Conference Agenda
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22 SES 08 D: Institutional Transformation
Paper Session | ||
| Presentations | ||
22. Research in Higher Education
Paper Between Theory and Practice: the Untapped Role of Innovation Models in Higher Education. Inholland University of Applied Sciences, Netherlands, The Presenting Author:Educational innovation is often framed as a necessary response to societal, technological, economic and ecological developments in higher education (Fullan, 2016; Kezar, 2018). Yet many innovation initiatives remain fragmented, short-lived or weakly connected to everyday educational practice. At the same time, higher education institutions operate in an environment saturated with research-based knowledge about change, improvement and implementation. Innovation models form a central part of this knowledge landscape, as they offer theoretically grounded ways of understanding how innovative change unfolds and how it can be guided. Despite the abundance of such models, however, their influence on educational practice remains limited, with innovations frequently persisting as isolated initiatives rather than becoming sustainably embedded. This gap is not merely a matter of implementation failure, but is rooted in the ways educational innovation itself is conceptualized. Innovation models embed assumptions about change, agency, context, and knowledge use, often drawing on disciplinary traditions that are not always made explicit. Against this background, it becomes relevant to examine how innovation models in education have developed over time, which disciplinary traditions they originate from, and to what extend they attend to conditions that enable sustainable education innovation in practice. The study therefore provides a systematic analysis of 19 established innovation models that are frequently referenced in the context of educational change and innovation, examining how educational research has conceptualized the relationship between theoretical knowledge about change and its translation into practical action in higher education. The objective of the study is to critically examine how innovation models in education conceptualize change, and how these conceptualizations shape their potential to inform sustainable educational innovation in practice. To this end, the study pursues three interrelated aims. First, it analyses how innovation models in education have evolved over time, making visible shifts in underlying assumptions about change and agency. Second, it examines the disciplinary traditions from which these models originate, as these traditions inform how the relationship between knowledge and action is understood. Third, it assesses to what extent these models attend to key aspects required for sustainable educational innovation, by analysing them against five core dimensions identified by Bocconi, Kampylis & Punie (2013). Conceptually, the study is grounded in a process-oriented understanding of educational innovation. Innovation is not treated as a single event or product adoption, but as a long-term, multi-layered process that unfolds within complex educational systems (Fullan, 2016; Kezar, 2018). The paper deliberately brings together insights from multiple scientific disciplines, reflecting the inherently interdisciplinary nature of educational innovation. This interdisciplinary grounding is important because different disciplines produce different forms of knowledge about how change works, how actors interact, and how action can be supported. In this way, the study examines under what conceptual conditions research-based knowledge about innovation becomes capable of informing practice, thereby contributing to discussions about the relationship between knowing and acting in higher education. The European and international relevance of this study lies in its broad theoretical scope and its focus on higher education as a shared context across countries. Innovation models are often transferred across national and institutional boundaries without sufficient reflection on their theoretical assumptions or contextual fit. This paper provides a framework for critically selecting or combining innovation models in ways that are sensitive to institutional scale, cultural context and the intended depth of change. Methodology, Methods, Research Instruments or Sources Used The study is based on a scoping review methodology, following the approach outlined by Westphaln et al. (2021). A systematic literature search was conducted in the ERIC database (via EBSCOhost) between December 2023 and February 2024. An English-language search query was developed focusing on innovation, implementation processes, conceptual or theoretical frameworks and higher education contexts. The initial search resulted in 185 peer-review publications. These were screened using four inclusion criteria: (1) a primary focus on innovation as a process rather than a product, (2) explicit reference to an innovation model, framework or theory, (3) relevance