchange in petroleum organizations. Despite these challenges, the implementation demonstrated the framework’s .exibility and adaptability. Utilizing pre-existing iso­related data signi.cantly reduced the burden of new data collection, proving that the cki can be integrated with existing quality man­agement systems without requiring major procedural overhauls. This characteristic is critical for encouraging adoption within resource-constrained or operationally conservative sectors. Furthermore,thecross-functionalinvolvementofoperational, hse, energy, and management personnel enriched the quality of the col­lected insights. This suggests that cki assessments are most e.ective when designed as multidisciplinary exercises rather than siloed tech­nical evaluations. Future applications could bene.t from formalizing this cross-functional collaboration early in the assessment process to streamline data collection and enhance diagnostic accuracy. Table 6 shows that the cki was calculated for the companies un­der study using the methodology described in equations (1) through (16), based on the data from table 5. The Climate Change Knowledge Management Index (cki) was mathematically computed according to equation (17), where the summation includes all selected kpis. This approach ensures that indicators with higher strategic importance, as determined by expert judgment, have a greater in.uence on the .nal cki score. A benchmark value of 0.606 was established based on evaluations Aly A. Ahmed et al. table 6 Final Calculations kpi w Company . Company . Ideal Iw×I Iw ×I Iw ×I I11 (e.) ...... ...... ...... ...... ...... ...... ...... [74] I12 (e.) ...... ...... ...... ...... ...... ...... ...... I13 (e.) ...... ...... ...... ...... ...... ...... ...... I21 (n.) ...... ...... ...... ...... ...... ...... ...... I22 (n.) ...... ...... ...... ...... ...... ...... ...... I23 (n.) ...... ...... ...... ...... ...... ...... ...... I31 (k.) ...... ...... ...... ...... ...... ...... ...... I32 (k.) ...... ...... ...... ...... ...... ...... ...... I33 (k.) ...... ...... ...... ...... ...... ...... ...... ien ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... iev ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ikm ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... cki ...... ...... ...... cki/Ideal ...... ...... by an expert panel. This value re.ects a realistic upper limit for mature organizations operating within the petroleum sector and represents the expected integration level of knowledge, energy, and environmen­tal management systems under current best practices. The cki score for the evaluated company that applies the kms was 0.208, equivalent to 46.67. of the theoretical maximum (0.208 0.606 × 100). In contrast, the cki score for the other company was 0.133, representing 21.99. of the theoretical maximum. The .rst company’s higher cki score indicates stronger formal­ization and integration of climate knowledge within its operational strategies. Conversely, the second company’s lower score suggests frag­mented or informal practices, particularly regarding knowledge sharing and environmental sustainability initiatives. This dimensionless index serves multiple purposes: it functions as a performance benchmark, a tool for tracking longitudinal improve­ment, and a comparative metric within the sector. Beyond the aggre-[75] gate cki scores,adeeperanalysisofindividual kpi trendsprovidesad­ditional insights into each organization’s speci.c focus areas and strate­gic behaviors. The resulting scores indicate a considerable opportunity to im­prove the organization’s climate knowledge management practices and progress toward alignment with best-practice standards. The results reveal a clear pattern: companies place greater emphasis on training employees about climate issues (awareness sessions) than on technical indicators like energy use or emissions. They prioritize these training programs three to nine times more than technical objectives. This behavior aligns with knowledge management theories that em­phasize externalization and socialization phases (Nonaka 1994), where cultivating awareness and shared understanding precedes technical system optimization. The results indicate that Egyptian petroleum companies prioritize culturally preparing their teams for climate action rather than merely setting strict targets. This .nding is consistent with Salaheldin et al.’s (2015) conclusion that changing workplace habits is often more com­plicated than achieving technical goals. future work Future research could examine the applicability of this framework in other sectors, particularly those that are resource-intensive or heavily reliant on knowledge management. Tracking the cki over time could provide valuable insights into how organizations mature in manag­ing climate-related knowledge. Moreover, raising awareness about the strategic value of km, not just as a tool for documentation but as a key driver of resilience, should be prioritized. Future studies could also explore the potential for sectoral bench­marking by applying the cki across industries such as mining, chemi­cal manufacturing, or logistics, where climate resilience is increasingly vital. Conducting cross-sector comparisons would validate the index’s adaptability and help re.ne its weighting structures to accommodate sector-speci.c challenges. In addition, future researchers may investigate the integration of digital technologies, such as arti.cial intelligence and blockchain, into cki assessments. Leveraging digital tools could enhance data col­lection accuracy, real-time monitoring, and transparency in climate [76] knowledge governance. Furthermore, integrating Geographic Information Systems (gis) into future cki assessments could provide critical spatial insights into climatevulnerabilities,resourceallocation,and operationalrisks.Com­panies could develop geographically targeted knowledge management strategies by mapping organizational facilities against climate expo­sure data, such as .ood zones, heat stress indices, or coastal erosion maps. This spatial integration would enhance the cki’s ability to guide location-speci.c adaptation planning, operational risk mitigation, and informed decision-making. conclusion The cki representsanovelcontributiontoclimateactionbysystemat­ icallyquantifyingtheroleof km inorganizationalresilience.Itsvalida­ tionacrosstwoEgyptianpetroleumcompanies,onewithan iso 30401­ compliant kms andonewithout,demonstrated strong diagnosticutil­ ity. The company’s signi.cantly higher cki score (0.283 vs. 0.133) with formalized kms implementation underscores the framework’s practi­ cal value for assessing climate knowledge maturity. While this initial study focused on a limited sample, the contrast in outcomes o.ers a robust foundation for future scalability testing across diverse organi­ zational contexts. The cki’s integrative framework bridges critical gaps between En­ergy Management System(enms),Environment Management System (ems), and Knowledge Management System (kms), o.ering a stan­dardized approach to measure climate-related knowledge governance. By translating technical practices into quanti.able metrics, the index aligns with global climate resilience priorities, particularly in high-impact sectors like petroleum. Its application within the Egyptian petroleum sector yielded opera­tionally meaningful results, suggesting the cki’s promise as a sector-speci.c benchmarking tool. Though not yet generalizable, the frame­work’s adaptability supports its use in assessments and cross-industry replication. Finally, the study revealed structural insights: downstream opera­tions showed greater engagement with environmental systems than upstream segments, and middle managers, who accounted for 58. of respondents, emerged as critical actors in climate knowledge dissem­ination. These .ndings point to two strategic imperatives: enhancing climate awareness in upstream operations and continuing investment [77] in middle management development programs to sustain progress in knowledge-driven climate adaptation. acknowledgments The authors sincerely thank the organizers and contributors of the Cli­mateChangeManagementthroughMitigation andAdaptation(adap­tm) project under Erasmus+. We would also like to thank our men­tors, colleagues, and the participating organizations in the Egyptian petroleum sector for their valuable contributions and insights, which were instrumental in the completion of this study. references Abdelwhab Ali, A., D. D. D. Panneer Selvam, L. Paris, and A. Gunaseka­ran. 2019. ’Key Factors In.uencing Knowledge Sharing Practices and Its Relationship with Organizational Performance within the Oil and Gas Industry.’ Journal of Knowledge Management 23 (9): 1806– 37. Ahmed, Aly A., and A. Elshazly. 2021. "A Knowledge Management Sys­tem as a Tool for Better Climate Change Management." In Innovation in Urban and Regional Planning, edited by D. La Rosa and R. Privitera. Lecture Notes in Civil Engineering 146. Springer. Awad, A., A. El-Sammak, A. Elshazly, and E. A. El-Masry. 2023. ’Carbon Sequestration in Mangrove Sediments as Climate Change Mitiga­tion Tool: A Case Study from the Red Sea, Egypt.’ Egyptian Journal of Aquatic Biology & Fisheries 27 (4). Beatty, P. C., D. Collins, L.Kaye, J.-L.Padilla,G. B.Willis, andA.Wilmot, eds. 2020. Advances in Questionnaire Design, Development, Evaluation, and Testing. Wiley. Galal, N. M., and A. F. A. Moneim. 2015. ’A Mathematical Programming Approach to the Optimal Sustainable Product Mix for the Process Industry.’ Sustainability 7 (10): 13085–103. Global Reporting Initiative. 2021. Consolidated Set of gri Sustainability Reporting Standards 2021. Global Sustainability Standards Board. Janus, S. S. 2016. Becoming a Knowledge-Sharing Organization. Interna­ tional Bank for Reconstruction and Development and The World Bank. [78] Liang, G., W. Fu, and K. Wang. 2019. ’Analysis of t-Test Misuses and spss Operations in Medical Research Papers.’ Burns and Trauma 7. https://doi.org/10.1186/s41038-019-0170-3. Ministry of Electricity and Renewable Energy. 2016. Integrated Sustain­able Energy Strategy (ises)to 2035. Arab Republic of Egypt. Nonaka, I. 1994. ’A Dynamic Theory of Organizational Knowledge Cre­ation.’ Organization Science 5(1): 14–37. Orsato, R. J., S. R. Barakat, and J. G. F. de Campos. 2017. ’Organizational Adaptation to Climate Change: Learning to Anticipate Energy Dis­ruptions.’ International Journal of Climate Change Strategies and Man­agement 9 (5): 645–65. Penca, J.,A.Barbanti, C. Cvitanovic,A.Hamza-Cha.ai, A. Elshazly,J.B. Jou.ray, N. Mejjad, and M. Mokos. 2024. ’Building Competences for Researchers Working Towards Ocean Sustainability.’ Marine Policy 163. https://doi.org/10.1016/j.marpol.2024.106132. Ramík, J. 2020. Pairwise Comparisons Method: Theory and Applications in Decision Making. Lecture Notes in Economics and Mathematical Sys­tems 690. Springer. Rashidi, M. Nor, R. Ara Begum, M. Mokhtar, and J. J. Pereira. 2014. ’The Conduct of Structured Interviews as Research Implementation Method.’ Journal of Advanced Research Design 1(1):28–34. Saaty, T. L. 1980. ’The Analytic Hierarchy Process (ahp).’ Journal of the Operational Research Society 41 (11): 1073–6. Saaty, T. L. 1990. ’How to Make a Decision: The Analytic Hierarchy Pro­cess.’ European Journal of Operational Research 48 (1): 9–26. Saaty, T. L. 2008. ’Decision Making with the Analytic Hierarchy Process.’ International Journal of Services Sciences 1(1): 83–98. Salaheldin, M. 2009. ’Solution of Fuzzy Analytic Hierarchy Process Us­ing Simulation.’ Paper presented at the pedac’09 International Conference on Production Engineering, Design, and Control, Alexan­dria, 10–12 February. Salaheldin, M.,A. F.Abdul Moneim,and M. N. Fors. 2015. ’Prioritiza­tion of Improvement Projects in Energy Management System.’ Pa­per presented at the 45th International Conference on Computers & Industrial Engineering (cie45), Metz, 28–30 October. Shaltout, M. L. 2019. ’Recent Sea Surface Temperature Trends and Fu­ture Scenarios for the Red Sea.’ Oceanologia 61 (4): 484–504. Shaltout,M.L., K. Tonbol, and A. Omstedt. 2015.’Sea-LevelChange and Projected Future Flooding Along the Egyptian Mediterranean Coast.’ Oceanologia 57 (4): 293–307. United Nations. 2015. ’The Paris Agreement.’ https://unfccc.int/sites /default/.les/english_paris_agreement.pdf United Nations. 2015. Transforming Our World: The 2030 Agenda for Sus­tainable Development. United Nations. Vogel, R. M. 2022. ’The Geometric Mean?’ Communications in Statistics – Theory and Methods 51 (1): 82–94. World Bank. 2012. Measuring Knowledge in the World’s Economies. The [79] World Bank. World Economic Forum. 2020. Measuring Stakeholder Capitalism: To­wards Common Metrics and Consistent Reporting of Sustainable Value Creation. World Economic Forum. Yang, M., T. T. Luu, and D. Wang. 2024. ’The E.ect of Internal Knowl­edge Transfer on the Relationship Between Personality Traits and Employee Service Performance: A Multilevel Model.’ Journalof Knowl­edge Management 28 (3): 799–826. appendix 1: survey 1 In the .eld of climate change and the development of plans of managing its impacts, a lot of scienti.c research and international institutions have emphasized the importance of having a knowledge management system to ensure increased awareness of the implementation of the best dally practices at work to ensure reducing the impacts of climate change as much as possible. In order to achieve the best value for a system for knowledge of climate change, I propose that it is important to think it to the existing management and quality systems. such as: • Energy Management System (enms). iso 50001 (Economic Pillar of Knowledge) • Environmental Management System (envms). iso 14001 (Envi­ronmental Pillar of Knowledge) • Knowledge Management System (kms). iso 30401 (Social Pillar of Knowledge) So it is important to know your valuable opinion to compare between the importance between these systems to the knowledge management of climate change (* indicates required question). 1Email* 2Name* 3 Gender* Male Female 4 Age range* <25 25–35 35–45 45–55 >55 5Company* 6 Position* Top Management Middle Management Section Head Other 7Country* 8 Industry* Re.ning Petrochemicals Natural Gas Other 9 Field of Work* Quality Assurance Operations Energy Management Health Safety and Environment Sustainable Development Other 10 (1) Regarding to Energy and Environment .elds. Which system is more important to the knowledge of climate change?* [80] Energy Management System Environmental Management System 11 In question 1, what is the degree of importance of your chosen sys­tem?* 123456789 12 (2) If you compare between Energy and Knowledge management .elds. Which system is more important to the knowledge of climate change?* Energy Management System Environmental Management System 13 In question 2, what is the degree of importance of your chosen sys­tem?* 123456789 14 (3) Finally, which system is more important to the knowledge of cli­ mate change?* Energy Management System Environmental Management System 15 In question 3, what is the degree of importance of your chosen sys­tem?