Academic Productivity in Turkish Gastronomy and Culinary Arts: A Multidimensional Quantitative Analysis (2020–2024)

Academic Productivity in Turkish Gastronomy and Culinary Arts: A Multidimensional Quantitative Analysis (2020–2024) | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Academic Productivity in Turkish Gastronomy and Culinary Arts: A Multidimensional Quantitative Analysis (2020–2024) Emre VAROL This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7408736/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The rapid development of Gastronomy and Culinary Arts as a young academic discipline raises questions about how research productivity evolves across career stages and institutional contexts. This study examines the academic output of Turkish scholars in this field between 2020 and 2024, aiming to identify patterns and disparities in publication performance. Using a multidimensional quantitative approach, data were collected from institutional records and bibliographic databases, and analyzed according to academic title, career stage, institutional affiliation, and regional location. The results indicate that seniority and academic rank are significant predictors of productivity, while regional and institutional factors further influence research output. Comparisons with international studies on emerging disciplines reveal similar trends, suggesting that the findings have relevance beyond the national context. Implications for higher education management include the need for discipline-specific performance evaluation, flexible incentive systems, and supportive policies for early-career academics. By linking local evidence to global literature, the study provides actionable insights for policymakers, university administrators, and scholars themselves, highlighting strategies to foster sustainable academic careers, enhance research performance, and inform governance practices in developing academic fields. Overall, this research contributes to understanding the dynamics of academic work in young disciplines, offering both theoretical and practical guidance for higher education institutions navigating the challenges of emerging fields. Hospitality and Tourism Special Education Research productivity Academic rank Universities Publication performance Socio-Economic Development Index (SEGE) Bibliometric Analysis Figures Figure 1 Introduction The measurement of individual performance is critically important for many institutions, particularly universities, as it informs target setting and strategic planning. Evaluating academics based on their scientific output is an integral aspect of the academic ecosystem, playing a decisive role in faculty appointments and the attainment of academic titles such as associate professorship and professorship (Güngör, Parlakyiğit & Tufan, 2023). In recent years, Gastronomy and Culinary Arts (GCA) has evolved from being primarily a vocational area to an established academic discipline (Seyitoğlu & Çalışkan, 2018). This transformation has led to a marked increase in scientific research in the field and has created a growing need to assess academic publication performance (Varol, Kara & Sormaz, 2024). Commonly used metrics in evaluating academic achievement include publication and citation counts, the h-index, and journal impact factors, among others (Garfield, 2006; Hirsch, 2005). Despite the growing interest, there remains a limited body of research specifically addressing academic productivity in the field of Gastronomy and Culinary Arts. Existing studies tend to rely on general social science metrics and often overlook discipline-specific dynamics (Varol, Kara & Sormaz, 2024). In particular, the imbalance between the ways in which local culinary cultures are represented in academic publications and their level of visibility in global journals highlights the need for a comprehensive evaluation framework. While international research on academic productivity in interdisciplinary fields is expanding, studies focusing on the Turkish context are especially scarce, underscoring the significance of the present study. This study aims to systematically examine academic publication performance in the field of Gastronomy and Culinary Arts. Within the scope of the research, books, book chapters, conference proceedings, and academic articles produced by academics in Gastronomy and Culinary Arts between 2020 and 2024 will be identified through the academic.yok.gov.tr platform. The h-index and i10-index, which are significant indicators of academic performance, will be determined using Google Scholar. The findings are intended to provide guidance for gastronomy researchers and academic institutions in performance evaluation processes and to inform national science policy and strategic development in the field. The primary aim of this research is to examine the academic publication and citation performance of academics working in the field of Gastronomy and Culinary Arts in Turkey between 2020 and 2024 through a multidimensional approach. The study quantitatively evaluates the effects of individual (e.g., field of graduation, academic title, gender, professional seniority) and environmental factors (e.g., geographical region, type of institution, SEGE—Socio-Economic Development Index—level) on publication performance. The specific objectives of this research are as follows: To provide a detailed profile of the publications and citations of academics in Gastronomy and Culinary Arts (including total publications, WoS & Scopus publications, national/international publications, h-index, i10-index, books, and conference proceedings); To test the impact of demographic and professional variables (such as field of graduation, academic title, gender, total duration in position, SEGE, region, etc.) on academic publication performance using a multiple linear regression model; To examine the principal components of academic performance indicators through Principal Component Analysis (PCA), thereby distinguishing dimensions such as productivity and seniority; To classify academics into different productivity levels based on their publication and index profiles, and to identify statistically significant differences among these clusters. The findings obtained within this framework are expected to contribute both to inter-institutional comparisons and to the development of individual career and performance evaluation policies. Theoretical Underpinnings and Research Hypotheses The determinants of academic productivity have been widely examined in the literature, with both individual and institutional factors highlighted as significant predictors (Garfield, 2006; Abramo et al., 2011; Varol et al., 2024). Previous research indicates that academic title, educational background, gender, career duration, geographical region, and socioeconomic development level may significantly affect publication and citation performance. Especially in bibliometric studies, indicators such as the h-index, i10 index, national and international publication counts, and WoS/Scopus output are commonly used to assess scholarly impact (Hirsch, 2005; Noruzi, 2016). Within the field of Gastronomy and Culinary Arts, which is inherently interdisciplinary, academic productivity is shaped by both individual and institutional dynamics (Seyitoğlu & Çalışkan, 2018; Varol et al., 2024). However, in the Turkish context, comprehensive and multidimensional analyses of academic productivity remain scarce. Based on these theoretical and empirical findings, the following main and subsidiary hypotheses are proposed: Research Hypotheses H1: The total publication and citation performance of academics in the field of Gastronomy and Culinary Arts in Turkey differs significantly according to individual and institutional factors (educational background, academic title, gender, career duration, region of employment, SEGE level, etc.). H1a: There is a positive and significant relationship between academics’ h-index and i10 index values and their total publication counts. H1b: As academic title increases (Asst. Prof., Assoc. Prof., Prof.), the number of publications, WoS/Scopus papers, and citations significantly increase. H1c: The geographical region and SEGE level where academics are employed create significant differences in academic publication performance. H1d: There is no statistically significant difference in publication and citation performance between male and female academics. H1e: Field of graduation (bachelor’s, master’s, Ph.D.) has a significant effect on academic productivity. H1f: Academic career duration (total tenure and faculty service) is significantly related to total publication performance. H1g: According to Principal Component Analysis (PCA), academic performance indicators are separated into two main dimensions: productivity and seniority. H1h: Academics can be classified into three distinct productivity clusters (high, medium, low) based on their publication and citation profiles, and there are significant differences between these groups. Literature Background Definition and Scope of the Field of Gastronomy and Culinary Arts The provision of formal gastronomy education at the higher education level in Türkiye began in 1997 with the establishment of a two-year associate degree program at Bolu Mengen Vocational School. At the undergraduate level, the first GCa was launched at Yeditepe University in 2003(Aydemir, 2018). The inception of graduate-level education in the field dates back to 2014, when Ankara Gazi University (later renamed Hacı Bayram Veli University) launched the first master's and doctoral programs (Sezen, 2018). According to data released by the Council of Higher Education (YÖK) in 2023, there are currently 95 GCA departments (35 in foundation universities and 60 in public universities) nationwide (Bişiren & Gençer, 2023). Furthermore, the YÖK Atlas 2023 statistics indicate the presence of 34 master's and 11 doctoral programs in the field of GCA (Buluk Eşitti & Bay, 2023). As of 2024, higher education in gastronomy and culinary arts in Türkiye encompasses five distinct academic tracks: at the associate level, culinary and maritime culinary programs; at the undergraduate level, gastronomy, gastronomy and culinary arts departments; and at the graduate level, programs in gastronomy, gastronomy and culinary culture, and gastronomy and culinary arts are available. Gastronomy is defined as an interdisciplinary field that examines the cultural, social, and scientific dimensions of eating practices throughout human history. As emphasized by Jean Anthelme Brillat-Savarin in his seminal work Le Physiologie du Goût (1825/2009), gastronomy is not merely about “good food,” but also concerns “the philosophy behind food.” This definition has been further expanded by Scarpato (2003), who highlights the role of gastronomy in the preservation and marketing of cultural identities in a globalizing world. Culinary arts, on the other hand, are described by Van Der Linden, McClements, and Ubbink (2008) as a synthesis of technical skill and artistic creativity, encompassing a wide spectrum from chef training to molecular gastronomy. Especially in recent years, the integration of concepts such as “food systems” and “sustainability” has broadened both the academic and practical boundaries of the field (Hall & Gössling, 2013). The interdisciplinary nature of gastronomy directs researchers to various methodologies, ranging from anthropology to economics. For example, anthropological studies reveal the relationship between food rituals, gender roles, and class distinctions (Sutton, 2010), while tourism-focused research examines the influence of local cuisines on destination branding (Björk & Kauppinen-Räisänen, 2016). Furthermore, the scientific study of cooking, once rooted in natural sciences such as chemistry, physics, and biology (McGee, 2004), has evolved into a more holistic approach, combining technical aspects of cuisine with social sciences, including local food cultures and gastronomic history. This diversity enables the concurrent use of quantitative data and qualitative research within the field of gastronomy. Academic studies in Gastronomy and Culinary Arts (GCA) encompass a broad spectrum of cultural, social, economic, and technological dimensions through an interdisciplinary perspective. These studies primarily focus on the preservation and transmission of cultural heritage, the formation of gastronomic identity, the socioeconomic impacts of geographically indicated products, sustainable production and consumption models, and the intersection of tourism dynamics. Gastronomy tourism, the role of food-themed festivals in destination branding, and the integration of intangible cultural heritage into tourism practices are among the prominent research topics (Durlu-Özkaya, Sünnetçioğlu & Can, 2013; Çalışkan, 2013; Kılıçhan & Köşker, 2015; Sarıışık & Özbay, 2015; Ağcakaya & Can, 2019; Özdemir & Altıner, 2019; Aktaş Alan & Şen, 2020; Teyin, 2020; Belli & Güneren, 2022; Deniz, 2024). In addition, studies on the integration of technological innovations into gastronomy, molecular gastronomy, sensory analysis methods, and health-oriented gastronomic approaches support the experimental and applied aspects of the field. The concept of sustainable gastronomy is examined through multidisciplinary research on resource management, ecological balance, and the development of local economies. Pedagogical models in GCA education, the influence of religious norms on dietary habits, and the relationship between menu design and tourist experiences are addressed in the academic literature with a diversity of methodologies, thereby aiming to provide an academic framework for the field of gastronomy (Cömert & Çavuş, 2016; Özel, 2018; Aydemir, 2018; Eren, 2020; Mutlu Öztürk, 2020; Cankül & Ünal, 2021; Aydın & Uçkan Çakır, 2022; Güner & Aydoğdu, 2022; Varol & Kara, 2024). Globalization and digitalization have further expanded the scope of gastronomy. Social media platforms and food blogs have facilitated access to the world of professional kitchens (Çaycı, 2019; Çelik, 2023). At the same time, Netflix documentaries (e.g., Chef’s Table , Final Table ) and TV shows (e.g., MasterChef ) have accelerated interest, curiosity, and cross-cultural interaction in gastronomy (Abrams, 2020; Aslan, Demir & Kurnaz, 2024). Indices in the Measurement of Academic Success The Institute for Scientific Information (ISI) established various indices in 1960 to classify scientific publications. The Science Citation Index Expanded (SCIE) covers the natural and health sciences, the Social Sciences Citation Index (SSCI) covers the social sciences, and the Arts and Humanities Citation Index (A&HCI) covers the arts and humanities. The Emerging Sources Citation Index (ESCI), added to the Web of Science in 2015, monitors journals of high academic value that are not yet included in the other main indices (Asan, 2004; Editor Resources, 2024). Scopus, launched in 2004, categorizes journals into four main areas: life sciences, physical sciences, health sciences, and social sciences and humanities. Scopus treats health and life sciences separately from physical sciences, includes arts and humanities within social sciences, and classifies some journals as multidisciplinary (Karasözen, Gökkurt Bayram & Zan, 2011). Among other major international indices are ERIC, PUBMED, EMBASE, PSYCINFO, ECONLIT, and the EBSCO Hospitality & Tourism Index. In Türkiye, TRDizin, developed by ULAKBIM, evaluates journals according to set criteria and provides online access to