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Yükseköğretimde Örgütsel Çeviklik Ölçeğinin Geliştirilmesi: Geçerlik ve Güvenirlik Çalışması

Year 2022, Volume: 12 Issue: 3, 384 - 396, 31.12.2022

Feride Öksüz Gül Münevver Çetin

https://doi.org/10.2399/yod.21.852759

Abstract

Üçüncü kuşak üniversite olma yolunda ilerlerken üniversiteler rekabet etmek, tüm paydaşları için değer yaratmak ve kendi bağlamında değişen piyasalara uyum sağlamak durumunda kalmaktadır. Değişim ve inovasyon yönetiminin artık tek başına yeterli olmadığı gözlemlenmekte ve vasatın üzerinde bir performansın sürekli hale gelmesi beklenmektedir. Bu sürekliliği sağlama potansiyelini irdeleyen örgütsel çeviklik kavramı, içsel ve dışsal sebeplerle ihtiyaç duyulan değişimi sezebilen, değişimi rutin olarak uygulayabilen ve sürekli öğrenme kapasitesine sahip, dinamik bir örgüt tasarımını ifade eder. Bu kavramdan hareketle, bu araştırmada akademik ve idari çalışanların örgütsel çeviklik bağlamında üniversiteye ilişkin algılarını keşfetmeye yönelik bir ölçek geliştirmek amaçlanmıştır. Bu ölçek için oluşturulan model sayesinde, Türkiye’deki kamu yükseköğretim kurumları için örgütsel çeviklik çerçevesi oluşturulmuştur. Geçerlik ve güvenirlik çalışmaları kapsamında Yükseköğretimde Örgütsel Çeviklik Ölçeği; İstanbul’daki 10 devlet üniversitesinde, pilot çalışma dahil, 893 akademik ve idari çalışana uygulanmıştır. Açımlayıcı faktör analizi sonucunda dört faktörlü bir yapı elde edilmiş ve ölçek strateji ve çalışan odaklı örgüt tasarımı, iç paydaş yönelimi, dış paydaşlarla iş birliği ve inovasyonu destekleme boyutlarından oluşmuştur. Doğrulayıcı faktör analizi sonucunda model uyum indekslerinin iyi uyum gösterdiği ya da kabul edilebilir seviyede olduğu görülmüştür. Kamu üniversiteleri bağlamında oluşturulan örgütsel çeviklik çerçevesinde üniversitenin insani yönüne eğilim olduğu görülmüştür. Bu sebeple üniversitenin iç ve dış paydaşlarını belirlemeye ve bu paydaşların ihtiyaçlarının tespit etmeye odaklanılması önerilmektedir. Yükseköğretim sistemimizin ulusal ve uluslararası bağlamda nasıl daha çevik ve esnek olabileceğini keşfetmek ve Türkiye yükseköğretimine ilişkin daha bütüncül bir anlayış elde etmek için vakıf üniversiteleri için de bir çeviklik çerçevesi oluşturulması faydalı olacaktır.

