Araştırma Makalesi
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Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi ile Bir Uygulama

Yıl 2023, Cilt: 24 Sayı: 3, 656 - 674, 04.12.2023
https://doi.org/10.17494/ogusbd.1301243

Öz

PLS algoritması ile kurulan Yapısal Eşitlik Modelleri, avantajlı ve kolaylaştırıcı yönleri ile sosyal bilimlerde artarak kullanılmaktadır. Sosyal bilimler araştırmacıları, PLS-YEM ile kurdukları araştırma modellerini SmartPLS başta olmak üzere birçok programda son kullanıcı olarak test etmektedirler. Ölçeklerin yapısı gereği, modellerde yer alan değişkenlerin büyük kısmı hiyerarşik çok boyutlu yapılardan oluşmaktadır. Bu çalışma, PLS-YEM kullanımında kullanıcının dikkat etmesi gereken noktalara dikkat çekmeyi amaçlamaktadır. Kontrol listesi ile bu yöntemin kullanımının kolaylaştırılması sağlanmaya çalışılmıştır. Ayrıca, ölçek yapısına göre hiyerarşik yapıların oluşturulması ve geçerlilik-güvenilirliğinin sağlanması gibi konularda üst-düzey yapı modelleme yaklaşımı için bir rehber sunulmuştur. Bu şekilde özellikle Türkçe literatürde rastlanmayan bir yol haritası ile hiyerarşik yapı modellemesinden yararlanacak gelecekteki araştırmalara uygulama, yorumlama ve raporlama konularında katkı sunulacağına inanılmaktadır.

