Use of Structural Equation Modeling in Quantitative Research in the field of Management and Economics: A Bibliometric Analysis in the Systematic Literature Review

• Autorzy: Agnieszka Zakrzewska-Bielawska , Anna M. Lis , Anna Ujwary-Gil
• Języki publikacji: EN

Abstrakty

EN

PURPOSE: This paper aims to provide a comprehensive review of scholarly research focusing on using quantitative methods and particularly structural equation modeling (SEM) in management and economics studies, as well as provide a bibliometric agenda including the time horizon of individual publications, the highest citation rate, geographic and industry areas, methodological context, and keywords. METHODOLOGY: A systematic literature review (SLR) was undertaken using the Web of Science and Scopus databases. We limited our search to the last five years to identify the newest research publications, and we used keywords related to quantitative research while excluding qualitative research. Then we analyzed papers related to SEM and those published in English. FINDINGS: Our results confirmed that quantitative methods are used both in management and economics research, and showed a growing trend in the number of publications in the last five years. However, there are many more publications on management than on economics as well as there are more papers published in the Scopus database than Web of Science. Taking into account structural equation modeling, this method is used primarily in management research. In terms of industry, publications using SEM considered both single- and multi-industry including, first, all Asian countries and then African ones. Publications, especially in the management field, are descriptive in nature and based on primary data collected using a survey questionnaire. Papers are published in various journals and the most cited are those published in journals with wider subject areas. IMPLICATIONS: The systematic literature review is a fundamental necessity in any field of knowledge, benefiting both academia and learners. Our results may be useful for future researchers planning research using quantitative methods, especially SEM, in the business or economic field, by indicating the most cited papers and journals as well as industry and country areas. ORIGINALITY AND VALUE: This paper represents a systematic attempt to link quantitative methods, with a particular emphasis on SEM, with research interests on managerial and economic subjects and papers published in the Web of Science and Scopus databases. Employing the bibliometric analysis within the systematic literature review, the paper shows interest and the current state of research using quantitative methods which proves its value and originality. (original abstract)

CEL: Celem artykułu jest przeprowadzenie kompleksowego przeglądu literatury z ostatnich pięciu lat aby zidentyfikować główne trendy zainteresowania badaczy zastosowaniem metod ilościowych, w szczególności modelowania równań strukturalnych (SEM). Badaniami objęto nauki o zarządzaniu i ekonomię. Określono aktywność badawczą ze względu na horyzont czasowy, najwyższy wskaźnik cytowań, kontekst geograficzny, branżowy i metodologiczny oraz słowa kluczowe wybranych do analizy publikacji. METODYKA: Badania przeprowadzono przy użyciu metody systematycznego przeglądu literatury (SLR) wykorzystując dwie kluczowe bazy danych, jak Web of Science i Scopus. Analizie poddano wyłącznie opracowania z ostatnich pięciu lat. W celu rozpoznania trendów badawczych wykorzystano słowa kluczowe związane z badaniami ilościowymi, wykluczając jednocześnie badania jakościowe jako kryterium poszukiwań. Następnie przeanalizowano publikacje związane z SEM oraz te opublikowane w języku angielskim. WYNIKI: Uzyskane wyniki potwierdziły, że metody ilościowe są wykorzystywane zarówno w badaniach z zakresu zarządzania, jak i ekonomii oraz wykazują trend rosnący w zakresie liczby publikacji w ciągu ostatnich pięciu lat. Jednocześnie publikacji z zakresu zarządzania jest znacznie więcej niż z ekonomii, przy większej ich liczebności w bazie Scopus niż Web of Science. Biorąc pod uwagę modelowanie równań strukturalnych, metoda ta jest stosowana przede wszystkim w badaniach z zakresu zarządzania. W ujęciu branżowym, publikacje wykorzystujące SEM dotyczyły zarówno analiz jedno-, jak i wielobranżowych, obejmując w pierwszej kolejności kraje azjatyckie, a następnie afrykańskie. Z kolei badania z zakresu ekonomii są bardziej jednorodne, obejmując najczęściej jedną branżę lub jeden kraj. Publikacje, zwłaszcza z zakresu zarządzania, mają charakter deskryptywny i bazują na danych pierwotnych zebranych za pomocą kwestionariusza ankiety. Opracowania podlegające analizie zostały opublikowane w różnych czasopismach, jednak najczęściej cytowane są te zamieszczone w czasopismach o szerszym zakresie tematycznym. IMPLIKACJE: Systematyczny przegląd literatury jest ważną metodą systematyzacji wiedzy i określania trendów badawczych w każdej dyscyplinie naukowej, inspirując i dostarczając implikacji badawczych. Nasze wyniki, poprzez wskazanie najczęściej cytowanych artykułów i czasopism a także branż i obszarów geograficznych prowadzonych analiz, mogą być przydatne dla przyszłych badaczy planujących badania z wykorzystaniem metod ilościowych, zwłaszcza SEM, w obszarze zarządzania lub ekonomii. ORYGINALNOŚĆ/WARTOŚĆ: Artykuł jest próbą powiązania metod ilościowych, ze szczególnym uwzględnieniem SEM, z problematyką nauk o zarzadzaniu i ekonomii przy wykorzystaniu publikacji indeksowanych w bazach Web of Science i Scopus. Wykorzystując systematyczny przegląd literatury i analizę cytowań, artykuł ukazuje trendy i aktualny stan badań w zakresie wykorzystania metod ilościowych w literaturze biznesowo-ekonomicznej, wypełniając lukę poznawczą w tym obszarze. (abstrakt oryginalny)