Keywords

İnovasyon örgütsel çeviklik paydaş yönelimi strateji yükseköğretim

References

  • Alzoubi, A. E. H., Al-otoum, F. J., & Albatainh, A. K. F. (2011). Factors associated affecting organization agility on product development. International Journal of Research and Reviews in Applied Sciences, 9(3), 503–515.
  • Amaral, A., & Magalhaes, A. (2002). The emergent role of external stakeholders in European higher education governance. In A. Amaral, G. Jones, & B. Karseth (Eds.), Governing higher education: National perspectives on institutional governance (pp. 1–21). Dordrecht: Springer.
  • Anderson, J. C., & Gerbing, D. W. (1984). The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis. Psychometrika, 49(2), 155–173.
  • Araza, A. (2015). The effect of environmental dynamism to organizational agility and performance relationship. Unpublished doctoral dissertation in Turkish, Yaşar University, İzmir.
  • Baskarada, S., & Koronios, A. (2018). The 5S organizational agility framework: A dynamic capabilities perspective. International Journal of Organizational Analysis, 26(2), 331–342.
  • Benneworth, P., & Jongbloed, B. W. (2010). Who matters to universities? A stakeholder perspective on humanities, arts and social sciences valorisation. Higher Education, 59(5), 567–588.
  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.
  • Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quinonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6, 1–18.
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research. New York, NY: Guilford Publications.
  • Browne, M. W., & Cudek, R. (1993). Alternate ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Thousand Oaks, CA: Sage Publications.
  • Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). New York, NY: Routledge-Taylor and Francis.
  • Chung, S., Lee, K. Y., & Kim, K. (2014). Job performance through mobile enterprise systems: The role of organizational agility, location independence, and task characteristics. Information & Management, 51(6), 605–617.
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2014). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları. Ankara: Pegem Akademi.
  • DeCoster, J. (1998). Overview of factor analysis. Retrieved from http://www.stat-help.com/notes.html (March 2, 2020).
  • Dubey, R., & Gunasekaran, A. (2015). Agile manufacturing: Framework and its empirical validation. The International Journal of Advanced Manufacturing Technology, 76(9–12), 2147–2157.
  • Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Structural Equation Modeling, 6(1), 56–83.
  • Freeman, R. (2010). Strategic management: A stakeholder approach. Cambridge: Cambridge University Press.
  • Ganguly, A., Nilchiani, R., & Farr, J. V. (2009). Evaluating agility in corporate enterprises. International Journal of Production Economics, 118(2), 410–423.
  • Gligor, D. M., Holcomb, M. C., & Stank, T. P. (2013). A multidisciplinary approach to supply chain agility: Conceptualization and scale development. Journal of Business Logistics, 34(2), 94–108.
  • Goldman, S. L., Nagel, R. N., & Priess, K. (1995). Agile competitors and virtual organizations: Strategies for enriching the customer. New York, NY: Van Nostrand Reinhold.
  • Gunasekaran, A. (1999). Agile manufacturing: A framework for research and development. International journal of production economics, 62(1–2), 87–105.
  • Harraf, A., Wanasika, I., Tate, K., & Talbott, K. (2015). Organizational agility. Journal of Applied Business Research (JABR), 31(2), 675–686.
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structural analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 55–65.
  • Inman, R. A., Sale, R. S., Green Jr, K. W., & Whitten, D. (2011). Agile manufacturing: Relation to JIT, operational performance and firm performance. Journal of Operations Management, 29(4), 343–355.
  • Jackson, M., & Johansson, C. (2003). An agility analysis from a production system perspective. Integrated Manufacturing Systems, 14(6), 482–488.
  • Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36.
  • Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575.
  • Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103(3), 391.
  • McDonald, R. P., & Ho, M. H. R. (2002). Principles and practice in reporting statistical equation analyses. Psychological Methods, 7(1), 64–82.
  • Menon, S., & Suresh, M. (2021). Enablers of workforce agility in engineering educational institutions. Journal of Applied Research in Higher Education, 13(2), 504–539.
  • Sambamurthy, V., Bharadwaj, A., & Grover, V. (2003). Shaping agility through digital options: Reconceptualizing the role of information technology in contemporary firms. MIS Quarterly, 27(2), 237–263.
  • Schmitt, T. A. (2011). Current methodological considerations in exploratory and confirmatory factor analysis. Journal of Psychoeducational Assessment, 29(4), 304–321.
  • Senge, P. M., (2013). Beşinci disiplin: Öğrenen organizasyon sanatı ve uygulaması (A. Üldeniz, A. Doğukan, & B. Pala, Çev., 16. baskı). İstanbul: Yapı Kredi Yayınları.
  • Sharifi, H., & Zhang, Z. (1999). A methodology for achieving agility in manufacturing organisations: An introduction. International Journal of Production Economics, 62(1–2), 7–22.
  • Sharifi, H., & Zhang, Z. (2001). Agile manufacturing in practice – Application of a methodology. International Journal of Operations & Production Management, 21(5/6), 772–794.
  • Sharma, S., Mukherjee, S., Kumar, A., & Dillon, W. R. (2005). A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models. Journal of Business Research, 58(7), 935–943.
  • Sherehiy, B., Karwowski, W., & Layer, J. K. (2007). A review of enterprise agility: Concepts, frameworks, and attributes. International Journal of industrial ergonomics, 37(5), 445–460.
  • Sümer, N. (2000). Structural equation modeling: Basic concepts and applications. [Article in Turkish] Türk Psikoloji Yazıları, 3(6), 49–74.
  • Tabachnick, B. G., & Fidell, L. S. (2000). Using multivariate statistics (4th ed.). New Tork, NY: Harper & Row Publishing.
  • Tallon, P. P., & Pinsonneault, A. (2011). Competing perspectives on the link between strategic information technology alignment and organizational agility: Insights from a mediation model. Management Information Systems Quarterly, 35(2), 463–486.
  • Teece, D., Peteraf, M., & Leih, S. (2016). Dynamic capabilities and organizational agility: Risk, uncertainty, and strategy in the innovation economy. California Management Review, 58(4), 13–35.
  • Tsourveloudis, N. C., & Valavanis, K. P. (2002). On the measurement of enterprise agility. Journal of Intelligent and Robotic Systems, 33(3), 329–342.
  • Vázquez-Bustelo, D., Avella, L., & Fernández, E. (2007). Agility drivers, enablers and outcomes. International Journal of Operations & Production Management, 27(12), 1302–1332.
  • Weber, Y., & Tarba, S. Y. (2014). Strategic agility: A state of the art introduction to the special section on strategic agility. California Management Review, 56(3), 5–12.
  • Wissema, J. G. (2009). Towards the third-generation university: Managing the university in transition. Cheltenham: Edward Elgar Publishing.
  • Worley, C. G., & Lawler, E. E. (2010). Agility and organization design: A diagnostic framework. Organizational Dynamics, 39(2), 194–204.
  • Worley, C. G., Williams, T. D., & Lawler III, E. E. (2014). Assessing organization agility: Creating diagnostic Profiles to Guide transformation. New York, NY: John Wiley & Sons.
  • Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806–838.
  • Yusuf, Y. Y., & Adeleye, E. O. (2002). A comparative study of lean and agile manufacturing with a related survey of current practices in the UK. International Journal of Production Research, 40(17), 4545–4562.
  • Yusuf, Y. Y., Sarhadi, M., & Gunasekaran, A. (1999). Agile manufacturing: The drivers, concepts and attributes. International Journal of production economics, 62(1–2), 33–43.
  • Zelbst, P. J., Sower, V. E., Green Jr, K. W., & Abshire, R. D. (2011). Radio frequency identification technology utilization and organizational agility. Journal of Computer Information Systems, 52(1), 24–33.
  • Zerfaß, A., Dühring, L., Berger, K., & Brockhaus, J. (2018). Fast and flexible: Corporate communications in agile organizations. Communication Insights, (5), 1–33.