Kaynakça

  • Ab Hamid, M. R., Sami, W. ve Sidek, M. M. (2017). Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion. Journal of Physics: Conference Series, 890(012163). https://doi.org/10.1088/1742-6596/890/1/012163
  • Astrachan, C. B., Patel, V. K. ve Wanzenried, G. (2014). A comparative study of CB-SEM and PLS-SEM for theory development in family firm research. Journal of family business strategy, 5(1), 116-128. https://doi.org/10.1016/j.jfbs.2013.12.002
  • Akter, S., D’Ambra, J. ve Ray, P. (2010). Service quality of mHealth platforms: development and validation of a hierarchical model using PLS. Electronic Markets, 20, 209-227. https://doi.org/10.1007/s12525-010-0043-x
  • Ali, F., Rasoolimanesh, S. M., Sarstedt, M., Ringle, C. M. ve Ryu, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30(1), 514-538. https://doi.org/10.1108/IJCHM-10-2016-0568
  • Aybek, G. ve Karakaş, H. (2022). Use The Silver Bullet on The Right Beast: A Guide on Usage of PLS-SEM in Tourism and Gastronomy Studies. Advances in Hospitality and Tourism Research (AHTR), 10(2), 327-336. https://doi.org/10.30519/ahtr.1097884
  • Aybek, G. ve Özdemir, B. (2022). Effects of ethnic restaurant experience on prospective tourist intentions: Mediating role of food image. Tourism Management Perspectives, 44, 101034. https://doi.org/10.1016/j.tmp.2022.101034
  • Barclay, D., Thompson, W. ve Higgins, C. (1995). The Partial Least Squares (PLS) approach to causal modeling: Personal computer use as an illustration. Technology Studies, 2(2), 285-309.
  • Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual differences, 42(5), 815-824. https://doi.org/10.1016/j.paid.2006.09.018
  • Bayat, B. (2014). Uygulamalı Sosyal Bilim Araştırmalarında Ölçme, Ölçekler Ve “Likert” Ölçek Kurma Tekniği. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(3), 1-24.
  • Becker, J. M., Klein, K. ve Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long range planning, 45(5-6), 359-394. https://doi.org/10.1016/j.lrp.2012.10.001
  • Becker, J. M., Cheah, J. H., Gholamzade, R., Ringle, C. M. ve Sarstedt, M. (2023). PLS-SEM’s most wanted guidance. International Journal of Contemporary Hospitality Management, 35(1), 321-346. https://doi.org/10.1108/IJCHM-04-2022-0474
  • Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. New York: Academic Press.
  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155
  • Coltman, T., Devinney, T. M., Midgley, D. F. ve Venaik, S. (2008). Formative versus reflective measurement models: Two applications of formative measurement. Journal of Business Research, 61(12), 1250-1262. https://doi.org/10.1016/j.jbusres.2008.01.013
  • Crocetta, C., Antonucci, L., Cataldo, R., Galasso, R., Grassia, M. G., Lauro, C. N. ve Marino, M. (2021). Higher-order PLS-PM approach for different types of constructs. Social Indicators Research, 154, 725-754. https://doi.org/10.1007/s11205-020-02563-w
  • Cronbach, L. J. ve Meehl, P. E. (1955). Construct validity in psychological tests. Psychological bulletin, 52(4), 281-302. https://doi.org/10.1037/h0040957
  • Dash, G. ve Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173, 121092. https://doi.org/10.1016/j.techfore.2021.121092
  • Diamantopoulos, A. ve Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British journal of management, 17(4), 263-282.https://doi.org/10.1111/j.1467-8551.2006.00500.x
  • do Valle, P. O. ve Assaker, G. (2016). Using partial least squares structural equation modeling in tourism research: A review of past research and recommendations for future applications. Journal of Travel Research, 55(6), 695-708. https://doi.org/10.1177/0047287515569779
  • Duarte, P. ve Amaro, S. (2018). Methods for modelling reflective-formative second order constructs in PLS: An application to online travel shopping. Journal of Hospitality and Tourism Technology, 9(3), 295-313. https://doi.org/10.1108/JHTT-09-2017-0092
  • Gaskin, J., Godfrey, S. ve Vance, A. (2018). Successful system use: It’s not just who you are, but what you do. AIS Transactions on Human-Computer Interaction, 10(2), 57-81. https://doi.org/10.17705/1thci.00104
  • Gontur, S., Gadi, P. D. ve Bagobiri, E. (2022). The moderating effect of positive word-of-mouth between service quality and customer loyalty in the hospitality sector: A PLS-SEM approach. Journal of Economics and Management, 44(1), 266-285. https://doi.org/10.22367/jem.2022.44.11
  • Hagger, M. S., Gucciardi, D. F. ve Chatzisarantis, N. L. (2017). On nomological validity and auxiliary assumptions: The importance of simultaneously testing effects in social cognitive theories applied to health behavior and some guidelines. Frontiers in psychology, 8, 1933. https://doi.org/10.3389/fpsyg.2017.01933
  • Hair, J. F., Ringle, C. M. ve Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202
  • Hair, J., Hollingsworth, C. L., Randolph, A. B. ve Chong, A. Y. L. (2017a). An updated and expanded assessment of PLS-SEM in information systems research. Industrial management & data systems, 117(3), 442-458. https://doi.org/10.1108/IMDS-04-2016-0130
  • Hair, J., Tomas, G., Hult, M., Ringle, C.M. ve Sarstedt., M. (2017b). A primer on partial least squares structural equation modeling. Los Angeles:Sage.