to educational contexts, particularly higher education, and (4) an international orientation rather than a country-specific focus. After screening, 54 publications remained for full analysis. From these sources, 19 distinct innovation models were identified. Each model was analysed along three analytical dimensions. First, the models were ordered chronologically to examine their historical development. Second, each model was categorized according to its dominant disciplinary origin. Third, the models were assessed using a structured scoring framework based on the five core aspects of educational innovation proposed by Bocconi et al. (2013). The scoring of the models was conducted independently by two researchers to enhance reliability. Differences in scoring were discussed until consensus was reached. This qualitative-quantitative approach allowed for a systematic comparison of models while retaining sensitivity to theoretical nuance. This analysis therefore goes beyond a historical or descriptive account and examines how different research traditions have produced distinct representations of change and different assumptions about how theoretical knowledge can inform practical action in educational settings. Conclusions, Expected Outcomes or Findings The findings demonstrate a persistent mismatch between how educational innovation is conceptualised in research and how it is enacted in practice. Early innovation models predominantly frame change in terms of individual behaviour, motivation, or adoption decisions, relying on linear or stage-based logics in which knowledge functions as prescriptive guidance for implementation. More recent models adopt broader, system-oriented perspectives that emphasise interactions among individuals, organisational structures, culture, and long-term learning. In these models, knowledge is framed not as instruction, but as a resource for collective sense-making in complex contexts. Although this shift reflects an important reorientation within educational research regarding what counts as actionable knowledge about change, the analysis shows that earlier assumptions persist. Instead, multiple and often incompatible logics coexist. Educational practice and policy continue to rely heavily on linear and instrumental approaches to innovation, frequently informed by earlier models that simplify pedagogical and organisational complexity. As a result, the analytical potential of more recent models remains underutilised, and the gap between theoretical knowledge about educational change and its enactment in practice is largely maintained. The disciplinary origins of innovation models further reinforce this pattern. Most widely cited models stem from psychology and organisational studies, while explicitly educationally grounded models remain scarce. Consequently, many innovation efforts prioritise behaviour change, adoption, or organisational alignment, while treating learning, pedagogy, and curriculum as secondary or implicit concerns. This imbalance helps explain why higher education innovations frequently struggle to reconcile pedagogical ambitions with organisational and managerial demands. Taken together, these findings indicate that innovation models constitute a largely underexamined factor in the knowledge-to-action gap in higher education. The issue is not the absence of models, but their unreflective use with implicit assumptions about change and practice. When used in narrow or instrumental ways, innovation models may reproduce rather than solve the problems they target. References Baregheh, A., Sambrook, S., & Rowley, J. (2009). Towards a Multidisciplinary Definition of Innovation. Management Decision 47(8), 1323-1339. https://doi.org/10.1108/00251740910984578 Bocconi, S. Kampylis, P. & Punie, Y. (2013). Framing ICT-enabled Innovation for Learning: the case of one-to-one learning initiatives in Europe. European Journal of Education 48(1), 113-130. https://doi.org/10.1111/ejed.12021 Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Machine studies, 39, 475-487. https://doi.org/10.1006/imms.1993.1022 Fullan, M. (2009). The Challenge of Change: Start School Improvement Now! (second edition). Corwin & SAGE Ltd Fullan, M. (2016). The NEW meaning of educational change (Fifth;5; ed.). Teachers College Press. Gess-Newsome, J., Southerland, S. A., Jonhnston, A., & Woodbury, S. (2003). Educational reform, personal practical theories and dissatisfaction: The anatomy of change in college science teaching. American Educational Research Journal, 40(3), 731-767. https://doi.org/10.3102/00028312040003731 Hall, G. E., & Ford, S. M. (1987). Change in Schools: Facilitating the Process. State University of New York Press, Albany. Jonker, H., März, V., & Voogt, J. (2020). Curriculum flexibility in a blended curriculum. Australasian Journal of Educational Technology, https://doi.org /10.14742/ajet.4926 Kezar, A. (2018). How college change: understanding, leading and enacting change. Routledge. https://doi.org/10.4324/9781315121178 