Development of Organizational Agility Scale in Higher Education: A Validity and Reliability Study

Year 2022, Volume: 12 Issue: 3, 384 - 396, 31.12.2022

Feride Öksüz Gül Münevver Çetin

https://doi.org/10.2399/yod.21.852759

Abstract

To become third generation university, higher education (HE) institutions must compete, create value for internal and external stakeholders, and adapt to changing market conditions. The concept of organizational agility (OA) refers to a dynamic organization that can sense the change imposed by internal and external elements, routinely implement change, and has the capacity to learn continuously. Based on this concept, this research aims to develop a scale to discover the perceptional evaluations of academic and administrative staff of public universities in the context of OA, and thereby to establish an OA framework for public universities. The research was carried out in psychometric design. The resulting Organizational Agility Scale in Higher Education was pilot tested and administered to 893 academic and administrative staff from 10 public universities in Istanbul. The principal components analysis with varimax rotation supported four dimensions. Through confirmatory factor analysis, four-factor structure was found to be at acceptable level. Four dimensions of the scale (strategy and staff-oriented organizational design, internal stakeholder orientation, cooperation with external stakeholders, support for innovation) focus more on human side of higher education institutions and less on change management and responsiveness, compared to business agility. The findings imply that institutional and national efforts are needed to form a strategy and stakeholder-oriented organization design for universities. A separate OA framework should be constructed for private universities to reach a more holistic understanding of Turkish HE and to compare public and private higher education institutions and to discover how Turkish HE system can be more agile and responsive in national and international contexts.

