Academic Intellectual Capital Scale: A Validity and Reliability Study

Yıl 2022, , 138 - 164, 10.03.2022

Uğur Özalp , Münevver Çetin

https://doi.org/10.21449/ijate.946530

Cited By: 1

Öz

The aim of this study was to develop a scale instrument for measuring academic intellectual capital in the Turkish higher education context depending on student perceptions. The sample consisted of students of higher education institutions in the 2020-2021 academic year. Data were gathered in two stages. Exploratory Factor Analysis (EFA) was conducted in the first stage and Confirmatory Factor Analysis (CFA) was conducted in the second stage. The EFA sample consisted of 538 students studying in 96 higher education institutions while the CFA sample consisted of 492 students studying in 112 higher education institutions. Principal Axis Factoring (PAF) extraction and Promax rotation methods were used in EFA. Results of EFA showed that the scale had a three-factor structure with 20 items. The three-factor structure was confirmed with CFA. Cronbach’s alpha, stratified alpha, Composite Reliability and McDonald’s omega were calculated in order to determine the reliability of the scores obtained from the scale. Item discrimination was verified by calculating item-total correlation and item-remainder correlation. Also, t-test was carried out between upper and lower 27% to check item discrimination. Analyses were conducted making use of R (ver. 4.1.2) and RStudio (ver. 2021.09.1 build 372). Overall, results showed that the structure of Academic Intellectual Capital Scale was valid. The measurement tool was concluded to have three factors and 20 items, all in affirmative form.

Anahtar Kelimeler

Academic intellectual capital, Intellectual capital, Higher education

Kaynakça

• American Educational Research Association. (2014). Standards for educational and psychological testing. American Educational Research Association.
• Asiaei, K., & Jusoh, R. (2017). Using a robust performance measurement system to illuminate intellectual capital. International Journal of Accounting Information Systems, 26, 1–19. https://doi.org/10.1016/j.accinf.2017.06.003
• Awang, Z. (2012). Structural equation modeling using AMOS graphic. Universiti Teknologi MARA Publication Centre (UPENA).
• Ayre, C., & Scally, A.J. (2014). Critical values for Lawshe’s content validity ratio: Revisiting the original methods of calculation. Measurement and Evaluation in Counseling and Development, 47(1), 79–86. https://doi.org/10.1177/0748175613513808
• Bagheri, A., & Saadati, M. (2021). Generalized structural equations approach in the of elderly self rated health. Journal of Physics: Conference Series, 1863(1), 1 10. https://doi.org/10.1088/1742-6596/1863/1/012041
• Basile, C.G. (2009). Intellectual capital: The tangible assets of professional development schools. State University of New York Press.
• Baş, M., Mısırdalı Yangil, F., & Aygün, S. (2014). Entelektüel sermaye alanında yapılan lisansüstü tez çalışmalarına yönelik bir içerik analizi: 2002 – 2012 dönemi [A content analysis on the dissertations on intellectual capital: 2002 – 2021 period]. International Journal of Management Economics and Business, 10(23), 207–226. https://doi.org/10.17130/ijmeb.2014.10.23.618
• Bontis, N. (1998). Intellectual capital: an exploratory study that develops measures and models. Management Decision, 36(2), 63–76. https://doi.org/10.1108/00251749810204142
• Bontis, N. (2002). Managing organizational knowledge by diagnosing intellectual capital: Framing and advancing the state of the field. In N. Bontis (Ed.), World Congress on Intellectual Capital Readings (pp. 13–56). Elsevier.
• Bontis, N., Crossan, M. M., & Hulland, J. (2002). Managing an organizational learning system by aligning stocks and flows. Journal of Management Studies, 39(4), 437–469. https://doi.org/10.1111/1467-6486.t01-1-00299
• Bontis, N., Keow, W.C.C., & Richardson, S. (2000). Intellectual capital and business performance in Malaysian industries. Journal of Intellectual Capital, 1(1), 85–100. https://doi.org/10.1108/14691930010324188
• Bozbura, F.T., & Toraman, A. (2004). Türkiye’de entelektüel sermayenin ölçülmesi ile ilgili model çalışması ve bir uygulama [A model study of measurement intellectual capital in Turkey and an application]. İTÜ Dergisi, 3(1), 55 66. http://itudergi.itu.edu.tr/index.php/itudergisi_d/article/viewFile/709/643
• Brătianu, C., & Pînzaru, F. (2015). Challenges for the university intellectual capital in the knowledge economy. Management Dynamics in the Knowledge Economy, 3(4), 609–627. https://www.managementdynamics.ro/index.php/journal/article/view/153/102
• Brenca, A., & Garleja, R. (2013). Intellectual capital in the higher education institutions of Latvia in the context of international trade. European Conference on Intellectual Capital, 495.