Kirschner, P. A., Paas, F., Wopereis, I. G. J. H., & Hendriks, M. (2005). Determinants for failure and success of innovation projects: The road to sustainable innovations. Heerlen: Open Universiteit Nederland. Kotter, J. P. (1996). Leading Change. The Leadership challenge. San Francisco, CA. OECD. (2005). Oslo Manual: Guidelines for collecting and interpreting innovation data (3e druk). OECD Publishing. Rogers, E. M. (1962). Diffusion of innovations. Free Press of Glencoe. Rogers, E. M. (2003). Diffusions of Innovations (Fifth Edition). Free Press, New York. Schaap, L. & Vanlommel, K. (2024). Why so many change efforts fail: using paradox theory as a lens to understand the complexity of educational change. International Journal of Leadership in Education, 1-14. https://doi.org/10.1080/13603124.2023.2298210 Tappel, A. P. M. (2024). The sustainability of Educational Innovations. [proefschrift]. Universiteit Twente. https://doi.org/10.3990/1.9789036561174 Tidd, J. & Bessant, J. (2013). Managing Innovation: Integrating Technological, Market and Organizational Change. West Sussex, UK.: Wiley. Westphaln, K. K., Regoeczi, W., Masotya, M., Vazquez-Westphaln, B., Lounsbury, K., McDavid, L., Lee, H., Johnson, J., & Ronis, S. D. (2021). From arksey and O’Malley and beyond: Customizations to enhance a team-based, mixed approach to scoping review methodology. Methodsx, 8, 101375-101375. https://doi.org/10.1016/j.mex.2021.101375 22. Research in Higher Education
Paper Ukrainian Universities in Wartime: Competitiveness and Patterns of Institutional Resilience University of Warsaw, The Faculty of Management, Poland Presenting Author:In education systems under a strong and prolonged influence of crisis conditions, undergoing processes of consolidation and organizational restructuring of universities, and, in some cases, relocation processes caused by the ongoing war, ensuring a high level of university competitiveness has become a critical factor, influencing institutional resilience and prospects for future development. Since the beginning of the war, the Ukrainian higher education system has experienced a pronounced structural contraction, driven by the combined effects of wartime disruption, institutional restructuring, and unfavourable demographic trends. The consequences of this influence are primarily related to (Protsyk, 2025; Dubynska et al., 2025; Guariglia et al., 2025): damage and destruction of universities and financial losses, relocation and migration of the students and academic teachers either abroad or to safer regions within Ukraine, war-related stress among university lecturers and students, decrease in publications and research productivity, relocation of higher education institutions, and ongoing processes of organizational consolidation and reorganization. In recent decades, the concept of university competitiveness has gained increasing attention in the literature on higher education systems, reflecting intensified competition for students, funding, academic staff, and international recognition (Hart & Rodgers, 2024; Maral, 2025). Broadly, university competitiveness is understood as a multidimensional construct capturing an institution’s ability to achieve and sustain superior performance in education, research, and societal engagement within a dynamic and often globalized environment (Pucciarelli & Kaplan, 2016; Musselin, 2018). In this context, composite indices have become an increasingly prominent tool in higher education policy and research, shaping funding allocation, strategic management, and international benchmarking of universities (Shin, Toutkoushian & Teichler, 2011; Hazelkorn, 2015). By aggregating multiple dimensions of performance into synthetic measures, composite indices offer a comparable assessment of institutional competitiveness. However, the growing reliance on international bibliometric databases and global rankings has also raised concerns regarding their limited coverage of national higher education systems, particularly in countries with heterogeneous institutional profiles and uneven research capacity. As a result, large segments of national university systems remain analytically underrepresented, while performance assessments tend to privilege internationally visible research-intensive institutions. Existing empirical literature reflects this imbalance. The majority of quantitative studies either focus on elite universities included in global rankings or adopt case-study approaches centered on a small number of institutions or countries (Marginson, 2014; Hazelkorn & Gibson, 2018). System-wide quantitative analyses that encompass all universities within a national system remain relatively rare. This gap is especially pronounced in contexts of higher education systems, affected by structural shocks, where institutional diversity and asymmetric adaptation processes challenge standard ranking-based assessments. This study addresses this gap by developing a system-wide competitiveness index for all public Ukrainian universities with a focused analysis of research-enhanced