BazEkon - The Main Library of the Cracow University of Economics

BazEkon home page

Main menu

Author
Rodríguez-Castro Dorys Y. (University of Deusto, Spain), Aparicio Juan (University Miguel Hernandez of Elche, Spain)
Title
Introducing a Functional Framework for Integrating the Empirical Evidence about Higher Education Institutions' Functions and Capabilities : a Literature Review
Source
Journal of Entrepreneurship, Management and Innovation (JEMI), 2021, vol. 17, nr 1, s. 231-267, rys., tab., bibliogr. s. 260-266
Issue title
Exploring the Link Between Entrepreneurial Capabilities, Cognition, and Behaviors
Keyword
Szkolnictwo wyższe, Efektywność, Przegląd literatury
Higher education, Effectiveness, Literature review
Note
JEL Classification: A20, I23
streszcz., summ.
Abstract
Cel: Artykuł przedstawia ramy funkcjonalne, które syntetyzują funkcje i możliwości, które obecnie kierują ocenami empirycznymi zidentyfikowanymi w literaturze. Metodyka: W artykule dokonano systematycznego przeglądu literatury przedmiotu, który rzuca światło na związek między modelowaniem produkcji uczelni a celami polityki szkolnictwa wyższego. Wyniki: Nasze wyniki dowodzą, że w modelach produkcyjnych stosowanych do pomiaru wyników instytucji szkolnictwa wyższego dominują cztery zależności między nakładami a wynikami. Jednak nasze wyniki wskazują na istnienie pewnych nierówności w pomiarze trzech misji uniwersyteckich. Implikacje dla teorii i praktyki: Przedstawione tutaj ramy funkcjonalne pokazują, że istnieje kilka rozbieżności między produkcją, która jest badana w ramach oceny wyników uczelni, a celami polityki szkolnictwa wyższego. Ma to istotne implikacje, zarówno dla środowiska akademickiego, jak i dla praktyki politycznej uczelni i HES, jeśli mamy osiągnąć uczciwą i sprawiedliwą reprezentację działań prowadzonych przez uczelnie i ich wielokrotny wkład w HES. Oryginalność i wartość: Przegląd ten podkreśla potrzebę zajęcia się szerszymi ramami analitycznymi, które pomogą uniknąć potencjalnych błędów systemowych, które mogą powstać z powodu braku lub nadmiernego znaczenia przypisywanego konkretnym funkcjom i możliwościom. (abstrakt oryginalny)

Purpose: The paper introduces a functional framework that synthesizes the functions and capabilities that currently guide the empirical evaluations identified in the literature. Methodology: In this paper, a systematic review of the literature is carried out, which sheds light on the relationship between the modeling of the production of higher education institutions and the objectives of higher education policies. Findings: Our results evidence that four input-output relationships predominate in the production models used to measure the performance of higher education institutions. However, our results point to the existence of certain imbalances in measuring the three university missions. Implications for theory and practice: The functional framework presented here shows that there are several mismatches between the production that is examined in the assessment of HEIs' performance and the goals of higher education policies. This has important implications, both for academia and for the policy practice of HEIs and HESs, if we are to achieve a fair and equitable representation of the activities performed by HEIs and their multiple contributions to HESs. Originality and value: This review emphasizes the need to address broader analytical frameworks that help to avoid possible systemic failures that may arise due to the absence or excessive importance given to concrete functions and capabilities. (original abstract)
Full text
Show
Bibliography
Show
  1. Abramo, G., & D'Angelo, C. A. (2014). How do you define and measure research productivity? Scientometrics, 101(2), 1129-1144. http://dx.doi.org/10.1007/s11192-014-1269-8
  2. Agasisti, T., & Dal Bianco, A. (2009). Measuring efficiency of higher education institutions. International Journal of Management and Decision Making, 10(5-6), 443-465. http://dx.doi.org/10.1504/IJMDM.2009.026687
  3. An, Q., Yang, M., Chu, J., Wu, J., & Zhu, Q. (2017). Efficiency evaluation of an interactive system by data envelopment analysis approach. Computers and Industrial Engineering, 103, 17-25. http://dx.doi.org/10.1016/j.cie.2016.10.010
  4. Aparicio, J., Pastor, J. T., Vidal, F., & Zofío, J. L. (2017). Evaluating productive performance: A new approach based on the product-mix problem consistent with Data Envelopment Analysis. Omega, 67, 134-144. http://dx.doi.org/10.1016/j.omega.2016.04.007
  5. Azagra Caro, J. M. (2003). La contribución de las universidades a la innovación: Efectos del fomento de la interacción universidad-empresa y las patentes universitarias. Universitat de Valencia. PhD dissertation.