• Brenca, A., & Gravite, A. (2013). Intellectual capital import for the benefit of higher education. Bulgarian Comparative Education Society, 1–6.
• Brody, N. (2017). Factor analysis: Rotated matrix. In M. Allen (Ed.), The SAGE encyclopedia of communication research methods (pp. 526–531). Sage Reference.
• Brown, T.A. (2015). Confirmatory factor analysis for applied research. The Guilford Press.
• Büyüköztürk, Ş., Kılıç Çakmak, E., Erkan Akgün, Ö., Karadeniz, Ş., & Demirel, F. (2020). Bilimsel araştırma yöntemleri [Scientific research methods in education]. Pegem Akademi. https://doi.org/10.14527/9789944919289
• Byrne, B.M. (2016). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Routledge.
• Cabrita, M. do R., & Bontis, N. (2008). Intellectual capital and business performance in the Portuguese banking industry. International Journal of Technology Management, 43(1–3), 212–237. http://dx.doi.org/10.1504/IJTM.2008.019416
• Cabrita, M. do R., & Vaz, J.L. (2005). Intellectual capital and value creation: Evidencing in Portuguese banking industry. In D. Remenyi (Ed.), Proceedings of the European Conference on Knowledge Management, ECKM (pp. 98–106). University of Limerick.
• Carpenter, S. (2018). Ten steps in scale development and reporting: A guide for researchers. Communication Methods and Measures, 12(1), 25 44. https://doi.org/10.1080/19312458.2017.1396583
• Carson, E., Ranzijn, R., Winefield, A., & Marsden, H. (2004). Intellectual capital: Mapping employee and work group attributes. Journal of Intellectual Capital, 5(3), 443–463. https://doi.org/10.1108/14691930410550390
• Chajewski, M. (2009). rela: Scale item analysis. R package version 4.1.
• Chan, K.H. (2009). Impact of intellectual capital on organisational performance: An empirical study of companies in the Hang Seng Index (Part 1). The Learning Organization, 16(1), 4–21. https://doi.org/10.1108/09696470910927641
• Chang, S.C., Chen, S.S., & Lai, J.H. (2008). The effect of alliance experience and intellectual capital on the value creation of international strategic alliances. Omega, 36(2), 298–316. https://doi.org/10.1016/j.omega.2006.06.010
• Chatterji, N., & Kiran, R. (2017). Relationship between university performance and dimensions of intellectual capital: An empirical investigation. Eurasian Journal of Educational Research, 71, 215–232. https://doi.org/10.14689/ejer.2017.71.12
• Chen, J., Zhu, Z., & Yuan Xie, H. (2004). Measuring intellectual capital: A new model and empirical study. Journal of Intellectual Capital, 5(1), 195 212. https://doi.org/10.1108/14691930410513003
• Child, D. (2006). The essentials of factor analysis. Continuum.
• Costello, A.B., & Osborne, J.W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research and Evaluation, 10(7).
• de Castro, G.M., Verde, M.D., Sáez, P.L., & López, J.E.N. (2010). Technological innovation: An intellectual capital based view. Palgrave Macmillan.
• de Frutos-Belizón, J., Martín-Alcázar, F., & Sánchez-Gardey, G. (2019). Conceptualizing academic intellectual capital: Definition and proposal of a measurement scale. Journal of Intellectual Capital, 20(3), 306–334. https://doi.org/10.1108/JIC-09-2018-0152
• Dean, A., & Kretschmer, M. (2007). Can ideas be capital? Factors of production in the postindustrial economy: A review and critique. Academy of Management Review, 32(2), 573–594. https://doi.org/10.5465/AMR.2007.24351866
• Delgado-Verde, M., & Cruz-González, J. (2010). An intellectual capital-based view of technological innovation. In P. L. Sáez, G. M. de Castro, J. E. N. López, & M. Delgado-Verde (Eds.), Intellectual capital and technological innovation: Knowledge-based theory and practice (pp. 166–193). Information Science Reference.