  • Hair, J. F., Matthews, L. M., Matthews, R. L. ve Sarstedt, M. (2017c). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123. https://doi.org/10.1504/IJMDA.2017.087624
  • Hair, J. F., Risher, J.J., Sarstedt, M. ve Ringle, M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  • Henseler, J., Ringle, C.M. ve Sinkovics, R.R. (2009), “The use of partial least squares path modeling in international marketing”, Sinkovics, R.R. and Ghauri, P.N. (Ed.) New Challenges to International Marketing (Advances in International Marketing, Vol. 20), Emerald Group Publishing Limited, Bingley, pp. 277-319. https://doi.org/10.1108/S1474-7979(2009)0000020014
  • Hu, L. T. ve Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods, 3(4), 424-453. https://doi.org/10.1037/1082-989X.3.4.424
  • Kock, N. ve Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information systems journal, 28(1), 227-261. https://doi.org/https://doi.org/10.1111/isj.12131
  • Liu, L., Li, C. ve Zhu, D. (2012). A new approach to testing nomological validity and its application to a second-order measurement model of trust. Journal of the Association for Information Systems, 13(12), 950-975. https://doi.org/10.17705/1jais.00320
  • Magno, F., Cassia, F. ve Ringle, C. M. (2022). A brief review of partial least squares structural equation modeling (PLS-SEM) use in quality management studies. The TQM Journal. https://doi.org/10.1108/TQM-06-2022-0197
  • Marcoulides, G. A. ve Saunders, C. (2006). Editor's comments: PLS: a silver bullet?. MIS quarterly, 30(2), iii-ix. https://doi.org/10.2307/25148727
  • Mateos-Aparicio, G. (2011). Partial least squares (PLS) methods: Origins, evolution, and application to social sciences. Communications in Statistics-Theory and Methods, 40(13), 2305-2317. https://doi.org/10.1080/03610921003778225
  • Matthews, L., Hair, J. O. E. ve Matthews, R. (2018). PLS-SEM: The Holy Grail for Advanced Analysis. The Marketing Management Journal, 28(1), 1-13.
  • Ngoc Ton, H. N., Shumshunnahar, M., Nhat Tu, T. N. ve Nguyen, P. T. (2023). Revisiting social capital and knowledge sharing processes in tertiary education: Vietnamese and Bangladeshi students as target populations. Cogent Social Sciences, 9(1), 2186579. https://doi.org/10.1080/23311886.2023.2186579
  • Paxton, P., Curran, P. J., Bollen, K. A., Kirby, J. ve Chen, F. (2001). Monte Carlo experiments: Design and implementation. Structural Equation Modeling, 8(2), 287-312. https://doi.org/10.1207/S15328007SEM0802_7
  • Peng, D. X. ve Lai, F. (2012). Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of operations management, 30(6), 467-480. https://doi.org/10.1016/j.jom.2012.06.002
  • Rasoolimanesh, S. M. (2022). Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach. Data Analysis Perspectives Journal, 3(2), 1-8.
  • Rigdon, E. E., Sarstedt, M. ve Ringle, C. M. (2017). On comparing results from CB-SEM and PLS-SEM: Five perspectives and five recommendations. Marketing: ZFP–Journal of Research and Management, 39(3), 4-16.
  • Salgado, J. F. (2017). Bandwidth-fidelity dilemma. Encyclopedia of personality and individual differences, 1-4. https://doi.org/10.1007/978-3-319-28099-8_1280-1
  • Sarstedt, M., Ringle, C.M., Smith,D., Reams, R. ve Hair J.F. (2014). Partial Least Squares Structural Equation Modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105-115. https://doi.org/10.1016/j.jfbs.2014.01.002
  • Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O. ve Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies!. Journal of business research, 69(10), 3998-4010. https://doi.org/10.1016/j.jbusres.2016.06.007
  • Sarstedt, M. (2019). Der Knacks and a Silver Bullet. In: Babin, B.J., Sarstedt, M. (eds) The Great Facilitator (s. 155-164). Springer. https://doi.org/10.1007/978-3-030-06031-2_19
  • Sarstedt, M., Hair Jr, J. F., Cheah, J. H., Becker, J. M. ve Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian marketing journal, 27(3), 197-211. https://doi.org/10.1016/j.ausmj.2019.05.003
  • Schuberth, F., Rademaker, M. E. ve Henseler, J. (2020). Estimating and assessing second-order constructs using PLS-PM: the case of composites of composites. Industrial Management & Data Systems, 120(12), 2211-2241. https://doi.org/10.1108/IMDS-12-2019-0642
  • SmartPLS. (2023, 11 Mart). Model Fit. SmartPLS. https://www.smartpls.com/documentation/algorithms-and-techniques/model-fit/
  • Sosik, J. J., Kahai, S. S. ve Piovoso, M. J. (2009). Silver bullet or voodoo statistics? A primer for using the partial least squares data analytic technique in group and organization research. Group & Organization Management, 34(1), 5-36. https://doi.org/10.1177/1059601108329198
  • Tenenhaus, M., Amato, S. ve Esposito Vinzi, V. (2004). A global goodness-of-fit index for PLS structural equation modelling. In Proceedings of the XLII SIS scientific meeting, 1(2), 739-742.
  • van Riel, A. C., Henseler, J., Kemény, I. ve Sasovova, Z. (2017). Estimating hierarchical constructs using consistent partial least squares: The case of second-order composites of common factors. Industrial management & data systems, 117(3), 459-477. https://doi.org/10.1108/IMDS-07-2016-0286
  • Wetzels, M., Odekerken-Schröder, G. ve Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 3(1), 177-195. https://doi.org/10.2307/20650284

