(Consistent) PLS-SEM vs. CB-SEM in Mobile Shopping
Yıl 2023,
Cilt: 10 Sayı: 2, 649 - 667, 25.10.2023
Oğuz Yıldız
,
Alpaslan Kelleci
Öz
This paper seeks to examine and compare the regular and consistent PLS-SEM and CB-SEM by employing the augmented TAM, which stands as a proportionately complicated model. The present paper presents the pros and cons of each method and guides researchers and academics concerning which particular method is the most appropriate to employ in their studies. The findings of this paper are twofold: (1) performing CB-SEM and consistent PLS-SEM for reflectively structured models would have more robust outputs and would be more appropriate and beneficial in lieu of executing regular PLS-SEM; (2) consistent PLS-SEM has softer provisions since it does not necessitate a two-step analysis, high sampling sizes and normal distribution requirements, thus performing consistent PLS-SEM appears more viable and practical for researchers.
Kaynakça
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- AJZEN, I. and FISHBEIN, M. (1980) Understanding Attitudes and Predicting Social Behavior, New Jersey Prentice-Hall Inc., USA.
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- BOLLEN, K. A. (1989). Structural equations with latent variables. New York: Wiley.
- CARLSON, J., RAHMAN, M. M., TAYLOR, A., & VOOLA, R. (2017). Feel the VIBE: Examining value-in-the-brand-page-experience and its impact on satisfaction and customer engagement behaviours in mobile social media. Journal of Retailing and Consumer Services, 46, 149-162.
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- CHEAH, J-H., MEMON, M.A., CHUAH, F., Ting, H., & RAMAYAH, T., (2018). Assessing Reflective
Models in Marketing Research: A Comparison Between Pls And Plsc Estimates International Journal of Business and Society, 19(1): 139-160.
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Mobil Alışveriş Düzleminde Consistent PLS-SEM ve CB-SEM Yöntemlerinin Karşılaştırılması
Yıl 2023,
Cilt: 10 Sayı: 2, 649 - 667, 25.10.2023
Oğuz Yıldız
,
Alpaslan Kelleci
Öz
Araştırma, nispeten karmaşık bir model olan artırılmış Teknoloji Kabul Modelini kullanarak geleneksel ve tutarlı PLS-SEM ile CB-SEM yöntemlerini incelemeyi ve karşılaştırmayı amaçlamaktadır. Araştırmada, her yöntemin avantajları ve dezavantajları ortaya konmakta böylelikle araştırmacılara ve uzmanlara çalışmalarında hangi yöntemin kullanımının uygun olduğu konusunda rehberlik etmektedir. Çalışmanın bulguları ikiye ayrılmaktadır. ilk olarak çalışma, reflektif olarak yapılandırılmış modellerde geleneksel PLS-SEM yöntemini tercih etmek yerine CB-SEM veya consistent PLS-SEM yöntemlerini kullanmanın daha sağlam sonuçlar sağladığına işaret etmektedir. İkincisi ise CB-SEM yönteminin aksine consistent PLS-SEM yönteminin, iki aşamalı analiz, yüksek örneklem hacmi ve normal dağılım şartları gibi katı koşullar gerektirmemesi araştırmacılar için daha elverişli bir yöntem olduğunu göstermektedir.
Kaynakça
- AGREBI, S. and JALLAIS, J. (2015). Explain the intention to use smartphones for mobile shopping, Journal of Retailing and Consumer Services, Vol. 22, No. 1, pp.16–23.
- AJZEN. I. (1991). The theory of planned behavior, Organizational Behavior and Human Decision Processes, (50,2),179–211.
- AJZEN, I. and FISHBEIN, M. (1980) Understanding Attitudes and Predicting Social Behavior, New Jersey Prentice-Hall Inc., USA.
- ALAM, M.Z., HU, W., HOQUE, M.R. and KAIUM, M.A. (2019), "Adoption intention and usage behavior of mHealth services in Bangladesh and China: A cross-country analysis", International Journal of Pharmaceutical and Healthcare Marketing, 14(1), 37-60.
- ALZUBI, M.M., AL-DUBAI, M.M., FAREA, M.M., (2018). Using the technology acceptance model in understanding citizens’ behavioural intention to use m-marketing among Jordanian citizen, Journal of Business and Retail Management Research; London, (12)2, 224-231.