competitiveness, examined within a subsample of institutions with sustained research activity. Methodologically, the analysis applies the CRITIC–TOPSIS approach. By doing so, the study contributes to the literature on higher education competitiveness by moving beyond elite-centered rankings and providing a comprehensive quantitative perspective on system-level dynamics under crisis conditions. Based on an analysis of theoretical and empirical studies, four hypotheses have been formulated for verification in this study: H1. University competitiveness exhibits substantial heterogeneity across the higher education system, reflecting structural differences between HEIs. H2. Universities with stronger research performance demonstrate higher levels of overall competitiveness under crisis conditions than institutions with weaker research profiles. H3. The competitiveness of the universities changes significantly in wartime, with the magnitude and direction of change varying across institutions. H4. The negative impact of war on competitiveness is uneven across dimensions, indicating differentiated resilience patterns within universities. Methodology, Methods, Research Instruments or Sources Used The assessment of the competitiveness of higher education institutions requires a multidimensional approach that takes into account a variety of criteria relating to institutional resources as well as the results of research, teaching, and organisational activities. To this end, MCDA methods are used to translate complex data into structured comparative results (Yüksel Kayadelen & Antmen, 2023; Maral, 2024). Setting the weights of the criteria is one of the key challenges in MCDA analysis. In research on higher education and university competitiveness, multi‑criteria decision‑making techniques such as CRITIC, ENTROPY, AHP, FAHP, IVN‑AHP, FDM, CIMAS, BWM, and BBWM are widely employed to derive criterion weights. In this regard, the significant advantages of the CRITIC method are: consideration of data variability, reduction of the influence of highly correlated indicators, and greater weighting of criteria that provide more unique information. As a result, weights are determined objectively and reflect differences in empirical data (Zavadskas, Turskis & Kildienė, 2014; Maral, 2024). In the procedures for comparing alternatives, the TOPSIS, VIKOR, and WASPAS methods offer a transparent way of constructing rankings. Among them, TOPSIS is widely used in ranking analyses of higher education institutions and studies of competitive advantages (Opricovic & Tzeng, 2004; Vrat, 2025). The TOPSIS method allows each unit to be evaluated in relation to the ideal solution (the best possible result) and the anti-ideal solution (the worst possible result), which significantly improves the interpretation of results for stakeholders (universities, policy makers, students). Taking the above arguments into account, a hybrid approach is adopted in this study: the weights of the criteria were determined using the CRITIC method, which avoids the subjectivity of expert assessments, and the university ranking was constructed using TOPSIS, which ensures the transparency and interpretability of the results. Conclusions, Expected Outcomes or Findings Due to the multidimensional nature of university competitiveness, the study adopts a two-tier analytical design distinguishing between system-wide and research-enhanced competitiveness. The baseline specification applies the CRITIC–TOPSIS procedure to the full sample of 115 public universities operating under the authority of the Ministry of Education and Science of Ukraine in 2021-2024, using a system-relevant set of indicators: publications per academic staff member, student-to-staff ratio, graduate employment rate, share of international students, and institutional visibility. The extended specification is estimated for a research-active subsample of 76 universities with bibliometric data available in the Elsevier SciVal database. In addition to the core indicators, it incorporates citations per publication and field-weighted citation impact, enabling a more direct assessment of research quality and international scientific influence. This framework enables comparative analysis of competitiveness dynamics under prolonged crisis conditions and highlights structural differences between teaching-oriented and research-intensive institutions. In conclusion, the study empirically evaluates university competitiveness in a higher education system operating in wartime, offering evidence relevant not only for Ukraine but also for other higher education systems in crisis conditions. References 1.Dubynska, O., Mondich, O., Krasilova, Y., Udovenko, J., & Holotenko, A. (2025). Ukrainian university teachers in wartime: intersectional stress and its impacts on teaching and student engagement. Research in Post-Compulsory Education, 1-24. 