• Demir, S. (2018). Entelektüel sermaye ile öğretmenlerin iş doyumları arasındaki ilişki üzerine bir çalışma [A study on the relationship between intellectual capital and teachers’ job satisfaction]. İnönü University Journal of the Faculty of Education, 19(3), 205–215. https://doi.org/10.17679/inuefd.385908
• DeVellis, R.F. (2017). Scale development: Theory and applications. Sage.
• Doll, W.J., Xia, W., & Torkzadeh, G. (1994). A confirmatory factor analysis of the end-user computing satisfaction instrument. MS Quarterly, 18(4), 453–461.
• Dorans, N.J. (2018). Scores, scales, and score linking. In P. Irwing, T. Booth, & D. J. Hughes (Eds.), The Wiley handbook of psychometric testing: A multidisciplinary reference on survey, scale and test development2 (pp. 573–605). Wiley Blackwell.
• Dowle, M., & Srinivasan, A. (2020). data.table: Extension of “data.frame.”
• Dzinkowski, R. (2000). The measurement and management of intellectual capital: An introduction. International Management Accounting Study, 32–36.
• el Hamdi, S., Abouabdellah, A., & Oudani, M. (2019). Industry 4.0: Fundamentals and main challenges. 12th International Colloquium on Logistics and Supply Chain Management, LOGISTIQUA 2019, 1–5. https://doi.org/10.1109/LOGISTIQUA.2019.8907280
• Fabrigar, L.R., Wegener, D.T., MacCallum, R.C., & Strahan, E. (1999). Evaluating the use of exploratory factor analysis in psychological research. Pyschological Methods, 4(3), 272–299. https://doi.org/10.1037/1082-989x.4.3.272
• Feißt, M., Hennigs, A., Heil, J., Moosbrugger, H., Kelava, A., Stolpner, I., Kieser, M., & Rauch, G. (2019). Refining scores based on patient reported outcomes - statistical and medical perspectives. BMC Medical Research Methodology, 19(1), 167. https://doi.org/10.1186/s12874-019-0806-9
• Field, A. (2018). Discovering statistics using IBM SPSS Statistics (5th Editio). Sage.
• Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Sage.
• Fink, A. (2010). Survey Research Methods. In P. Peterson, E. Baker, & B. McGraw (Eds.), International encyclopedia of education (pp. 152–160). Elsevier.
• Fitz-enz, J. (2019). The ROI of human capital: Measuring the economic value of employee performance. Amacom.
• Fletcher, T.D. (2015). Package ‘QuantPsyc.’ https://cran.r project.org/web/packages/QuantPsyc
• Forza, C., & Filippini, R. (1998). TQM impact on quality conformance and customer satisfaction: A causal model. International Journal of Production Economics, 55(1), 1–20. https://doi.org/10.1016/S0925-5273(98)00007-3
• Gilbert, G.E., & Prion, S. (2016). Making sense of methods and measurement : Lawshe’s content validity index. Clinical Simulation in Nursing, 12(12), 530–531. https://doi.org/10.1016/j.ecns.2016.08.002
• Görmüş, A.Ş. (2009). Entelektüel sermaye ve i̇nsan kaynaklari yöneti̇mi̇ni̇n artan önemi̇ [The growing importance of intellectual capital and human resource management]. Afyon Kocatepe University Journal of Economics and Administrative Sciences, 10(1), 57–75. https://acikerisim.aku.edu.tr/xmlui/handle/AKU/1310
• Greenspoon, P.J., & Saklofske, D.H. (1998). Confirmatory factor analysis of the multidimensional Students’ Life Satisfaction Scale. Personality and Individual Differences, 25(5), 965–971. https://doi.org/10.1016/S0191-8869(98)00115-9
• Hair, J.F., Black, W.C., Babin, B.J., & Anderson, R.E. (2018). Multivariate data analysis. Cengage.