articles. Other national databases such as Asos Index, Turkish Education Index, SOBİAD, and the Turkish Tourism Index also aim to increase the visibility of academic publications (Aslan, 2019; TRDizin, 2024; Varol, Kara & Sormaz, 2024). The evaluation of a researcher commonly relies on fundamental criteria such as published articles and books, presented papers, the number of citations received, involvement in scientific research projects, and participation in teaching activities. In recent years, additional indicators have become widely used in the evaluation process. One of the most prominent of these is the h-index, which is defined as the highest number h for which the researcher has published h articles that have each received at least h citations. For example, a researcher with an h-index of 10 has 10 articles that have each been cited at least 10 times, and additional citations beyond this do not increase the h-index (Güngör, Parlakyiğit & Tufan, 2023). The h-index is used by Google Scholar, Web of Science (WoS), and Scopus. Another widely used metric, the i10-index, represents the number of publications by a researcher that have received at least 10 citations (Noruzi, 2016). The i10-index aims to quickly quantify the number of “high-impact” works produced by a researcher and is primarily used by Google Scholar. The Socio-Economic Development Index (SEGE) The Socio-Economic Development Index (SEGE) is a nationally recognized composite metric developed by the Turkish Ministry of Industry and Technology, widely utilized by regional development agencies to assess the socio-economic development of provinces and districts in Turkey. SEGE encompasses a comprehensive array of indicators, including demography, employment, education, health, innovation capacity, fiscal resources, accessibility, and quality of life. These domains are synthesized using principal component analysis (PCA) to determine indicator weights and facilitate classification into six development levels, ranging from Level 1 (most developed) to Level 6 (least developed) (Turkish Ministry of Industry and Technology, 2022). Since its initial release in the late 1960s, SEGE has been periodically updated, with the most recent provincial dataset published in 2017 and subsequent district-level updates reported in 2022. The index functions as a strategic instrument for regional planning, guiding public investment allocations, incentive policies, and the monitoring of interregional socio-economic disparities (Tuncer, 2019). In the academic literature, SEGE has been frequently employed as an analytical framework for investigating disparities in academic productivity and access to educational resources. For example, Pırnal (2014) demonstrated a statistically significant relationship between SEGE-based development levels and student performance in national high school entrance examinations. Furthermore, international studies such as Kotomina and Tretiakova (2024) have highlighted a strong correlation between universities’ performance and key socio-economic indicators of regional development. In summary, SEGE provides a statistically robust and contextually nuanced foundation for examining the association between regional socio-economic development and outcomes in higher education, research infrastructure, and academic productivity across Turkey. Method Research Design This study employed a quantitative and cross-sectional research design to examine the academic publication and citation performance of academics working in the field of Gastronomy and Culinary Arts in Turkey. The research was conducted using a secondary data analysis approach, adopting a systematic methodology that adhered to established standards throughout the processes of data collection, coding, and analysis. Population and Sample The population of this study consisted of all academics working in Gastronomy and Culinary Arts departments at public and private universities in Turkey as of 2024. Following a comprehensive screening using the YÖK (Council of Higher Education, Turkey) Academic Database, a total of n=412 academics were included in the study. The inclusion criteria were based on the official title of the department and the active academic status of the faculty members. Data Collection Process and Sources All data used in this study were collected from open-access academic databases covering the period between 2020 and 2024. Publication, citation, and index information for each academic was manually compiled from the following platforms: akademik.yok.gov.tr (YÖK Academic) and Google Scholar. For each academic, performance indicators such as the number of books, book chapters, national and international articles, conference proceedings, WoS & Scopus publications, h-index, and i10-index were individually recorded. Demographic and professional information (including gender, academic rank, faculty/school, region, province, SEGE level, and field of graduation) was verified using YÖK Academic and the official websites of higher education institutions. Data were collected between May 5, 2025, and June 2, 2025. Publication Classification In this study, academic publications were classified into four categories according to their indexing status and scope: (1) WoS & Scopus-indexed publications—articles published in journals indexed by the Web of Science or Scopus databases; (2) International indexed publications—articles published in international indexed journals but not indexed by WoS, Scopus or TR Dizin; (3) TR Dizin publications—articles published in journals included in the Turkish Academic Journals Index (TR Dizin); (4) National publications—articles published in peer-reviewed national journals not indexed in any of the aforementioned databases. This classification enabled a more nuanced analysis of publication performance, capturing both the global visibility and local impact of academic outputs. Assignment of publications to these categories was based on the journal’s indexing status at the time of publication, as verified by the official lists of the respective indexing services. Variables and Operational Definitions Dependent Variable Total Publication Count: The sum of all national and international articles, books, book chapters, and conference proceedings published by each academic between 2020 and 2024. Independent Variables Demographic Variables: Gender (female/male); academic rank (Asst. Prof., Assoc. Prof., Prof.); geographical region of the institution (Marmara, Aegean, Mediterranean, Central Anatolia, Eastern Anatolia, Southeastern Anatolia, Black Sea); type of institution (faculty/vocational school); and field of graduation (coded separately for bachelor’s, master’s, and Ph.D. degrees). Career Variables: Total duration in academic position (years); duration as a faculty member (years); SEGE level (province-based Socio-Economic Development Index, ranging from 1 to 6). Academic Performance Indicators: h-index, i10-index, number of WoS & Scopus-indexed publications, number of TR Dizin and national publications, number of international publications, number of books and book chapters, and number of conference proceedings. Coding and Transformations: Categorical variables (e.g., academic rank, gender, region, field of graduation) were coded as dummy variables for the analysis. Continuous variables (e.g., total publications, h-index, i10-index, duration in position) were analyzed directly without transformation. Statistical Analysis Process Descriptive Statistics Initially, the demographic and professional distribution of the sample was summarized using frequency, percentage, mean, and standard deviation. Publication and index profiles across different academic ranks and regions were presented using tables and figures. Multiple Linear Regression Analysis Factors influencing academic productivity (total publication count) were tested using a multiple linear regression model. In the regression analysis:The dependent variable was the total publication count. Independent variables included region, academic rank, gender, type of institution (faculty/school), field of graduation, total duration in position, i10-index, and SEGE level. Variance inflation factor (VIF) values were calculated to assess the risk of multicollinearity; with all variables showing VIF < 10, the model was deemed reliable. The significance level was set at p < 0.05. Regression results were tabulated, reporting coefficients (B), standard error, t, p values, and 95% confidence intervals. Principal Component Analysis (PCA) PCA was conducted to identify the principal dimensions of academic performance. Only continuous variables were included in this analysis, and factor loadings and explained variance ratios were reported. The first two principal components explained 53.2% of the total variance. The first component (PC1) represented "overall academic productivity and scholarly impact," while the second component (PC2) reflected "experience and seniority." These findings illustrate the distinction between productivity and seniority among Turkish academics, in line with previous literature. Cluster Analysis Academics were grouped into three clusters (high, medium, and low productivity) using non-hierarchical clustering (K-means) based on total publications, h-index, i10-index, WoS & Scopus publications, and other performance indicators. The means of academic indicators for each group were presented in tables, and statistically significant productivity differences were demonstrated. Additional Analyses and Ethics Where appropriate, ANOVA and post hoc tests were used to examine differences between subgroups. Data analyses were conducted using IBM SPSS Statistics v22.0. As the research relied solely on open-access and publicly available data, ethical approval was not required. Nevertheless, full compliance with data privacy and academic ethical principles was ensured. Limitations The primary limitation of this study is its reliance solely on information obtained from open-access databases, with data compiled manually. As some academics’ publications may be indexed differently across various databases, there is a minor risk of incomplete records. Results and Discussion A total of 412 academics working in the field of Gastronomy and Culinary Arts in Türkiye were included in this study. The distribution of participants according to their undergraduate, master's, and doctoral degree fields, academic rank, gender, institutional affiliation, and geographical region is presented in Table 1. Varol, Kara, and Sormaz (2024) identified the number of academics in the field as 394 in their research conducted in 2024. Based on these findings, the number of faculty members in the field has increased by 4.97% over the past year. Among the participants, the most common undergraduate major was Tourism Management (28.16%), followed by Other Departments (26.94%), Food Engineering (25.49%), and Hospitality Management (8.74%). Regarding graduate education, Tourism Management was again the most prevalent field at the master’s level (38.11%), while at the doctoral level, the majority of degrees were in Tourism Management (37.86%) and Other Departments (26.46%). The findings of Semint and Özbay (2021) corroborate this distribution, reporting that among academics in the field, 33% held degrees in Tourism, 24% in Food Engineering, 14% in Gastronomy, 11% in Food and Beverage Management, 6% in Hospitality Management, 4% in Business Administration, 3% in Nutrition and Dietetics, 3% in Veterinary Medicine, and 2% in other fields. When the trends over the past four years are considered, the proportions of academics with degrees in Tourism and Food Engineering have remained relatively stable, while the share of those with a Gastronomy and Culinary Arts background has exhibited a noticeable decline. According to Karaca (2018), in terms of academic competence and professional experience, it is recommended that at least 70–75% of faculty members in gastronomy departments should possess an academic background in gastronomy or closely related fields. However, the findings of this study reveal that only 21 academics have completed their undergraduate, master’s, or doctoral degrees specifically in Gastronomy and Culinary Arts, corresponding to merely 5.10% of all faculty members. This notably low proportion can be attributed to the relatively recent establishment of gastronomy departments in Türkiye, with the first program launched in 2003, resulting in the employment of a considerable number of academics from other disciplines during the formative period. Nonetheless, despite the introduction of doctoral programs in the field since 2014 and the steadily increasing number of graduates each year, the persistent underrepresentation of GCA graduates among academic staff strongly suggests that, in addition to institutional practices, favoritism (nepotism) and cronyism continue to play a significant and visible role in academic appointments and recruitment processes (Dirlik and Alptekin, 2022). Regarding academic rank, nearly half of the participants were Assistant Professors (Dr., 49.51%), followed by Associate Professors (33.01%) and Professors (17.23%). The gender distribution was relatively balanced, with women representing 55.10% and men 44.90% of the sample. Most participants were affiliated with faculties (86.89%), while 13.11% worked in vocational schools. Geographically, the Marmara Region had the highest representation (29.13%), followed by Central Anatolia (16.02%) and Mediterranean (13.83%) regions. Table 1. Demographic and Academic Characteristics of Academics in Gastronomy and Culinary Arts (n=412) Variable Category n % Undergraduate Degree Tourism Management 116 28.16 Other Departments 111 26.94 Food Engineering 105 25.49 Hospitality Management 36 8.74 Gastronomy and Culinary Arts 26 6.31 Travel Management 10 2.43 Food & Beverage Management 8 1.94 Master’s Degree Tourism Management 157 38.11 Other Departments 113 27.43 Food Engineering 105 25.49 Gastronomy and Culinary Arts 37 8.98 Doctoral Degree Tourism Management 156 37.86 Other Departments 109 26.46 Food Engineering 97 23.54 Gastronomy and Culinary Arts 50 12.14 Academic Rank Assistant Professor 204 49.51 Associate Professor 136 33.01 Professor 71 17.23 Gender Female 227 55.10 Male 185 44.90 Department Structure Faculty 358 86.89 Vocational School 54 13.11 Region Marmara 120 29.13 Central Anatolia 66 16.02 Mediterranean 57 13.83 Black Sea 53 12.86 Southeastern Anatolia 41 9.95 Eastern Anatolia 39 9.47 Aegean 36 8.74 The publication and citation performance of academics according to their academic titles (Assistant Professor, Associate Professor, Professor) is summarized in Table 2. Both the h-index and i10 index values increased significantly with higher academic titles (p<0.05). Professors had the highest mean h-index (11.92±4.28), followed by associate professors (8.46±3.00) and assistant professors (4.98±2.74). Similarly, the i10 index was highest among professors (15.43±9.40), compared to associate professors (8.38±5.34) and assistant professors (3.63±3.38). The number of WoS & Scopus-indexed publications was significantly higher among associate professors (3.47±4.46) compared to other groups (p<0.05). The number of international publications was also higher among professors and associate professors compared to assistant professors. For TrDizin and national publications, there were no significant differences between groups. In terms of books and book chapters, professors and associate professors had significantly higher means than assistant professors. The number