- AMEEN, N., SHAH, M.H., SIMS, J., CHOUDRIE, J., WILLIS, R., (2020). Are there peas in a pod when considering mobile phone and mobile applications use: A quantitative study, Journal of Retailing and Consumer Services, 55(July), 969-989.
- ANTONAKIS, J., BENDAHAN, S., JACQUART, P., & LALIVE, R. (2010). On Making Causal Claims: A Review and Recommendations. The Leadership Quarterly, 21(6), 1086–1120.
- BAKARE, A. S., OWUSU, A., & ABDURRAHAMAN, D. T. (2017). The behavior response of the Nigerian youths toward mobile advertising: An examination of the influence of values, attitudes and culture, Cogent Business & Management, 4(1), 1-18.
- BARCLAY, D. W., HIGGINS, C. A., & THOMPSON, R. (1995). The partial least squares approach to causal modeling: Personal computer adoption and use as illustration. Technology Studies, 2, 285–309.
- BOLLEN, K. A. (1989). Structural equations with latent variables. New York: Wiley.
- CARLSON, J., RAHMAN, M. M., TAYLOR, A., & VOOLA, R. (2017). Feel the VIBE: Examining value-in-the-brand-page-experience and its impact on satisfaction and customer engagement behaviours in mobile social media. Journal of Retailing and Consumer Services, 46, 149-162.
- CELIK, H., KOCAMAN, R, (2017). Roles of self-monitoring, fashion involvement and technology readiness in an individual's propensity to use mobile shopping, Journal of Systems and Information Technology, 19(3/4), 166-182.
- CHEAH, J-H., MEMON, M.A., CHUAH, F., Ting, H., & RAMAYAH, T., (2018). Assessing Reflective
Models in Marketing Research: A Comparison Between Pls And Plsc Estimates International Journal of Business and Society, 19(1): 139-160.
- CHEN, H.-J. (2018). What drives consumers’ mobile shopping? 4Ps or shopping preferences? Asia Pacific Journal of Marketing and Logistics, 30(4), 797-815.
- CHEN, C. and TSAI, J. (2019) ‘Determinants of behavioral intention to use the personalized location-based mobile tourism application: an empirical study by integrating TAM with ISSM’, Future Generation Computer Systems, 96, 628–638.
- CHIN, W.W. (1998) ‘The partial least squares approach to structural equation modeling’, in Marcoulides, G.A. (Ed.): Modern Methods for Business Research, pp.295–358, Erlbaum, Mahwah.
- DAKDUK, S., SANTALLA-BANDERALI, Z., & Siqueira, J. R. (2020). Acceptance of mobile commerce in low-income consumers: evidence from an emerging economy. Heliyon, 6(11), 1-15.
- DAVIS, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly,13(3), 319–340.
- DAVIS, F.D., BAGOZZI, R.P. & WARSHAW, P.R. (1989) ‘User acceptance of computer technology: a comparison of two theoretical models’, The Institute of Management Science, (35,8), 982–1002.
- DIJKSTRA T.K. & HENSELER, J. (2015a). Consistent and asymptotically normal PLS estimators for linear structural equations, Computational Statistics & Data Analysis, 81(1),10–23.
- DIJKSTRA T.K. and HENSELER, J. (2015b). Consistent partial least squares path modeling, MIS Quarterly, 39(2),297–316.
- DUARTE, P.A.O., RAPOSO, M.L.B. (2010). A PLS Model to Study Brand Preference: An Application to the Mobile Phone Market, in: V. Esposito Vinzi, W. W. Chin, J. Henseler, H. Wang (Ed.). Handbook of partial least squares: Concepts, methods, and applications Heidelberg/Dordrecht/London/New York: Springer, (pp.449-485).
- ENEIZAN, B., MOHAMMED, A.G., ALNOOR, A., ALABBOODI, A.S., and ENAIZAN, O. (2019). Customer acceptance of mobile marketing in Jordan: An extended UTAUT2 model with trust and risk factors, International Journal of Engineering Business Management, 11, 1–10
- FAQIH, K. M. S., & JARADAT, M.-I. R. M. (2015). Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective. Journal of Retailing and Consumer Services, 22, 37–52.
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