Pls-Sem Guide for Social Sciences: An Application with Hierarchical Component Modelling

Yıl 2023, Cilt: 24 Sayı: 3, 656 - 674, 04.12.2023
https://doi.org/10.17494/ogusbd.1301243

Öz

PLS based Structural Equation Models are widens in usage thanks to their expedient and facilitator aspects. Social scientists test their models with PLS-SEM with many programs which are led by SmartPLS. Accordingly with structures of scales, most of the models consists hierarchical multi-dimensional variables. The current paper aims to indicate critical points to be considered while using PLS-SEM. The given checklist offers a list for requirements of convenient usage of PLS-SEM. Additionally, this study guides researchers to build hierarchical structures and to grant their validity & reliability. This knowledge fills the blank which is needed in the Turkish literature with a rare application of the higher-order constructing process. The contribution of this paper includes usage, interpratetion, and reporting issues for end-users.

Kaynakça

  • Ab Hamid, M. R., Sami, W. ve Sidek, M. M. (2017). Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion. Journal of Physics: Conference Series, 890(012163). https://doi.org/10.1088/1742-6596/890/1/012163
  • Astrachan, C. B., Patel, V. K. ve Wanzenried, G. (2014). A comparative study of CB-SEM and PLS-SEM for theory development in family firm research. Journal of family business strategy, 5(1), 116-128. https://doi.org/10.1016/j.jfbs.2013.12.002
  • Akter, S., D’Ambra, J. ve Ray, P. (2010). Service quality of mHealth platforms: development and validation of a hierarchical model using PLS. Electronic Markets, 20, 209-227. https://doi.org/10.1007/s12525-010-0043-x
  • Ali, F., Rasoolimanesh, S. M., Sarstedt, M., Ringle, C. M. ve Ryu, K. (2018). An assessment of the use of partial least squares structural equation modeling (PLS-SEM) in hospitality research. International Journal of Contemporary Hospitality Management, 30(1), 514-538. https://doi.org/10.1108/IJCHM-10-2016-0568
  • Aybek, G. ve Karakaş, H. (2022). Use The Silver Bullet on The Right Beast: A Guide on Usage of PLS-SEM in Tourism and Gastronomy Studies. Advances in Hospitality and Tourism Research (AHTR), 10(2), 327-336. https://doi.org/10.30519/ahtr.1097884
  • Aybek, G. ve Özdemir, B. (2022). Effects of ethnic restaurant experience on prospective tourist intentions: Mediating role of food image. Tourism Management Perspectives, 44, 101034. https://doi.org/10.1016/j.tmp.2022.101034
  • Barclay, D., Thompson, W. ve Higgins, C. (1995). The Partial Least Squares (PLS) approach to causal modeling: Personal computer use as an illustration. Technology Studies, 2(2), 285-309.
  • Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and Individual differences, 42(5), 815-824. https://doi.org/10.1016/j.paid.2006.09.018
  • Bayat, B. (2014). Uygulamalı Sosyal Bilim Araştırmalarında Ölçme, Ölçekler Ve “Likert” Ölçek Kurma Tekniği. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(3), 1-24.
  • Becker, J. M., Klein, K. ve Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long range planning, 45(5-6), 359-394. https://doi.org/10.1016/j.lrp.2012.10.001
  • Becker, J. M., Cheah, J. H., Gholamzade, R., Ringle, C. M. ve Sarstedt, M. (2023). PLS-SEM’s most wanted guidance. International Journal of Contemporary Hospitality Management, 35(1), 321-346. https://doi.org/10.1108/IJCHM-04-2022-0474
  • Cohen, J. (1988). Statistical Power Analysis for the Behavioral Sciences. New York: Academic Press.
  • Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159. https://doi.org/10.1037/0033-2909.112.1.155
  • Coltman, T., Devinney, T. M., Midgley, D. F. ve Venaik, S. (2008). Formative versus reflective measurement models: Two applications of formative measurement. Journal of Business Research, 61(12), 1250-1262. https://doi.org/10.1016/j.jbusres.2008.01.013
  • Crocetta, C., Antonucci, L., Cataldo, R., Galasso, R., Grassia, M. G., Lauro, C. N. ve Marino, M. (2021). Higher-order PLS-PM approach for different types of constructs. Social Indicators Research, 154, 725-754. https://doi.org/10.1007/s11205-020-02563-w