• Han, Y., & Li, D. (2015). Effects of intellectual capital on innovative performance: The role of knowledge-based dynamic capability. Management Decision, 53(1), 40–56. https://doi.org/10.1108/MD-08-2013-0411
• Harris, V., Brett, J., Hirst, S., McClelland, Z., Phizackerley-Sugden, E., & Brown, S. (2007). Using a quality enhancement audit approach to review provision for international students: A case study. In E. Jones & S. Brown (Eds.), Internationalising higher education (pp. 95–106). Routledge.
• Hayashi, K., & Yuan, K.-H. (2010). Exploratory factor analysis. In N. J. Salkind (Ed.), Encyclopedia of research design (pp. 458–465). Sage.
• Holland, J., & Holland, J. (2010). Globalization of instruction: Developing intellectual capital. In P. L. Sáez, G. M. de Castro, J. E. N. López, & M. Delgado-Verde (Eds.), Intellectual capital and technological innovation: Knowledge-based theory and practice (pp. 39–54). Information Science Reference.
• Hooper, D., Coughlan, J., & Mullen, M.R. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60. https://doi.org/10.21427/D79B73
• Hsu, Y.H., & Fang, W. (2009). Intellectual capital and new product development performance: The mediating role of organizational learning capability. Technological Forecasting and Social Change, 76(5), 664–677. https://doi.org/10.1016/j.techfore.2008.03.012
• Hu, L.T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
• Huang, C.C., Luther, R., & Tayles, M. (2007). An evidence-based taxonomy of intellectual capital. Journal of Intellectual Capital, 8(3), 386 408. https://doi.org/10.1108/14691930710774830
• Huang, C.C., Tayles, M., & Luther, R. (2010). Contingency factors influencing the availability of internal intellectual capital information. Journal of Financial Reporting and Accounting, 8(1), 4–21. https://doi.org/10.1108/19852511011055916
• Irwing, P., Booth, T., & Hughes, D.J. (2018). The Wiley handbook of psychometric testing: A multidisciplinary reference on survey, scale and test development. Wiley Blackwell.
• Irwing, P., & Hughes, D.J. (2018). Test development. In P. Irwing, T. Booth, & D. J. Hughes (Eds.), The Wiley handbook of psychometric testing: A multidisciplinary reference on survey, scale and test development (pp. 3–48). Wiley Blackwell.
• Jakubowska, A., & Rosa, A. (2014). Significance of higher education in creating of intellectual capital. Human Resources Management & Ergonomics, 8, 48–60.
• Johnson, R.L., & Morgan, G.B. (2016). Survey scales: A guide to development, analysis, and reporting. The Guilford Press.
• Jorgensen, T.D., Pornprasertmanit, S., Schoemann, A.M., & Rosseel, Y. (2021). semTools: Useful tools for structural equation modeling.
• Karakuş, M. (2008). Eǧitim örgütlerinde entelektüel sermayenin yönetimi [Management of intellectual capital in educational organizations]. Milli Egitim, 178, 334–349.
• Kaya, N., & Kesen, M. (2014). İnsan kaynaklarının insan sermayesine dönüşümü: Bir literatür taraması [Transforming human resources into human capital: A scan of the literature]. Journal of Academic Researches and Studies, 6(10), 23 38. https://dergipark.org.tr/tr/download/article-file/180494
• Kelly, A. (2004a). The intellectual capital of schools: Analysing government policy statements on school improvement in light of a new theorization. Journal of Education Policy, 19(5), 609–629. https://doi.org/10.1080/0268093042000269180
• Kelly, A. (2004b). The intellectual capital of schools - Measuring and managing knowledge responsibility and reward: Lessons from the commercial sector. Springer Science+Business Media, Inc.
• Kline, R.B. (2015). Principles and practices of structural equation modelling. The Guilford Press.
• Kutlu, H.A. (2009). Entelektüel sermaye: Türkiye muhasebe sisteminde raporlanabilir mi? [Intellectual capital: Can it be reported in the accounting system of Turkey?] Hacettepe University Journal of Economics and Administrative Sciences, 27(1), 235–257. https://dergipark.org.tr/en/download/article-file/302681
• Lane, S., Raymond, M.R., Haladyna, T.M., & Downing, S.M. (2016). Test development process. In S. Lane, M. R. Raymond, & T. M. Haladyna (Eds.), Handbook of test development (pp. 3–18). Routledge.