Słowa kluczowe

EN

Quantitative methods; Structural Equation Modeling; Management; Economics; Bibliometric analysis; Databases

PL

Metody ilościowe; Modelowanie równań strukturalnych; Zarządzanie; Ekonomia; Analiza bibliometryczna; Bazy danych

• Czasopismo: Journal of Entrepreneurship, Management and Innovation (JEMI)
• Rocznik: 2022
• Tom: 18
• Numer: nr 2 Quantitative Research in Economics and Management Sciences
• Strony: 7--40

Twórcy

autor

Agnieszka Zakrzewska-Bielawska

• Lodz University of Technology, Poland

autor

Anna M. Lis

• University of Technology, Poland

autor

Anna Ujwary-Gil

• Polish Academy of Sciences, Warsaw, Poland

Bibliografia

• Adnan, A., Ahmad, A., & Khan, M. N. (2017). Examining the role of consumer lifestyles on ecological behavior among young Indian consumers. Young Consumers, 18(4), 348-377. https://doi.org/10.1108/YC-05-2017-00699
• Agyabeng-Mensah, Y., Ahenkorah, E., Afum, E., Agyemang, A. N., Agnikpe, C., & Rogers, F. (2020). Examining the influence of internal green supply chain practices, green human resource management and supply chain environmental cooperation on firm performance. Supply Chain Management: An International Journal, 25(5), 585-599. https://doi.org/10.1108/SCM-11-2019-0405
• Anggadwita, G., Luturlean, B. S., Ramadani, V., & Ratten, V. (2017). Socio-cultural environments and emerging economy entrepreneurship: Women entrepreneurs in Indonesia. Journal of Entrepreneurship in Emerging Economies, 9(1), 85-96. https://doi.org/10.1108/JEEE-03-2016-0011
• Balcerzak, A. P., & Pietrzak, M. B. (2017). Sustainable development in the European Union in the years 2004-2013. In M. Bilgin, H. Danis, E. Demir, & U. Can (Eds.), Regional Studies on Economic Growth, Financial Economics and Management (pp. 193-213). Cham: Springer. https://doi.org/10.1007/978-3-319-54112-9_12
• Baškarada, S., & Koronios, A. (2018). A philosophical discussion of qualitative, quantitative, and mixed methods research in social science. Qualitative Research Journal, 18(1), 2-21. https://doi.org/10.1108/QRJ-D-17-00042
• Bharadwaj, S., & Deka, S. (2021). Behavioural intention towards investment in cryptocurrency: An integration of Rogers' diffusion of innovation theory and the technology acceptance model. Forum Scientiae Oeconomia, 9(4), 137-159. https://doi.org/10.23762/FSO_VOL9_NO4_7
• Blunch, N. J. (2008). Introduction to structural equation modelling using SPSS and AMOS. Thousand Oaks: SAGE.
• Bowen, N. K., & Guo, S. (2011). Structural Equation Modeling. Oxford: Oxford University Press.
• Bruning, P. F., & Campion, M. A. (2018). A role-resource approach-avoidance model of job crafting: A multimethod integration and extension of job crafting theory. Academy of Management Journal, 61(2), 499-522. https://doi.org/10.5465/amj.2015.0604
• Czakon, W. (Ed.). (2015). Podstawy Metodologii Badań w Naukach o Zarządzaniu. Warsaw: Oficyna Wolters Kluwer Business.
• DeFreese, E. W., & Nissley, G. E. (2020). Idiographic vs. nomothetic research. In The Wiley Encyclopedia of Personality and Individual Differences: Measurement and Assessment (pp. 19-23). Hoboken: John Wiley & Sons.
• Dow, S. C. (2012). Methodological pluralism and pluralism of method. In Foundations for New Economic Thinking (pp. 129-139). London: Palgrave Macmillan.
• Eisingerich, A. B., Marchand, A., Fritze, M. P., & Dong, L. (2019). Hook vs. hope: How to enhance customer engagement through gamification. International Journal of Research in Marketing, 36(2), 200-215. https://doi.org/10.1016/j.ijresmar.2019.02.003
• Etter, M., Colleoni, E., Illia, L., Meggiorin, K., & D'Eugenio, A. (2018). Measuring organizational legitimacy in social media: Assessing citizens' judgments with sentiment analysis. Business & Society, 57(1), 60-97. https://doi.org/10.1177/0007650316683926
• Evans, J. S. B., & Over, D. E. (2013). Reasoning to and from belief: Deduction and induction are still distinct. Thinking & Reasoning, 19(3-4), 267-283. https://doi.org/10.1080/13546783.2012.745450
• Fauzi, M. A., Martin, T., & Ravesangar, K. (2021). The influence of transformational leadership on Malaysian students' entrepreneurial behaviour. Entrepreneurial Business and Economics Review, 9(1), 89-103. https://doi.org/10.15678/EBER.2021.090106