of conference proceedings was highest among associate professors (7.71±8.10), followed by professors and assistant professors. Varol, Kara, and Sormaz (2024) reported that associate professors produced a higher number of publications compared to both professors and assistant professors. Similarly, Jung (2014), in a study on Korean academics, found that early-career academics exhibited greater research productivity than their late-career counterparts. In contrast, Abramo, D’Angelo, and Di Costa (2011) demonstrated that professors generally display superior academic performance; however, they also noted that in certain fields, such as medicine, academics at other ranks may outperform professors. Likewise, Çalıkoğlu (2023) found that professors exhibited the highest levels of research performance. Similarly, the result of Zhou and Volkwein (2004) differ from the current study’s findings. Nevertheless, when bibliometric indices such as the h-index and i10-index are considered, it is evident that professors hold significantly higher values (p < 0.05). The variation in findings across studies may be attributed to differences in academic discipline, institutional and national contexts, and personal factors such as life expectancy and academic fatigue, all of which can influence research productivity. Table 2. Publication and Citation Performance by Academic Title Variable Assistant Prof. (Mean±SD) Associate Prof. (Mean±SD) Professor (Mean±SD) H-index 4.98±2.74ᵃ 8.46±3.00ᵇ 11.92±4.28ᶜ i10 Index 3.63±3.38ᵃ 8.38±5.34ᵇ 15.43±9.40ᶜ WoS & Scopus 2.04±3.22ᵃ 3.47±4.46ᵇ 2.75±3.73ᵃ International 1.64±2.96ᵃ 3.97±5.04ᵇ 3.35±4.06ᶜ TrDizin 2.92±3.12ᵃ 5.45±4.12ᵇ 5.44±6.08ᵃ National 0.22±0.77ᵃ 0.29±0.93ᵃ 0.48±2.06ᵃ Book 0.32±0.99ᵃ 0.60±1.12ᵇ 0.94±1.95ᶜ Book Chapter 5.56±5.54ᵃ 11.49±7.19ᵇ 8.44±9.18ᵃ Proceedings 4.56±4.23ᵃ 7.71±8.10ᵇ 4.65±5.24ᵃ Values with different superscript letters in the same row indicate statistically significant differences between groups (p<0.05). The total publication output was analyzed according to the Socio-Economic Development Index (SEGE) levels of the provinces where the academics are employed. The results are presented in Table 3. The average total publication number significantly decreased as the SEGE level decreased, indicating a positive relationship between the socio-economic development of a province and academic productivity. The most developed provinces (SEGE 1) had the highest average publication number (422.00±408.85), followed by SEGE 2 (220.00±218.61) and SEGE 4 (160.88±145.42). The lowest productivity was observed in the least developed provinces (SEGE 6: 84.92±61.71). These findings suggest that academic productivity in the field of gastronomy and culinary arts is strongly associated with the socio-economic development level of the province, with a clear decline in total publication numbers as the SEGE level decreases. Table 3. Total Publication Output by Socio-Economic Development Level (SEGE) of Provinces SEGE Level (Development) n (Province) Mean Total Publications ± SD 1 (Most Developed) 8 422.00 ± 408.85ᵃ 2 11 220.00 ± 218.61ᵃᵇ 4 16 160.88 ± 145.42ᵃᵇ 3 14 122.50 ± 103.09ᵇ 5 12 102.67 ± 83.62ᵇ 6 (Least Developed) 13 84.92 ± 61.71ᵇ Groups sharing the same superscript letter do not differ significantly; groups with different letters indicate statistically significant differences (p<0.05, post hoc test). A multiple linear regression analysis was conducted to determine the predictors of total publication output among academics (Table 4). Only variables that were found to be statistically significant are reported in the table. The results showed that region (Central Anatolia), total years in position, and i10 index were significant predictors of total publication output (p < 0.05). Specifically, being employed in the Central Anatolia region was associated with a significant increase in total publication number (β = 10.10, p = 0.001) compared to the reference group (Eastern Anatolia). Total years in position was found to have a small but significant negative effect on total publication output (β = -0.41, p = 0.032). On the other hand, a one-unit increase in the i10 index was associated with a substantial increase in total publications (β = 0.74, p < 0.001). The predominance of publications originating from the Central Anatolia region may be attributed to several factors, including the presence of the capital city, relatively high SEGE (Socio-Economic Development Index) levels in the region's provinces, and the existence of well-established and pioneering gastronomy departments such as Hacı Bayram Veli University, Necmettin Erbakan University, and Nevşehir Hacı Bektaş Veli University. Furthermore, the establishment of the first graduate and doctoral programs in gastronomy in this region likely provided an additional advantage in terms of academic output. On the other hand, a decline in academic publication productivity with increasing years spent in academia has also been documented in prior studies (Çalıkoğlu, 2023; Jung, 2014). Specifically, Çalıkoğlu (2023) reported that academic staff aged 60 and over exhibit the lowest levels of publication productivity. Similarly, Albert, Davia, and Legazpe (2015) found a negative relationship between age and scientific productivity. Conversely, an increase in the i10 index serves as a robust indicator of research productivity, as it reflects a higher number of publications surpassing a minimum citation threshold and thus signals sustained scholarly impact and visibility (Hirsch, 2005; Bornmann & Daniel, 2008). Table 4. Multiple Linear Regression Results (Dependent Variable: Total Publication Number) Variable β Std. Error T p-value 95% Lower 95% Upper Constant (Intercept) 10.46 15.15 0.69 0.490 -19.31 40.24 Region Central Anatolia 10.10 2.99 3.38 0.001 4.23 15.97 Total Years in Position -0.41 0.19 -2.16 0.032 -0.78 -0.03 i10 Index 0.74 0.14 5.23 0.000 0.46 1.02 Only statistically significant variables are presented. Reference categories: Region = Eastern Anatolia, Academic Title = Assistant Professor (Dr), Gender = Male, Department Structure = Faculty, Undergraduate Degree = Gastronomy and Culinary Arts. Model R² = 0.466; Adjusted R² = 0.434 Variance inflation factors (VIF) were examined for all independent variables included in the regression model (Table 5). All VIF values were below 10, indicating that no severe multicollinearity problem was present in the model. The highest VIF was observed for the academic title variables (Dr.: 6.73; Associate Professor: 6.29; Professor: 5.78). Table 5. VIF Values for Selected Independent Variables Variable VIF Asst. Prof. 6.73 Associate Professor 6.29 Professor 5.78 Total Years in Position 5.11 Marmara Region 4.11 i10 Index 3.11 Others <3 Principal Component Analysis (PCA) was performed to explore the underlying structure among publication and citation-related variables. The loadings of the first two principal components are shown in Table 6. The first principal component (PC1) showed strong positive loadings for h-index (0.36), i10 index (0.35), TrDizin publications (0.36), international publications (0.35), book chapters (0.33), proceedings (0.33), and total publication number (0.46). This component can be interpreted as a general indicator of overall academic productivity and research impact. The second principal component (PC2) was primarily associated with total years in position (0.56) and years as a faculty member (0.55), suggesting that this dimension reflects academic seniority and experience. Other variables had relatively lower loadings on this component. The first principal component (PC1) represents academic productivity and research performance, while the second principal component (PC2) reflects seniority and length of academic experience. The relatively low loading of WoS & Scopus publications on PC1 (0.17) may indicate that internationally indexed outputs are less correlated with other productivity metrics in this sample, possibly due to structural or field-specific publication trends in Turkey. The first two components together accounted for approximately 53.2% of the total variance, suggesting that the majority of the variation among the variables is adequately summarized by these two dimensions. The pattern of loadings indicates that productivity indicators and experience variables often load on distinct components, highlighting the multidimensional nature of academic achievement. Table 6. Principal Component Loadings for Academic Productivity Variables Variable PC1 PC2 Total Years in Position 0.09 0.56 Years as Faculty Member 0.10 0.55 h-index 0.36 0.29 i10 Index 0.35 0.31 WoS & Scopus 0.17 0.04 International 0.35 -0.14 TrDizin 0.36 -0.05 National 0.10 -0.07 Book 0.16 0.04 Book Chapter 0.33 -0.22 Proceedings 0.33 -0.27 Total Publication 0.46 -0.22 The cluster analysis revealed a highly stratified structure in academic productivity among Turkish gastronomy and culinary arts scholars. Statistically significant differences (p < 0.001) 7were observed across all key publication and citation indicators (see Table 7), with a small group of highly productive academics (n = 40) outperforming their peers by a substantial margin. This group displayed the highest averages for total publications, WoS & Scopus-indexed articles, international publications, books, book chapters, and proceedings, while the majority of academics fell into the medium or low productivity clusters. This pronounced disparity in research performance echoes broader findings in the literature. For instance, Abramo et al. (2011) demonstrated that research productivity among Italian academics is highly skewed by academic rank, with full professors significantly outperforming lower ranks in both publication volume and citation impact. Although their study does not explicitly identify a “small elite group,” it provides strong evidence of an unequal distribution of research output within the academic system. The present study's findings suggest that such structural inequality is also pronounced in the relatively new field of gastronomy and culinary arts in Turkey. In particular, the nearly fivefold difference in WoS & Scopus publications between the highest and lowest clusters underlines persistent barriers to global research engagement. These may include disparities in access to research funding, international networks, and institutional support, as also discussed by Çalıkoğlu (2023). Table 7. Publication and Index Profiles of Academic Productivity Clusters Cluster Name Total Publications h-index i10 Index WoS & Scopus International TrDizin National Book Proceedings n (Academics) High Productivity 62.9* 12.7* 17.5* 4.7* 10.5* 12.1* 1.0* 1.7* 15.6* 40 Medium Productivity 27.3* 8.9* 9.0* 3.9* 2.5* 4.8* 0.3* 0.6* 6.1* 183 Low Productivity 12.5* 4.3* 2.8* 1.0* 1.2* 1.9* 0.2* 0.2* 3.0* 189 *Statistically significant at p < 0.05. From a policy perspective, targeted support for medium and low productivity groups—such as structured mentoring, increased research training, and enhanced incentives for international publishing—could help bridge the existing productivity gap. Furthermore, future studies should examine longitudinal patterns and within-cluster variability to better understand the mechanisms underlying academic success in this field. Table 8 . Summary of Hypotheses Testing Results on Academic Productivity Factors Hypothesis Statement Result Supporting Evidence H1 Academic productivity significantly differs according to individual and institutional factors. Accepted ANOVA, regression, and cluster analysis indicated significant differences (p<0.05). H1a Positive relationship between h-index / i10-index and total publications. Accepted PCA and regression showed strong positive correlations (p<0.001). H1b Higher academic title is associated with higher publication, WoS/Scopus, and citation counts. Accepted Table 2; significant differences across ranks (p<0.05). H1c Region and SEGE level cause significant differences in productivity. Accepted Table 3; higher SEGE levels linked to higher output (p<0.05). H1d No gender difference in publication and citation performance. Rejected No statistically significant results supporting this claim. H1e Field of graduation significantly affects productivity. Accepted Distribution analysis; significant effect in regression models. H1f Academic career duration significantly related to productivity. Accepted Regression showed negative relationship (p<0.05). H1g PCA reveals two dimensions: productivity and seniority. Accepted PCA results, 53.2% variance explained. H1h Academics can be classified into three productivity clusters with significant differences. Accepted K-means clustering; significant differences across clusters (p<0.001). The results of the hypotheses testing provide robust empirical evidence regarding the determinants of academic productivity in Gastronomy and Culinary Arts in Turkey. Out of the nine hypotheses proposed, eight were supported by the data, while one (H1d) was rejected. Firstly, H1 was supported, indicating that individual and institutional characteristics jointly contribute to significant differences in research output. This is consistent with prior bibliometric studies (Abramo et al., 2011; Jung, 2014), which highlight the multifactorial nature of scholarly productivity. The acceptance of H1a confirms a strong and positive association between core bibliometric indices (h-index and i10-index) and total publication counts, reinforcing the validity of these metrics as performance indicators. Similarly, H1b and H1c demonstrate that higher academic rank and favorable geographical/SEGE conditions are associated with superior productivity, suggesting that both individual career progression and regional socio-economic factors shape scholarly output. H1e was supported, indicating that educational background exerts a significant influence on publication performance. This finding emphasizes the advantage of disciplinary alignment between formal education and academic appointment, echoing the concept of domain-specific expertise as a driver of productivity. The significant negative association between career duration and output (H1f) aligns with research documenting potential declines in productivity due to factors such as research fatigue or shifting professional priorities at later career stages (Albert et al., 2016). The PCA results (H1g) confirmed the conceptual distinction between productivity-oriented and seniority-oriented performance dimensions, explaining over 53% of total variance—an indication of the multidimensional nature of academic success. The cluster analysis (H1h) further validated the existence of three distinct productivity tiers with statistically significant disparities, pointing to structural inequalities within the field. Only H1d was rejected, as gender was not found to be a statistically significant determinant of productivity. This neutrality contrasts with some prior studies suggesting gender disparities but is aligned with others showing negligible differences in certain academic contexts (Abramo et al., 2011). Collectively, these results suggest that academic productivity in GCA is shaped by a combination of structural, institutional, and personal factors, with academic title, regional development level, and educational background being particularly influential. Policy interventions targeting medium- and low-productivity clusters, as well as strategies to enhance institutional support in lower-SEGE regions, could mitigate disparities and foster a more balanced distribution of research output. Conclusion This study offers the most