  6. Berbegal Mirabent, J., & Solé Parellada, F. (2012). What are we measuring when evaluating universities' efficiency? Regional and Sectoral Economic Studies, 12(3), 31-46. Retrieved from https://www.usc.gal/economet/reviews/eers1233.pdf
  7. Benneworth, P., Pinheiro, R., & Sánchez-Barrioluengo, M. (2016). One size does not fit all! New perspectives on the university in the social knowledge economy. Science and Public Policy, 43(6), 731-735. http://dx.doi.org/10.1093/scipol/scw018
  8. Brennan, J., Broek, S., Durazzi, N., Kamphuis, B., Ranga, M., & Ryan, S. (2014). Study on Innovation in Higher Education: Final report. European Commission Directorate for Education and Training Study on Innovation in Higher Education, Publications Office of the European Union, Luxembourg. ISBN 9789279350818. Retrieved from http://eprints.lse.ac.uk/55819/
  9. Cuff, E. C., Sharrock, W. W., & Francis, D. W. (2006). Perspectives in Sociology (5th ed.). New York: Routledge.
  10. Calvo, A., & Rodríguez, M. (2003). Análisis discriminante múltiple. In J.-P. Lévy & J. Varela (Eds.), Análisis multivariable para las ciencias sociales (pp. 251-276). Madrid, España: Pearson, Prentice Hall.
  11. Castano, M. C. N., & Cabanda, E. C. (2007). Performance evaluation of the efficiency of Philippine Private Higher Educational Institutions: Application of frontier approaches. International Transactions in Operational Research, 14, 431-444. http://dx.doi.org/10.1111/j.1475-3995.2007.00599.x
  12. Castells, M. (1993). The university system: Engine of development in the new world economy. In A. Ranson, S. Khoo, & V. Selvaratnam (Eds.), Improving Higher Education in Developing Countries (pp. 65-94). Washington D.C.: The World Bank.
  13. Castells, M. (2001). Universities as dynamic systems of contradictory functions. In J. Muller, N. Cloete, & F. van Schalkwyk (Eds.), Castells in Africa: Universities & Development (pp. 35-55). Cape Town, South Africa: African Minds.
  14. Chang, T. S., Tone, K., & Wu, C. H. (2015). Past-present-future Intertemporal DEA models. Journal of the Operational Research Society, 66(1), 16-32. http://dx.doi.org/10.1057/jors.2013.139
  15. Cheng, G., & Wu, K. (2008). The internal efficiency in higher education: An analysis based on economies of scope. Frontiers of Education in China, 3(1), 79-96. http://dx.doi.org/10.1007/s11516-008-0005-7
  16. Cherchye, L., De Rock, B., Dierynck, B., Roodhooft, F., & Sabbe, J. (2013). Opening the 'Black Box' of efficiency measurement - Input allocation in multi-output settings. Operations Research, 61(5), 1148-1165. https://doi.org/10.1287/opre.2013.1185
  17. Cherchye, L., De Rock, B., & Hennebel, V. (2017). Coordination efficiency in multi-output settings: A DEA approach. Annals of Operations Research, 250(1), 205-233. http://dx.doi.org/10.1007/s10479-015-1892-7
  18. Clermont, M. (2016). Effectiveness and efficiency of research in Germany over time: An analysis of German business schools between 2001 and 2009. Scientometrics, 108(3), 1347-1381. http://dx.doi.org/10.1007/s11192-016-2013-3
  19. Cook, W. D., Liang, L., & Zhu, J. (2010). Measuring performance of two-stage network structures by DEA: A review and future perspective. Omega, 38(6), 423-430. http://dx.doi.org/10.1016/j.omega.2009.12.001
  20. Cohn, E., Rhine, S. L. W., & Santos, M. C. (1989). Institutions of higher education as multi-product firms: Economies of scale and scope. The Review of Economics and Statistics, 71(2), 284. http://dx.doi.org/10.2307/1926974
  21. De Witte, K., & López-Torres, L. (2017). Efficiency in education: A review of literature and a way forward. Journal of the Operational Research Society, 68(4), 339-363. http://dx.doi.org/10.1057/jors.2015.92
  22. de Guzman, M. C. G. N., & Cabanda, E. (2009). Selected private higher educational institutions in Metro Manila: A DEA efficiency measurement. American Journal of Business Education, 2(6), 97-108. https://doi.org/10.19030/ajbe.v2i6.4092