* 123456789 appendix 2: survey 2 Energy Percentage of employees e1 The ratio of employees having awareness sessions aware of the energy man-of Environment Manage-agement system to the to­ ment System tal number of employees. Energy intensity e2 Amount of energy used to produce a given level of output or activity All indirect ghg emissions n3 Capturing the thorough­(not included in Scope 2) ness of companies’ ac-that occur in the value counting processes and chain of the reporting understanding how com-company, including both panies analyze their emis­upstream and downstream sions footprints. For most emissions (Scope 3) [tons] companies, the majority of Energy e.ciency midterm e3 How the company aims to target [.] (3–5 years) achieve its emissions re­ duction targets and cap­ ture the company’s ambi­ tion to use energy more e.ciently can reduce its energy costs and lower ghg emissions. Environ-Percentage of employees n1 The ratio of employees ment having awareness sessions aware of the environmen­ of Environment Manage­ tal management system to ment System the total number of em- Direct and indirect ghg n2 ployees Measuring carbon foot­ [81] emissions from sources prints from direct emis­ owned or controlled by sions & emissions from the company and from purchased or acquired the generation of acquired electricity, steam, heat, and consumed electric- and cooling ity, steam, heat, or cooling (collectively referred to as ‘electricity’) (Scope 1 & 2) [tons] emissions occur indirectly from value-chain activities Knowl- Percentage of employees k1 The ratio of employees edge having Awareness sessions aware of the Knowledge of knowledge Manage- management system to ment System the total number of em­ ployees Percentage of climate­ k2 The ratio of climate- related collected ideas related ideas to the total from employees number of collected ideas Percentage of climate­ k3 The ratio of climate-relat­ related converted knowl­ ed converted knowledge to edge (implicit to explicit) the total number of c Name Company Managerial level Work .eld e198765432123456789e2 e198765432123456789e3 e298765432123456789e3 n1 98765432123456789 n2 [82] n1 98765432123456789 n3 n2 98765432123456789 n3 k198765432123456789k2 k198765432123456789k3 k298765432123456789k3 ijems | scientific article Post-Crisis Analysis of Media Consumption and Perceptions of the covid-19 Pandemic: A Study of Moroccan Youth in Urban Areas anoire el attari abderrahman tenkoul Euro-Mediterranean University Euro-Mediterranean University of Fes, Morocco of Fes, Morocco a.elattari@ueuromed.org a.tenkoul@ueuromed.org hind belaziz nouhaila bourass National School of Business and University Ibn Tofail, Morocco Management of Tangier, Morocco nouhaila.bourass@uit.ac.ma belaziz.hind@gmail.com This study investigates the impact of media consumption habits on the perceptions of the covid-19 pandemic among Moroccan youth in urban areas. A quantitative method was employed, combining survey data, chi-square tests, correlation analysis, and regression analysis. In total, 872 responses were collected, and the analyses revealed that digital media consumption by Moroccan youth led them to more crit­ical views of the pandemic’s media coverage. The regression analysis showed that the emphasis on the origins of the virus was an impor­tant aspect that in.uenced the respondents’ assessment of the cover­age. The .ndings highlight the importance of understanding how dif­ferent age groups perceive and interpret media coverage during health crises. E.ective communication strategies must consider the informa­tional needs and motivations of diverse audiences. Key Words: media, youth, covid-19, Morocco, urban areas © 2024 Anoire El Attari, Hind Belaziz, Abderrahman Tenkoul, and Nouhaila Bourass https://doi.org/10.70908/2232-6022/18.83-101 introduction The covid-19 pandemic outbreak marked this era as one of the most unprecedented phenomena with a global reach. Spreading around the world, covid-19a.ectedpeople’shealthandalsoforcedgovernments to impose lockdowns, which impacted economies, education systems, and the environment. Its global reach, combined with a lack of under­standing of its characteristics, made covid-19 a source of fear, stress, and anxiety. The media industry played a pivotal role in the crisis management [84] process by disseminating important information, such as reports on in­fection rates, public health measures, and analyses of the impact of the crisis on the economy and political decisions (De Coninck et al. 2020). Reports, headlines, and interviews-the media devoted its e.orts en­tirely to coverage of the pandemic. On the other side of the screen, the public was eager to get information; from the records of the .rst cases in Morocco, fear started spreading, leading people to make unreason­abledecisions,likeemptyingsupermarketshelves.The covid-19crisis did not just reveal vulnerabilities in health systems around the world; it also exposed the intricacies of media in.uence, public trust, and the im­portance of responsible journalism in combating misinformation and fake news (Leicht et al. 2022). From another perspective, the covid-19 crisis was also character­ized by a complete lockdown, which forced people to stay home, glued to their screensand feeding their craving for information. In this con­text, social media platforms (Instagram, Facebook, TikTok) played a signi.cant role in disseminating information through viral content that often came from uno.cial sources (Hendricks and Mehlsen 2022). This research aims to analyze the media consumption habits of Mo­roccans from a retrospective standpoint regarding covid-19 media coverage. The existing literature on crisis perceptions focuses on how di.erent demographics within the Moroccan population respond to media during crises based on the nature of the information they con­sume. However, little evidence-based research has been done on the ef­fect of variation in media consumption patterns on crisis perceptions. This paper aims to address this by exploring the role of media diver­sity in consumption on the perceived e.cacy of media outlets, as well as analyzing the in.uence of increased digital media consumption com­pared to traditional media in terms of perceived media e.cacy among youth. To do that, we .rst analyzed the existing literature on perception studies of media communication through a literature review, enabling us to identify the following research question: How do variations in me­dia consumption habits a.ect perceptions of the covid-19 pandemic among Moroccan youth from urban areas? To answer this research question, two hypotheses may be consid­ ered: (h1) the perceived relevance of speci.c media channels can pre­dict positive or negative assessments of the media coverage of the crisis situation; (h2) the frequency of following digital media during times of crisis and the nature of the content itself may predict youths’ positive or negative assessments of the media coverage. [85] Through this analysis, we will o.er insights into the media con­sumption habits of Moroccan youth and also understand their percep­tion of the covid-19 crisis as in.uenced by media coverage. media crisis communication: theoretical framework Addressing and understanding the public’s perception during and after media coverage is essential for any media studies research (Driedger 2007). Analyzing how individuals respond to and interpret the mes­sages they receive on di.erent platforms allows researchers to under­stand how the public is in.uenced by those messages. This is especially important in a context of crisis, where the public is confronted with a large volume of media content, which can raise concerns about the spread of misinformation and misleading narratives (Bode and Vraga 2018; Buturoiu et al. 2021). From a theoretical perspective, the e.ects of media on public per­ception have been widely discussed by the research community. Some theories, such as the hypodermic needle model-which suggests that media messages are directly accepted by the receiver-have been largely criticized (Döveling 2011). However, more robust theories, like the agenda-setting model by Maxwell McCombs and Donald Lewis Shaw, and the two-step .ow theory developed by Lazarsfeld and Katz, are more widely accepted in the study of media e.ects on public opinion. There is also a growing body of literature that recognizes the signi.­cantroleofmediaplatformsinshapingpublicopinionaround covid­19 and related issues, such as its socio-political e.ects and vaccine e.­cacy (Cascini et al. 2022; Flew 2021; León et al. 2023). A study conducted on risk perception during the pandemic by Diana Tsoy et al. (2021) pro­posedtheExtended ParallelProcess Model (eppm),whichexplains the impact of social media on perceived threat and e.cacy during the pan­demic. This model suggests that individuals will experience fear and anxiety when facing a highly threatening situation, but these senti­ments can be reduced if they believe they can take e.ective actions to mitigate the threat, thereby increasing their willingness to engage in preventive behavior. Thus, the eppm suggests that social media can promote preventive behaviors by providing individuals with informa­tion that reduces threat perceptions and enhances their perceived e.­cacy through taking preventive measures (Tsoy et al. 2021). [86] When discussing the impact of media communication on public per­ception, it is essential to connect perception with the content itself (McLeod et al. 2017). This often necessitates a qualitative approach to better understand the nature of the content. For example, Buturoiu et al. (2021) conducted a content analysis of both television and online news in Romania. Their research showed that these media primarily discussed topics related to covid-19, such as government decisions and the e.ects of the virus, and that the content published in main­stream media often originated from digital sources, creating an inter­mediate agenda-setting e.ect. The Social-Mediated Communication Theory also provides a frame­work that focuses on the role of social media in crisis communication, seeking to understand how information is shared during crisis man­agement through these platforms. This model emphasizes audience be­havior, information sources, credibility, trust, and new communica­tion strategies as key components in the dissemination of crisis-related information (Austin et al. 2012). By highlighting the transformative impact of social media and changes in audience behavior, the Social-Mediated Communication Theory acknowledges that people now have access to a broader and larger volume of information sources. This ac­cess allows real-time updates and o.ers the possibility of interactivity and engagement with the content shared by organizations, crisis man­agement institutions, and authorities (Austin and Jin 2015; 2016). crisis perceptions in morocco A number of studies have been conducted in the Moroccan context, so it is important for this paper to assess the speci.c characteristics of the Moroccan public. In media studies,itis wellknown that individuals are culturally and linguistically a.ected by the type of media they con- sume.Indeed,in the contextof the covid-19 pandemic,Hattani and Jai (2022) examined how crisis communication during the pandemic shaped citizens’ perceptions and helped them understand and respond to the crisis. This research established that Moroccans judged the crisis communication positively, highlighting its e.ectiveness in enhancing resilience, prevention, and mitigation. A similar study conducted by Berni et al. (2021), which monitored the adoption of safety behaviors related to covid-19, concluded that the Moroccan population generally complied with the safety measures enforced by authorities. However, high perceived risk, lack of available treatment, and availability of clear information were the factors asso­ciated with this compliance, suggesting that feelings of fear about per-[87] sonal health were the motivating reason for adopting safety measures. From a di.erent perspective, Aboulghazi (2022) assessed that youn­ger Moroccans, from the beginning of the crisis, perceived the au­thorities’ communication strategies negatively, especially because their main source of information was social media. Nevertheless, the older age groups were proven to have a more positive standpoint as they received their information from o.cial political sources and main­stream media. However, the same author, in di.erent research, showed that the o.cial mainstream media failed to debunk misinformation through fact-checking, with media regulators failing to adapt to the speci.c characteristics of fake news circulating on social media and the Internet (Aboulghazi 2021). Based on a content analysis, Ben Abdelaziz et al. (2021) showed that these de.ciencies may be addressed through poor psychosocial support and a lack of strengthening community par­ticipation. Social media, being the main source of information for Moroccan youth during the pandemic, has been shown to foster narratives of fear, distrust, and polarization, especially about scienti.c uncertainty (Zag and Mifdal, n.d.). This may be explained by many challenges that journalists faced during pandemic coverage, such as restricted access to information, travel restrictions, and increased work overload (Lacroix and Carignan 2020), which in numerous cases accelerated the digital­ization of work processes, focusing on digital innovation in gather­ing and disseminating information, even for traditional media outlets (Matsilele et al. 2022). So far, we have analyzed the existing body of literature contextual­izing both the theoretical framework and the crisis perceptions in the Moroccan case. In the following section, we will provide details about the methodology, the survey content, and the data analysis process. methodology To understand youths’ consumption habits and their perceived under­standing of the covid-19 pandemic, we adopted a quantitative ap­proach based on a survey that gathered 872 responses. The survey was distributed in both physical form to university students at the Euro-Mediterranean University of Fez and University Ibn Tofail of Kenitra. A digital form was also published on the author’s social media accounts (Facebook, Instagram, X, and LinkedIn). Considering Morocco’s linguistic diversity, the survey was available [88] in three languages: French, English, and Arabic. To ensure minimal translation bias and improve clarity, the survey was translated and cross-veri.ed by two independent peers. Survey Content The survey design aimed to collect data on a Likert scale on the follow­ing aspects: • Media consumption behaviors: Frequency, media preferences (digital, television, radio, newspapers), perceived relevance of each media channel. • Perceived understanding of the pandemic. • Assessment of media coverage. Data Analysis Thecollecteddatawerethentranscribedandanalyzedusing spss soft­ware, version 26. Initially, the data analysis included descriptive statis­tics to provide a basic understanding of the data distribution. Subse­quently, a frequency analysis, including cross-tabulation between vari­ables, was initiated to understand patterns in media consumption and perception among the surveyed age groups. For a detailed analysis of the collected data, chi-square tests were used to assess the independence between age groups and their media channel preferences, as well as their perceived relevance and under­standing of the media coverage. A correlation analysis was aimedto ex­amine relationships between age, media preferences, media consump­tion frequency, and perceived relevance to provide deeper insight into the age di.erences in media engagement during health crises. Additionally, to quantify the strength of association and predict trends, a multinomial logistic regression analysis was used to under­stand how di.erent factors in.uence respondents’ overall assessment of the media coverage. Demographic Overview The demographics of our respondents included both genders with a balanced distribution: 50.9. male and 49.1. female. The majority of the surveyed individuals were predominantly young adults (18 to 35 years), comprising 56.9. of the sample, with smaller representation from other age groups. The majority of the respondents had university-level education, representing 79. of the total sample. [89] study results Descriptive Statistics Table 1 provides a cross-tabulation of media channel preferences with age as a dependent variable. Breaking it down, it clearly shows that the distribution of media preferences is very heterogeneous across the age groups.Digitalmedia/Internetand tv,forexample,aremorepreferred by themajority ofthe 18 to 35 agegroup (N =442, N =431). Newspa­pers, on the other hand, are overall less likely to be preferred, especially among respondents under 18 years old. Chi-Square Test Results: • Digital Media/Internet: 47.508 (df =3, p <0.001) •Newspapers: 43.707 (df =3, p < 0.001) •tv: 34.170 (df =3, p < 0.001) • Radio: 227.120 (df =3, p < 0.001) Chi-Square Test Results: • Digital Media/Internet: 47.508 (df =3, p <0.001) •Newspapers: 43.707 (df =3, p < 0.001) •tv: 34.170 (df =3, p < 0.001) • Radio: 227.120 (df =3, p < 0.001) Conducting the Chi-square test for independence, we tested if there’s a signi.cant association between age groups and media channel pref­erence. The p-value for all media types is 0.000, which is less than the table 1 Media Channel Preferences by Age Groups Age Media Channel Total (.) (.) (.) (.) Under .. .. . .. . .. Between .. and .. ... .. ... ... .... Between .. and .. ... ... ... ... ... Over .. .. .. .. .. ... Total ... ... ... ... .... notes Column headings are as follows: (1) digital media/internet, (2) newspapers, (3) tv, (4) radio. volume 18 | 2025 | number 1 Anoire El Attari et al. table 2 Perceived Relevance of Media Coverage by Media Channels Media Channel Perceived Relevance (.) (.) (.) (.) (.) tv . .. ... ... .. [90] Radio .. ... ... ... .. Newspapers ... ... ... ... . Digital Media/Internet .. ... ... ... .. notes Column headings are as follows: (1) not at all relevant, (2) slightly relevant, (3) relevant, (4) very relevant, (5) extremely relevant. signi.cance level of 0.05, indicating that the distribution of media pref­erences di.ers between the age groups. The table clearly shows digital media as the main source of information for youth; however, it also shows that even with the growing trend of digital media, more tradi­tional channels remain of interest to Moroccan youth (e.g., N(tv) = 431, between 18 and 35). Chi-Square Test Results: •tv: 59.260 (df = 12, p < 0.001) •Radio: 284.857 (df = 12, p < 0.001) • Newspapers: 221.666 (df = 12, p <0.001) • Digital Media/Internet: 303.056 (df =12, p <0.001) The Chi-Square tests presented in table 2 reveal signi.cant associa­tions between agegroups and theperceived relevanceofmedia cover­age for tv, radio, newspapers, and digital media/Internet. E.ect sizes (Cramer’s V) are moderate, indicating practical importance. Both youth and older adults show moderate associations, suggesting that age plays a signi.cant role in in.uencing perceptions of media coverage rele­vance. Chi-Square Test Results: •Pearson’s Chi-Square: 82.475 (df =12, p <0.001) • Likelihood Ratio Chi-Square: 112.161 (df = 12, p <0.001) • Linear-by-Linear Association Chi-Square: Not applicable (df =1, p = 0.991) Table 3 presents the cross-tabulation of respondents’ age groups against their perceived understanding of covid-19 through media consumption. The chi-square test results indicate a signi.cant associa­tion between age groups and the perceived understanding of covid­ 19. Both Pearson’s and Likelihood Ratio Chi-Square tests yielded p­ Post-Crisis Analysis of Media Consumption table 3 Perceived Understanding of the Crisis by Age Group Age Perceived understanding of covid-.. Total (.) (.) (.) (.) (.) Under.. ... ... ... ..