comprehensive quantitative examination to date of academic publication and citation performance among scholars in Gastronomy and Culinary Arts (GCA) in Turkey, with direct implications for higher education policy and governance. The results reveal a markedly stratified academic landscape, in which academic rank, i10-index, and regional socio-economic development levels (SEGE) emerge as significant predictors of research productivity. Conversely, career duration is negatively associated with output, indicating potential challenges in sustaining productivity across academic life cycles. The Principal Component Analysis (PCA) confirms that productivity and seniority represent distinct dimensions of academic achievement, while cluster analysis identifies a small elite group of highly productive academics alongside a large proportion of medium- and low-productivity faculty. The persistently low representation of GCA graduates among academic staff, despite the rapid expansion of related programs, highlights a structural misalignment between disciplinary qualifications and recruitment practices. This mismatch risks slowing the development of a robust disciplinary identity and undermining the quality of academic programs. These findings underscore the need for policy frameworks that address regional disparities, establish discipline-specific appointment and promotion criteria, and create targeted mechanisms to enhance research capacity in underrepresented groups. By aligning recruitment, promotion, and funding policies with the specific needs of GCA, higher education institutions in Turkey can both strengthen the field and contribute to a more equitable and competitive national research environment. Policy Implications Regional Equity in Research Funding: Implement differentiated funding models that channel greater resources to universities in lower-SEGE regions, ensuring accountability and measurable outcomes. Discipline-Specific Recruitment and Promotion Standards: Introduce department-level benchmarks for academic appointments and promotions, reflecting the publication norms and competencies required in GCA. Capacity Building for Medium- and Low-Productivity Groups: Establish structured mentoring, research training, and mobility programs targeting underperforming faculty, particularly in disadvantaged regions. Career Development Across the Academic Life Cycle: Provide sabbaticals, research leave, and international collaboration opportunities to sustain productivity among senior academics. Internationalization Strategies: Expand access to global research networks, joint projects, and conference participation, especially for academics in peripheral regions. Limitations This research is limited by its reliance on open-access data sources, which may lead to incomplete or misclassified publication records. The cross-sectional design precludes causal inferences and limits the analysis of temporal changes in productivity. Cluster analysis relied on mean values and could not fully account for certain indices due to low variance. Furthermore, the study focuses exclusively on Turkish academics, restricting generalizability to other national contexts. Future Research Directions Future studies should employ longitudinal data to track publication trajectories over time and enable causal analysis. Comparative research involving other emerging academic disciplines or higher education systems with similar structural challenges would provide valuable benchmarks. Qualitative investigations could deepen understanding of institutional barriers, career motivations, and the lived experiences of academics in developing disciplines. 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MANAS Sosyal Araştırmalar Dergisi, 13 (1), 310-322. https://doi.org/10.33206/mjss.1256365 Zhou, Y., & Volkwein, J. F. (2004). Examining the influences on faculty departure intentions: A comparison of tenured versus nontenured faculty at research universities using NSOPF-99. Research in Higher Education, 45 , 139–176. https://doi.org/10.1023/B:RIHE.0000015693.38603.4c Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7408736","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":502569169,"identity":"c07ca8ac-0db1-447e-ae97-27832a288aab","order_by":0,"name":"Emre VAROL","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABC0lEQVRIiWNgGAWjYFADduYDQFICymMjRgszWwKqFh7CWngMkHh4tPCLnX34gLHNLp+fmefj44o/Fnn87WcPMHwoO8xgL30AqxbJ2enGBoxtyZYzm3k3G57hkSiWOJOXwDjj3GEGHr4ErFoMbqexSTCcYTYwOMy7TbJBQiJxA0OOATNvG1ALDpfZ305j/8Fwph6ohef5zwYDoBb+NwbMf/FoMZBOA/q04jBICxtjQwJQiwTQFkY8WiRupzFLJFQcN5BsZjOWbDggkTjjxhuDgz3n0nl4zuAIsdlpjB8+GFQb8LM3P/zY8Kcusb8/x/DBjzJrOfYe7FrAACNkDjAQE5OjYBSMglEwCnACAGj8T8/eafcEAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0511-2602","institution":"Erzincan Binali Yıldırım University","correspondingAuthor":true,"prefix":"","firstName":"Emre","middleName":"","lastName":"VAROL","suffix":""}],"badges":[],"createdAt":"2025-08-19 12:42:19","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7408736/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7408736/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89530120,"identity":"b8f47a05-aec9-43d6-aac7-8ea05951625d","added_by":"auto","created_at":"2025-08-21 03:42:15","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":87276,"visible":true,"origin":"","legend":"\u003cp\u003eUnnumbered image in the Introduction section.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7408736/v1/9a790dbee7b3c1e9bf521d04.png"},{"id":89530400,"identity":"b0d7999e-2822-4c6a-a0fe-53d31aeb926b","added_by":"auto","created_at":"2025-08-21 03:50:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1395640,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7408736/v1/e515863a-b243-4bca-8deb-63698102e588.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eAcademic Productivity in Turkish Gastronomy and Culinary Arts: A Multidimensional Quantitative Analysis (2020–2024)\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe measurement of individual performance is critically important for many institutions, particularly universities, as it informs target setting and strategic planning. Evaluating academics based on their scientific output is an integral aspect of the academic ecosystem, playing a decisive role in faculty appointments and the attainment of academic titles such as associate professorship and professorship (G\u0026uuml;ng\u0026ouml;r, Parlakyiğit \u0026amp; Tufan, 2023).\u003c/p\u003e\n\u003cp\u003eIn recent years, Gastronomy and Culinary Arts (GCA) has evolved from being primarily a vocational area to an established academic discipline (Seyitoğlu \u0026amp; \u0026Ccedil;alışkan, 2018). This transformation has led to a marked increase in scientific research in the field and has created a growing need to assess academic publication performance (Varol, Kara \u0026amp; Sormaz, 2024). Commonly used metrics in evaluating academic achievement include publication and citation counts, the h-index, and journal impact factors, among others (Garfield, 2006; Hirsch, 2005).\u003c/p\u003e\n\u003cp\u003eDespite the growing interest, there remains a limited body of research specifically addressing academic productivity in the field of Gastronomy and Culinary Arts. Existing studies tend to rely on general social science metrics and often overlook discipline-specific dynamics (Varol, Kara \u0026amp; Sormaz, 2024). In particular, the imbalance between the ways in which local culinary cultures are represented in academic publications and their level of visibility in global journals highlights the need for a comprehensive evaluation framework. While international research on academic productivity in interdisciplinary fields is expanding, studies focusing on the Turkish context are especially scarce, underscoring the significance of the present study.\u003c/p\u003e\n\u003cp\u003eThis study aims to systematically examine academic publication performance in the field of Gastronomy and Culinary Arts. Within the scope of the research, books, book chapters, conference proceedings, and academic articles produced by academics in Gastronomy and Culinary Arts between 2020 and 2024 will be identified through the academic.yok.gov.tr platform. The h-index and i10-index, which are significant indicators of academic performance, will be determined using Google Scholar. The findings are intended to provide guidance for gastronomy researchers and academic institutions in performance evaluation processes and to inform national science policy and strategic development in the field.\u003c/p\u003e\n\u003cp\u003eThe primary aim of this research is to examine the academic publication and citation performance of academics working in the field of Gastronomy and Culinary Arts in Turkey between 2020 and 2024 through a multidimensional approach. The study quantitatively evaluates the effects of individual (e.g., field of graduation, academic title, gender, professional seniority) and environmental factors (e.g., geographical region, type of institution, SEGE\u0026mdash;Socio-Economic Development Index\u0026mdash;level) on publication performance.\u003c/p\u003e\n\u003cp\u003eThe specific objectives of this research are as follows:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003eTo provide a detailed profile of the publications and citations of academics in Gastronomy and Culinary Arts (including total publications, WoS \u0026amp; Scopus publications, national/international publications, h-index, i10-index, books, and conference proceedings);\u003c/li\u003e\n \u003cli\u003eTo test the impact of demographic and professional variables (such as field of graduation, academic title, gender, total duration in position, SEGE, region, etc.) on academic publication performance using a multiple linear regression model;\u003c/li\u003e\n \u003cli\u003eTo examine the principal components of academic performance indicators through Principal Component Analysis (PCA), thereby distinguishing dimensions such as productivity and seniority;\u003c/li\u003e\n \u003cli\u003eTo classify academics into different productivity levels based on their publication and index profiles, and to identify statistically significant differences among these clusters.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThe findings obtained within this framework are expected to contribute both to inter-institutional comparisons and to the development of individual career and performance evaluation policies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTheoretical Underpinnings and Research Hypotheses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe determinants of academic productivity have been widely examined in the literature, with both individual and institutional factors highlighted as significant predictors (Garfield, 2006; Abramo et al., 2011; Varol et al., 2024). Previous research indicates that academic title, educational background, gender, career duration, geographical region, and socioeconomic development level may significantly affect publication and citation performance. Especially in bibliometric studies, indicators such as the h-index, i10 index, national and international publication counts, and WoS/Scopus output are commonly used to assess scholarly impact (Hirsch, 2005; Noruzi, 2016).\u003c/p\u003e\n\u003cp\u003eWithin the field of Gastronomy and Culinary Arts, which is inherently interdisciplinary, academic productivity is shaped by both individual and institutional dynamics (Seyitoğlu \u0026amp; \u0026Ccedil;alışkan, 2018; Varol et al., 2024). However, in the Turkish context, comprehensive and multidimensional analyses of academic productivity remain scarce.\u003c/p\u003e\n\u003cp\u003eBased on these theoretical and empirical findings, the following main and subsidiary hypotheses are proposed:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch Hypotheses\u003c/strong\u003e\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eH1:\u003c/strong\u003e The total publication and citation performance of academics in the field of Gastronomy and Culinary Arts in Turkey differs significantly according to individual and institutional factors (educational background, academic title, gender, career duration, region of employment, SEGE level, etc.).\u003cul type=\"circle\"\u003e\n \u003cli\u003e\u003cstrong\u003eH1a:\u003c/strong\u003e There is a positive and significant relationship between academics\u0026rsquo; h-index and i10 index values and their total publication counts.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eH1b:\u003c/strong\u003e As academic title increases (Asst. Prof., Assoc. Prof., Prof.), the number of publications, WoS/Scopus papers, and citations significantly increase.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eH1c:\u003c/strong\u003e The geographical region and SEGE level where academics are employed create significant differences in academic publication performance.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eH1d:\u003c/strong\u003e There is no statistically significant difference in publication and citation performance between male and female academics.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eH1e:\u003c/strong\u003e Field of graduation (bachelor\u0026rsquo;s, master\u0026rsquo;s, Ph.D.) has a significant effect on academic productivity.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eH1f:\u003c/strong\u003e Academic career duration (total tenure and faculty service) is significantly related to total publication performance.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eH1g:\u003c/strong\u003e According to Principal Component Analysis (PCA), academic performance indicators are separated into two main dimensions: productivity and seniority.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eH1h:\u003c/strong\u003e Academics can be classified into three distinct productivity clusters (high, medium, low) based on their publication and citation profiles, and there are significant differences between these groups.\u003c/li\u003e\n \u003c/ul\u003e\n \u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Literature Background","content":"\u003cp\u003e\u003cstrong\u003eDefinition and Scope of the Field of Gastronomy and Culinary Arts\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe provision of formal gastronomy education at the higher education level in T\u0026uuml;rkiye began in 1997 with the establishment of a two-year associate degree program at Bolu Mengen Vocational School. At the undergraduate level, the first GCa was launched at Yeditepe University in 2003(Aydemir, 2018). The inception of graduate-level education in the field dates back to 2014, when Ankara Gazi University (later renamed Hacı Bayram Veli University) launched the first master\u0026apos;s and doctoral programs (Sezen, 2018). According to data released by the Council of Higher Education (Y\u0026Ouml;K) in 2023, there are currently 95 GCA departments (35 in foundation universities and 60 in public universities) nationwide (Bişiren \u0026amp; Gen\u0026ccedil;er, 2023). Furthermore, the Y\u0026Ouml;K Atlas 2023 statistics indicate the presence of 34 master\u0026apos;s and 11 doctoral programs in the field of GCA (Buluk Eşitti \u0026amp; Bay, 2023). As of 2024, higher education in gastronomy and culinary arts in T\u0026uuml;rkiye encompasses five distinct academic tracks: at the associate level, culinary and maritime culinary programs; at the undergraduate level, gastronomy, gastronomy and culinary arts departments; and at the graduate level, programs in gastronomy, gastronomy and culinary culture, and gastronomy and culinary arts are available.