• Green, T. (2016). A methodological review of structural equation modelling in higher education research. Studies in Higher Education, 41(12), 2125-2155. https://doi.org/10.1080/03075079.2015.1021670
• Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. (2010). Multivariate Data Analysis: Pearson Education. New Jersey: Upper Saddle River.
• Han, H., Yu, J., Chua, B. L., Lee, S., & Kim, W. (2019). Impact of core-product and service-encounter quality, attitude, image, trust and love on repurchase: Full-service vs low-cost carriers in South Korea. International Journal of Contemporary Hospitality Management, 31(4), 1588-1608. https://doi.org/10.1108/IJCHM-05-2018-0376
• Haque, A. ul, Sher, A., & Urbański, M. (2020). Is the role of authentic leadership effective in managing occupational stress and psychological capital?. Forum Scientiae Oeconomia, 8(2), 59-77. https://doi.org/10.23762/FSO_VOL8_NO2_4
• Hassan, Z. (2022). Employee retention through effective human resource management practices in Maldives: Mediation effects of compensation and rewards system. Journal of Entrepreneurship, Management and Innovation, 18(2), 137-173. https://doi.org/10.7341/20221825
• Hershberger, S. L. (2003). The growth of structural equation modeling: 1994-2001. Structural Equation Modeling, 10(1), 35-46. https://doi.org/10.1207/S15328007SEM1001_2
• Hirschmann, J., & Swoboda, B. (2017). Multilevel structural equation modelling in marketing and management research. Marketing: ZFP-Journal of Research and Management, 39(3), 50-75.
• Hoa, N. D., Thanh, V. B., Mai, V. T., Tung, L. V., & Quyen, H. V. T. (2020). Knowledge sharing influence on innovation: A case of textile and garment enterprises in Vietnam. The Journal of Asian Finance, Economics, and Business, 7(7), 555-563. https://doi.org/10.13106/jafeb.2020.vol7.no7.555
• Hosseini, S., Ivanov, D., & Dolgui, A. (2019). Review of quantitative methods for supply chain resilience analysis. Transportation Research Part E: Logistics and Transportation Review, 125, 285-307. https://doi.org/10.1016/j.tre.2019.03.001
• Ivanov, D., Dolgui, A., Sokolov, B., & Ivanova, M. (2017). Literature review on disruption recovery in the supply chain. International Journal of Production Research, 55(20), 6158-6174. https://doi.org/10.1080/00207543.2017.1330572
• Jiménez-Barreto, J., & Campo-Martínez, S. (2018). Destination website quality, users' attitudes and the willingness to participate in online co-creation experiences. European Journal of Management and Business Economics, 27(1), 26-41. https://doi.org/10.1108/EJMBE-11-2017-0048
• Keith, T. K. (2006). Multiple Regression and Beyond. London: Pearson.
• Khalid, B., Lis, M., Chaiyasoonthorn, W., Chaveesuk, S. (2021). Factors influencing behavioural intention to use MOOCs. Engineering Management in Production and Services, 13(2), 83-95. https://doi.org/10.2478/emj-2021-0014
• Klimontowicz, M., & Majewska, J. (2022). The contribution of intellectual capital to banks' competitive and financial performance: The evidence from Poland. Journal of Entrepreneurship, Management and Innovation, 18(2), 105-136. https://doi.org/10.7341/20221824
• Liamputtong, P. (2020). Qualitative Research Methods. Oxford: Oxford University Press.
• Liamputtong, P., & Ezzy, D. (2005). Qualitative Research Methods. Oxford: Oxford University Press.
• Loan, L., Doanh, D., Thang, H., Viet Ng, aN., Van, P., & Hoa, P. (2021). Entrepreneurial behaviour: The effects of the fear and anxiety of Covid-19 and business opportunity recognition. Entrepreneurial Business and Economics Review, 9(3), 7-23. https://doi.org/10.15678/EBER.2021.090301
• Martínez-López, F. J., Gázquez-Abad, J. C., & Sousa, C. M. (2013). Structural equation modelling in marketing and business research: Critical issues and practical recommendations. European Journal of Marketing, 47(1/2), 115-152. https://doi.org/10.1108/03090561311285484
• Mohajan, H. K. (2018). Qualitative research methodology in social sciences and related subjects. Journal of Economic Development, Environment and People, 7(1), 23-48.