–.. . ... ... ... .. ... [91] ..–.. . .. ... .. . ... Over.. . ..... ... Total . ... ... ... .. ... notes Column headings are as follows: (1) not at all, (2) slightly, (3) moderately, (4) very, (5) completely. values less than 0.001, suggesting that the distribution of responses is unlikely to be due to random chance. The Linear-by-Linear Associ­ation Chi-Square test did not show a signi.cant linear trend in the association between age groups and the perceived understanding of covid-19. Chi-Square Test Results: • Age Group vs. Assessment of Media Coverage: 58.781 (df =12, p <0.001) • Measure of Association (f): 0.260 • Measure of Association (Cramer’s V): 0.150 Correlation Analysis Table 4 presents the results of the association between age group and perception of media coverage of the crisis. The Chi-Square test indi­cates a signi.cant association between the age of the respondents and their assessment of the media coverage (p < 0.001). However, it was im­portant to calculate the strength of this association; therefore, the Phi table 4 Cross-Tab between Age Group and the Assessment of the Media Coverage Age Overall assessment Total (.) (.) (.) (.) (.) Under.. ..... . ... ..–.. . ... ... .. .. ... ..–.. . .. ... .. . ... Over.. . ..... ... Total . ... ... ... .. ... notes Column headings are as follows: (1) strongly dissatis.ed, (2) dissatis.ed, (3) neutral, (4) satis.ed, (5) very satis.ed. volume 18 | 2025 | number 1 coe.cient (0.260) and Cramér’s V (0.150) further con.rm a moderate association. Age-Related Trends in Media Consumption: Traditional vs. Digital [92] Media Preferences A positive correlation between age and the frequency of media follow­up (r =0.34, p < 0.01) reveals a gap based on the age of the respondents, with seniors showing more interest in media coverage than youth. There is also a positive correlation between seniors and the perceived relevance of traditional media such as newspapers (r =0.31, p <0.01) and radio (r =0.32, p < 0.01), indicating a reliance on these sources of information by seniors. However, youth are more inclined towards dig­ital media, as demonstrated by a signi.cant negative correlation (r = –0.39, p <0.01). The correlation matrix also indicates a positive correlation between the perceived relevance among traditional media consumers, suggest­ing that individuals who perceive one traditional medium as relevant are more likely to perceive other traditional media as relevant as well. For example, there’s a strong positive correlation between the per­ceived relevance of radio and newspapers (r =0.66, p <0.01) anda moderate correlation between tv and radio (r =0.29, p <0.01). On the other hand, the weak negative correlation between digital media table 5 Correlation Matrix (.) (.) (.) (.) (.) (.) (.) (.) (.) (..) (.) .... (.) .... .... (.) –.... .... .... (.) .... .... .... .... (.) .... .... .... .... .... (.) –.... .... –.... –.... .... .... (.) .... –.... .... .... .... –.... .... (.) .... –.... .... .... .... –.... .... .... (.) –.... .... .... .... –.... .... –.... –.... .... (..) .... .... .... .... .... –.... .... .... –.... .... notes Column/row headings are as follows : (1) age, (2) media follow-up, (3) TV relevance, (4) radio relevance, (5) newspapers relevance, (6) digital media relevance, (7) understanding of covid-19, (8) awareness measures topic (9) vaccine progress topic (10) overall media assessment. Post-Crisis Analysis of Media Consumption table 6 Model Fit information Model –. Log Likelihood .2 df Sig. Constant Only ........ – – – Final Model ........ ....... .. ..... [93] and tv relevance (r = –0.02, p < 0.01) suggests that respondents who believe digital media is more relevant may view tv as less relevant. Table 5 also shows a weak positive correlation between the age of the respondents and their perceived understanding of the crisis, imply­ing that youth felt slightly less informed about covid-19 compared to the older demographic. Concerning the relevance of speci.c topics cov­ered during the pandemic, the results show a weak negative correlation, especially with vaccine progress (r =–0.16 with age) and awareness-related topics (r = –0.24 with media follow-up). Finally, there’s a mod­erate positive correlation between the perceived understanding of the crisis and how the respondents assess the media coverage (r =0.30). In fact, media coverage tends to be rated more favorably if the individual’s perceived understanding of the crisis is higher. Multinomial Regression Analysis The results of the multinomial logistic regression analysis provide in­sight into how di.erent factors in.uence respondents’ overall assess­ment of media coverage during the pandemic. The model .t informa­tion, with a .nal model log likelihood of 1396.343 and a Chi-Square value of 282.358, suggests that the predictors signi.cantly contribute to explaining the variance in the dependent variable (overall assess­ment of the media coverage). Additionally, the calculated Nagelkerke R-Squared of 0.307 indicates that this model accounts for approximately 30.7. of the variance in respondents’ overall dissatisfaction with the media coverage. Results of table 7 show that several variables signi.cantly a.ect in­dividuals’ overall assessment of the media coverage. The perceived role of the media as informative (.2 = 40.578), as an instrument of govern­ment oversight (.2 = 17.599), and as a source of entertainment (.2 = 64.422) indicate a strong e.ect of these variables on overall media as­sessment. Additionally, variables such as perceived understanding, fo­cus on the most important aspects (.2 =40.369), and emphasis on the origins of the virus (.2 = 48.073) highlight the importance of media content itself in shaping youth’s perception of the crisis. Anoire El Attari et al. table 7 Likelihood Ratio Tests E.ect –. Log Likelihood* .2 df Sig. Constant ........ ..... . – Perceived Role: Advocacy for Collective Action ........ ..... . ..... [94] Perceived Role: Informative ........ ...... . ..... Perceived Role: Government Oversight ........ ...... . ..... Perceived Role: Entertainment ........ ...... . ..... Perceived Understanding ........ – .. – Focus on Important Aspects ........ ...... .. ..... Emphasis on Origins of Virus ........ ...... .. ..... Appropriate Coverage of covid-.. Crisis ........ ...... .. ..... notes *Ofreducedmodel. table 8 Parameter Estimates for ‘Strongly Dissatis.ed’ Category Predictor (.) (.) (.) (.) (.) Constant –..... ...... ..... ..... – Perceived Role: Advocacy –..... ..... ..... ..... ..... Perceived Role: Informative –..... ..... ..... ..... ..... Government Oversight ..... ..... ..... ..... ..... Entertainment ..... ..... ..... ..... ...... Perceived Understanding ..... ..... ..... ..... ...... Focus on Important Aspects ..... ..... ..... ..... ...... Emphasis on Origins ..... ..... ..... ..... ...... Appropriate Coverage –..... ..... ..... ..... – notes Columnheadingsareasfollows:(1)coe.cient(B), (2) tandard error, (3) Wald statistic, (4) signi.cance, (5) exp(B). Results from table 8 show the relationship between speci.c predic­tors and dissatisfaction with media coverage, using dissatisfaction as the reference category. For instance, Moroccan youth are more likely to feel dissatis.ed with the media, especially when the origins of the virus were not adequately emphasized (B =3.504,exp(B) = 33.246, p =0.008). This .nding further supports the likelihood test, indicating that the way the media covered certain crisis-related topics signi.cantly in.u­enced negative assessments. However, it can be observed that the role of media in government oversight (B =1.022, exp(B)=2.779, p = 0.833) and entertainment (B =2.942, exp(B)=18.950, p = 0.538) are strong predictors of negative assessments, but the high p-values indicate that these associations are not statistically signi.cant. Hypothesis 1 is accepted, as the perceived relevance of speci.c media channels does predict positive or negative assessments of media cover­age. This is supported by the signi.cant associations between di.er­ent age groups and the perceived relevance of media channels (tv, ra­dio, digital media, newspapers) presented in table 2 and the correlation [95] analysis heatmap in .gure 1, which indicates an increasingly favorable assessment with higher perceived relevance (r =0.30, p <0.01). The re­gression analysis further supports this hypothesis by showing how the perceived roles (informative, oversight) signi.cantly a.ect the overall assessment of the media coverage. Based on the results, Hypothesis 2 is also accepted, as the frequency of following digital media during the pandemic and the nature of the content itself may predict youth’s positive or negative assessments of the media coverage. This is supported by results from table 1, which show that digital media is preferred as a source of information by youth, and the correlation analysis in .gure 1 demonstrating a posi­tive correlation between age and the frequency of following the media (r =0.34, p < 0.01), indicating that the older the respondents are, the more frequently crisis-related content is consumed. Furthermore, the regression analysis in table 8 indicates that speci.c topics, such as the emphasis on the origin of the virus, signi.cantly in.uence negative assessments among youth. discussion This study set out with the aim of assessing the in.uence of media con­sumption habits in terms of diversity and their impact on the perceived understanding of the crisis, as well as the general satisfaction or dis­satisfaction with the media coverage of the crisis. The results of this re­search show that variations in media consumption patterns in.uence the perceived e.cacy of the covid-19 coverage. The main .ndings of the study answer the research question by highlighting di.erent pat­terns in media consumption and exploring the e.ect of these habits on perceived understanding and overall assessment. The analysis aligns with the existing literature regarding the pref­erence for digital media among Moroccan youth compared to their se­niors, who rely more on traditional media (Aboulghazi 2022). However, the same results show that in the case of covid-19, traditional media seems not to be completely ignored by youth, suggesting that Moroccan youth still consume information from these channels in times of crisis, indicating an inclination towards a diversity of sources, alternating be­ tween traditional and digital sources. Additionally, the results reveal a correlation between youth media engagement and their varied perceptions of the crisis, with seniors [96] showing stronger engagement with mainstream media narratives and reporting a better understanding of the situation compared to younger respondents. However, youth exhibit more diverse perceptions, sug­gesting that consuming a broader range of media channels leads to greater variation in perceived e.cacy. This may be attributed to the con.icting narratives surrounding covid-19 virus and the fact that younger generations encounter a wider range of content on the Inter­net, including misinformation and fake news (Aboulghazi 2021). Our study, in contrast, distinct generational patterns in media per­ception, with younger respondents generally expressing a favorable perception of the media coverage, while older individuals – particularly those over 55 – adopted a more cautious and critical stance. Interest­ingly, a study by Ceccato et al. (2021) on the Italian context reported di.erent .ndings, indicating that older adults experienced lower lev­els of negative emotion compared to younger. These contrasting out­comes suggest that generational di.erences in media perception and emotional response may be shaped by cultural and societal contexts. When comparing the assessment of media coverage within speci.c age groups, subtle di.erences were also identi.ed. Youths’ perception tends to be more diverse, expressing both satisfaction and dissatisfac­tion to a signi.cant extent, which underscores that age is not the only variable that may a.ect the public’s perception. The diverse digital me­dia sources themselves may result in di.erent perceptions of the crisis (Chauhan and Hughes 2020; Wu 2020). These di.erences may also be explained by varying levels of digital literacy and other socio-cultural factors. Seniors, particularly those over 55 years old, expressed more polar­ized views, often conveying stronger negative opinions regarding the depth and accuracy of the coverage. This could be explained by a loss of trust in traditional media sources, greater susceptibility to misinfor­mation, or subjective interpretations of what constitutes appropriate coverage (Tucker et al. 2018; Wagner and Boczkowski 2019). The correlation analysis highlights interesting results, especially the negative correlations between several topics – such as awareness mea­sures and vaccine progress – and both age and frequency of media follow-up, indicating both hesitancy towards mainstream media nar­ratives and a sense of information overload among the younger gen­eration. Similar results were found through a qualitative approach by Zimmermann (2024), who observed that in the Swedish case, a higher tendency to express feelings of fatigue and information overload ap-[97] peared to contribute to growing polarization and societal segmentation in the later stages of the crisis. The results of the regression analysis further emphasize the role me­dia coverage plays in shaping perceptions of dissatisfaction, indicating that the lack of emphasis on origins of the virus, insu.cient govern­ment oversight, and limited entertainment value are strong predictors of negative assessments. This suggests that the perceived imbalance in the coverage of certain crisis-related topics was a source of dissatisfac­tion, leading to varying perceptions of the e.cacy of the media’s ef­fectiveness. This .uctuation in perception was also observed in other cases where levels of trust appeared to decline as the crisis progressed. It’s crucial to keep in mind that these .ndings should be approached with caution. The limitations indicate a sampling bias, which could mean that certain demographics are not adequately represented in the sample, thereby a.ecting the generalizability of the results. Lookingatitfrom another angle, this study speci.cally focused on age-related di.erences in how the media is perceived, without consid­ering important factors that might impact how the Moroccan public views issues such as information quality, trust in the media, or levels of media literacy across di.erent age groups. This