\u003c/p\u003e\n\u003cp\u003eGastronomy is defined as an interdisciplinary field that examines the cultural, social, and scientific dimensions of eating practices throughout human history. As emphasized by Jean Anthelme Brillat-Savarin in his seminal work \u003cem\u003eLe Physiologie du Go\u0026ucirc;t\u003c/em\u003e (1825/2009), gastronomy is not merely about \u0026ldquo;good food,\u0026rdquo; but also concerns \u0026ldquo;the philosophy behind food.\u0026rdquo; This definition has been further expanded by Scarpato (2003), who highlights the role of gastronomy in the preservation and marketing of cultural identities in a globalizing world. Culinary arts, on the other hand, are described by Van Der Linden, McClements, and Ubbink (2008) as a synthesis of technical skill and artistic creativity, encompassing a wide spectrum from chef training to molecular gastronomy. Especially in recent years, the integration of concepts such as \u0026ldquo;food systems\u0026rdquo; and \u0026ldquo;sustainability\u0026rdquo; has broadened both the academic and practical boundaries of the field (Hall \u0026amp; G\u0026ouml;ssling, 2013).\u003c/p\u003e\n\u003cp\u003eThe interdisciplinary nature of gastronomy directs researchers to various methodologies, ranging from anthropology to economics. For example, anthropological studies reveal the relationship between food rituals, gender roles, and class distinctions (Sutton, 2010), while tourism-focused research examines the influence of local cuisines on destination branding (Bj\u0026ouml;rk \u0026amp; Kauppinen-R\u0026auml;is\u0026auml;nen, 2016). Furthermore, the scientific study of cooking, once rooted in natural sciences such as chemistry, physics, and biology (McGee, 2004), has evolved into a more holistic approach, combining technical aspects of cuisine with social sciences, including local food cultures and gastronomic history. This diversity enables the concurrent use of quantitative data and qualitative research within the field of gastronomy.\u003c/p\u003e\n\u003cp\u003eAcademic studies in Gastronomy and Culinary Arts (GCA) encompass a broad spectrum of cultural, social, economic, and technological dimensions through an interdisciplinary perspective. These studies primarily focus on the preservation and transmission of cultural heritage, the formation of gastronomic identity, the socioeconomic impacts of geographically indicated products, sustainable production and consumption models, and the intersection of tourism dynamics. Gastronomy tourism, the role of food-themed festivals in destination branding, and the integration of intangible cultural heritage into tourism practices are among the prominent research topics (Durlu-\u0026Ouml;zkaya, S\u0026uuml;nnet\u0026ccedil;ioğlu \u0026amp; Can, 2013; \u0026Ccedil;alışkan, 2013; Kılı\u0026ccedil;han \u0026amp; K\u0026ouml;şker, 2015; Sarıışık \u0026amp; \u0026Ouml;zbay, 2015; Ağcakaya \u0026amp; Can, 2019; \u0026Ouml;zdemir \u0026amp; Altıner, 2019; Aktaş Alan \u0026amp; Şen, 2020; Teyin, 2020; Belli \u0026amp; G\u0026uuml;neren, 2022; Deniz, 2024). In addition, studies on the integration of technological innovations into gastronomy, molecular gastronomy, sensory analysis methods, and health-oriented gastronomic approaches support the experimental and applied aspects of the field. The concept of sustainable gastronomy is examined through multidisciplinary research on resource management, ecological balance, and the development of local economies. Pedagogical models in GCA education, the influence of religious norms on dietary habits, and the relationship between menu design and tourist experiences are addressed in the academic literature with a diversity of methodologies, thereby aiming to provide an academic framework for the field of gastronomy (C\u0026ouml;mert \u0026amp; \u0026Ccedil;avuş, 2016; \u0026Ouml;zel, 2018; Aydemir, 2018; Eren, 2020; Mutlu \u0026Ouml;zt\u0026uuml;rk, 2020; Cank\u0026uuml;l \u0026amp; \u0026Uuml;nal, 2021; Aydın \u0026amp; U\u0026ccedil;kan \u0026Ccedil;akır, 2022; G\u0026uuml;ner \u0026amp; Aydoğdu, 2022; Varol \u0026amp; Kara, 2024).\u003c/p\u003e\n\u003cp\u003eGlobalization and digitalization have further expanded the scope of gastronomy. Social media platforms and food blogs have facilitated access to the world of professional kitchens (\u0026Ccedil;aycı, 2019; \u0026Ccedil;elik, 2023). At the same time, Netflix documentaries (e.g., \u003cem\u003eChef\u0026rsquo;s Table\u003c/em\u003e, \u003cem\u003eFinal Table\u003c/em\u003e) and TV shows (e.g., \u003cem\u003eMasterChef\u003c/em\u003e) have accelerated interest, curiosity, and cross-cultural interaction in gastronomy (Abrams, 2020; Aslan, Demir \u0026amp; Kurnaz, 2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndices in the Measurement of Academic Success\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institute for Scientific Information (ISI) established various indices in 1960 to classify scientific publications. The Science Citation Index Expanded (SCIE) covers the natural and health sciences, the Social Sciences Citation Index (SSCI) covers the social sciences, and the Arts and Humanities Citation Index (A\u0026amp;HCI) covers the arts and humanities. The Emerging Sources Citation Index (ESCI), added to the Web of Science in 2015, monitors journals of high academic value that are not yet included in the other main indices (Asan, 2004; Editor Resources, 2024). Scopus, launched in 2004, categorizes journals into four main areas: life sciences, physical sciences, health sciences, and social sciences and humanities. Scopus treats health and life sciences separately from physical sciences, includes arts and humanities within social sciences, and classifies some journals as multidisciplinary (Karas\u0026ouml;zen, G\u0026ouml;kkurt Bayram \u0026amp; Zan, 2011). Among other major international indices are ERIC, PUBMED, EMBASE, PSYCINFO, ECONLIT, and the EBSCO Hospitality \u0026amp; Tourism Index. In T\u0026uuml;rkiye, TRDizin, developed by ULAKBIM, evaluates journals according to set criteria and provides online access to articles. Other national databases such as Asos Index, Turkish Education Index, SOBİAD, and the Turkish Tourism Index also aim to increase the visibility of academic publications (Aslan, 2019; TRDizin, 2024; Varol, Kara \u0026amp; Sormaz, 2024).\u003c/p\u003e\n\u003cp\u003eThe evaluation of a researcher commonly relies on fundamental criteria such as published articles and books, presented papers, the number of citations received, involvement in scientific research projects, and participation in teaching activities. In recent years, additional indicators have become widely used in the evaluation process. One of the most prominent of these is the h-index, which is defined as the highest number h for which the researcher has published h articles that have each received at least h citations. For example, a researcher with an h-index of 10 has 10 articles that have each been cited at least 10 times, and additional citations beyond this do not increase the h-index (G\u0026uuml;ng\u0026ouml;r, Parlakyiğit \u0026amp; Tufan, 2023). The h-index is used by Google Scholar, Web of Science (WoS), and Scopus. Another widely used metric, the i10-index, represents the number of publications by a researcher that have received at least 10 citations (Noruzi, 2016). The i10-index aims to quickly quantify the number of \u0026ldquo;high-impact\u0026rdquo; works produced by a researcher and is primarily used by Google Scholar.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe Socio-Economic Development Index (SEGE)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Socio-Economic Development Index (SEGE) is a nationally recognized composite metric developed by the Turkish Ministry of Industry and Technology, widely utilized by regional development agencies to assess the socio-economic development of provinces and districts in Turkey. SEGE encompasses a comprehensive array of indicators, including demography, employment, education, health, innovation capacity, fiscal resources, accessibility, and quality of life. These domains are synthesized using principal component analysis (PCA) to determine indicator weights and facilitate classification into six development levels, ranging from Level 1 (most developed) to Level 6 (least developed) (Turkish Ministry of Industry and Technology, 2022).\u003c/p\u003e\n\u003cp\u003eSince its initial release in the late 1960s, SEGE has been periodically updated, with the most recent provincial dataset published in 2017 and subsequent district-level updates reported in 2022. The index functions as a strategic instrument for regional planning, guiding public investment allocations, incentive policies, and the monitoring of interregional socio-economic disparities (Tuncer, 2019).\u003c/p\u003e\n\u003cp\u003eIn the academic literature, SEGE has been frequently employed as an analytical framework for investigating disparities in academic productivity and access to educational resources. For example, Pırnal (2014) demonstrated a statistically significant relationship between SEGE-based development levels and student performance in national high school entrance examinations. Furthermore, international studies such as Kotomina and Tretiakova (2024) have highlighted a strong correlation between universities\u0026rsquo; performance and key socio-economic indicators of regional development.\u003c/p\u003e\n\u003cp\u003eIn summary, SEGE provides a statistically robust and contextually nuanced foundation for examining the association between regional socio-economic development and outcomes in higher education, research infrastructure, and academic productivity across Turkey.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003e\u003cstrong\u003eResearch Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study employed a quantitative and cross-sectional research design to examine the academic publication and citation performance of academics working in the field of Gastronomy and Culinary Arts in Turkey. The research was conducted using a secondary data analysis approach, adopting a systematic methodology that adhered to established standards throughout the processes of data collection, coding, and analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePopulation and Sample\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe population of this study consisted of all academics working in Gastronomy and Culinary Arts departments at public and private universities in Turkey as of 2024. Following a comprehensive screening using the Y\u0026Ouml;K (Council of Higher Education, Turkey) Academic Database, a total of n=412 academics were included in the study. The inclusion criteria were based on the official title of the department and the active academic status of the faculty members.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection Process and Sources\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data used in this study were collected from open-access academic databases covering the period between 2020 and 2024. Publication, citation, and index information for each academic was manually compiled from the following platforms: akademik.yok.gov.tr (Y\u0026Ouml;K Academic) and Google Scholar.\u003c/p\u003e\n\u003cp\u003eFor each academic, performance indicators such as the number of books, book chapters, national and international articles, conference proceedings, WoS \u0026amp; Scopus publications, h-index, and i10-index were individually recorded. Demographic and professional information (including gender, academic rank, faculty/school, region, province, SEGE level, and field of graduation) was verified using Y\u0026Ouml;K Academic and the official websites of higher education institutions. Data were collected between May 5, 2025, and June 2, 2025.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePublication Classification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, academic publications were classified into four categories according to their indexing status and scope:\u003c/p\u003e\n\u003cp\u003e(1) WoS \u0026amp; Scopus-indexed publications\u0026mdash;articles published in journals indexed by the Web of Science or Scopus databases;\u003c/p\u003e\n\u003cp\u003e(2) International indexed publications\u0026mdash;articles published in international indexed journals but not indexed by WoS, Scopus or TR Dizin;\u003c/p\u003e\n\u003cp\u003e(3) TR Dizin publications\u0026mdash;articles published in journals included in the Turkish Academic Journals Index (TR Dizin);\u003c/p\u003e\n\u003cp\u003e(4) National publications\u0026mdash;articles published in peer-reviewed national journals not indexed in any of the aforementioned databases.\u003c/p\u003e\n\u003cp\u003eThis classification enabled a more nuanced analysis of publication performance, capturing both the global visibility and local impact of academic outputs. Assignment of publications to these categories was based on the journal\u0026rsquo;s indexing status at the time of publication, as verified by the official lists of the respective indexing services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariables and Operational Definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent Variable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTotal Publication Count: The sum of all national and international articles, books, book chapters, and conference proceedings published by each academic between 2020 and 2024.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic Variables: Gender (female/male); academic rank (Asst. Prof., Assoc. Prof., Prof.); geographical region of the institution (Marmara, Aegean, Mediterranean, Central Anatolia, Eastern Anatolia, Southeastern Anatolia, Black Sea); type of institution (faculty/vocational school); and field of graduation (coded separately for bachelor\u0026rsquo;s, master\u0026rsquo;s, and Ph.D. degrees).\u003c/p\u003e\n\u003cp\u003eCareer Variables: Total duration in academic position (years); duration as a faculty member (years); SEGE level (province-based Socio-Economic Development Index, ranging from 1 to 6).\u003c/p\u003e\n\u003cp\u003eAcademic Performance Indicators: h-index, i10-index, number of WoS \u0026amp; Scopus-indexed publications, number of TR Dizin and national publications, number of international publications, number of books and book chapters, and number of conference proceedings.\u003c/p\u003e\n\u003cp\u003eCoding and Transformations: Categorical variables (e.g., academic rank, gender, region, field of graduation) were coded as dummy variables for the analysis. Continuous variables (e.g., total publications, h-index, i10-index, duration in position) were analyzed directly without transformation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis Process\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDescriptive Statistics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInitially, the demographic and professional distribution of the sample was summarized using frequency, percentage, mean, and standard deviation. Publication and index profiles across different academic ranks and regions were presented using tables and figures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultiple Linear Regression Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFactors influencing academic productivity (total publication count) were tested using a multiple linear regression model. In the regression analysis:The dependent variable was the total publication count.