  • Cronbach, L. J. ve Meehl, P. E. (1955). Construct validity in psychological tests. Psychological bulletin, 52(4), 281-302. https://doi.org/10.1037/h0040957
  • Dash, G. ve Paul, J. (2021). CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting. Technological Forecasting and Social Change, 173, 121092. https://doi.org/10.1016/j.techfore.2021.121092
  • Diamantopoulos, A. ve Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: A comparison and empirical illustration. British journal of management, 17(4), 263-282.https://doi.org/10.1111/j.1467-8551.2006.00500.x
  • do Valle, P. O. ve Assaker, G. (2016). Using partial least squares structural equation modeling in tourism research: A review of past research and recommendations for future applications. Journal of Travel Research, 55(6), 695-708. https://doi.org/10.1177/0047287515569779
  • Duarte, P. ve Amaro, S. (2018). Methods for modelling reflective-formative second order constructs in PLS: An application to online travel shopping. Journal of Hospitality and Tourism Technology, 9(3), 295-313. https://doi.org/10.1108/JHTT-09-2017-0092
  • Gaskin, J., Godfrey, S. ve Vance, A. (2018). Successful system use: It’s not just who you are, but what you do. AIS Transactions on Human-Computer Interaction, 10(2), 57-81. https://doi.org/10.17705/1thci.00104
  • Gontur, S., Gadi, P. D. ve Bagobiri, E. (2022). The moderating effect of positive word-of-mouth between service quality and customer loyalty in the hospitality sector: A PLS-SEM approach. Journal of Economics and Management, 44(1), 266-285. https://doi.org/10.22367/jem.2022.44.11
  • Hagger, M. S., Gucciardi, D. F. ve Chatzisarantis, N. L. (2017). On nomological validity and auxiliary assumptions: The importance of simultaneously testing effects in social cognitive theories applied to health behavior and some guidelines. Frontiers in psychology, 8, 1933. https://doi.org/10.3389/fpsyg.2017.01933
  • Hair, J. F., Ringle, C. M. ve Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing theory and Practice, 19(2), 139-152. https://doi.org/10.2753/MTP1069-6679190202
  • Hair, J., Hollingsworth, C. L., Randolph, A. B. ve Chong, A. Y. L. (2017a). An updated and expanded assessment of PLS-SEM in information systems research. Industrial management & data systems, 117(3), 442-458. https://doi.org/10.1108/IMDS-04-2016-0130
  • Hair, J., Tomas, G., Hult, M., Ringle, C.M. ve Sarstedt., M. (2017b). A primer on partial least squares structural equation modeling. Los Angeles:Sage.
  • Hair, J. F., Matthews, L. M., Matthews, R. L. ve Sarstedt, M. (2017c). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107-123. https://doi.org/10.1504/IJMDA.2017.087624
  • Hair, J. F., Risher, J.J., Sarstedt, M. ve Ringle, M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
  • Henseler, J., Ringle, C.M. ve Sinkovics, R.R. (2009), “The use of partial least squares path modeling in international marketing”, Sinkovics, R.R. and Ghauri, P.N. (Ed.) New Challenges to International Marketing (Advances in International Marketing, Vol. 20), Emerald Group Publishing Limited, Bingley, pp. 277-319. https://doi.org/10.1108/S1474-7979(2009)0000020014
  • Hu, L. T. ve Bentler, P. M. (1998). Fit indices in covariance structure modeling: Sensitivity to underparameterized model misspecification. Psychological methods, 3(4), 424-453. https://doi.org/10.1037/1082-989X.3.4.424
  • Kock, N. ve Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information systems journal, 28(1), 227-261. https://doi.org/https://doi.org/10.1111/isj.12131
  • Liu, L., Li, C. ve Zhu, D. (2012). A new approach to testing nomological validity and its application to a second-order measurement model of trust. Journal of the Association for Information Systems, 13(12), 950-975. https://doi.org/10.17705/1jais.00320
  • Magno, F., Cassia, F. ve Ringle, C. M. (2022). A brief review of partial least squares structural equation modeling (PLS-SEM) use in quality management studies. The TQM Journal. https://doi.org/10.1108/TQM-06-2022-0197
  • Marcoulides, G. A. ve Saunders, C. (2006). Editor's comments: PLS: a silver bullet?. MIS quarterly, 30(2), iii-ix. https://doi.org/10.2307/25148727