study was also con­ducted at a speci.c point in time, meaning that it does not take into account potential changes in perceptions or trends. A longitudinal study would provide more in-depth insight into the evolvingperceptionsofthe covid-19crisisbythepopulation,tracking how attitudes change over time in response to evolving events and me­dia narratives, especially during a prolonged crisis like the covid-19 pandemic. As a future research avenue, we could complement this research with a qualitative analysis, such as a content analysis of media narratives or by conducting in-depth focus groups and interviews to analyze behav­iors that may be more di.cult to detect using surveys alone. Technol­ogy and data analytics could also o.er valuable real-time insights into large-scale datasets on social media, allowing us to explore public sen­timent, media framing, and information dissemination during crises. conclusion Analyzing Moroccan youth’s perception of the covid-19 pandemic through the lens of Moroccan media coverage reveals the complex interplay between media narratives and public understanding of the [98] virus. Several key conclusions and implications can be drawn from this research, emphasizing the intricate relationship between media con­sumption habits and youth perceptions. The results con.rm variations in media channel preferences across Moroccan demographics, highlighting the importance for mainstream media outlets to diversify and adapt their content across a wider range of digital media platforms to e.ectively reach youth and young adults. The empirical .ndings of this paper provide valuable insights for Mo­roccan media organizations regarding public preferences in terms of media consumption and their perceived assessment of the coverage of a globally signi.cant phenomenon. One key implication is the need for targeted communication strategies that address the speci.c needs and behaviors of di.erent age groups. While digital media appears to be the main source of information among youth, results indicate that they still rely on traditional media. However, negative perceptions tend to increase when there is a per­ceived lack of government oversight and in-depth information. This suggests to media organizations that fact-checking, accountability, and adherence to ethical responsibilities are crucial for maintaining public trust and engagement. Another important aspect highlighted in this research is the grow­ing need for media literacy skills among youth. Misinformation, fake news, and conspiracy theories have been widely shared on digital plat­forms during and after the covid-19 pandemic, a.ecting their under­standing. Media education programs and fact-checking workshops may help enhance young people’s skills in seeking information online. Adaptability and agility in crisis response are also key implications of this study. As media consumption patterns evolve during a crisis, media organizations and authorities should adapt their communica­tion strategies based on public feedback and needs. This includes lever­aging innovative formats such as podcasts, livestreams, and other in­teractive content. The study also underscores the importance of research and interdis­ciplinary approaches to media coverage during health-related crises. A reasonable approach to addressing this issue would be to emphasize the need for collaborative e.orts among policymakers, media practi­ tioners, public health authorities, and researchers to develop evidence- based strategies for e.ective crisis communication and public engage­ ment. [99] references Aboulghazi, H. 2021. ‘Moroccan Social Media Platforms and covid-19 Misinformation.’ International Journal of Linguistics and Translation Studies 2(4): 4. Aboulghazi, H. 2022. ‘Covid-19 Crisis Communication Management in Morocco: Investigating Male and Female Publics’ Perceptions and Assessments of Moroccan Public Authorities’ Crisis Response Strategies.’ The Journal of Quality in Education 12 (19): 19. Austin, L., B. Fisher Liu, and Y. Jin. 2012. ‘How Audiences Seek Out Cri­sis Information: Exploring the Social-Mediated Crisis Communica­tion Model.’ Journal of Applied Communication Research 40 (2): 188– 207. Austin, L., and Y. Jin. 2015. ‘Approaching Ethical Crisis Communication with Accuracy and Sensitivity: Exploring Common Ground and Gaps between Journalism and Public Relations.’ The Public Relations Jour­nal 9(1):2. Austin,L., andY. Jin.2016. ‘SocialMedia andCrisis Communication: Explicating the Social-Mediated Crisis Communication Model.’ In Strategic Communication: New Agendas in Communication, edited by A. Dudo and L. A. Kahlor. Routledge. Ben Abdelaziz, A., N. El Haddad, H. Hannachi, S. Nouira, S. Melki, D. Chebil, S. Chelly, A. Quessar, and N. Boussouf. 2021. ‘Qualité dessupportsdecommunication de crise lorsdelapandémiede la covid-19 au Grand Maghreb.’ Revue d’Épidémiologie et de Santé Publique 69 (3): 116–26. Berni, I., A. Menouni,Y. F.Zegzouti, M.-P. Kestemont,L. Godderis, and S. El Jaafari. 2021. ‘marocovid: Snapshot Monitoring of Knowl­edgeandPerceptionsofSafetyBehaviorsduringthe covid-19Out­break in Morocco.’ International Journal of Environmental Research and Public Health 18 (11): 11. Bode, L., andE.K.Vraga. 2018. ‘See Something, SaySomething:Cor­rection of Global Health Misinformation on Social Media.’ Health Communication 33 (9): 1131–40. Buturoiu, R., G. Udrea, D.-A. Oprea, and N. Corbu. 2021. ‘Who Believes in Conspiracy Theories about the covid-19 Pandemic in Romania: An Analysis of Conspiracy Theories Believers’ Pro.les.’ Societies 11 (4): 138. [100] Cascini, F., A. Pantovic, Y.-A. Al-Ajlouni, G. Failla, V. Puleo, A. Melnyk, A. Lontano, and W. Ricciardi. 2022. ‘Social Media and Attitudes to­wards a covid-19 Vaccination: A Systematic Review of the Litera­ture.’ eClinicalMedicine 48:101454. Ceccato, I., R.Palumbo, A.DiCrosta, P. La Malva, D. Marchetti, R. Maiella, M. C. Verrocchio, A. Marin, N. Mammarella, R. Palumbo, and A. Di Domenico. 2021. ‘Age-Related Di.erences in the Percep­tion of covid-19 Emergency during the Italian Outbreak.’ Aging & Mental Health 25 (7): 1305–13. Chauhan, A., and A. L. Hughes. 2020. ‘Trustworthiness Perceptions of Social Media Resources Named after a Crisis Event.’ Proceedings of the acm onHuman-ComputerInteraction 4:44. De Coninck, D., L. d’Haenens, and K. Matthijs. 2020. ‘Perceived Vulner­ability to Disease and Attitudes towards Public Health Measures: covid-19 in Flanders, Belgium.’ Personality and Individual Di.er­ences 166:110220. Döveling, K., ed. 2011. The Routledge Handbook of Emotions and Mass Me­dia. Routledge. Driedger,S.M.2007. ‘Risk andthe Media: AComparisonofPrint and Televised News Stories of a Canadian Drinking Water Risk Event.’ Risk Analysis 27 (3): 775–86. Flew, T. 2021. ‘Trusting and Valuing News in a Pandemic: Attitudes to Online News Media Content during covid-19 and Policy Implica­tions.’ Journal of Digital Media & Policy 12:11–26 Hattani, A., and A. Jai. 2022. ‘Crisis Communication amid the covid­19 Pandemic in Morocco.’ Journal of Arab & Muslim Media Research 15 (1): 45–63. Hendricks, V. F., and C. Mehlsen. 2022. The Ministry of Truth: BigTech’s In.uence on Facts, Feelings and Fictions. Springer Nature. Lacroix, C.,andM.-È. Carignan. 2020. ‘Pandémiede covid-19:denou­velles contraintes journalistiques qui menacent le droit à l’informati­on.’ Enjeux et société: approches transdisciplinaires 7 (2): 271–96. Leicht,K. T., J. Yun, B. Houston, L. Auvil, and E.Bracht. 2022.‘The Presentation of Self in Virtual Life: Disinformation Warnings and the Spread of Misinformation Regarding covid-19.’ rsf: The Rus­sell Sage Foundation Journal of the Social Sciences 8 (8): 52–68. León,E.de, M. Makhortykh,T.Gil-Lopez,A.Urman,and S. Adam.2023. ‘News, Threats, and Trust: How covid-19 News Shaped Political Trust, and How Threat Perceptions Conditioned This Relationship.’ The International Journal of Press/Politics 28 (4): 952–74. Matsilele, T., L. Tshuma, and M. Msimanga. 2022. ‘Reconstruction and Adaptation in Times of a Contagious Crisis: A Case of African News­ rooms’ Response to the Covid-19 Pandemic.’ Journal of Communica­tion Inquiry 46 (3): 268–88. McLeod, D.M., D. Wise, and M. Perryman.2017. ‘Thinking aboutthe Media: A Review of Theory and Research on Media Perceptions, Me­dia E.ects Perceptions, and Their Consequences.’ Review of Commu­ [101] nication Research 5:35–83. Tucker, J. A., A. Guess, P. Barbera, C. Vaccari, A. Siegel, S. Sanovich, D. Stukal, and B. Nyhan. 2018. ‘Social Media, Political Polarization, and Political Disinformation: A Review of the Scienti.c Literature.’ ssrn Scholarly Paper 3144139. Tsoy,D., D. Godinic, Q. Tong,B.Obrenovic,A.Khudaykulov,and K. Kur­payanidi. ‘Impact of Social Media, Extended Parallel Process Model (eppm)ontheIntentiontoStayatHomeduringthe covid-19Pan­demic.’ Sustainability 14 (12): 7192. Wagner,M. C., andP.J.Boczkowski. 2019. ‘The ReceptionofFakeNews: The Interpretations and Practices That Shape the Consumption of Perceived Misinformation.’ Digital Journalism 7 (7): 870–85. Wu,S.(2020). ‘WhenNew MediaOperateswithin a State-Mediated Press System: Assessing New Media’s Impact on Journalism Crisis Perceptions in Singapore and Hong Kong.’ Information, Communica­tion & Society 23 (4): 572–87. Zag, H., and M. Mifdal. (2024). ‘Polarized Framing of Scienti.c Uncer­tainty during covid-19 Pandemic in Morocco.’ Atlantic Journal of Communication 33 (1): 50–70. Zimmermann, B. M. ‘Swiss Residents’ Information Behavior Percep­tions during the covid-19 Pandemic: A Longitudinal Qualitative Study.’ Social Science & Medicine 344:116647. ijems | scientific article Economic Integration of Mediterranean States janez fabijan draško veselinovi. Gea-College, Slovenia Gea-College, Slovenia janez.fabijan@gea-college.si drasko.veselinovic@gea-college.si jaka vadnjal Euro-Mediterranean University, Slovenia jaka.vadnjal@emuni.si Times of economic crisis are an opportunity for greater integration of the markets of the Mediterranean countries. The chosen method makes it possible to con.rm this hypothesis. Unfortunately, this can­not be realized without greater, comprehensive institutional connec­tivity within he economic space. The greatest role in this can be played by the major members of the Mediterranean basin, which are very im­portant to global trade and through which the e.ects of major crises are also transmitted most signi.cantly to the economic space of the Mediterranean basin. Key Words: Mediterranean countries, economic integration, Markov chains © 2024 Janez Fabijan, Jaka Vadnjal, and Draško Veselinovic https://doi.org/10.70908/2232-6022/18.103-127 introduction At .rst glance, the title of this article and its .eld of analysis may seem overly optimistic, especially in light of the current geopolitical situation and the ongoing war in the Middle East between two members of the Mediterranean basin – Israel and Palestine. However, we believe that, regardless of the circumstances – or perhaps precisely because of them – it is essential to maintain a degree of optimism and to redouble e.orts toward identifying pathways to peaceful coexistence and cooperation for the common good. Our focus, of course, is on economic cooperation. A strong understanding of the past can always help to .nd better and more lasting solutions for the future.¹ ¹ ‘Interestingly, national in.uences tend to correlate negatively with regional in.uences, suggesting that national speci.cities play a somewhat countercyclical role in the West­ ern Mediterranean region (Portugal, Spain, France, Italy)’ (Canova and Ciccarelli 2011). basic research concept This analysis focuses on the general characteristics of international trade among the countries of the Mediterranean basin over a period of nearly a quarter of a century. Our primary interest lies in examining [104] the current state and nature of mutual trade relations, particularly in terms of their potential for improvement. Speci.cally, we concentrate on the level of connectivity or integra­tion of the economies of the Mediterranean countries during the period from 1995 to 2018. From this foundation, however, we move toward a ‘what if’ type of analysis: what might thefuture hold if the existingna­ture of these relationships continues to prevail? We deliberately con­clude our analysis before the onset of major external, non-market dis­ruptions such as the covid-19 pandemic, energy crises, wars, and in­terventionist state policies. However, the period under review does in­clude the signi.cant global .nancial and economic crisis that followed the collapse of Lehman Brothers in the United States on September 15, 2008. statistical methods and data management A major problem in conducting a comprehensive and long-term analy­ sis of international trade in goods and services among the twenty-one countries bordering the Mediterranean Sea is the availability and com­ parability of data. More than a third of these countries, or eight in to­ tal, aremembersof theEuropean Union(eu),andthreeof them(rank­ ing second, third, and fourth in gdpwithin the eu, after Germany) also belong to the European Monetary Union (emu). Consequently, it makes sense to pursue data consistency by relying on European statis­ tical standards and methodologies. Setting aside considerable hetero­ geneity of these economies – whose past cooperation we seek to exam­ ine over an extended period to inform future possibilities for deeper integration – we should concentrate on the relative shares of mutual trade, expressed as a percentage of each country’s gdp. In light of the above, we concluded that the most useful database is provided by the European Central Bank (ecb) through its public data portal. In the context of international relations and in view of current geopolitical, environmental, demographic, and other external factors, the ecb has emphasized a strong need to jointly address the major challenges of our time, including, or especially, with the rest of the Mediterranean countries outside the emu (Lagarde 2023). We aim to estimate the minimum, average and maximum levels of cooperation, or economic integration, in the past by analyzing the avail­ able 24-year time series of the aforementioned data on international trade in goods, covering the period from 1995 to 2018. These scenar­ ios – representing low (minimum), typical (average), and high (maxi-[105] mum) levels of cooperation – serve as the foundation for constructing and applying matrices of integration rates among individual countries in the Mediterranean basin, with a view toward potential future col­ laboration. To explore long-term established relationships, we employ methods of forecasting and extrapolation. The integration stage can be understood as the degree of import or export interdependence among the countries of the Mediterranean basin. For the purpose of this analysis, we focus exclusively on one- sided trade .ows – exports. The most appropriate measure is the dou­ ble export weight, which re.ects the degree of competitiveness of an exporting country within a particular market. This indicator accounts for the exporting country’s relative share in total exports, its market position relative to other exporters in the same market and compe­ tition from domestic suppliers, in other words, all relevant market competitors. In our analysis, the competitive position of each Mediter­ ranean country in the market of another Mediterranean country is represented by the rows of a square matrix (square matrix row), while the competitive positions of other Mediterranean countries within the market of the country under consideration are represented by the columns (square matrix column). Thus, exports are illustrated as .ows from the i-th row to the j-th column. Conversely, the reverse direction of the matrix re.ects the import activity of each Mediterranean coun­ try from the other members of the basin. Methodologically, we aim to extrapolate the available data using the quantitative Markov chain method, as it allows for the possibility of establishing an equilibrium distribution over time. The association for the use of this method stems from its relevance to the gravitational model commonly used to study mutual trade relations among countries (unctad 2012).