\u003c/p\u003e\n\u003cp\u003eIndependent variables included region, academic rank, gender, type of institution (faculty/school), field of graduation, total duration in position, i10-index, and SEGE level.\u003c/p\u003e\n\u003cp\u003eVariance inflation factor (VIF) values were calculated to assess the risk of multicollinearity; with all variables showing VIF \u0026lt; 10, the model was deemed reliable. The significance level was set at p \u0026lt; 0.05. Regression results were tabulated, reporting coefficients (B), standard error, t, p values, and 95% confidence intervals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrincipal Component Analysis (PCA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePCA was conducted to identify the principal dimensions of academic performance. Only continuous variables were included in this analysis, and factor loadings and explained variance ratios were reported. The first two principal components explained 53.2% of the total variance. The first component (PC1) represented \u0026quot;overall academic productivity and scholarly impact,\u0026quot; while the second component (PC2) reflected \u0026quot;experience and seniority.\u0026quot; These findings illustrate the distinction between productivity and seniority among Turkish academics, in line with previous literature.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCluster Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcademics were grouped into three clusters (high, medium, and low productivity) using non-hierarchical clustering (K-means) based on total publications, h-index, i10-index, WoS \u0026amp; Scopus publications, and other performance indicators. The means of academic indicators for each group were presented in tables, and statistically significant productivity differences were demonstrated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAdditional Analyses and Ethics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWhere appropriate, ANOVA and post hoc tests were used to examine differences between subgroups. Data analyses were conducted using IBM SPSS Statistics v22.0. As the research relied solely on open-access and publicly available data, ethical approval was not required. Nevertheless, full compliance with data privacy and academic ethical principles was ensured.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary limitation of this study is its reliance solely on information obtained from open-access databases, with data compiled manually. As some academics\u0026rsquo; publications may be indexed\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003edifferently across various databases, there is a minor risk of incomplete records.\u003c/p\u003e"},{"header":"Results and Discussion","content":"\u003cp\u003eA total of 412 academics working in the field of Gastronomy and Culinary Arts in T\u0026uuml;rkiye were included in this study. The distribution of participants according to their undergraduate, master\u0026apos;s, and doctoral degree fields, academic rank, gender, institutional affiliation, and geographical region is presented in Table 1. Varol, Kara, and Sormaz (2024) identified the number of academics in the field as 394 in their research conducted in 2024. Based on these findings, the number of faculty members in the field has increased by 4.97% over the past year.\u003c/p\u003e\n\u003cp\u003eAmong the participants, the most common undergraduate major was Tourism Management (28.16%), followed by Other Departments (26.94%), Food Engineering (25.49%), and Hospitality Management (8.74%). Regarding graduate education, Tourism Management was again the most prevalent field at the master\u0026rsquo;s level (38.11%), while at the doctoral level, the majority of degrees were in Tourism Management (37.86%) and Other Departments (26.46%).\u003c/p\u003e\n\u003cp\u003eThe findings of Semint and \u0026Ouml;zbay (2021) corroborate this distribution, reporting that among academics in the field, 33% held degrees in Tourism, 24% in Food Engineering, 14% in Gastronomy, 11% in Food and Beverage Management, 6% in Hospitality Management, 4% in Business Administration, 3% in Nutrition and Dietetics, 3% in Veterinary Medicine, and 2% in other fields. When the trends over the past four years are considered, the proportions of academics with degrees in Tourism and Food Engineering have remained relatively stable, while the share of those with a Gastronomy and Culinary Arts background has exhibited a noticeable decline.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAccording to Karaca (2018), in terms of academic competence and professional experience, it is recommended that at least 70\u0026ndash;75% of faculty members in gastronomy departments should possess an academic background in gastronomy or closely related fields. However, the findings of this study reveal that only 21 academics have completed their undergraduate, master\u0026rsquo;s, or doctoral degrees specifically in Gastronomy and Culinary Arts, corresponding to merely 5.10% of all faculty members. This notably low proportion can be attributed to the relatively recent establishment of gastronomy departments in T\u0026uuml;rkiye, with the first program launched in 2003, resulting in the employment of a considerable number of academics from other disciplines during the formative period. Nonetheless, despite the introduction of doctoral programs in the field since 2014 and the steadily increasing number of graduates each year, the persistent underrepresentation of GCA graduates among academic staff strongly suggests that, in addition to institutional practices, favoritism (nepotism) and cronyism continue to play a significant and visible role in academic appointments and recruitment processes (Dirlik and Alptekin, 2022).\u003c/p\u003e\n\u003cp\u003eRegarding academic rank, nearly half of the participants were Assistant Professors (Dr., 49.51%), followed by Associate Professors (33.01%) and Professors (17.23%). The gender distribution was relatively balanced, with women representing 55.10% and men 44.90% of the sample. Most participants were affiliated with faculties (86.89%), while 13.11% worked in vocational schools. Geographically, the Marmara Region had the highest representation (29.13%), followed by Central Anatolia (16.02%) and Mediterranean (13.83%) regions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eDemographic and Academic Characteristics of Academics in Gastronomy and Culinary Arts (n=412)\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUndergraduate Degree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eTourism Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e28.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eOther Departments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e26.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eFood Engineering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e25.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eHospitality Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e8.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eGastronomy and Culinary Arts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e6.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eTravel Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e2.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eFood \u0026amp; Beverage Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaster\u0026rsquo;s Degree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eTourism Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e38.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eOther Departments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e27.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eFood Engineering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e25.49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eGastronomy and Culinary Arts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e8.98\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"4\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDoctoral Degree\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eTourism Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e37.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eOther Departments\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e26.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eFood Engineering\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e23.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eGastronomy and Culinary Arts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e12.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcademic Rank\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eAssistant Professor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e49.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eAssociate Professor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e33.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eProfessor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e17.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e55.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e44.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDepartment Structure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eFaculty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e86.89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eVocational School\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e13.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"7\" style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eMarmara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e29.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eCentral Anatolia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e16.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eMediterranean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e13.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eBlack Sea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e12.86\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eSoutheastern Anatolia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e9.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eEastern Anatolia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e9.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 48px;\"\u003e\n \u003cp\u003eAegean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e8.74\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe publication and citation performance of academics according to their academic titles (Assistant Professor, Associate Professor, Professor) is summarized in Table 2.\u003c/p\u003e\n\u003cp\u003eBoth the h-index and i10 index values increased significantly with higher academic titles (p\u0026lt;0.05). Professors had the highest mean h-index (11.92\u0026plusmn;4.28), followed by associate professors (8.46\u0026plusmn;3.00) and assistant professors (4.98\u0026plusmn;2.74). Similarly, the i10 index was highest among professors (15.43\u0026plusmn;9.40), compared to associate professors (8.38\u0026plusmn;5.34) and assistant professors (3.63\u0026plusmn;3.38).\u003c/p\u003e\n\u003cp\u003eThe number of WoS \u0026amp; Scopus-indexed publications was significantly higher among associate professors (3.47\u0026plusmn;4.46) compared to other groups (p\u0026lt;0.05). The number of international publications was also higher among professors and associate professors compared to assistant professors. For TrDizin and national publications, there were no significant differences between groups. In terms of books and book chapters, professors and associate professors had significantly higher means than assistant professors. The number of conference proceedings was highest among associate professors (7.71\u0026plusmn;8.10), followed by professors and assistant professors.\u003c/p\u003e\n\u003cp\u003eVarol, Kara, and Sormaz (2024) reported that associate professors produced a higher number of publications compared to both professors and assistant professors. Similarly, Jung (2014), in a study on Korean academics, found that early-career academics exhibited greater research productivity than their late-career counterparts.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn contrast, Abramo, D\u0026rsquo;Angelo, and Di Costa (2011) demonstrated that professors generally display superior academic performance; however, they also noted that in certain fields, such as medicine, academics at other ranks may outperform professors. Likewise, \u0026Ccedil;alıkoğlu (2023) found that professors exhibited the highest levels of research performance. Similarly, the result of Zhou and Volkwein (2004) differ from the current study\u0026rsquo;s findings.\u003c/p\u003e\n\u003cp\u003eNevertheless, when bibliometric indices such as the h-index and i10-index are considered, it is evident that professors hold significantly higher values (p \u0026lt; 0.05). The variation in findings across studies may be attributed to differences in academic discipline, institutional and national contexts, and personal factors such as life expectancy and academic fatigue, all of which can influence research productivity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003ePublication and Citation Performance by Academic Title\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAssistant Prof. (Mean\u0026plusmn;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAssociate Prof. (Mean\u0026plusmn;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProfessor (Mean\u0026plusmn;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH-index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e4.98\u0026plusmn;2.74ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e8.46\u0026plusmn;3.00ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e11.92\u0026plusmn;4.28ᶜ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ei10 Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e3.63\u0026plusmn;3.38ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e8.38\u0026plusmn;5.34ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e15.43\u0026plusmn;9.40ᶜ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWoS \u0026amp; Scopus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e2.04\u0026plusmn;3.22ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e3.47\u0026plusmn;4.46ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e2.75\u0026plusmn;3.73ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternational\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e1.64\u0026plusmn;2.96ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e3.97\u0026plusmn;5.04ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e3.35\u0026plusmn;4.06ᶜ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrDizin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e2.92\u0026plusmn;3.12ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e5.45\u0026plusmn;4.12ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e5.44\u0026plusmn;6.08ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNational\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e0.22\u0026plusmn;0.77ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e0.29\u0026plusmn;0.93ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e0.48\u0026plusmn;2.06ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBook\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e0.32\u0026plusmn;0.99ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e0.60\u0026plusmn;1.12ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e0.94\u0026plusmn;1.95ᶜ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBook Chapter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e5.56\u0026plusmn;5.54ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e11.49\u0026plusmn;7.19ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e8.44\u0026plusmn;9.18ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 15px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProceedings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e4.56\u0026plusmn;4.23ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 29px;\"\u003e\n \u003cp\u003e7.71\u0026plusmn;8.10ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 23px;\"\u003e\n \u003cp\u003e4.65\u0026plusmn;5.24ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues with different superscript letters in the same row indicate statistically significant differences between groups (p\u0026lt;0.05).