• Molina-Azorin, J. F. (2016). Mixed methods research: An opportunity to improve our studies and our research skills. European Journal of Management And Business Economics, 25(2), 37-38.
• Mouhammed, A. H. (2015). Quantitative Methods for Business and Economics. New York: Routledge.
• Mueller, R. O., & Hancock, G. R. (2019). Structural Equation Modeling. New York: Routledge.
• Nardi, P. M. (2018). Doing Survey Research: A Guide to Quantitative Methods. New York: Routledge.
• Oakshott, L. (2020). Essential Quantitative Methods: For Business, Management And Finance. Basingstoke, UK: Macmillan Education.
• Paulino, E.E. (2022). Amplifying organizational performance from business intelligence: Business analytics implementation in the retail industry. Journal of Entrepreneurship, Management and Innovation, 18(2), 69-104. https://doi.org/10.7341/20221823
• Pini, M., & Tchorek, G. (2022). Comparative analysis of export determinants in Italian and Polish firms: The moderating role of non-family management. Journal of Entrepreneurship, Management and Innovation, 18(2), 41-67. https://doi.org/10.7341/20221822
• Rinjit, K. (2020). Research Methodology. Thousand Oaks: SAGE.
• Sánchez, A. D., Del Río, M. D. L. C., & García, J. Á. (2017). Bibliometric analysis of publications on wine tourism in the databases Scopus and WoS. European Research on Management and Business Economics, 23(1), 8-15. https://doi.org/10.1016/j.iedeen.2016.02.001
• Srikalimah, S., Wardana, L. W., Ambarwati, D., Sholihin, U., Shobirin, R. A., Fajariah, N., & Wibowo, A. (2020). Do creativity and intellectual capital matter for SMEs sustainability? The role of competitive advantage. The Journal of Asian Finance, Economics, and Business, 7(12), 397-408. https://doi.org/10.13106/jafeb.2020.vol7.no12.397
• Stadler, F. (Ed.). (2004). Induction and Deduction in the Sciences. Cham: Springer Science & Business Media.
• Staniec, I. (2018). Modelowanie równań strukturalnych w naukach o zarządzaniu. Organizacja i Kierowanie, 181(2), 65-77.
• Stockemer, D. (2019). Quantitative Methods for the Social Sciences. Cham: Springer International Publishing.
• Tan, R., & Antonio, F. (2022). New insights on employee adaptive performance during the COVID-19 pandemic: Empirical evidence from Indonesia. Journal of Entrepreneurship, Management, and Innovation, 18(2), 175-206. https://doi.org/10.7341/20221826
• Tarka, P. (2018). An overview of structural equation modeling: Its beginnings, historical development, usefulness and controversies in the social sciences. Quality & Quantity, 52(1), 313-354. https://doi.org/10.1007/s11135-017-0469-8
• Tarling, R. (2009). Statistical Modelling for Social Researchers: Principles and Practices. New York: Routledge.
• Tranfield, D., Denyer, D., & Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207-222. https://doi.org/10.1111/1467-8551.00375
• Wijaya, P., & Suasih, N. N. (2020). The effect of knowledge management on competitive advantage and business performance: A study of silver craft SMEs. Entrepreneurial Business and Economics Review, 8(4), 105-121. https://doi.org/10.15678/EBER.2020.080406
• Williams, L. J., Vandenberg, R. J., & Edwards, J. R. (2009). 12 structural equation modeling in management research: A guide for improved analysis. Academy of Management Annals, 3(1), 543-604. https://doi.org/10.5465/19416520903065683
• Wilson, L.A. (2019) Quantitative research. In P/ Liamputtong (Ed.), Handbook of Research Methods in Health Social Sciences (pp. 27-50). Cham: Springer.
• Xia, Y., & Yang, Y. (2019). RMSEA, CFI, and TLI in structural equation modeling with ordered categorical data: The story they tell depends on the estimation methods. Behavior Research Methods, 51(1), 409-428.https://doi.org/10.3758/s13428-018-1055-2
• Zakrzewska-Bielawska, A. (2021). Ambidextrous Strategy: Antecedents, Strategic Choices, and Performance. New York: Routledge.
• Zhang, M. F., Dawson, J. F., & Kline, R. B. (2021). Evaluating the use of covariance-based structural equation modelling with reflective measurement in organizational and management research: A review and recommendations for best practice. British Journal of Management, 32(2), 257-272. https://doi.org/10.1111/1467-8551.12415

Identyfikatory

DOI

https://doi.org/10.7341/20221821