² ² ‘It has been known since the seminal work of Jan Tinbergen (1962) that the size of bi­lateral trade .ows between any two countries can be approximated by a law called the ‘gravity equation’ by analogy with the Newtonian theory of gravitation. Just as plan­ets are mutually attracted in proportion to their sizes and proximity, countries trade The concept of double-weighted trade often involves using a gravity model to analyze trade .ows. The gravity model in international trade is analogous to Newton’s law of gravitation and is typically expressed as: [106] Tij = Dij × A × Yi ×Yj, (1) where Tij is the trade .ow between country (i)and country (j), A is a constant, Yi and Yj are the economic sizes (usually gdp) of countries Yj(i)and (j), respectively, and Dij is the distance between the two coun­tries, which can also include other factors like trade barriers. To apply the Markov chain method, we require a square transition matrix in which each row sums to one (and, where appropriate, sym­metry is maintained). This approach is well suited to our study because Markov chains are ‘memoryless’ – they depend only on the most re­cent state – which aligns perfectly with our characterization of ‘bad,’ ‘mediocre,’ and ‘promising’ trade periods. Since the sum of the proba­bility of transition from a single row to all columns of the matrix must be equal to 1, we will use import probabilities to de.ne our baseline scenarios, and for each scenario, we then compute the average of each column in the transition matrix to serve as the last known state of the Markov chain – e.ectively quantifying the export attractiveness of each Mediterranean country to its counterparts (Hudoklin-Božic 1999). As a unit of measure, we use a relative measure expressed in hun­dredths of a percent of double-weighted exports, i.e. in percentages to four decimal places, because the competitive position of each country in question, assuming the absence of major crises, usually changes over time with very small relative changes in its market position. Example of the time series dimension of the relative market share of Slovenian exports of goods and serviceson the Algerian market: ‘wts. a.si. dz.z0z. x0. t.tms. f, Slovenia, Annual:’ • wts: This likely stands for ‘World Trade Statistics.’ • a: Indicates that the data is annual. • si: Refers to Slovenia as the reference area. • dz: Represents Algeria. in proportion to their respective gdps and geographic closeness. Initially, the grav­ity equation was thought of merely as a representation of an empirically stable rela­tionship between the size of economies, their distance and the volume of their trade.’ unctad (2012). • z0z: This part is not immediately clear without additional con­text, but it could be related to speci.c trade categories or prod­ucts. • x0: Indicates that it’s a double export weight. [107] • t: The unit of measurement is in hundredths of a percent. • tms: Possibly related to total manufactured products (sitc 5 to 8). • f: The frequency of data collection is annual. The Standard International Trade Classi.cation (sitc) distinguish­esfourmaingroupsofindustrialgoods:(i)chemicals(sitc 5) –thiscat­egory includes chemical products and industrial goods classi.ed mainly by material, (ii) manufactured goods (sitc 6) – that is, goods made mainly from special materials, such as textiles, wood, paper, and cork (iii)machineryandtransport equipment(sitc 7) –thisgroupincludes machinery, equipment, and vehicles, (iv) miscellaneous manufactured articles (sitc 8) – products that do not fall into other categories are classi.ed here. This classi.cation also includes the service component of trade, where transport, commerce, tourism, and .nancial services have historically played leading roles. Signi.cant progress has been made in the latter since 2013, but there remains substantial closure in the sector, often due to dominant state ownership of .nancial institu­tions. The less developed countries of the Mediterranean basin tend to focus excessively on low-value-added activities, are relatively less open to international markets, their mutual trade is lower and their depen­dence on trade with eu countries is signi.cantly higher (Ayadi 2013; Giovannetti 2013) Table 1 highlights the problematic nature of data availability in the desired comparison of twenty-one countries. ‘Shadow’ countries do not provide data on the relative strength of mutual international trade. The statistical principles of data availability and transparency are not met. As a result, the planned analysis can focus on the twelve non-shadowed countries listed in table 1 – essentially, a good half of the total. High sta­tisticalstandardsaremaintainedbyall eu and emu members. The op­posite is true for members in the Middle East, with the exception of Is­rael. From a representational standpoint, it is encouraging that we have harmonized data from two North West African countries: Morocco and Algeria. As the chosen method requires full methodological comparability Janez Fabijan, Jaka Vadnjal, and Draško Veselinovic table 1 Availability of Comparable Data within a Symmetric Matrix ma dz tn ly eg ps il lb sy tr cy mt gr al me ba hrsi it fr es ma • • • • • • • • • dz • • • • • • • • • tn • • • • • • • • • • • • • • • • • • • • [108] ly eg • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • ps • • • • • • • • • • • • • • • • • • • • il • • • • • • • • • lb • • • • • • • • • • • • • • • • • • • • sy • • • • • • • • • • • • • • • • • • • • tr • • • • • • • • • cy • • • • • • • • • mt • • • • • • • • • gr • • • • • • • • • al • • • • • • • • • • • • • • • • • • • • me • • • • • • • • • • • • • • • • • • • • ba • • • • • • • • • • • • • • • • • • • • h r • • • • • • • • • si • • • • • • • • • it • • • • • • • • • fr • • • • • • • • • es • • • • • • • • • notes ma–Morocco,dz–Algeria,tn –Tunisia, ly–Libya, eg –Egypt,ps–Palestine,Stateof,il –Israel,lb – Lebanon, sy–SyrianArabRepublic, tr –Turkey, cy –Cyprus, mt –Malta,gr –Greece, al–Albania, me –Mon­tenegro, ba – Bosnia and Herzegovina, hr – Croatia, si – Slovenia, it – Italy, fr – France, es – Spain. We used a concept of the Union for the Mediterranean, which, for our analytical purposes, includes only all the coastal Mediter­raneancountries(EuropeanParliament2014).Basedondatafromthe ecb DataPortal(https://data.ecb.europa.eu). of the data, we unfortunately only need to focus on 12 of the 21 coun­tries of the Mediterranean basin (table 1). As can be seen from ta­ble 1, a Mediterranean country is de.ned for our analysis by its loca­tion on the Mediterranean Sea. For these twelve, we have a time se­ries of methodologically completely comparable data for the period up to and including 2018, i.e., for the period before the outbreak of the covid-19 crisis and the Ukrainian war or the energy crisis, all of which signi.cantly a.ect international trade .ows by disrupting trans­port routes and constraining supply chains. Subsequent disruptions in­clude the war in Gaza and the trade war resulting from us tari. policy through 2025. Nevertheless, despite the limitations in comparative in­tegrity across all twenty-one Mediterranean countries, focusing on a subset of twelve with the highest statistical standards underscores the importance of data quality as the foundation for analysis. In the fu­ture, harmonization of statistical monitoring under international (Eu­ropean) statistical standards should be a prerequisite for improved eco­nomic cooperation and, consequently, a higher degree of integration. table 2 Average Values of Double-Weighted Exports from the Country in Row (i) of the Table to the Country in Column (j) ofthe Tablefor thePeriod 1995–2018, Relative to the gdpof the Exporting Country dz hr c y f r gr il it mt ma si e s tr  dz ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... hr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... [109] cy ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... fr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... gr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... il ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... it ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... mt ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ma ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... si ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... es ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... tr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ¯x ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... notes Based ondatafromthe ecbDataPortal(https://data.ecb.europa.eu). Since1996,the eu hasprovidedtechnicalassistancetoMediterranean countries inthisarea in.ve packages under the medstat program, which ends in 2025 (Eurostat 2022). Based on the basic methodological data framework outlined above, we have selected the Markov chain method to estimate the potential degree of integration, assuming the exclusion of major external crisis factors (i.e., the analysis covers the period up to 2018). We have constructed a data warehouse that enables the prepara­tion of a content-complete and comparable square matrix for twelve Mediterranean countries. For the entire period under consideration, from 1995 to 2018, we calculate minimum, average and maximum val­ues, in accordance with the three prede.ned scenarios. Since double-weighted exports are expressed as a percentage of each country’s total exports, we present the baseline average values for the twelve selected Mediterranean countries over the observed period. In table 2, we observe that the countries with the largest average market shares of exports of goods and services – by each of the other eleven Mediterranean countries under consideration – on world mar­kets are: France (7.55.), Italy (6.5.), Spain (3.6.), Turkey (1.47.) and Greece (1.3.).Israelfalls somewherein the middle(0.65.). Onthe other hand, the markets of the smaller Mediterranean members appear more diversi.ed in terms of international trade. Exporters from non-Mediterranean countries are clearly present in greater proportions in these smaller markets. While caution is warranted due to data limita­tions – the remaining nine Mediterranean countries are not included in the table – this pattern may be generalized to the broader group of twenty-one Mediterranean countries. The calculated average (x¯)of each column represents the degree of import integration of each coun­ [110] try within the Mediterranean basin into this common market (import integration as an export attraction for other members). For example, Algeria is integrated at a rate of 0.31., meaning that, on average, other countries of the Mediterranean basin will export to the Algerian mar­ket with such an average probability. Similarly, the Moroccan market is integrated into the Mediterranean basin at a rate of 0,49 .. As shown in table 2, the most integrated or desirable export markets within the Mediterranean basin are those of France (7.55.), Italy (6.5.), Spain (3.6.), Turkey (1.47.), and Greece (1.3.). For all the Mediterranean markets listed, the integration rate (i.e., the column average) exceeds 1 ., indicating a relatively high level of market integration into the Mediterranean basin, measured against the global economy. If we examine the rows of the square matrix, following the approach described above, we can identify a signi.cant variation in the export presence of each member country in the markets of other compara­ble countries. In the Algerian market (.rst column), France (0.76.), Turkey (0.68.), and Spain (0.51.) demonstrate a relatively higher ex­port interest compared to other Mediterranean countries – highlight­ing the methodological importance of using double-weighted exports. If we read the matrix row by row, then the average probability, taking into account its total world exports and the entire period considered (1995–2018), that France will export to the Algerian market is 0.76 .. During the same period, Spain exported to the markets of the other (eleven) Mediterranean countries with a probability of almost 23 . (sum of the line; 22.91 .), accounting for the predominant share of the probability of its world exports to France (11.68 .) and Italy (6.68 .). Even at the level of world trade, the matrix reveals relatively strong competitive presences in certain Mediterranean markets. For exam­ple, Greece exports to Cyprus with a 2.41. probability, while Slovenia exports to Croatia with a 4.45. probability – both .gures indicating meaningful regional trade dynamics within the Mediterranean basin. It is therefore useful to narrow the analytical scope from the level of total global exports to the subset of exports within the Mediterranean countries under consideration. Let us make the same calculation as in table 2 for the minimum and maximum values of the relative data of the table 3 Square Matrix of Markov Properties for Transition Probabilities Based on Minimum Values of Double-Weighted Exports among a Sample of Mediterranean Countries, for the Period 1995–2018, Relative to the gdpof the Exporting Member dz dz hr ...... ...... c y f r gr il ...... ...... ...... ...... it ...... mt ma ...... ...... si e s tr ...... ...... ......  .... [111] hr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... cy ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... fr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... gr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... il ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... it ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... mt ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ma ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... si ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... es ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... tr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ¯x ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... notes Based ondatafromthe ecbDataPortal(https://data.ecb.europa.eu). double-weighted exports of the selected countries at the world level. In the ‘total’ column and the ‘average’ row of table 2, we can see that, on average, during the period under consideration, trade in goods among the twelve countries under consideration accounted for almost 22. of their total world exports (21.22.) Depending on the chosen analytical method (Markov chains) we construct a square matrix in tables 3 to 5 that represents the transition probabilities from each row country to each column country – that is, the probability of mutual trade among a selected sample of Mediter­ranean countries. The matrices are constructed to ensure that all con­ditions required for a Markov chain are satis.ed, speci.cally that the sum of each row equals 1. When converting basic matrices such as that in table 2 to Markov-type transition probability matrices (tables 3 to 5), it is not to be ex­pected that the probability data for the minimum, average, or maxi­mum values will maintain a similar relationship overall. This is because we must satisfy the condition that the sum of the probability of state transitions in the row is equal to 1. The last rowofaveragesintables3to 5representsthe average proba­bilities of the degree of market integration over the period under study for each country represented in the columns of the matrix, taking into account the closed trade system of the twelve countries in question. Let’s call it an initial matrix of states of the .rst order of 1 × 12. We have Janez Fabijan, Jaka Vadnjal, and Draško Veselinovic table 4 Square Matrix of Markov Properties for Transition Probabilities Based on the Average Values of Double-Weighted Exports among a Sample of Mediterranean Countries, for the Period 1995–2018, Relative to the gdp1of the Exporting Member [112] dz dz hr cy fr ...... ...... ...... ...... g r ...... i l i t mt ma si e s tr ...... ...... ...... ...... ...... ...... ......  .... hr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... cy ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... fr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... gr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... il ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... it ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... mt ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ma ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... si ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... es ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... tr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ¯x ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... notes Basedondatafromthe ecbDataPortal(https://data.ecb.europa.eu). table 5 Square Matrix of Markov Properties for Transition Probabilities Based on the Maximum Values of Double-Weighted Exports among a Sample of Mediterranean Countries, for the Period 1995–2018, Relative to the gdpof the Exporting Member dz hr cy fr g r i l i t mt ma si e s tr  dz ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... hr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... cy ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... fr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... gr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... il ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... it ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... mt ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ma ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... si ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... es ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... tr ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ¯x ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... notes Basedondatafromthe ecbDataPortal(https://data.ecb.europa.eu). three such matrices depending on the calculated historical minimum, average, or maximum trade participation of the twelve countries con­sidered in the period 1995–2018. In addition, tables 3 to 5 provide three transition matrices P,one for each individual scenario. For example, to try to .nd out how the states or probabilities of the transition matrix gravitate across n periods from 2019 onwards, we convert the last row (tables 3, 4 or 5) to a matrix of size 1×12 and we can multiply it by the previous matrix of size 12x12 of the probability of transitions according to the expected scenario in the future by n number of periods. Sn = Ikij ×Pn , (2) klij lij whereby [113] • k = 3, in the case of initial matrices also Ikij of the order 1×12 and l = 3 in the case of transient matrices Pn of order 12 × 12, and kij their set of values is: min, avg, max, since they arise from the same ‘history,’ • therefore, there are two variables k and l with the same sets of values, and given their chosen combination, i.e. the chosen base state I and the selected transition matrix P, we can obtain nine combinations of Markov matrices S; •the matrix S, due to the characteristics of the Markov chain that they depend only on the last known state, is decisively in.uenced by the selection of the scenario l in the future: thus, we obtain three calculations of matrices for the pessimistic scenario (l = min), the baseline scenario (l = avg) and the best case – optimistic scenario (l = max) of the values of the probability of transition af­ter Sn – n number of periods in the future. klij In thefollowing approach,weattempt to determinethe dynamics of further economic integration among Mediterranean countries by cal­culating transitional matrices of order of 1×12 in the n-th years. In such a simpli.ed model, based on equation 1 or the logic of the gravitational model, the baseline states at a given point in time can be adjusted due to the in.uence of various external factors (variable Sn Dij in equation klij 1) on trade relations between two countries (e.g. changed tari.s). Al­ternatively, a di.erent initial matrix of states I may be applied within the closed group of countries to re.ect such changes. hypothesis The average level of integration (the average of each column) was ex­pressed, within the selected sample of Mediterranean countries, as the probability of transition (export likelihood) from other Mediter­ranean countries in the sample to each country in the sample (i.e., transition from row to column in the table). We aim to determine the range of the integration rates for individual countries in the Mediter­ranean sample over the long-term period of cooperation. Thus, the transitional – initial matrix (table 4), based on average values (the baseline scenario) indicates probabilities of 1.42. for Algeria, 2.02. for Morocco, and 32.02., 27.75. and 15.87. for France, Italy and Spain respectively. The matrix of minimum values of the probability of tran­ [114] sition (table 3) is constructed using the lowest relative gdpshares of total (global) double-weighted exports for each country from any year within the 1995–2018 period. It therefore represents the worst-case scenario of economic cooperation or integration. In contrast, table 5, is based on the maximum observed relative shares in gdpof bilateral double-weighted exports over the period and represents the best-case scenario for economic cooperation or integration among the Mediter­ranean basin countries, drawn from various years depending on each bilateral trade relationship. The trade-cooperation probabilities (the likelihood that exports .ow from a country in a row to a country in a column of the matrix) within our selected sample of Mediterranean countries are therefore based on each country’s total trade with the world during the study period and then translated into the three scenarios described. We examine a 24­year period of methodologically consistent data up to 2018, that is, be­fore the onset of major external crises that have signi.cantly a.ected mutual trade relations worldwide (covid-19 pandemic, the Ukraine-Russia war and energy crisis, and tari. wars). We then hypothetically extrapolate the normal long-term cooperation of the Mediterranean countries and establish equilibrium matrices of cooperation for the three scenarios described, assuming that external factors would not occur. We are therefore interested in the trend of economic integra­tion of Mediterranean countries during downturns, average periods, andupswingsin global goodstrade.Inthis way,weexplore the nature of long-term cooperation and the potential for its improvement, while remaining aware of the signi.cant risks of the present time. Hypothet­ically, we expect that favorable conditions would enhance the levels of economic integration for the less developed Mediterranean countries within the basin’s internal trade. In our case, we are dealing with a Markov process with discrete states in discrete time, which means that we are dealing with Markian chains that are homogeneous, since the conditional probability of being in a given state depends only on the length of the time interval – the year, and not on the speci.c time – period. Conditional probabilities over a longer period can be expressed in terms of the conditional probabilities over shorter intervals. In a Markov process – or in our extrapolation – the conditional probability distribution of a random variable depends only on the most recent state, not on its previous history. The latest situation is created on the basis of three selected scenarios for the en­tire considered period and is obtained in the average of the column of [115] calculated transitional matrices for di.erent scenarios (the degree of integration of each country into the Mediterranean market). We then multiply such states by the selected transitional matrix for each sce­nario six times (n = 6), covering the period from 2019 to 2024. Although this period has passed and data are not yet fully comparable, it is char­acterized by major external crises. Theory predicts that, over long time horizons, the properties of these Markov chains cause the state proba­bilities to converge to a stationary distribution. This limit distribution allows us to determine the equilibrium probabilities for each state. Thus, for each projected year studied in the future under each sce­nario, we can calculate a transitional matrix representing the proba­bilities of occupying each state. However, our primary interest lies in whether there is a matrix of equilibrium states for each scenario. This depends on the nature of the individual states (i.e.,the probability of transition for a particular country). An analysis of the properties of the states of the Markov chain under consideration con.rms that the conditions for the existence of a matrix of equilibrium states are met. This means that, regardless of the initial probabilities of occupying the states, i.e. the initial level of economic integration of an individual member of the Mediterranean basin, there exists a long-term equilib­rium probability of integration, which re.ects the dynamics and pat­terns of cooperation observed during the historical period under study. The key question, however,is how external factors on one hand, and economic and integration policies on the other, can in.uence changes in equilibrium distributions (Hudoklin-Božic 1999). Positively recurrent, associated, non-periodic states re.ect the tra­ditional Mediterranean trade established over the centuries, each state represented by an individual country (table 6) is related to another state and, theoretically, can return in one step. Therefore, these are inter­connected, non-periodic states. All countries were, to varying degrees, engaged in international trade of goods with one another, conducted across or along the Mediterranean basin (Lagarde 2023). However, we are dealing with a closed set of conditions within a sam­ple of Mediterranean countries. On the one hand, we do not have com- Janez Fabijan, Jaka Vadnjal, and Draško Veselinovic table 6 Properties of the Markov Chain of States under Consideration State Type Class num. State Type Class num. Algeria (dz) Recurrent . Italy (it) Recurrent . Croatia (hr) Recurrent . Malta (mt) Recurrent . [116] Cyprus (cy) Recurrent . Morocco (ma) Recurrent . France (fr) Recurrent . Slovenia (si) Recurrent . Greece (gr) Recurrent . Spain (es) Recurrent . Israel (il) Recurrent . Turkey (tr) Recurrent . notes Own calculations using pom qm (Weiss 2005). prehensive data for all 21 countries of the Mediterranean basin, and on the other hand, Palestine is e.ectively isolated or excluded from eco­nomic activities in 2024 and 2025. Hypothetically, if comparable data were available for all twenty-one, we would be faced with a discon­nected chain and an absorbing state. In that case, stochastic processes would more accurately re.ect the current reality, which is not captured by our analysis based on the available data (1995–2018). Our Markov chain is therefore irreducible in nature, .nite, and composed of non-periodic states. As a result, there exist equilibrium distributions that are invariant for state occupation. Thus, for example, the average level of economic cooperation (ma­trix I, k = avg) observed during the period 1995 to 2018 can, under the in.uence of major structural crises in the following 6 years, be mul­tiplied by the matrix P, which represents the worst-case scenario (l = min). However, we begin by assuming consistent scenarios for both the past and the future. Accordingly, the average initial cost I in the base­line scenario is multiplied by the transition matrix for the transverse transition states P to the desired power (n)orthe number of transi­tions (transitions) and similar in the other two scenarios (an example of the calculation in the appendix). Using a ‘what if’ type analysis, we can simulate how trade in goods might have continued from 2019 to 2024 under normal conditions. Over the long term – or in the limit – this approach yields an equilibrium distribution that re.ects the stable probabilities of mutual trade among the countries. A major advantage of the transition matrices developed for the worst-and best-case scenarios lies in the method of selecting the min­imum or maximum values from the 24-year dataset for each country in the sample. These scenarios establish an estimated corridor of min­imum and maximum levels of economic cooperation among the coun­tries of the Mediterranean basin e.ectively outlining the lower and up­per bounds of potential economic integration. Such a corridor can be assessed or extrapolated over a six-year horizon, or extended to deter­mine its long-term equilibrium state. The key question, however, is how the eu’s economic and integration policies might alter this dynamic [117] for the better and in.uence the transitional matrices in the context of creating scenarios for the future development of the Mediterranean basin. results and analysis In particular, in the selected sample of Mediterranean countries, we highlight two African countries or countries in the south of the Mediter­ranean basin, Algeria and Morocco, recognizing that the European inte­gration processes have strongly linked all Mediterranean eu members in international trade. From the perspective of examining the degree of economic integration across the entire Mediterranean basin, we be­lieve that both countries could serve as important indicators of general trends in the eu’s trade relationship with the North African countries of the Mediterranean basin. Unfortunately, there are no comparable data available for Tunisia, Libya and Egypt. We observe that in all selected scenarios, the degree of economic integration of Algeria and Morocco into the Mediterranean basin in­creases, but to a much higher level in the optimistic scenario and to a lower level in the pessimistic scenario (table 7). The integration pro­cesses in the southern Mediterranean basin are therefore occurring re­gardless of major external crises, such as the global .nancial and eco­nomic crisis during the period under consideration. On the other hand, when using data from the best or worst individual years of economic participation by individual members in the transitional matrix of min­imum probabilities for occupying states and the transitional matrix of maximum probabilities for occupying states, we can conclude that the levels of integration for these countries are much stronger and higher inthe absence ofcrises. Thisisdetermined by analyzing a ‘what-if’ sce­nario in which we extrapolate these integration rates over the next six years (2019–2024), to the present day (ending), and further into the steady state. We use the Markov chains method, the properties of which allow us to calculate a matrix of equilibrium states. We .nd that their levels of integration, measured by the attractiveness of their market to other Mediterranean members during both bad and good .. initial state .. ending state .. steady state ...... ...... ...... ....... .. initial state .. ending state .. steady state Owncalculationsusing pom qm (Weiss2005).ThedegreeofeconomicintegrationofacountryintheMediterranean basin is de.ned as the degree of export attractiveness of its market for other members of the Mediterranean basin. The initial states for Algeria are represented by the .rst value of the matrix of the .rst order of magnitude 1×12, and the ninth value corresponds for Morocco. The Ending states for n =6andfor n = the limit value in the equilibrium matrix (Steady) are shown in the examples in .gure 1 and correspond to the same positions (the .rst value for Algeria and the ninth for Morocco) in the matrix S. f igure 1 Degree of Economic Integration of the Markets of Algeria and Morocco with Other Mediterranean Countries under the Selected Scenario, Shown for the Initial (2018), Final (2024) and Equilibrium Phases (Steady State) times of world trade, increase more signi.cantly during favorable peri­ods than during unfavorable ones. Table 7 shows the aggregate results of the calculations for all three selected scenarios for the sample of Mediterranean countries, based on the assumption that the scenario of initial cooperation simply contin­ues. The central, or baseline, scenario – based on the average values, shows that the .nal probabilities for the occupation of states after 6 iterations (transitions) for each individual member are very similar to, or even identical with, the long-term equilibrium probabilities for the occupation of states. his suggests that the number of iterations already approximates the limiting number of iterations quite well. This obser­vation is reminiscent of the gravitational model. It is very clear that the economic Mediterranean basin is dominated by the three largest Economic Integration of Mediterranean States table 7 Rates of Economic Integration for a Sample of Mediterranean Countries dz hr c y fr g r i l i t mt ma si e s tr Pessimistic (a) ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... (b) ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... (c) ...... Base line ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... [119] (a) ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... (b) ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... (c) ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... Optimistic (a) ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... (b) ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... (c) ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... Optimistic – Pessimistic (a) ...... ...... ...... –...... ...... ...... ...... ...... ...... –...... –...... ...... (b) ...... ...... ...... –...... ...... ...... ...... ...... ...... –...... –...... ...... (c) ...... –...... ...... –...... ...... –...... –...... ...... ...... –...... –...... ...... notes Row headings are as follows: (a) initial, (b) ending, (c) steady. Own calculations using pom qm (Weiss 2005). eu and emu members, namely France, where the average long-term equilibrium probability of economic integration (de.ned as the attrac­tiveness of its market for the export from other Mediterranean coun­tries) into the Mediterranean basin is equal to 30.38., Italy 25.17. and Spain 20.12.. These large markets are undoubtedly the great export po­tential for the rest of the Mediterranean countries in the sample. Other markets also show a fairly high equilibrium level of economic integra­tion into the Mediterranean basin, with Turkey at (7.46.), followed by Greece (4.1.), Morocco (2.99.), Israel (2.82.), Algeria (2.67.), Slove­nia (1.47.), Croatia (1.44.), Cyprus (0.89.) and Malta (0.47.). The di.erences between the optimistic and pessimistic scenarios (last section of table 4) show that after six iterations, or in the long­term equilibrium probability of the distribution of stocks, the rates of economic integration into the Mediterranean basin increase the most for Greece (from 3.32. to 4.32. after 6 iterations, and from 3.46. to 4.12. at equilibrium rates, followed by Algeria (from 2.22. to 2.98. and from 2.32. to 2.84.) and Morocco (from 2.76. to 3.34. and from 2.88. to 3.18., respectively). The strong global economic situation al­lows these countries to import more from other Mediterranean part­ners. Long-term equilibrium levels of integration are also slightly in­creased for Turkey (by 0.19 percentage points), Cyprus (by 0.17 per­centage points) and Malta (by 0.1 percentage points). The equilibrium distribution remains almost unchanged in Croatia (down 0.01 p.p.), ...... ...... [120] ...... ...... ...... ....... .. initial state .. ending state .. steady state ...... Italy ...... ...... ...... ...... ...... ...... . .. initial state .. ending state .. steady state ...... ...... Spain ...... Worst case ...... ...... ....... .. initial state .. ending state .. steady state figure 2 DegreeofEconomicIntegrationoftheMarketsofFrance,ItalyandSpain with Other Mediterranean Countries under the Chosen Scenario, Shown for the Initial(2018), Final(2024) and Equilibrium Phases(Steady State) slightly decreasing in Israel (by 0.11 p.p.) and Slovenia (by 0.32 p.p.). The di.erences in the initial levels of integration between the op­timistic and pessimistic scenarios are strongly negative for France and Spain, but not for Italy, where this di.erence is positive. The latter indi­cates that in the baseline optimistic scenario for Italy, we expect an in­crease in its level of integration, as hypothesized. However, as we shall see, this is not the case. After six iterations (Ending State), Italy’s integration rate declines, in the optimistic scenario, by almost 3 percentage points and is nearly identical (central graph in .gure 2) across all three scenarios at the .­nal time at n = 6 (Ending state). In equilibrium, the attractiveness of its market for other Mediterranean countries in the sample increases in the pessimistic scenario and decreases in the optimistic scenario, in [121] both cases by almost 2 percentage points. Similarly, Spain’s equilibrium level of integration decreases in the optimistic scenario and increases in the pessimistic scenario, by approximately one percentage point (third graph in .gure 2), or by almost 2.5 percentage points when compared to the optimistic scenario. The degree of integration, or export attrac­tiveness, of its market for other members of the Mediterranean basin increases over 6 iterations through 2024 in all scenarios by nearly 4 per­centage points. Conversely, during this extrapolated period up to 2024, integration rates decline across all scenarios for Italy, and for both the baseline and pessimistic scenarios for France. France’s initial degree of integration in the optimistic scenario is lower than the initial level of integration in the pessimistic scenario by as much as 5.64 percent­age points, and in the case of long-term equilibrium distributions, by slightly more, 5.75 percentage points. The integration processes of the Mediterranean basin are signi.­cantly dependent on the economic policies of its three largest members: France, Spain and Italy, as they (table 2) absorb an average of 13.2. of the annual global exports of the other Mediterranean basin coun­tries studied during the period from 1995 to 2018. The transition from the .nal stage (2. Ending State, 2024) to the equilibrium distribution (3. Steady State) for all three countries shows roughly the same pat­tern in terms of the ratios of the probabilities of occupying each state across di.erent scenarios. Their rates of integration into the Mediter­ranean basin ((i.e., the export attractiveness of their markets for other Mediterranean members) increase signi.cantly in the pessimistic sce­nario and, conversely, decrease signi.cantly in the optimistic scenario, while remaining roughly stable relative to 2024 (2. Ending State) un­der the baseline scenario. Thus, periods of global economic crisis, which have a major impact on the global export capacity of the three largest Mediterranean economies, may represent an opportunity for an in­crease in exports and mutual trade by other Mediterranean members to these markets. The hypothesis that this opportunity arises in op­timistic scenarios can generally be rejected. Is this opportunity being realized in pessimistic scenarios? Janez Fabijan, Jaka Vadnjal, and Draško Veselinovic table 8 Relative Shares of Global Double-Weighted Exports for Algeria in the Period 1995–2018 within a Sample of Mediterranean Countries h r cy fr gr il it mt ma si es tr .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... [122] .... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... notes Basedondatafromthe ecbDataPortal(https://data.ecb.europa.eu). For the entire period studied, the .nding that the integration pro­cess is present, whether in its negative or positive form, is supported by the use of Markov, which track changes in the probability of occupy­ing states and focus exclusively on relations within the Mediterranean basin (i.e., the selected sample of countries). However, it is necessary to revisit the analysis and examine the time dynamics of the source data on global export trade over time. If we consider Algeria and Morocco, both of which have generally increased their levels of integration into the Mediterranean basin (becoming more attractive destinations for exports from other Mediterranean countries, including each other), in relation to the three largest countries, which, according to our .ndings, can signi.cantly in.uence integration processes, we have to analyze the time periods corresponding to minimum, average and maximum levels of economic cooperation (the method of creating matrix I at k =min or k =max, orthe P matrices at l =min or l = max) taking into account the source data on the relative share of their world exports. Table 8 which presents data for Algeria, and similarly table 9 for table 9 Relative Shares of Global Double-Weighted Exports for Morocco in the Period 1995–2018 within a Sample of Mediterranean Countries dz hr cy fr gr il it mt si es tr .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... [123] .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... .... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... ...... notes Based on data from the ecb Data Portal (https://data.ecb.europa.eu). Morocco, shows strong relative shares of exports to the three large Mediterranean eu members, particularly in the early years of the pe­riod under review, from 1995 until the onset of the great global .nancial and economic crisis in 2007. These years account for their maximum export shares, which form the basis for the optimistic scenario in the transition matrices. However, after 2007, a gradual cooling occurred, followed by a sharp decline in the relative export presence of Algeria and Morocco in France, Spain and Italy. The pessimistic scenario is thus grounded in these developments, with the selected minimum values coming primarily from the post-crisis years – especially the .nal years of the period under consideration. The patterns of minimum, average and maximum periods of export competitiveness in the markets of the eu’s Big Three Mediterranean countries are similar to those of Algeria and Morocco as they are for other members of the selected sample of Mediterranean countries, par­ticularly Turkey and Cyprus. Slovenia, Greece and Malta signi.cantly increased their export competitiveness on the Spanish market during the post-crisis period. Greece and Croatia also managed to maintain a [124] high level of export competitiveness in the French market, and to some extent in Israel as well. Greece was able to increase its export competi­tiveness in the Mediterranean basin after the post-crisis period by rela­tively maintaining its export share in the Italian market. The eu’s sup­port for Greece during the peak of the crisis is also re.ected in a rise in its level of integration (measured as the attractiveness of the Greek market to other Mediterranean members), when considering the entire period from 1995 to 2018. This trend also highlights the institutional strength of the large Mediterranean members of the euro area in sup­porting integration processes. discussion and implications A study of the long-term trade relations among 12 members of the Mediterranean basin, out of a total of 21 countries geographically bor­ dering the Mediterranean Sea, focused on measuring the dynamics of their degree of integration, particularly for North African countries, initially suggests a general trend of increased integration during the period under review. A more detailed analysis reveals that the global .nancial and economic crisis had a signi.cant impact on the mutual relations between the three large eu countries and the other Mediter­ ranean nations during the same period. Their global market power is so substantial that each Mediterranean country’s level of integration, is heavily in.uenced by the export competitiveness of these major play­ ers on world markets. There has been a notable substitution e.ect, where other Mediterranean markets have partly replaced the domi­ nant markets of the larger eu countries, as countries such as Algeria and Morocco attempt to maintain or enhance their level of integra­ tion. However, despite these e.orts, it is di.cult to ignore the trend indicated by the prevailing pessimistic scenario when forecasting in­ tegration processes for the period already elapsed (2019–2024), for which reliable data are not yet available. A ‘what if’ analysis, based on Markov chains and extrapolation of historical relations, surpris­ ingly provides optimistic projections for a possible greater integration within the Mediterranean basin, particularly under a pessimistic global scenario, and thereby challenges the basic hypothesis that global trade booms necessarily lead to greater regional integration . The gravita­tional analysis method, used to determine equilibrium distributions of trade within a sample of twelve Mediterranean countries suggests that a weaker global economic climate may o.er a better opportunity for deeper economic integration of the Mediterranean basin than a [125] strong one. This conclusion is supported by similar .ndings in research conducted by the European Central Bank, using a di.erent method­ological approach (Canova and Ciccarelli 2011). Several broad factors may explain this trend: a greater incentive to share resources and mar­kets during economic downturns, cost reductions through economies of scale, a stronger foundation for diversi.cation and resilience to eco­nomic shocks, enhanced political stability, and improved access to in­ternational funding and aid through closer economic cooperation. On the other hand, the last period studied, from 2007 to 2018, high­lights the impact of the Great Financial Crisis on the stance of the three eu members of the Mediterranean basin towards the other members, indicating a reduced commitment to the region’s integration processes. This trend is particularly concerning in light of major external crises that have occurred since 2019. On the one hand, the analysis highlights the potential strength of the eu in enabling greater integration of Mediterranean markets and, on the other hand, underscores its necessity or even urgency. In an in­creasinglyuncertaingeopoliticalenvironment,the eu shouldurgently pursue an agenda for deeper integration of the Mediterranean basin. If we further emphasize this key .nding and focus on the importance and role of France, Spain and Italy in advancing economic integration in the region, then the data underpinning our analysis – double-weighted exports in total world trade in goods – show that under globally favor­able conditions, as these countries’ exports to the rest of the world in­crease, their integration rates within the Mediterranean basin actually decline, even in an optimistic scenario. In other words, during favorable phases of the economic cycle, the relative importance of other Mediter­ranean economies to the Big Three economies of the Mediterranean basin is relatively smaller (table 7). Conversely, under less favorable global economic conditions, the relative interconnectedness of their markets with other countries of the Mediterranean basin becomes sig­ni.cantly more important. Unfortunately, the original post-crisis data (see tables 8 and 9 for Algeria and Morocco, for example) do not yet re­.ect actual developments in this direction. The most notable exception is the positive trend obserrved in theSpanish market. Other Mediter­ranean countries have mostly compensated for the decline in the share of exports to the three major Mediterranean economies during crises through mutual trade in goods (Lagarde 2023). [126] Therefore, the crises that occurred from 2019 to 2024 certainly can­not have a positive impact on increasing the economic integration of the Mediterranean basin by themselves, and not without urgent and more decisive integration policies, especially from the major European economies of the region. It is thus a fundamental conclusion that major crises represent a signi.cant opportunity to deepen economic integra­tion in the Mediterranean basin (as shown by pessimistic scenarios and steady-state distributions). However, this opportunity cannot be real­ized without more systemic, regionally focused, and less bilateral .nan­cial support, along with stronger integration e.orts from eu institu­tions,³ which, despite numerous initiatives, have not materialized over the past decade. Currently, the eu’s enlargement agenda for 2025 is fo­cused on Ukraine, Moldova, and the Western Balkan countries. Some of these Western Balkan countries are also part of the Mediterranean basin considered in this analysis: Bosnia and Herzegovina, Montenegro and Albania. references Canova, F., and M. Ciccarelli. 2011. ‘Cyclical Fluctuations in the Medi­terranean Basin.’ ecb Working Paper Series 1367. European Central Bank. European Parliament. 2014. Regional Integration in the Mediterranean: Ipact and Limits of Community and Bilateral Policies. European Union. Eurostat. 2022. ‘medstat Programme.’ https://ec.europa.eu /eurostat/statistics-explained/index.php?title=MEDSTAT _programme Giovannetti, G. 2013. ‘Trade Relations among Mediterranean Coun­ tries.’ iemed MediterraneanYearbook, 238–43. Hudoklin-Božic, A. 1999. Stohasticni procesi. Moderna oganizacija. Lagarde, C. 2023. ‘A Mediterranean Odyssey: From Ancient Origins to Future Strength.’ Speech at the Mediterranean Meetings, Marseille, 21 September. Ayadi, R., E. Arbak, and W. P. De Groen. 2013. ‘Convergence and Integra­tion of Banking Sector Regulations in the Euro-Mediterranean Area ³ ‘The overall institutional system is complicated, and the division of tasks is unclear’ (European Parliament 2014). Trends and Challenges.’ medpro Technical Report 34. European Commission. Tinbergen, J. 1962. Shaping the World Economy: Suggestions for an Inter­national Economic Policy. Twentieth Century Fund. unctad. 