\u003c/p\u003e\n\u003cp\u003eThe total publication output was analyzed according to the Socio-Economic Development Index (SEGE) levels of the provinces where the academics are employed. The results are presented in Table 3.\u003c/p\u003e\n\u003cp\u003eThe average total publication number significantly decreased as the SEGE level decreased, indicating a positive relationship between the socio-economic development of a province and academic productivity. The most developed provinces (SEGE 1) had the highest average publication number (422.00\u0026plusmn;408.85), followed by SEGE 2 (220.00\u0026plusmn;218.61) and SEGE 4 (160.88\u0026plusmn;145.42). The lowest productivity was observed in the least developed provinces (SEGE 6: 84.92\u0026plusmn;61.71).\u003c/p\u003e\n\u003cp\u003eThese findings suggest that academic productivity in the field of gastronomy and culinary arts is strongly associated with the socio-economic development level of the province, with a clear decline in total publication numbers as the SEGE level decreases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eTotal Publication Output by Socio-Economic Development Level (SEGE) of Provinces\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSEGE Level (Development)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (Province)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean Total Publications \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e1 (Most Developed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e422.00 \u0026plusmn; 408.85ᵃ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e220.00 \u0026plusmn; 218.61ᵃᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e160.88 \u0026plusmn; 145.42ᵃᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e122.50 \u0026plusmn; 103.09ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e102.67 \u0026plusmn; 83.62ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 38px;\"\u003e\n \u003cp\u003e6 (Least Developed)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 17px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 41px;\"\u003e\n \u003cp\u003e84.92 \u0026plusmn; 61.71ᵇ\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eGroups sharing the same superscript letter do not differ significantly; groups with different letters indicate statistically significant differences (p\u0026lt;0.05, post hoc test).\u003c/p\u003e\n\u003cp\u003eA multiple linear regression analysis was conducted to determine the predictors of total publication output among academics (Table 4). Only variables that were found to be statistically significant are reported in the table. The results showed that region (Central Anatolia), total years in position, and i10 index were significant predictors of total publication output (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003eSpecifically, being employed in the Central Anatolia region was associated with a significant increase in total publication number (\u0026beta; = 10.10, p = 0.001) compared to the reference group (Eastern Anatolia). Total years in position was found to have a small but significant negative effect on total publication output (\u0026beta; = -0.41, p = 0.032). On the other hand, a one-unit increase in the i10 index was associated with a substantial increase in total publications (\u0026beta; = 0.74, p \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eThe predominance of publications originating from the Central Anatolia region may be attributed to several factors, including the presence of the capital city, relatively high SEGE (Socio-Economic Development Index) levels in the region\u0026apos;s provinces, and the existence of well-established and pioneering gastronomy departments such as Hacı Bayram Veli University, Necmettin Erbakan University, and Nevşehir Hacı Bektaş Veli University. Furthermore, the establishment of the first graduate and doctoral programs in gastronomy in this region likely provided an additional advantage in terms of academic output.\u003cbr\u003e\u0026nbsp;On the other hand, a decline in academic publication productivity with increasing years spent in academia has also been documented in prior studies (\u0026Ccedil;alıkoğlu, 2023; Jung, 2014). Specifically, \u0026Ccedil;alıkoğlu (2023) reported that academic staff aged 60 and over exhibit the lowest levels of publication productivity. Similarly, Albert, Davia, and Legazpe (2015) found a negative relationship between age and scientific productivity.\u003cbr\u003e\u0026nbsp;Conversely, an increase in the i10 index serves as a robust indicator of research productivity, as it reflects a higher number of publications surpassing a minimum citation threshold and thus signals sustained scholarly impact and visibility (Hirsch, 2005; Bornmann \u0026amp; Daniel, 2008).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eMultiple Linear Regression Results (Dependent Variable: Total Publication Number)\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStd. Error\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Lower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% Upper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConstant (Intercept)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e10.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e15.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.490\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-19.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e40.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion Central Anatolia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e10.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e4.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e15.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Years in Position\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e-0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e-2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 30px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ei10 Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e5.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOnly statistically significant variables are presented. Reference categories: Region = Eastern Anatolia, Academic Title = Assistant Professor (Dr), Gender = Male, Department Structure = Faculty, Undergraduate Degree = Gastronomy and Culinary Arts. Model R\u0026sup2; = 0.466; Adjusted R\u0026sup2; = 0.434\u003c/p\u003e\n\u003cp\u003eVariance inflation factors (VIF) were examined for all independent variables included in the regression model (Table 5). All VIF values were below 10, indicating that no severe multicollinearity problem was present in the model. The highest VIF was observed for the academic title variables (Dr.: 6.73; Associate Professor: 6.29; Professor: 5.78).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u0026nbsp;\u003c/strong\u003eVIF Values for Selected Independent Variables\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVIF\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eAsst. Prof.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e6.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eAssociate Professor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e6.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eProfessor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e5.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eTotal Years in Position\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eMarmara Region\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e4.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003ei10 Index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e3.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 79px;\"\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 16px;\"\u003e\n \u003cp\u003e\u0026lt;3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003ePrincipal Component Analysis (PCA) was performed to explore the underlying structure among publication and citation-related variables. The loadings of the first two principal components are shown in Table 6.\u003c/p\u003e\n\u003cp\u003eThe first principal component (PC1) showed strong positive loadings for h-index (0.36), i10 index (0.35), TrDizin publications (0.36), international publications (0.35), book chapters (0.33), proceedings (0.33), and total publication number (0.46). This component can be interpreted as a general indicator of overall academic productivity and research impact.\u003c/p\u003e\n\u003cp\u003eThe second principal component (PC2) was primarily associated with total years in position (0.56) and years as a faculty member (0.55), suggesting that this dimension reflects academic seniority and experience. Other variables had relatively lower loadings on this component. The first principal component (PC1) represents academic productivity and research performance, while the second principal component (PC2) reflects seniority and length of academic experience.\u003c/p\u003e\n\u003cp\u003eThe relatively low loading of WoS \u0026amp; Scopus publications on PC1 (0.17) may indicate that internationally indexed outputs are less correlated with other productivity metrics in this sample, possibly due to structural or field-specific publication trends in Turkey. The first two components together accounted for approximately 53.2% of the total variance, suggesting that the majority of the variation among the variables is adequately summarized by these two dimensions. The pattern of loadings indicates that productivity indicators and experience variables often load on distinct components, highlighting the multidimensional nature of academic achievement.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6.\u003c/strong\u003e Principal Component Loadings for Academic Productivity Variables\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePC2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Years in Position\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eYears as Faculty Member\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eh-index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ei10 Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWoS \u0026amp; Scopus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternational\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrDizin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNational\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBook\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBook Chapter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProceedings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 68px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Publication\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 14px;\"\u003e\n \u003cp\u003e-0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe cluster analysis revealed a highly stratified structure in academic productivity among Turkish gastronomy and culinary arts scholars. Statistically significant differences (p \u0026lt; 0.001) 7were observed across all key publication and citation indicators (see Table 7), with a small group of highly productive academics (n = 40) outperforming their peers by a substantial margin. This group displayed the highest averages for total publications, WoS \u0026amp; Scopus-indexed articles, international publications, books, book chapters, and proceedings, while the majority of academics fell into the medium or low productivity clusters.\u003c/p\u003e\n\u003cp\u003eThis pronounced disparity in research performance echoes broader findings in the literature. For instance, Abramo et al. (2011) demonstrated that research productivity among Italian academics is highly skewed by academic rank, with full professors significantly outperforming lower ranks in both publication volume and citation impact. Although their study does not explicitly identify a \u0026ldquo;small elite group,\u0026rdquo; it provides strong evidence of an unequal distribution of research output within the academic system.\u003c/p\u003e\n\u003cp\u003eThe present study\u0026apos;s findings suggest that such structural inequality is also pronounced in the relatively new field of gastronomy and culinary arts in Turkey. In particular, the nearly fivefold difference in WoS \u0026amp; Scopus publications between the highest and lowest clusters underlines persistent barriers to global research engagement. These may include disparities in access to research funding, international networks, and institutional support, as also discussed by \u0026Ccedil;alıkoğlu (2023).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7.\u003c/strong\u003e Publication and Index Profiles of Academic Productivity Clusters\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCluster Name\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Publications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eh-index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ei10 Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWoS \u0026amp; Scopus\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInternational\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTrDizin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNational\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBook\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProceedings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003en (Academics)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHigh Productivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e62.9*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e12.7*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e17.5*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e4.7*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e10.5*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e12.1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1.0*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e1.7*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e15.6*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedium Productivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e27.3*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e8.9*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e9.0*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e3.9*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e2.5*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e4.8*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.3*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.6*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e6.1*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow Productivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e12.5*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e4.3*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e2.8*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 6px;\"\u003e\n \u003cp\u003e1.0*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e1.2*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7px;\"\u003e\n \u003cp\u003e1.9*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e0.2*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 5px;\"\u003e\n \u003cp\u003e0.2*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e3.0*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e189\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Statistically significant at p \u0026lt; 0.05.