  23. Doty, D. H., & Glick, W. H. (1994). Typologies as a unique form of theory building: Toward improved understanding and modeling. The Academy of Management Review, 19(2), 230-251. http://dx.doi.org/10.2307/258704
  24. Edquist, C., Zabala-Iturriagagoitia, J.M., Barbero, J., & Zofío, J.L. (2018). On the meaning of innovation performance: Is the synthetic indicator of the Innovation Union Scoreboard flawed? Research Evaluation, 27(3), 196-211. http://dx.doi.org/10.1093/reseval/rvy011
  25. Emrouznejad, A., & Thanassoulis, E. (2005). A mathematical model for dynamic efficiency using data envelopment analysis. Applied Mathematics and Computation, 160(2), 363-378. http://dx.doi.org/10.1016/j.amc.2003.09.026
  26. Etzkowitz, H. (2017). The Entrepreneurial University. In J. C. Shin & P. Teixeira (Eds.), Encyclopedia of International Higher Education Systems and Institutions (pp. 91-95). Netherlands: Springer. https://doi.org/10.1007/978-94-017-9553-1_17-1
  27. Etzkowitz, H., Webster, A., Gebhardt, C., & Terra, B. R. C. (2000). The future of the university and the university of the future: Evolution of ivory tower to entrepreneurial paradigm. Research Policy, 29(2), 313-330. http://dx.doi.org/10.1016/S0048-7333(99)00069-4
  28. Färe, R., & Grosskopf, S. (1997). Intertemporal production frontiers: With dynamic DEA. The Journal of the Operational Research Society, 48(6), 656-659. http://dx.doi.org/10.1038/sj.jors.2600779
  29. Gralka, S. (2018). Stochastic frontier analysis in higher education: A systematic review. CEPIE Working Paper, No. 05/18. Retrieved from http://hdl.handle.net/10419/189968
  30. Giuri, P., Munari, F., Scandura, A., & Toschi, L. (2019). The strategic orientation of universities in knowledge transfer activities. Technological Forecasting and Social Change, 138, 261-278. http://dx.doi.org/10.1016/j.techfore.2018.09.030
  31. Hekkert, M. P., Suurs, R. A. A., Negro, S. O., Kuhlmann, S., & Smits, R. E. H. M. (2007). Functions of innovation systems: A new approach for analysing technological change. Technological Forecasting and Social Change, 74(4), 413-432. http://dx.doi.org/10.1016/j.techfore.2006.03.002
  32. Ho, M., Liu, J., Lu, W., & Huang, C. (2014). A new perspective to explore the technology transfer efficiencies in US universities. Journal of Technology Transfer, 39(2), 247-275. http://dx.doi.org/10.1007/s10961-013-9298-7
  33. Jackson, M. C. (2009). Fifty years of systems thinking for management. Journal of the Operational Research Society, 60(1), 24-32. https://doi.org/10.1057/jors.2008.176.
  34. Johnes, G. (1998). The costs of multi-product organizations and the heuristic evaluation of industrial structure. Socio-Economic Planning Sciences, 32(3), 199-209. http://dx.doi.org/10.1016/S0038-0121(97)00035-9
  35. Johnes, G., & Johnes, J. (2009). Higher education institutions' costs and efficiency: Taking the decomposition a further step. Economics of Education Review, 28(1), 107-113. http://dx.doi.org/10.1016/j.econedurev.2008.02.001
  36. Johnes, J. (2015). Operational research in education. European Journal of Operational Research, 243(3), 683-696. http://dx.doi.org/10.1016/j.ejor.2014.10.043
  37. Kao, C. (2014). Network data envelopment analysis: A review. European Journal of Operational Research, 239(1), 1-16. http://dx.doi.org/10.1016/j.ejor.2014.02.039
  38. Kitagawa, F., & Oba, J. (2010). Managing differentiation of higher education system in Japan: Connecting excellence and diversity. Higher Education, 59(4), 507-524. http://dx.doi.org/10.1007/s10734-009-9262-5
  39. Kudła, J., & Stachowiak-Kudła, M. (2016). Quality of teaching and research in public higher education in Poland: Relationship with financial indicators and efficiency. Journal of Management and Business Administration. Central Europe, 24(4), 88-108. http://dx.doi.org/10.7206/jmba.ce.2450-7814.184
  40. Laredo, P. (2007a). Toward a third mission for universities. Regional Seminar "Globalizing Knowledge: European and North American Regions and Policies addressing the Priority Issues of other UNESCO Regions". 5-6 March 2007, UNESCO, Paris.