• Lawshe, C.H. (1975). A quantitative approach to content validity. Personnel Psychology, 28, 563–575. https://doi.org/10.1111/j.1744-6570.1975.tb01393.x
• Leech, N.L., Barrett, K.C., & Morgan, G.A. (2015). IBM SPSS intermediate statistics. Routledge.
• Leitner, K.H. (2004). Intellectual capital reporting for universities: Conceptual background and application for Austrian universities. Research Evaluation, 13(2), 129–140. https://doi.org/10.3152/147154404781776464
• Li, C.H. (2016). Confirmatory factor analysis with ordinal data: Comparing robust maximum likelihood and diagonally weighted least squares. Behavior Research Methods, 48(3), 936–949. https://doi.org/10.3758/s13428-015-0619-7
• Litwin, M.S. (2002). How to assess and interpret survey psychometrics. Sage Publications.
• Lu, W.M. (2012). Intellectual capital and university performance in Taiwan. Economic Modelling, 29(4), 1081–1089. https://doi.org/10.1016/j.econmod.2012.03.021
• Mariani, G., Carlesi, A., & Scarfò, A.A. (2018). Academic spinoffs as a value driver for intellectual capital: The case of the University of Pisa. Journal of Intellectual Capital, 19(1), 202–226. https://doi.org/10.1108/JIC-03-2017-0050
• Markus, K.A., & Lin, C. (2010). Construct validity. In N. J. Salkind (Ed.), Encyclopedia of research design (pp. 229–233). Sage.
• Markus, K.A., & Smith, K.M. (2010). Content validity. In N. J. Salkind (Ed.), Encyclopedia of research design (pp. 238–243). Sage.
• Martínez-Torres, M. R. (2006). A procedure to design a structural and measurement model of intellectual capital: An exploratory study. Information and Management, 43(5), 617–626. https://doi.org/10.1016/j.im.2006.03.002
• Martinez, L.S. (2017). Validity, face and content. In M. Allen (Ed.), The SAGE encyclopedia of communication research methods (pp. 1822–1824). Sage Reference.
• Martinková, P., & Drabinová, A. (2018). ShinyItemAnalysis for teaching psychometrics and to enforce routine analysis of educational tests. The R Journal, 10(2), 503–515. https://doi.org/10.32614/RJ-2018-074
• Matos, F., Vairinhos, V., Selig, P. M., & Edvinsson, L. (2019). Intellectual capital management as a driver of sustainability: Perspectives for organizations and society. Springer.
• Mohamed, M. (2018). Challenges and benefits of industry 4.0: An overview. International Journal of Supply Operating Management, 5(3), 256 265. https://doi.org/10.22034/2018.3.7
• Motta, G. (2017). Factor analysis. In M. Allen (Ed.), The SAGE encyclopedia of communication research methods (pp. 502–505). Sage Reference.
• Mura, M., & Longo, M. (2013). Developing a tool for intellectual capital assessment: An individual level perspective. Expert Systems, 30(5), 436 450. https://doi.org/10.1111/j.1468-0394.2012.00650.x
• Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational change. Academy Ol Managemeni Review, 23(2), 242–266.
• Netemeyer, R.G., Bearden, W.O., & Sharma, S. (2003). Scaling procedures: Issues and applications. Sage Publications.
• O’Connor, B.P. (2020). EFA.dimensions: Exploratory factor analysis functions for assessing dimensionality.
• O’Donnell, D., & O’Regan, P. (2000). The structural dimensions of intellectual capital : Emerging challenges for management and accounting. Southern African Business Review, 4(2), 14–20.