Keywords

Higher education innovation organizational agility stakeholder orientation strategy

References

  • Alzoubi, A. E. H., Al-otoum, F. J., & Albatainh, A. K. F. (2011). Factors associated affecting organization agility on product development. International Journal of Research and Reviews in Applied Sciences, 9(3), 503–515.
  • Amaral, A., & Magalhaes, A. (2002). The emergent role of external stakeholders in European higher education governance. In A. Amaral, G. Jones, & B. Karseth (Eds.), Governing higher education: National perspectives on institutional governance (pp. 1–21). Dordrecht: Springer.
  • Anderson, J. C., & Gerbing, D. W. (1984). The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis. Psychometrika, 49(2), 155–173.
  • Araza, A. (2015). The effect of environmental dynamism to organizational agility and performance relationship. Unpublished doctoral dissertation in Turkish, Yaşar University, İzmir.
  • Baskarada, S., & Koronios, A. (2018). The 5S organizational agility framework: A dynamic capabilities perspective. International Journal of Organizational Analysis, 26(2), 331–342.
  • Benneworth, P., & Jongbloed, B. W. (2010). Who matters to universities? A stakeholder perspective on humanities, arts and social sciences valorisation. Higher Education, 59(5), 567–588.
  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246.
  • Boateng, G. O., Neilands, T. B., Frongillo, E. A., Melgar-Quinonez, H. R., & Young, S. L. (2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6, 1–18.
  • Brown, T. A. (2015). Confirmatory factor analysis for applied research. New York, NY: Guilford Publications.
  • Browne, M. W., & Cudek, R. (1993). Alternate ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Thousand Oaks, CA: Sage Publications.
  • Byrne, B. M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming (3rd ed.). New York, NY: Routledge-Taylor and Francis.
  • Chung, S., Lee, K. Y., & Kim, K. (2014). Job performance through mobile enterprise systems: The role of organizational agility, location independence, and task characteristics. Information & Management, 51(6), 605–617.
  • Çokluk, Ö., Şekercioğlu, G., & Büyüköztürk, Ş. (2014). Sosyal bilimler için çok değişkenli istatistik: SPSS ve LISREL uygulamaları. Ankara: Pegem Akademi.
  • DeCoster, J. (1998). Overview of factor analysis. Retrieved from http://www.stat-help.com/notes.html (March 2, 2020).
  • Dubey, R., & Gunasekaran, A. (2015). Agile manufacturing: Framework and its empirical validation. The International Journal of Advanced Manufacturing Technology, 76(9–12), 2147–2157.
  • Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Structural Equation Modeling, 6(1), 56–83.
  • Freeman, R. (2010). Strategic management: A stakeholder approach. Cambridge: Cambridge University Press.
  • Ganguly, A., Nilchiani, R., & Farr, J. V. (2009). Evaluating agility in corporate enterprises. International Journal of Production Economics, 118(2), 410–423.
  • Gligor, D. M., Holcomb, M. C., & Stank, T. P. (2013). A multidisciplinary approach to supply chain agility: Conceptualization and scale development. Journal of Business Logistics, 34(2), 94–108.
  • Goldman, S. L., Nagel, R. N., & Priess, K. (1995). Agile competitors and virtual organizations: Strategies for enriching the customer. New York, NY: Van Nostrand Reinhold.
  • Gunasekaran, A. (1999). Agile manufacturing: A framework for research and development. International journal of production economics, 62(1–2), 87–105.
  • Harraf, A., Wanasika, I., Tate, K., & Talbott, K. (2015). Organizational agility. Journal of Applied Business Research (JABR), 31(2), 675–686.
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structural analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 55–65.
  • Inman, R. A., Sale, R. S., Green Jr, K. W., & Whitten, D. (2011). Agile manufacturing: Relation to JIT, operational performance and firm performance. Journal of Operations Management, 29(4), 343–355.
  • Jackson, M., & Johansson, C. (2003). An agility analysis from a production system perspective. Integrated Manufacturing Systems, 14(6), 482–488.
  • Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39(1), 31–36.
  • Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563–575.
  • Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103(3), 391.
  • McDonald, R. P., & Ho, M. H. R. (2002). Principles and practice in reporting statistical equation analyses. Psychological Methods, 7(1), 64–82.
  • Menon, S., & Suresh, M. (2021). Enablers of workforce agility in engineering educational institutions. Journal of Applied Research in Higher Education, 13(2), 504–539.