\u003c/p\u003e\n\u003cp\u003eFrom a policy perspective, targeted support for medium and low productivity groups\u0026mdash;such as structured mentoring, increased research training, and enhanced incentives for international publishing\u0026mdash;could help bridge the existing productivity gap. Furthermore, future studies should examine longitudinal patterns and within-cluster variability to better understand the mechanisms underlying academic success in this field.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 8\u003c/strong\u003e. Summary of Hypotheses Testing Results on Academic Productivity Factors\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypothesis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatement\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResult\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSupporting Evidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eAcademic productivity significantly differs according to individual and institutional factors.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eANOVA, regression, and cluster analysis indicated significant differences (p\u0026lt;0.05).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1a\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003ePositive relationship between h-index / i10-index and total publications.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003ePCA and regression showed strong positive correlations (p\u0026lt;0.001).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1b\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eHigher academic title is associated with higher publication, WoS/Scopus, and citation counts.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eTable 2; significant differences across ranks (p\u0026lt;0.05).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1c\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eRegion and SEGE level cause significant differences in productivity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eTable 3; higher SEGE levels linked to higher output (p\u0026lt;0.05).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1d\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eNo gender difference in publication and citation performance.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRejected\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eNo statistically significant results supporting this claim.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eField of graduation significantly affects productivity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eDistribution analysis; significant effect in regression models.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1f\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eAcademic career duration significantly related to productivity.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eRegression showed negative relationship (p\u0026lt;0.05).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1g\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003ePCA reveals two dimensions: productivity and seniority.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003ePCA results, 53.2% variance explained.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eH1h\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 39px;\"\u003e\n \u003cp\u003eAcademics can be classified into three productivity clusters with significant differences.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAccepted\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 35px;\"\u003e\n \u003cp\u003eK-means clustering; significant differences across clusters (p\u0026lt;0.001).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe results of the hypotheses testing provide robust empirical evidence regarding the determinants of academic productivity in Gastronomy and Culinary Arts in Turkey. Out of the nine hypotheses proposed, eight were supported by the data, while one (H1d) was rejected.\u003c/p\u003e\n\u003cp\u003eFirstly, H1 was supported, indicating that individual and institutional characteristics jointly contribute to significant differences in research output. This is consistent with prior bibliometric studies (Abramo et al., 2011; Jung, 2014), which highlight the multifactorial nature of scholarly productivity.\u003c/p\u003e\n\u003cp\u003eThe acceptance of H1a confirms a strong and positive association between core bibliometric indices (h-index and i10-index) and total publication counts, reinforcing the validity of these metrics as performance indicators. Similarly, H1b and H1c demonstrate that higher academic rank and favorable geographical/SEGE conditions are associated with superior productivity, suggesting that both individual career progression and regional socio-economic factors shape scholarly output.\u003c/p\u003e\n\u003cp\u003eH1e was supported, indicating that educational background exerts a significant influence on publication performance. This finding emphasizes the advantage of disciplinary alignment between formal education and academic appointment, echoing the concept of domain-specific expertise as a driver of productivity.\u003c/p\u003e\n\u003cp\u003eThe significant negative association between career duration and output (H1f) aligns with research documenting potential declines in productivity due to factors such as research fatigue or shifting professional priorities at later career stages (Albert et al., 2016).\u003c/p\u003e\n\u003cp\u003eThe PCA results (H1g) confirmed the conceptual distinction between productivity-oriented and seniority-oriented performance dimensions, explaining over 53% of total variance\u0026mdash;an indication of the multidimensional nature of academic success. The cluster analysis (H1h) further validated the existence of three distinct productivity tiers with statistically significant disparities, pointing to structural inequalities within the field.\u003c/p\u003e\n\u003cp\u003eOnly H1d was rejected, as gender was not found to be a statistically significant determinant of productivity. This neutrality contrasts with some prior studies suggesting gender disparities but is aligned with others showing negligible differences in certain academic contexts (Abramo et al., 2011).\u003c/p\u003e\n\u003cp\u003eCollectively, these results suggest that academic productivity in GCA is shaped by a combination of structural, institutional, and personal factors, with academic title, regional development level, and educational background being particularly influential. Policy interventions targeting medium- and low-productivity clusters, as well as strategies to enhance institutional support in lower-SEGE regions, could mitigate disparities and foster a more balanced distribution of research output.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study offers the most comprehensive quantitative examination to date of academic publication and citation performance among scholars in Gastronomy and Culinary Arts (GCA) in Turkey, with direct implications for higher education policy and governance. The results reveal a markedly stratified academic landscape, in which academic rank, i10-index, and regional socio-economic development levels (SEGE) emerge as significant predictors of research productivity. Conversely, career duration is negatively associated with output, indicating potential challenges in sustaining productivity across academic life cycles.\u003c/p\u003e\u003cp\u003eThe Principal Component Analysis (PCA) confirms that productivity and seniority represent distinct dimensions of academic achievement, while cluster analysis identifies a small elite group of highly productive academics alongside a large proportion of medium- and low-productivity faculty. The persistently low representation of GCA graduates among academic staff, despite the rapid expansion of related programs, highlights a structural misalignment between disciplinary qualifications and recruitment practices. This mismatch risks slowing the development of a robust disciplinary identity and undermining the quality of academic programs.\u003c/p\u003e\u003cp\u003eThese findings underscore the need for policy frameworks that address regional disparities, establish discipline-specific appointment and promotion criteria, and create targeted mechanisms to enhance research capacity in underrepresented groups. By aligning recruitment, promotion, and funding policies with the specific needs of GCA, higher education institutions in Turkey can both strengthen the field and contribute to a more equitable and competitive national research environment.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePolicy Implications\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eRegional Equity in Research Funding: Implement differentiated funding models that channel greater resources to universities in lower-SEGE regions, ensuring accountability and measurable outcomes.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eDiscipline-Specific Recruitment and Promotion Standards: Introduce department-level benchmarks for academic appointments and promotions, reflecting the publication norms and competencies required in GCA.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCapacity Building for Medium- and Low-Productivity Groups: Establish structured mentoring, research training, and mobility programs targeting underperforming faculty, particularly in disadvantaged regions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eCareer Development Across the Academic Life Cycle: Provide sabbaticals, research leave, and international collaboration opportunities to sustain productivity among senior academics.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eInternationalization Strategies: Expand access to global research networks, joint projects, and conference participation, especially for academics in peripheral regions.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis research is limited by its reliance on open-access data sources, which may lead to incomplete or misclassified publication records. The cross-sectional design precludes causal inferences and limits the analysis of temporal changes in productivity. Cluster analysis relied on mean values and could not fully account for certain indices due to low variance. Furthermore, the study focuses exclusively on Turkish academics, restricting generalizability to other national contexts.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003eFuture Research Directions\u003c/h2\u003e\u003cp\u003eFuture studies should employ longitudinal data to track publication trajectories over time and enable causal analysis. Comparative research involving other emerging academic disciplines or higher education systems with similar structural challenges would provide valuable benchmarks. Qualitative investigations could deepen understanding of institutional barriers, career motivations, and the lived experiences of academics in developing disciplines. Additionally, exploring the impact of national research funding schemes, governance reforms, and international collaborations on academic productivity would generate actionable insights for both policymakers and institutional leaders.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cspan\u003eEthics Statement This study did not involve human participants, animals, or the collection of sensitive personal data. All data analyzed were obtained from publicly available sources. Therefore, ethics approval was not required.\u003c/span\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlbert, C., Davia, M. A., \u0026amp; Legazpe, N. (2016). Determinants of research productivity in Spanish academia. \u003cem\u003eEuropean Journal of Education, 51\u003c/em\u003e(4), 535-549. https://doi.org/10.1111/ejed.12142\u003c/li\u003e\n\u003cli\u003eAlan, A. A., \u0026amp; Şen, \u0026Ouml;. (2020). 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Examining the influences on faculty departure intentions: A comparison of tenured versus nontenured faculty at research universities using NSOPF-99. \u003cem\u003eResearch in Higher Education, 45\u003c/em\u003e, 139\u0026ndash;176. https://doi.org/10.1023/B:RIHE.0000015693.38603.4c\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Research productivity, Academic rank, Universities, Publication performance, Socio-Economic Development Index (SEGE), Bibliometric Analysis","lastPublishedDoi":"10.21203/rs.3.rs-7408736/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7408736/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe rapid development of Gastronomy and Culinary Arts as a young academic discipline raises questions about how research productivity evolves across career stages and institutional contexts. This study examines the academic output of Turkish scholars in this field between 2020 and 2024, aiming to identify patterns and disparities in publication performance. Using a multidimensional quantitative approach, data were collected from institutional records and bibliographic databases, and analyzed according to academic title, career stage, institutional affiliation, and regional location. The results indicate that seniority and academic rank are significant predictors of productivity, while regional and institutional factors further influence research output. Comparisons with international studies on emerging disciplines reveal similar trends, suggesting that the findings have relevance beyond the national context. Implications for higher education management include the need for discipline-specific performance evaluation, flexible incentive systems, and supportive policies for early-career academics. By linking local evidence to global literature, the study provides actionable insights for policymakers, university administrators, and scholars themselves, highlighting strategies to foster sustainable academic careers, enhance research performance, and inform governance practices in developing academic fields. Overall, this research contributes to understanding the dynamics of academic work in young disciplines, offering both theoretical and practical guidance for higher education institutions navigating the challenges of emerging fields.\u003c/p\u003e","manuscriptTitle":"Academic Productivity in Turkish Gastronomy and Culinary Arts: A Multidimensional Quantitative Analysis (2020–2024)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-21 03:42:11","doi":"10.21203/rs.3.rs-7408736/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ba06bfdf-3fd7-4373-bb6c-e169e8b3c8ec","owner":[],"postedDate":"August 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53477731,"name":"Hospitality and Tourism"},{"id":53477732,"name":"Special Education"}],"tags":[],"updatedAt":"2025-08-21T03:42:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-21 03:42:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7408736","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7408736","identity":"rs-7408736","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}