  41. Laredo, P. (2007b). Revisiting the third mission of universities: Toward a renewed categorization of university activities? Higher Education Policy, 20(4), 441-456. http://dx.doi.org/10.1057/palgrave.hep.8300169
  42. Lee, B. L., & Worthington, A. C. (2016). A network DEA quantity and quality-orientated production model: An application to Australian university research services. Omega, 60, 26-33. http://dx.doi.org/10.1016/j.omega.2015.05.014
  43. Liu, J. S., Lu, L. Y. Y., Lu, W. M., & Lin, B. J. Y. (2013). A survey of DEA applications. Omega, 41(5), 893-902. http://dx.doi.org/10.1016/j.omega.2012.11.004
  44. Martin, B. R., & Etzkowitz, H. (2000). The origin and evolution of the university species. Science and Technology Policy Research (SPRU), Electronic Working Paper Series, Paper No. 59. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.599.5719&rep=rep1&type=pdf
  45. Molas-Gallart, J., & Castro-Martínez, E. (2007). Ambiguity and conflict in the development of "Third Mission" indicators. Research Evaluation, 16(4), 321-330. http://dx.doi.org/10.3152/095820207X263592
  46. Molas-Gallart, J., Salter, A., Patel, P., Scott, A., & Duran, X. (2002). Measuring third stream activities: Final Report to the Russell Group of Universities. SPRU-Science and Technoly Policy Research (April), 85.
  47. OECD (2017a). Benchmarking Higher Education System Performance: Conceptual framework and data. Paris: OECD Publishing. Retrieved from https://www.oecd.org/education/skillsbeyondschool/Benchmarking%20Report.pdf
  48. OECD (2017b). Systems Approaches to Public Sector Challenges. Paris: OECD Publishing. Retrieved from https://www.oecd.org/publications/systems-approaches-to-public-sector-challenges-9789264279865-en.htm
  49. Olivares, M., & Wetzely, H. (2014). Competing in the higher education market: Empirical evidence for economies of scale and scope in German higher education institutions. CESifo Economic Studies, 60(4), 653-680. http://dx.doi.org/10.1093/cesifo/ifu001
  50. Philpott, K., Dooley, L., Oreilly, C., & Lupton, G. (2011). The entrepreneurial university: Examining the underlying academic tensions. Technovation, 31(4), 161-170. http://dx.doi.org/10.1016/j.technovation.2010.12.003
  51. Porto Gómez, I. Zabala-Iturriagagoitia, J.M., & Aguirre Larrakoetxea, U. (2018). Old wine in old bottles: The neglected role of vocational training centres in innovation. Vocations and Learning, 11(12), 205-221. http://dx.doi.org/10.1007/s12186-017-9187-6
  52. Potschin, M., & Haines-young, R. (2013). Conceptual frameworks and the cascade model. In M. Potschin & K. Jax (Eds.), OpenNESS Ecosystem Services Reference Book (pp. 1-6). Retrieved from: http://www.openness-project.eu/library/reference-book
  53. Powell, B., Suitt, D., & Pearson, L. C. (2012). Expenditures, efficiency, and effectiveness in U.S. undergraduate higher education: A national benchmark model. The Journal of Higher Education, 83(1), 102-127. http://dx.doi.org/10.1353/jhe.2012.0005
  54. Rhaiem, M. (2017). Measurement and determinants of academic research efficiency: A systematic review of the evidence. Scientometrics, 110(2), 581-615. http://dx.doi.org/10.1007/s11192-016-2173-1
  55. Salmi, J. (2009). El desafío de crear universidades de rango mundial. Washington D.C. The World Bank. Retrieved from http://hdl.handle.net/123456789/1435
  56. Salmi, J. (2017). The Tertiary Education Imperative Knowledge, Skills and Values for Development. Global Perspectives on Higher Education. [EPub] Rotterdam: Sense Publishers.