2.Guariglia, A., Nikolsko-Rzhevskyy, A., Talavera, O., Zadorozhna, O. (2025). Research productivity during the Russian war in Ukraine. Public Choice . https://doi.org/10.1007/s11127-025-01258-5 3.Hart, P. F., & Rodgers, W. (2024). Competition, competitiveness, and competitive advantage in higher education institutions: a systematic literature review, Studies in Higher Education, 49:11, 2153-2177, https://doi.org/10.1080/03075079.2023.2293926 4.Hazelkorn, E. (2015). Rankings and the reshaping of higher education: The battle for world-class excellence. Springer. https://doi.org/10.1057/9781137446671 5.Hazelkorn, E., & Gibson, A. (2018). The impact and influence of rankings on the quality, performance and accountability agenda. In Research handbook on quality, performance and accountability in higher education (pp. 232-246). Edward Elgar Publishing. 6.Maral, M. (2024). Examining the research performance of universities with multi-criteria decision-making methods. Sage Open, 14(4), 21582440241300542. 7.Maral, M. (2025). Bibliometric and content analysis on competition in higher education. Higher Education, 1-48. https://doi.org/10.1007/s10734-025-01425-z 8.Marginson, S. (2014). University rankings and social science. European Journal of Education, 49(1), 45–59. https://doi.org/10.1111/ejed.12061 9.Opricovic, S., & Tzeng, G. H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445-455. 10.Protsyk, H. (2025). Higher education amid the war: A resilience test for Ukraine’s integration into the European Higher Education Area. Ukraine’s Thorny Path to the EU From “Integration without Membership” to “Integration through War” Edited by M. Rabinovych and A. Pintsch (pp. 279-310). Palgrave Studies in European Union Politics. https://doi.org/10.1007/978-3-031-69154-6_12 11.Pucciarelli, F., & Kaplan, A. (2016). Competition and strategy in higher education: Managing complexity and uncertainty. Business Horizons, 59(3), 311–320. https://doi.org/10.1016/j.bushor.2016.01.003 12.Shin, J. C., Toutkoushian, R. K., & Teichler, U. (2011). University rankings: Theoretical basis, methodology and impacts on global higher education. Springer Dordrecht. https://doi.org/10.1007/978-94-007-1116-7 13.Vrat, P. (2025). Application of TOPSIS for world ranking of institutions/universities. Journal of Advances in Management Research. https://doi.org/10.1108/JAMR-11-2024-0426 14.Yüksel, F. Ş., Kayadelen, A. N., & Antmen, F. (2023). A systematic literature review on multi-criteria decision making in higher education. International Journal of Assessment Tools in Education, 10(1), 12-28. https://doi.org/10.21449/ijate.1104005 15.Zavadskas, E. K., Turskis, Z., & Kildienė, S. (2014). State of art surveys of overviews on MCDM/MADM methods. Technological and economic development of economy, 20(1), 165-179. 22. Research in Higher Education
Paper Mapping Organizational Actorhood and Strategic Positioning in Higher Education: A Bibliometric Review 1: Anadolu University, Turkey (Türkiye); 2: Nazarbayev University, Kazakhstan Presenting Author:In recent years, dynamics such as internationalization, competitive pressures, and policy instruments rooted in the knowledge economy have accelerated a shift in university governance from the ideal-typical model of a ‘republic of scholars’ toward a ‘stakeholder organization’ (Bleiklie & Kogan, 2007). In this transition, institutional autonomy has increasingly become the basis for strategic decision-making, while academic freedom has been reframed vis-à-vis the interests of other stakeholders and hierarchical leadership structures (Thoenig & Paradeise, 2016). Many scholars describe this transformation in terms of the centralization of decision-making, the strengthening of hierarchical management, and the standardization and formalization of organizational administration (Maassen & Stensaker, 2019). In practice, these tendencies shape institutional behavior through regulatory reforms, market-oriented funding mechanisms, and various evaluation and measurement systems (Whitley & Gläser, 2007). In the face of these governance pressures, universities’ responses vary according to their levels of autonomy, institutional profiles, and embedded organizational logics (Olsen, 2005). Because political–administrative regimes, institutional legacies, and path dependencies of national contexts shape the effects of reforms, the resulting outcomes are highly heterogeneous (Zapp, Marques & Powell, 2021). This heterogeneity becomes increasingly complex as universities operate within nested organizational fields, thereby exposing strategic positioning to multi-level environmental demands (Hüther & Krücken, 2016). While this trajectory highlights organizational actorhood, managerial rationalization, and strategic capacity, change processes simultaneously unfold through mechanisms such as loose coupling, ceremonial conformity, and selective coupling, producing heightened hybridity within institutions (Krücken & Meier, 2006). These multi-layered pressures diversify differentiation and positioning strategies at both the organizational and field levels. In this context, strategic positioning refers to universities’ efforts to generate both