• OECD/Eurostat. (2018). Oslo manual 2018: Guidelines for collecting, reporting and using data on innovation. OECD. https://doi.org/10.1787/9789264304604-en
• Osburn, H.G. (2000). Coefficient alpha and related internal consistency reliability coefficients. Psychological Methods, 5(3), 343–355. https://doi.org/10.1037/1082-989X.5.3.343
• Pedrini, M.P. (2007). Human capital convergences in intellectual capital and sustainability reports. Journal of Intellectual Capital, 8(2), 346 366. https://doi.org/10.1108/14691930710742880
• Pedro, E. de M., Leitão, J., & Alves, H. (2020). Bridging intellectual capital, sustainable development and quality of life in higher education institutions. Sustainability, 12(2), 1–27. https://doi.org/10.3390/su12020479
• Preacher, K.J., Zhang, G., Kim, C., & Mels, G. (2013). Choosing the optimal number of factors in exploratory factor analysis: A model selection perspective. Multivariate Behavioral Research, 48(1), 28–56. https://doi.org/10.1080/00273171.2012.710386
• R Core Team. (2021). R: A language and environment for statistical comouting. R Foundation for Statistical Computing. https://www.r-project.org/
• Rae, G. (2007). A note on using stratified alpha to estimate the composite reliability of a test composed of interrelated nonhomogeneous items. Psychological Methods, 12(2), 177–184. https://doi.org/10.1037/1082-989X.12.2.177
• Ramírez, Y., & Gordillo, S. (2013). Recognition of intellectual capital importance in the university sector. International Journal of Business and Social Research, 3(4), 27–41. https://doi.org/10.18533/ijbsr.v3i4.27
• Ramírez, Y., & Gordillo, S. (2014). Recognition and measurement of intellectual capital in Spanish universities. Journal of Intellectual Capital, 15(1), 173 188. https://doi.org/10.1108/JIC-05-2013-0058
• Ramírez Córcoles, Y., & Tejada Ponce, Á. (2013). Cost-benefit analysis of intellectual capital disclosure: University stakeholders’ view. Revista de Contabilidad-Spanish Accounting Review, 16(2), 106–117. https://doi.org/10.1016/j.rcsar.2013.07.001
• Ramirez, Y., Tejada, A., & Manzaneque, M. (2016). The value of disclosing intellectual capital in Spanish universities: A new challenge of our days. Journal of Organizational Change Management, 29(2), 176–198. https://doi.org/10.1108/JOCM-02-2015-0025
• Ren, J.Y. (2009). The empirical study on the relationship between corporate intellectual capital and corporate performance. IE and EM 2009 - Proceedings 2009 IEEE 16th International Conference on Industrial Engineering and Engineering Management, 2054–2058. https://doi.org/10.1109/ICIEEM.2009.5344238
• Revelle, W. (2020). psych: Procedures for personality and psychological research. Northwestern University.
• Robitzsch, A. (2021). sirt: Supplementary item response theory models. R package version 3.11-21. https://cran.r-project.org/package=sirt
• Roos, J., Roos, G., Edvinsson, L., & Dragonetti, N. C. (1997). Intellectual capital: Navigating in the new business landscape. Macmillan Business.
• Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2). http://dx.doi.org/10.18637/jss.v048.i02
• Rstudio Team. (2021). RStudio: Integrated development for R. RStudio. https://www.rstudio.com/
• Saint-Ogne, H. (1996). Tacit knowledge the key to the strategic alignment of intellectual capital. Planning Review, 24(2), 10–16. https://doi.org/10.1108/eb054547
• Sánchez, M.P., Elena, S., & Castrillo, R. (2009). Intellectual capital dynamics in universities: A reporting model. Journal of Intellectual Capital, 10(2), 307–324. https://doi.org/10.1108/14691930910952687
• Schermelleh-Engel, K., Moosbrugger, H., & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8, 23–74.
• Schmitt, T.A. (2011). Current methodological considerations in exploratory and confirmatory factor analysis. Journal of Psychoeducational Assessment, 29(4), 304–321. https://doi.org/10.1177/0734282911406653
• Schneider, P. (2018). Managerial challenges of Industry 4.0: an empirically backed research agenda for a nascent field. Review of Managerial Science, 12(3), 803–848. https://doi.org/10.1007/s11846-018-0283-2
• Schumacker, R.E., & Lomax, R.G. (2016). A beginner’s guide to structural equation modeling. Routledge.
• Segars, A.H., & Grover, V. (1993). Re-examining perceived ease of use and usefulness: A confirmatory factor analysis. MIS Quarterly: Management Information Systems, 17(4), 517–525. https://doi.org/10.2307/249590
• Semenov, V. (2016). Institutional features of strategic management of intellectual capital reproduction. 2015 4th Forum Strategic Partnership of Universities and Enterprises of Hi Tech Branches (Science. Education. Innovation), 52 54. https://doi.org/10.1109/IVForum.2015.7388251
• Silva, T.M., & Ferreira, A. (2019). Intellectual capital sustainability in Brazilian public higher education. In F. Matos, V. Vairinhos, P. M. Selig, & L. Edvinsson (Eds.), Intellectual capital management as a driver of sustainability: Perspectives for organizations and society. Springer.