  57. Sánchez-Barrioluengo, M. (2014). Articulating the "three-missions" in Spanish universities. Research Policy, 43(10), 1760-1773. http://dx.doi.org/10.1016/j.respol.2014.06.001
  58. Sarrico, C. S., Rosa, M. J., Teixeira, P. N., & Cardoso, M. F. (2010). Assessing quality and evaluating performance in higher education: Worlds apart or complementary views? Minerva, 48(1), 35-54. http://dx.doi.org/10.1007/s11024-010-9142-2
  59. Sav, G. T. (2016). Declining state funding and efficiency effects on public higher education: Government really does matter. International Advances in Economic Research, 22(4), 397-408. http://dx.doi.org/10.1007/s11294-016-9602-z
  60. Schalk, J., Torenvlied, R., & Allen, J. (2010). Network embeddedness and public agency performance: The strength of strong ties in Dutch higher education. Journal of Public Administration Research and Theory, 20(3), 629-653. http://dx.doi.org/10.1093/jopart/mup018
  61. Smits, R., & Kuhlmann, S. (2004). The rise of systemic instruments in innovation policy. International Journal of Foresight and Innovation Policy, 1(1-2), 4-32. http://dx.doi.org/10.1504/IJFIP.2004.004621
  62. Thanassoulis, E., Sotiros, D., Koronakos, G., & Despotis, D. (2018). Assessing the cost-effectiveness of university academic recruitment and promotion policies. European Journal of Operational Research, 264(2), 742-755. http://dx.doi.org/10.1016/j.ejor.2017.06.046
  63. Thanassoulis, E., Witte, K. De, Johnes, J., & Johnes, G. (2016). Applications of data envelopment analysis in education. In J. Zhu (Ed.), Data Envelopment Analysis. International Series in Operations Research & Management Science (pp. 367-438). Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7684-0_12
  64. Tone, K., & Tsutsui, M. (2014). Dynamic DEA with network structure: A slacks-based measure approach. Omega, 42(1), 124-131. http://dx.doi.org/10.1016/j.omega.2013.04.002
  65. Torraco, R. J. (2016). Writing integrative literature reviews: Using the past and present to explore the future. Human Resource Development Review, 15(4), 404-428. http://dx.doi.org/10.1177/1534484316671606
  66. UNESCO Institute for Statistics. (2014). ISCED Fields of Education and Training 2013, Montreal: UNESCO Institute for Statistics. http://dx.doi.org/10.15220/978-92-9189-150-4-en
  67. Weber, K. M., & Rohracher, H. (2012). Legitimizing research, technology and innovation policies for transformative change: Combining insights from innovation systems and multi-level perspective in a comprehensive "failures" framework. Research Policy, 41(6), 1037-1047. http://dx.doi.org/10.1016/j.respol.2011.10.015
  68. Whittemore, R., & Knafl, K. (2005). The integrative review: Updated methodology. Journal of Advanced Nursing, 52(5), 546-553. http://dx.doi.org/10.1111/j.1365-2648.2005.03621.x
  69. Wieczorek, A. J., & Hekkert, M. P. (2012). Corrigendum to "Systemic instruments for systemic innovation problems: A framework for policy makers and innovation scholars." Science and Public Policy, 39(6), 842. http://dx.doi.org/10.1093/scipol/scs094
  70. Yang, G.L., Fukuyama, H., & Song, Y.Y. (2018). Measuring the inefficiency of Chinese research universities based on a two-stage network DEA model. Journal of Informetrics, 12(1), 10-30. http://dx.doi.org/10.1016/j.joi.2017.11.002
  71. Zwaan, B. van Der. (2017). Higher Education in 2040. A Global Approach. (1th Ed.). [EPub], Amsterdam: University of Chicago Press. Retrieved from https://library.oapen.org/bitstream/handle/20.500.12657/31675/625978.pdf?sequence=1^
Cited by
Show
ISSN
2299-7075
Language
eng
URI / DOI
https://doi.org/10.7341/20211718
Share on Facebook Share on Twitter Share on Google+ Share on Pinterest Share on LinkedIn Wyślij znajomemu