vertical and horizontal differentiation by defining distinctive niches, profiles, and focal mix of services under competitive and institutional pressures (Fumasoli & Huisman, 2013). On the one hand, universities are subjected to quality-based stratification through excellence agendas, rankings, and performance metrics; on the other, they seek to identify with specific markets and stakeholder groups through mission statements, strategic plans, and institutional profiles. In this process, positioning becomes a balancing practice situated in the tension between legitimacy and distinctiveness, requiring universities to resemble other institutions while differentiating sufficiently to create sustainable resource niches (Barbato & Turri, 2020). Today, universities are gaining visibility as organizational actors endowed with strategic decision-making capacity, while simultaneously diversifying their adaptation strategies in response to stakeholder expectations and accountability regimes. This conceptual plurality and multi-field orientation make the literature on organizational actorhood and strategic positioning increasingly fragmented, multi-threaded, and interdisciplinary, thereby rendering a systematic mapping of this scholarship both academically and methodologically meaningful. This study seeks to uncover the scope, thematic structure, and evolutionary trajectories of this body of literature. Accordingly, the analysis focuses on two core research questions: (i) around which conceptual clusters does the literature on organizational actorhood and strategic positioning cohere, and (ii) what patterns of orientation, differentiation, and development emerge over time. Employing a bibliometric science-mapping approach, the study aims to offer a comprehensive overview of the field’s current structure and dynamics, to generate novel insights into the intersections between organizational sociology and higher education governance, and to provide a systematic assessment of potential future directions for research. Methodology, Methods, Research Instruments or Sources Used This study adopts a bibliometric science-mapping approach to examine the literature on organizational actorhood and strategic positioning in a comprehensive manner. Bibliometric analysis is particularly suited to dispersed and interdisciplinary bodies of research due to its capacity to reveal conceptual clusters, intellectual structures, and evolutionary trajectories (Zupic & Čater, 2015). Methodologically, this orientation is well aligned with the aim of mapping the intersection between organizational sociology and higher education governance. In the data collection phase, the Web of Science (WoS) Core Collection and Scopus databases were used. Employing both databases helps mitigate potential biases associated with the disciplinary coverage, geographical representation, and publication type distributions of single data sources, thereby enabling a more comprehensive data universe (Mongeon & Paul-Hus, 2016). Keyword sets related to organizational actorhood, strategic positioning, higher education governance, and organizational sociology were derived from prior conceptual studies and field scans. Search results were subsequently refined through document type, language, and subject-area filters. The WoS and Scopus datasets were merged into a common data structure using the mergeDbSources function in the bibliometrix package (Aria & Cuccurullo, 2017), followed by a two-step deduplication procedure based on DOI matching and title/author cross-checking. After this stage, the total number of records declined to 447. An inclusion–exclusion screening was then conducted to remove off-topic entries (e.g., health, marketing, K-12, psychological agency, brand positioning), resulting in a final dataset of 287 publications. The overall data flow was documented following a protocol adapted from PRISMA guidelines. The analysis proceeded along three dimensions: (i) performance analysis (annual production, citation indicators, leading authors, journals and countries); (ii) science mapping (co-citation, bibliographic coupling, and co-authorship networks); and (iii) conceptual–thematic analysis (keyword co-occurrence networks, thematic evolution, and conceptual structure). All analyses were conducted in R using the bibliometrix/biblioshiny environment, and the resulting clusters were interpreted in light of the substantive orientations of the field (Hallinger & Kovačević, 2019). This approach has several limitations. Database-oriented bibliometric analyses tend to exclude alternative publication formats such as books, reports and grey literature. Moreover, citation-based indicators do not necessarily correspond to research quality, and citation practices may vary asymmetrically across disciplinary and interdisciplinary domains (Bornmann & Daniel, 2008). Nevertheless, bibliometric mapping offers a robust means of visualizing the structural configuration, emerging trends and existing blind spots of the field (Donthu et al., 2021). Conclusions, Expected