2012. A Practical Guide to Trade Policy Analysis. United Nations [127] Publications. Weiss, H. J. 2005. pom-qm for Windows Software for Decision Sciences: Quantitative Methods, Production and Operations Management. Pear­son Education. Résumés Musiciens, un pilier essentiel du tourisme rural en Méditerranée aleksandra govedarica, nataša kraljevi., darko lacmanovi., urša lamut, predrag ljubotina, andrej raspor, bojan rojko, and ajda srdi. Cet article examine le rôle signi.catif des musiciens dans l’enrichissement de l’o.re touristique en milieu rural. Le tourisme rural constitue l’un des prin­cipaux piliers du développement économique et de la préservation cultu­relle, car il permet la création d’emplois, améliore la qualité de vie locale et soutient la restauration des sites historiques. Grâce à leur créativité, les mu­siciens protègent et valorisent le patrimoine culturel immatériel, tel que la musique et la danse traditionnelles, ce qui in.uence positivement la perfor­mance .nancière des acteurs du tourisme rural. Les festivals et événements musicaux organisés à la campagne représentent également une source im­portante de tourisme rural. Ils génèrent des revenus substantiels et contri­buent à la construction d’une image positive de la destination. Les événe­ments organisés dans des zones défavorisées attirent les visiteurs en diver­si.ant l’o.re touristique et en favorisant le développement régional. Tou­tefois, leur réussite dépend d’une plani.cation rigoureuse et d’une bonne organisation. Cette étude analyse l’impact de facteurs tels que le soutien de l’État, la proactivité, la satisfaction professionnelle, la chance et les traits de personnalité sur le succès et l’évolution des musiciens dans les pays méditer­ranéens, en particulier en Slovénie et au Monténégro. Il a été démontré que l’intégration des ressources culturelles dans les stratégies touristiques rend les zones rurales plus attractives et compétitives. Les études empiriques sur le tourisme rural suggèrent que les musiciens jouent un rôle clé dans le tou­risme culturel en attirant les visiteurs, en préservant le patrimoine local et en stimulant la croissance économique, contribuant ainsi au développement durable des zones rurales. Mots clés : musiciens, tourisme rural, région méditerranéenne, soutien de l’État, con.ance en soi ijems 18 (1): 9–29 Comment les entraîneurs de gymnastique serbes prennent-ils leurs décisions? edvard kolar, saša veli.kovi., rado pišot, marijo možnik, and matej tušak [130] Di.érents auteurs a.rment que l’entraînement est fondamentalement un processus de prise de décision (ci-après : pd), et la pd des entraîneurs a été identi.ée comme un élément clé de leur pratique. Dans cette étude, nous avons examiné le comportement décisionnel des entraîneurs de gymnastique serbes. L’échantillon était composé de 53 entraîneurs (âge : 40,96 ± 13,04 ans). Le comportement décisionnel manifeste a été mesuré lors du séminaire national d’entraînement à l’aide de l’Inventaire général des styles de pd, qui comprend cinq styles de pd dé.nis comme : rationnel, intuitif, dépendant, spontané et évitant. Des analyses factorielles ont été réalisées pour révéler la structure des styles de pd. Le coe.cient de corrélation de Pearson a été utilisé pour identi.er l’association entre les styles de pd, les caractéristiques démographiques et professionnelles, et une anova a permis de détecter les di.érences entre les entraîneurs les plus expérimentés et les moins expéri­mentés. Les résultats ont montré que les entraîneurs utilisent une combinai­son des cinq styles pour prendre des décisions, mais privilégient les styles ra­tionnel et dépendant. Sur la base de la structure moyenne découverte, nous pouvons conclure que les entraîneurs de gymnastique serbes sont principa­lement des décideurs rationnels qui renforcent leur rationalité en sollicitant les conseils, les avis et les connaissances de leurs collègues. De plus, les en­traîneurs les plus expérimentés prennent des décisions de manière plus au­tonome et plus rapide, notamment dans des situations urgentes ou limitées dans le temps. Mots clés : entraîneurs de gymnastique serbes, styles de prise de décision, structure, caractéristiques démographiques, caractéristiques professionnelles, expérience ijems 18 (1): 31–52 Indice de gestion des connaissances pour une meilleure gestion du changement climatique : étude de cas dans le secteur pétrolier égyptien aly a. ahmed, mohamed shaltout, mohamed salaheldin, and ahmed elshazly Le changement climatique présente d’importants dé.s pour les organisa­tions, nécessitant des stratégies d’adaptation et d’atténuation fondées sur la connaissance climatique et l’innovation technologique. Le secteur pétrolier fait face à des pressions réglementaires et environnementales croissantes. En réponse, cette étude introduit l’Indice de Gestion des Connaissances Cli­matiques (cki), un nouvel indicateur conçu pour évaluer la préparation des organisations en matière de gestion des connaissances climatiques en inté­grant les systèmes de gestion de l’énergie, de l’environnement et de la connais­sance. Le cki fournit un cadre standardisé permettant d’évaluer comment [131] les organisations pétrolières gèrent, structurent et appliquent les connais­sances liées au climat dans la prise de décision stratégique. L’indice a été ap­pliqué à deux compagnies pétrolières égyptiennes ayant des approches di.é­rentes en matière de gestion des connaissances, révélant des di.érences no­tables en termes de résilience climatique. L’entreprise dotée de pratiques for­melles de gestion des connaissances a obtenu un score de 0,283, démontrant une meilleure intégration, de plus faibles émissions et des décisions clima­tiques mieux informées, tandis que l’entreprise de comparaison a obtenu un score de 0,133. Les deux résultats ont été comparés à une valeur optimale de référence .xée à 0,606. Ces résultats soulignent le rôle essentiel de la gestion structurée des connaissances dans le renforcement de la résilience climatique et le soutien des choix stratégiques dans les secteurs à fortes émissions. Le cki fournit aux décideurs un outil pratique pour évaluer et améliorer la gou­vernance des connaissances, en particulier dans les économies en développe­ment. Sa capacité diagnostique o.re des conseils précieux pour les secteurs en transition vers des opérations plus durables. Mots clés : gestion du changement climatique, indice de gestion des connais­sances, prise de décision stratégique, systèmes de gestion de l’énergie, sys­tèmes de management environnemental, secteur pétrolier ijems 18 (1): 53–82 Analyse post-crise de la consommation des médias et de la perception de la pandémie de covid-19 : une étude sur la jeunesse marocaine en milieu urbain anoire el attari, hind belaziz, abderrahman tenkoul, and nouhaila bourass Cette analyse explore l’in.uence des habitudes de consommation des médias sur les perceptions des jeunes Marocains de milieu urbain concernant la pan­démiedu covid-19. Uneapprochequantitative a été miseenplace viales données recueillies d’un questionnaire, combinant ensuite des test chi-carré, une analyse de corrélation et une analyse de régression. L’analyse des du to­tal des réponses (872) révèle que la consommation des médias digitaux par les jeunes les amène à avoir des positions plus critiques par rapport à la cou­verture médiatique. De plus, l’analyse de régression montre que l’accentua­tion sur les origines du virus a été un aspect important de la couverture. Ces résultats, soutiennent que connaitre comment les di.érentes tranches d’âges de la société consomment, perçoivent et interprétèrent les médias pendant des situation d’urgence sanitaire. Pour cela, des stratégies de communica­tions d’urgence doivent prendre en compte les besoins et motivations infor­mationnelles de leurs audiences. [132] Mots clés : communication médiatique, perceptions des jeunes, covid-19, couverture médias, médias Marocains, jeunes Marocains, zones urbaines ijems 18 (1): 83–101 Intégration économique des États méditerranéens janez fabijan, jaka vadnjal, and draško veselinovi. Les périodes de crise économique représentent une opportunité pour une plus grande intégration des marchés des pays méditerranéens. La méthode choisie, celle des chaînes de Markov, permet de con.rmer cette hypothèse. Pour cette analyse, nous nous concentrons sur les données relatives aux parts du commerce mutuel par rapport au produit intérieur brut national, et nous avons trouvé que la base de données de la Banque centrale européenne(bce) était la plus utile. Malheureusement, cette intégration souhaitée ne peut être réalisée sans une connectivité institutionnelle plus large et plus complète de l’espace économique. Les grands pays du bassin méditerranéen peuvent jouer un rôle majeur dans ce processus, car ils occupent une place importante dans le commerce mondial et sont les principaux vecteurs de transmission des ef­fets des grandes crises dans l’espace économique méditerranéen. Mots clés : pays méditerranéens, degré d’intégration économique, chaînes de Markov ijems 18 (1): 103–127 Povzetki Glasbeniki kot pomemben gradnik sredozemskega podeželskega turizma aleksandra govedarica, nataša kraljevi., darko lacmanovi., urša lamut, predrag ljubotina, andrej raspor, bojan rojko, and ajda srdi. Ta clanek preucuje pomembno vlogo glasbenikov pri izboljšanju ponudbe podeželskega turizma. Podeželski turizem je eden glavnih stebrov gospo­darskega razvoja in ohranjanja kulture, saj je orodje, ki zagotavlja delovna mesta, izboljšuje lokalno kakovost življenja in podpira obnova zgodovin­skih znamenitosti. Glasbeniki s svojo ustvarjalnostjo varujejo in promovi­rajo nesnovno kulturno dedišcino, kot sta tradicionalna glasba in ples, kar pozitivno vpliva na .nancno uspešnost podjetnikov v podeželskem turizmu. Glasbeni festivali in dogodki na podeželju so tudi odlicen vir kmeckega tu­rizma. Ustvarjajo znatne prihodke in pomagajo oblikovati ugodno podobo destinacije. Dogodki na obmocjih z manj možnostmi so pritegnili obiskovalce z diverzi.kacijo turisticne ponudbe in spodbujanjem regionalnega razvoja. Vendar je njihov uspeh odvisen od skrbnega nacrtovanja in pravilne organi­zacije. Raziskava raziskuje vpliv dejavnikov, kot so državna podpora, proak­tivnost, zadovoljstvo z delom, sreca in osebnostne lastnosti na uspeh in ra­zvoj glasbenikov v sredozemskih državah, zlasti v Sloveniji in Crni gori. Po­kazalo se je, da je z vkljucevanjem kulturnih virov v turisticne strategije po­deželje privlacnejše in konkurencnejše. Empiricne študije o podeželskem tu­rizmu kažejo, da imajo glasbeniki pomembno vlogo v kulturnem turizmu, saj privabljajo obiskovalce, ohranjajo lokalno dedišcino in spodbujajo gospodar­sko rast, s cimer podpirajo trajnostni razvoj podeželja. Kljucne besede: glasbeniki, kmecki turizem, sredozemska regija, državna pod­pora, samozavest ijems 18 (1): 9–29 Kako se srbski gimnasticni trenerji odlocajo? edvard kolar, saša veli.kovi., rado pišot, marijo možnik, and matej tušak Razlicni avtorji trdijo, da je treniranje v bistvu proces odlocanja (v nadalj­njem besedilu: dm), medtem ko je bil trenerjev dm opredeljen kot kljucni element trenerjeve prakse. V tej študiji smo preucili dm vedenje srbskih tre­nerjev gimnastike. Vzorec je sestavljalo 53 avtobusov (starost: 40,96±13,04 leta). Manifestirano vedenje dm je bilo izmerjeno na nacionalnem seminarju treniranja z uporabo General dm Style Inventory, ki vkljucuje pet dm stilov, ki so opredeljeni kot racionalni, intuitivni, odvisni, spontani in izogibajoci se dm. Pearsonov korelacijski koe.cient je bil uporabljen za ugotavljanje pove­zave med slogi dm, demografskimi in profesionalnimi znacilnostmi, anova [134] pa je bila uporabljena za odkrivanje razlik med bolj izkušenimi in manj izku­šenimi trenerji. Rezultati so pokazali, da trenerji pri sprejemanju odlocitev uporabljajo kombinacijo vseh petih stilov dm, vecinoma pa uporabljajo ra­cionalneinodvisnesloge dm. Napodlagiodkritepovprecnestrukturesti­lov dm lahko sklepamo, da so srbski trenerji gimnastike vecinoma racionalni odlocevalci, ki svojo racionalnost povecujejo tako, da pri odlocanju išcejo na­svete, mnenja in znanje sodelavcev. Poleg tega lahko bolj izkušeni trenerji sprejemajo odlocitve bolj samostojno in tudi hitreje, ko je situacija nujna ali casovno omejena. Kljucne besede: srbski trenerji gimnastike, stili odlocanja, struktura, demo­grafske znacilnosti, strokovne znacilnosti, izkušnje ijems 18 (1): 31–52 Indeks upravljanja znanja za boljše obvladovanje podnebnih sprememb: študija primera v egiptovskem naftnem sektorju aly a. ahmed, mohamed shaltout, mohamed salaheldin, and ahmed elshazly Podnebne spremembe predstavljajo velike izzive za organizacije, ki zahte­vajo strategije prilagajanja in blažitve podnebnih sprememb, ki temeljijo na podnebnem znanju in tehnoloških inovacijah. Naftni sektor se sooca z vse vecjimi regulativnimi in okoljskimi pritiski. V odgovor na to ta študija uvaja indeks upravljanja znanja o podnebju(kki), nov kazalnik, namenjen ocenje­vanju pripravljenosti organizacij na upravljanje znanja o podnebju z vklju­cevanjem energetskih, okoljskih in sistemov upravljanja znanja. cki zago­tavlja standardiziran okvir za ocenjevanje, kako naftne in plinske organiza­cije upravljajo, strukturirajo in uporabljajo znanje, povezano s podnebjem, pri strateškem odlocanju. Indeks je bil uporabljen za dve egiptovski naftni družbi z razlicnimi pristopi k upravljanju znanja, kar je razkrilo opazne raz­like v smislu odpornosti na podnebne spremembe. Podjetje s formalnimi praksami upravljanja znanja je doseglo 0,283, kar kaže na boljšo integracijo, nižje emisije in bolje informirane podnebne odlocitve, medtem ko je primer­jalnopodjetjedoseglo 0,133. Obarezultata sta bilaprimerjanaz optimalno referencno vrednostjo 0,606. Ti rezultati poudarjajo kljucno vlogo struktu­riranega upravljanja znanja pri krepitvi odpornosti proti podnebnim spre­membam in podpiranju politicnih odlocitev v sektorjih z visokimi emisijami. cki zagotavlja oblikovalcem politik prakticno orodje za ocenjevanje in izbolj­šanje upravljanja znanja, zlasti v gospodarstvih v razvoju. Njegove diagno­sticne zmogljivosti ponujajo dragocene nasvete za sektorje, ki prehajajo na bolj trajnostno poslovanje. Kljucne besede: obvladovanje podnebnih sprememb, indeks upravljanja zna-[135] nja, strateško odlocanje, sistemi upravljanja z energijo, sistemi ravnanja z okoljem, naftni sektor ijems 18 (1): 53–82 Pokrizna analiza medijske potrošnje in dojemanja pandemije covid-19: študija maroške mladine v mestnih obmocjih anoire el attari, hind belaziz, abderrahman tenkoul, and nouhaila bourass Ta študija raziskuje vpliv potrošniških navad medijev na dojemanje pande­mije covid-19 med maroško mladino na mestnih obmocjih. Uporabljena je bila kvantitativna metoda, ki združuje anketne podatke, hi-kvadrat teste, ko­relacijsko analizo in regresijsko analizo. Skupaj je bilo zbranih 872 odgovo­rov, analize pa so pokazale, da uporaba digitalnih medijev maroške mladine vodi do bolj kriticnega dojemanja medijske pokritosti pandemije. Regresijska analiza je pokazala, da je bil poudarek na izvoru virusa pomemben vidik, ki je vplival na oceno anketirancev o pokritosti. Ugotovitve poudarjajo pomen ra­zumevanja, kako razlicne starostne skupine dojemajo in interpretirajo medij­sko porocanje med zdravstvenimi krizami. Ucinkovite komunikacijske stra­tegije morajo upoštevati informacijske potrebe in motivacije razlicnih obcin­stev. Kljucne besede: medijsko komuniciranje, dojemanje mladih, covid-19, medij­ska pokritost, maroški mediji, maroška mladina, mestna obmocja ijems 18 (1): 83–101 Gospodarsko povezovanje sredozemskih držav janez fabijan, jaka vadnjal, and draško veselinovi. Casi gospodarske krize so priložnost za vecje povezovanje trgov sredozem­skih držav. Izbrana metoda Markovljevih verig omogoca potrditev takšne hi­poteze. Pri analizi se osredotocamo na podatke o relativnih (glede na naci­onalni bruto domaci proizvod) deležih medsebojne trgovine, pri cemer smo ugotovili, da bi bila najbolj uporabna podatkovna baza Evropske centralne banke (ecb). Žal tega želenega povezovanja ni mogoce uresniciti brez ve­cjeceloviteinstitucionalne povezljivosti gospodarskega prostora. Najvecjo vlogo pri tem lahko igrajo velike clanice sredozemskega bazena, ki so zelo pomembne v celotni svetovni trgovini in prek katerih se ucinki velikih kriz v najvecji meri prenašajo tudi na gospodarski prostor sredozemskega bazena. Kljucne besede: sredozemske države, stopnja gospodarske integracije, Marko­vske verige [136] ijems 18 (1): 103–127 ã ã Ó Ó . Û Ë . Ó ó ë . . Ë í ß ã ÷ . ÷ . í . í Ë . í £ Ó ó . § Ï ÷ Ó í . . ÷ í ÷ ß . í . § ã . . . Ë . ë í í í í © ³ Ó í © Ó í ç Ë . í . 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