  • Mateos-Aparicio, G. (2011). Partial least squares (PLS) methods: Origins, evolution, and application to social sciences. Communications in Statistics-Theory and Methods, 40(13), 2305-2317. https://doi.org/10.1080/03610921003778225
  • Matthews, L., Hair, J. O. E. ve Matthews, R. (2018). PLS-SEM: The Holy Grail for Advanced Analysis. The Marketing Management Journal, 28(1), 1-13.
  • Ngoc Ton, H. N., Shumshunnahar, M., Nhat Tu, T. N. ve Nguyen, P. T. (2023). Revisiting social capital and knowledge sharing processes in tertiary education: Vietnamese and Bangladeshi students as target populations. Cogent Social Sciences, 9(1), 2186579. https://doi.org/10.1080/23311886.2023.2186579
  • Paxton, P., Curran, P. J., Bollen, K. A., Kirby, J. ve Chen, F. (2001). Monte Carlo experiments: Design and implementation. Structural Equation Modeling, 8(2), 287-312. https://doi.org/10.1207/S15328007SEM0802_7
  • Peng, D. X. ve Lai, F. (2012). Using partial least squares in operations management research: A practical guideline and summary of past research. Journal of operations management, 30(6), 467-480. https://doi.org/10.1016/j.jom.2012.06.002
  • Rasoolimanesh, S. M. (2022). Discriminant validity assessment in PLS-SEM: A comprehensive composite-based approach. Data Analysis Perspectives Journal, 3(2), 1-8.
  • Rigdon, E. E., Sarstedt, M. ve Ringle, C. M. (2017). On comparing results from CB-SEM and PLS-SEM: Five perspectives and five recommendations. Marketing: ZFP–Journal of Research and Management, 39(3), 4-16.
  • Salgado, J. F. (2017). Bandwidth-fidelity dilemma. Encyclopedia of personality and individual differences, 1-4. https://doi.org/10.1007/978-3-319-28099-8_1280-1
  • Sarstedt, M., Ringle, C.M., Smith,D., Reams, R. ve Hair J.F. (2014). Partial Least Squares Structural Equation Modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1), 105-115. https://doi.org/10.1016/j.jfbs.2014.01.002
  • Sarstedt, M., Hair, J. F., Ringle, C. M., Thiele, K. O. ve Gudergan, S. P. (2016). Estimation issues with PLS and CBSEM: Where the bias lies!. Journal of business research, 69(10), 3998-4010. https://doi.org/10.1016/j.jbusres.2016.06.007
  • Sarstedt, M. (2019). Der Knacks and a Silver Bullet. In: Babin, B.J., Sarstedt, M. (eds) The Great Facilitator (s. 155-164). Springer. https://doi.org/10.1007/978-3-030-06031-2_19
  • Sarstedt, M., Hair Jr, J. F., Cheah, J. H., Becker, J. M. ve Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian marketing journal, 27(3), 197-211. https://doi.org/10.1016/j.ausmj.2019.05.003
  • Schuberth, F., Rademaker, M. E. ve Henseler, J. (2020). Estimating and assessing second-order constructs using PLS-PM: the case of composites of composites. Industrial Management & Data Systems, 120(12), 2211-2241. https://doi.org/10.1108/IMDS-12-2019-0642
  • SmartPLS. (2023, 11 Mart). Model Fit. SmartPLS. https://www.smartpls.com/documentation/algorithms-and-techniques/model-fit/
  • Sosik, J. J., Kahai, S. S. ve Piovoso, M. J. (2009). Silver bullet or voodoo statistics? A primer for using the partial least squares data analytic technique in group and organization research. Group & Organization Management, 34(1), 5-36. https://doi.org/10.1177/1059601108329198
  • Tenenhaus, M., Amato, S. ve Esposito Vinzi, V. (2004). A global goodness-of-fit index for PLS structural equation modelling. In Proceedings of the XLII SIS scientific meeting, 1(2), 739-742.
  • van Riel, A. C., Henseler, J., Kemény, I. ve Sasovova, Z. (2017). Estimating hierarchical constructs using consistent partial least squares: The case of second-order composites of common factors. Industrial management & data systems, 117(3), 459-477. https://doi.org/10.1108/IMDS-07-2016-0286
  • Wetzels, M., Odekerken-Schröder, G. ve Van Oppen, C. (2009). Using PLS path modeling for assessing hierarchical construct models: Guidelines and empirical illustration. MIS quarterly, 3(1), 177-195. https://doi.org/10.2307/20650284
Toplam 52 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Sosyolojik Metodoloji ve Araştırma Yöntemleri
Bölüm Makaleler
Yazarlar