Outcomes or Findings The thematic mapping indicates that research on organizational actorhood and strategic positioning has gained considerable momentum over the past decade and has become increasingly institutionalized. The “higher education – education – competitive positioning” axis exhibits high centrality and moderate density, forming the conceptual core of the field. In contrast, themes such as “diversity”, “differentiation” and “universities” function as bridging themes that connect governance-oriented and strategy-oriented research streams. Meanwhile, topics such as “leadership”, “capacity building” and “autonomy” appear as niche themes that have developed but remain relatively isolated within the thematic landscape. Trend and thematic evolution analyses show that early research in the field centered on access, organizational capacity and knowledge production, whereas recent studies increasingly emphasize competition, legitimacy, strategic positioning, innovation and impact. This shift indicates the growing influence of performance-based governance instruments and global comparability demands on universities. At the country level, research production and citation influence are concentrated in the United Kingdom, the United States and Northern Europe, while contributions from the Global South remain marginal. The findings indicate that the field has entered a maturity phase, suggesting that further advances are likely to emerge through theoretical refinement, contextual diversification and comparative research designs. Three research directions stand out: (i) extending the concept of actorhood beyond Anglo-European settings to systems characterized by constrained autonomy and complex governance arrangements; (ii) analyzing strategic positioning not merely as competitive behavior but as a relational and system-embedded process shaped by ranking regimes, policy transfer and asymmetric global hierarchies; and (iii) strengthening qualitative, comparative and mixed-method approaches that complement bibliometric insights in a maturing field. Taken together, these directions point to the need for more context-sensitive and system-embedded explanations at the intersection of organizational sociology and higher education governance. References Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007 Barbato, G., & Turri, M. (2020). What do positioning paths of universities tell about the diversity of higher education systems? An exploratory study. Studies in Higher Education, 45(9), 1919-1932. https://doi.org/10.1080/03075079.2019.1619681 Bleiklie, I., & Kogan, M. (2007). Organization and governance of universities. Higher Education Policy, 20(4), 477-493. https://doi.org/10.1057/palgrave.hep.8300167 Bornmann, L., & Daniel, H.-D. (2008). What do citation counts measure? A review of studies on citing behavior. Journal of Documentation, 64(1), 45–80. https://doi.org/10.1108/00220410810844150 Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070 Fumasoli, T., & Huisman, J. (2013). Strategic agency and system diversity: Conceptualizing institutional positioning in higher education. Minerva, 51(2), 155-169. https://doi.org/10.1007/s11024-013-9225-y Hallinger, P., & Kovačević, J. (2019). A bibliometric review of research on educational administration: Science mapping the literature, 1960 to 2018. Review of Educational Research, 89(3), 335-369. https://doi.org/10.3102/00346543198303 Hüther, O., & Krücken, G. (2016). Nested organizational fields: Isomorphism and differentiation among European universities. In E. P. Berman & C. Paradeise (Eds.), The university under pressure. Research in the Sociology of Organizations, 46, 53–83. Emerald. https://doi.org/10.1108/S0733-558X20160000046003 Krücken, G., & Meier, F. (2006). Turning the university into an organizational actor. In G. S. Drori, J. W. Meyer, & H. Hwang (Eds.), Globalization and organization (pp. 241-257). Oxford University. Maassen, P., & Stensaker, B. (2019). From organised anarchy to de‐coupled bureaucracy: The transformation of university organisation. Higher Education Quarterly, 73(4), 456-468. https://doi.org/10.1111/hequ.12229 Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213–228. https://doi.org/10.1007/s11192-015-1765-5 Olsen, J. P. (2005). The institutional dynamics of the (European) University, Arena Working Paper No. 15, University of Oslo: Arena. Thoenig, J. C., & Paradeise, C. (2016). Strategic capacity and organisational capabilities: A challenge for universities. Minerva, 54(3), 293-324. https://doi.org/10.1007/s11024-016-9297-6 Whitley, R., & Gläser, J. (Eds.) (2007). The changing governance of the sciences. The advent of research evaluation systems. Springer. Zapp, M., Marques, M., & Powell, J. J. (2021). Blurring the boundaries. University actorhood and institutional change in global higher education. Comparative Education, 57(4), 538-559. https://doi.org/10.1080/03050068.2021.1967591 Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472. https://doi.org/10.1177/109442811456262 | ||