• Sohrabi, B., Raeesi, I., & Khanlari, A. (2010). Intellectual capital components, measurement and management: A literature survey of concepts and measures. In P. L. Sáez, G. M. de Castro, J. E. N. López, & M. Delgado-Verde (Eds.), Intellectual capital and technological innovation: Knowledge-based theory and practice (pp. 1–38). Information Science Reference.
• Steiger, J.H. (2007). Understanding the limitations of global fit assessment in structural equation modeling. Personality and Individual Differences, 42(5), 893–898. https://doi.org/10.1016/j.paid.2006.09.017
• Steiner, M.D., & Grieder, S.G. (2020). EFAtools: An R package with fast and flexible implementations of exploratory factor analysis tools. Journal of Open Source Software, 5(53). https://doi.org/10.21105/joss.02521
• Subramaniam, M., & Youndt, M.A. (2005). The influence of intellectual capital on the types of innovative capabilities. Academy of Management Journal, 48(3), 450–463. https://doi.org/10.5465/amj.2005.17407911
• Suciu, M., & Năsulea, D. (2019). Intellectual capital and creative economy as key drivers for competitiveness towards a smart and sustainable development: Challenges and opportunities for cultural and creative communities. In F. Matos, V. Vairinhos, P. M. Selig, & L. Edvinsson (Eds.), Intellectual capital management as a driver of sustainability: Perspectives for organizations and society (pp. 67–97). Springer.
• Sultan, P., & Wong, H.Y. (2019). How service quality affects university brand performance, university brand image and behavioural intention: the mediating effects of satisfaction and trust and moderating roles of gender and study mode. Journal of Brand Management, 26(3), 332–347. https://doi.org/10.1057/s41262-018-0131-3
• Şencan, H. (2005). Sosyal ve davranışsal ölçümlerde güvenilirlik ve geçerlilik [Reliability and validity in social and behavioral measures]. Seçkin.
• Tabachnick, B.G., & Fidell, L.S. (2014). Using multivariate statistics. Pearson.
• Tajvidi, M., & Karami, A. (2015). Product development strategy: Innovation capacity and entrepreneurial firm performance in high-tech SMEs. Palgrave Macmillan.
• Todericiu, R., & Stanit, A. (2016). Universities intellectual capital. Management and Economics, 4(84), 348–356.
• Todericiu, R., & Şerban, A. (2015). Intellectual capital and its relationship with universities. Procedia Economics and Finance, 27(15), 713–717. https://doi.org/10.1016/s2212-5671(15)01052-7
• Ullman, J.B. (2014). Structural equation modeling. In B. G. Tabachnick & L. S. Fidell (Eds.), Using multivariate statistics (pp. 731–836). Pearson.
• Urban, B., & Joubert, G.C.D.S. (2017). Multidimensional and comparative study on intellectual capital and organisational performance. Journal of Business Economics and Management, 18(1), 84–99. https://doi.org/10.3846/16111699.2016.1255990
• Watkins, M.W. (2021). A step-by-step guide to exploratory factor analysis with R and RStudio. In A Step-by-Step Guide to Exploratory Factor Analysis with R and RStudio. Routledge. https://doi.org/10.4324/9781003120001
• Welch, G.W. (2010). Confirmatory factor analysis. In N. J. Salkind (Ed.), Encyclopedia of research design (pp. 216–220). Sage.
• Wickham, H., François, R., Henry, L., & Müller, K. (2020). dplyr: A grammar of data manipulation.
• Williams, B., Onsman, A., & Brown, T. (2010). Exploratory factor analysis: A five-step guide for novices. Journal of Emergency Primary Health Care (JEPHC), 8(3), 1–13. https://doi.org/10.33151/ajp.8.3.93
• Wilson, F.R., Pan, W., & Schumsky, D.A. (2012). Recalculation of the critical values for Lawshe’s content validity ratio. Measurement and Evaluation in Counseling and Development, 45(3), 197–210. https://doi.org/10.1177/0748175612440286
• 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. https://doi.org/10.1177/0011000006288127
• Youndt, M. A., & Snell, S. A. (2004). Human resource configurations, intellectual capital, and organizational performance. Journal of Managerial Issues, 16(3), 337–360.