Gürkan Aybek 0000-0002-5536-5440

Hatice Karakaş 0000-0001-5893-1199

Erken Görünüm Tarihi 18 Ekim 2023
Yayımlanma Tarihi 4 Aralık 2023
Gönderilme Tarihi 24 Mayıs 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 24 Sayı: 3

Kaynak Göster

APA Aybek, G., & Karakaş, H. (2023). Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi ile Bir Uygulama. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, 24(3), 656-674. https://doi.org/10.17494/ogusbd.1301243
AMA Aybek G, Karakaş H. Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi ile Bir Uygulama. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi. Aralık 2023;24(3):656-674. doi:10.17494/ogusbd.1301243
Chicago Aybek, Gürkan, ve Hatice Karakaş. “Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi Ile Bir Uygulama”. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi 24, sy. 3 (Aralık 2023): 656-74. https://doi.org/10.17494/ogusbd.1301243.
EndNote Aybek G, Karakaş H (01 Aralık 2023) Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi ile Bir Uygulama. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi 24 3 656–674.
IEEE G. Aybek ve H. Karakaş, “Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi ile Bir Uygulama”, Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, c. 24, sy. 3, ss. 656–674, 2023, doi: 10.17494/ogusbd.1301243.
ISNAD Aybek, Gürkan - Karakaş, Hatice. “Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi Ile Bir Uygulama”. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi 24/3 (Aralık 2023), 656-674. https://doi.org/10.17494/ogusbd.1301243.
JAMA Aybek G, Karakaş H. Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi ile Bir Uygulama. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi. 2023;24:656–674.
MLA Aybek, Gürkan ve Hatice Karakaş. “Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi Ile Bir Uygulama”. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi, c. 24, sy. 3, 2023, ss. 656-74, doi:10.17494/ogusbd.1301243.
Vancouver Aybek G, Karakaş H. Sosyal Bilimlerde PLS-YEM Kullanım Rehberi: Hiyerarşik Yapı Modellemesi ile Bir Uygulama. Eskişehir Osmangazi Üniversitesi Sosyal Bilimler Dergisi. 2023;24(3):656-74.