  • Sambamurthy, V., Bharadwaj, A., & Grover, V. (2003). Shaping agility through digital options: Reconceptualizing the role of information technology in contemporary firms. MIS Quarterly, 27(2), 237–263.
  • Schmitt, T. A. (2011). Current methodological considerations in exploratory and confirmatory factor analysis. Journal of Psychoeducational Assessment, 29(4), 304–321.
  • Senge, P. M., (2013). Beşinci disiplin: Öğrenen organizasyon sanatı ve uygulaması (A. Üldeniz, A. Doğukan, & B. Pala, Çev., 16. baskı). İstanbul: Yapı Kredi Yayınları.
  • Sharifi, H., & Zhang, Z. (1999). A methodology for achieving agility in manufacturing organisations: An introduction. International Journal of Production Economics, 62(1–2), 7–22.
  • Sharifi, H., & Zhang, Z. (2001). Agile manufacturing in practice – Application of a methodology. International Journal of Operations & Production Management, 21(5/6), 772–794.
  • Sharma, S., Mukherjee, S., Kumar, A., & Dillon, W. R. (2005). A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models. Journal of Business Research, 58(7), 935–943.
  • Sherehiy, B., Karwowski, W., & Layer, J. K. (2007). A review of enterprise agility: Concepts, frameworks, and attributes. International Journal of industrial ergonomics, 37(5), 445–460.
  • Sümer, N. (2000). Structural equation modeling: Basic concepts and applications. [Article in Turkish] Türk Psikoloji Yazıları, 3(6), 49–74.
  • Tabachnick, B. G., & Fidell, L. S. (2000). Using multivariate statistics (4th ed.). New Tork, NY: Harper & Row Publishing.
  • Tallon, P. P., & Pinsonneault, A. (2011). Competing perspectives on the link between strategic information technology alignment and organizational agility: Insights from a mediation model. Management Information Systems Quarterly, 35(2), 463–486.
  • Teece, D., Peteraf, M., & Leih, S. (2016). Dynamic capabilities and organizational agility: Risk, uncertainty, and strategy in the innovation economy. California Management Review, 58(4), 13–35.
  • Tsourveloudis, N. C., & Valavanis, K. P. (2002). On the measurement of enterprise agility. Journal of Intelligent and Robotic Systems, 33(3), 329–342.
  • Vázquez-Bustelo, D., Avella, L., & Fernández, E. (2007). Agility drivers, enablers and outcomes. International Journal of Operations & Production Management, 27(12), 1302–1332.
  • Weber, Y., & Tarba, S. Y. (2014). Strategic agility: A state of the art introduction to the special section on strategic agility. California Management Review, 56(3), 5–12.
  • Wissema, J. G. (2009). Towards the third-generation university: Managing the university in transition. Cheltenham: Edward Elgar Publishing.
  • Worley, C. G., & Lawler, E. E. (2010). Agility and organization design: A diagnostic framework. Organizational Dynamics, 39(2), 194–204.
  • Worley, C. G., Williams, T. D., & Lawler III, E. E. (2014). Assessing organization agility: Creating diagnostic Profiles to Guide transformation. New York, NY: John Wiley & Sons.
  • Worthington, R. L., & Whittaker, T. A. (2006). Scale development research: A content analysis and recommendations for best practices. The Counseling Psychologist, 34(6), 806–838.
  • Yusuf, Y. Y., & Adeleye, E. O. (2002). A comparative study of lean and agile manufacturing with a related survey of current practices in the UK. International Journal of Production Research, 40(17), 4545–4562.
  • Yusuf, Y. Y., Sarhadi, M., & Gunasekaran, A. (1999). Agile manufacturing: The drivers, concepts and attributes. International Journal of production economics, 62(1–2), 33–43.
  • Zelbst, P. J., Sower, V. E., Green Jr, K. W., & Abshire, R. D. (2011). Radio frequency identification technology utilization and organizational agility. Journal of Computer Information Systems, 52(1), 24–33.
  • Zerfaß, A., Dühring, L., Berger, K., & Brockhaus, J. (2018). Fast and flexible: Corporate communications in agile organizations. Communication Insights, (5), 1–33.
There are 52 citations in total.

Details

Primary Language English
Subjects Studies on Education
Journal Section Original Empirical Research
Authors

Feride Öksüz Gül 0000-0002-4958-7928

Münevver Çetin 0000-0002-1203-9098

Publication Date December 31, 2022
Published in Issue Year 2022 Volume: 12 Issue: 3

Cite

APA Öksüz Gül, F., & Çetin, M. (2022). Development of Organizational Agility Scale in Higher Education: A Validity and Reliability Study. Yükseköğretim Dergisi, 12(3), 384-396. https://doi.org/10.2399/yod.21.852759
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