Araştırma Makalesi
BibTex RIS Kaynak Göster

(Consistent) PLS-SEM vs. CB-SEM in Mobile Shopping

Yıl 2023, Cilt: 10 Sayı: 2, 649 - 667, 25.10.2023
https://doi.org/10.17336/igusbd.1014138

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

  • 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.
  • GASKIN, J. (2016). MasterValidity, Gaskination's Statistics. http://statwiki.kolobkreations.com
  • GASKIN, J. (2017). Common Method Bias (CMB) in PLS (partial least squares), Gaskination's Statistics. http://youtube.com/Gaskination
  • GHAZALI, E. M., MUTUM, D. S., CHONG, J. H., & NGUYEN, B. (2018). Do consumers want mobile commerce? A closer look at M-shopping and technology adoption in Malaysia. Asia Pacific Journal of Marketing and Logistics, 30(4), 1064-1086.
  • GEFEN, D., STRAUB, D. W., & RIGDON, E.E. (2011). An Update and Extension to SEM Guidelines for Administrative and Social Science Research, MIS Quarterly (35:2), pp. iii-xiv.
  • GOH, M. L., ANG, H. C. TAN, S. H., OUN, W. L. ()2020. Examining the Determinants of Consumer Purchase Intention towards Mobile Advertising, Global Business and Management Research; Boca Raton, 12(2), 89-103.
  • GONG, X., LIU, Z., ZHENG, X., & WU, T. (2018). Why are experienced users of WeChat likely to continue using the app? Asia Pacific Journal of Marketing and Logistics, 30(4), 1013-1039
  • GROß, M. (2014) ‘Exploring the acceptance of technology for mobile shopping: an empirical investigation among smartphone users’, The International Review of Retail, Distribution and Consumer Research, 25(3), 215–235.
  • GROß, M. (2016). Impediments to mobile shopping continued usage intention: A trust-risk-relationship. Journal of Retailing and Consumer Services, 33, 109–119.
  • GUPTA, K. and ARORA, N. (2019), "Investigating consumer intention to accept mobile payment systems through unified theory of acceptance model: An Indian perspective", South Asian Journal of Business Studies, Vol. 9 No. 1, pp. 88-114.
  • GUPTA, A., DOGRA, N., & GEORGE, B. (2018). What determines tourist adoption of smartphone apps? Journal of Hospitality and Tourism Technology, 9(1), 50–64.
  • HAIR, J. F., BLACK, W. C., BABIN, B. J., & ANDERSON, R. E. (2010). Multivariate data analysis (7th ed.). NJ: Prentice Hall
  • HAIR, J. F., RINGLE, C. M., & SARSTEDT, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 18(2), 139–152
  • HAIR, J.F., HULT, G.T.M., RINGLE, C.M. & SARSTEDT, M. (2014), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Sage, Thousand Oaks.
  • HAIR, J., HOLLINGSWORTH, C.L., RANDOLPH, A.B. & CHONG, A.Y.L. (2017). An updated and expanded assessment of PLS-SEM in information systems research, Industrial Management & Data Systems, 117(3),442-458
  • HARIGUNA, T., ADIANDARI, A.M. and RUANGKANJANASES, A. (2020), "Assessing customer intention use of mobile money application and the antecedent of perceived value, economic trust and service trust", International Journal of Web Information Systems, Vol. 16 No. 3, pp. 331-345.
  • HENSELER, J., RINGLE, C.M., RUDOLF R. & SINKOVICS, R.R. (2009), “The Use of Partial Least Squares Path Modeling in International Marketing,” Advances in International Marketing, vol. 20, Rudolf R. Sinkovics and Pervez N. Ghauri, eds., Bingley, UK: Emerald Group, 277–320.
  • HENSELER, J., DIJKSTRA, T. K., SARSTEDT, M., RINGLE, C. M., DIAMANTOPOULOS, A., STRAUB, D. W., ...CALANTONE, R. J. (2014). Common beliefs and reality about partial least squares: Comments on Rönkkö & Evermann (2013). Organizational Research Methods, 17(2),182–209.
  • HENSELER, J., RINGLE, C.M. & SARSTEDT, M. (2015) ‘A new criterion for assessing discriminant validity in variance-based structural equation modeling’, Journal of the Academy of Marketing Science, 43(1), 115–135.
  • HONG, H., MUKUN, C., WANG, G. A., (2017) THE EFFECTS OF NETWORK EXTERNALITIES AND HERDING ON USER SATISFACTION WITH MOBILE SOCIAL APPS, Journal of Electronic Commerce Research, 18(1), 18-31.
  • HSIEH, S. H., & LEE, C. T. (2020). Traces of mobility: Examining location disclosure on social networks with mobile location tagging. Telematics and Informatics, 49, 1-14.
  • INFORMATION AND COMMUNICATION TECHNOLOGIES AUTHORITY ICTA Quarterly Market Report) (2020) Electronic Communications Market in Turkey Market Data (2020 Q2) [online] https://www.btk.gov.tr/uploads/pages/pazar-verileri/turkiye-haberlesme-raporu-002.pdf (accessed 19 Jan 2021).
  • JIMENEZ, N., SAN-MARTIN, S., & PUENTE, N. (2018). The path to mobile shopping compatibility. The Journal of High Technology Management Research, 30(1), 1-12.
  • KLINE, R.B. (2016). Principles and Practice of Structural Equation Modeling, Fourth Edition, NY: The Guilford Press.
  • KUO T., HUANG, K., NGUYEN Q.T., NGUYEN, P.H. (2019). Adoption of mobile applications for identifying tourism destinations by travellers: an integrative approach, Journal of Business Economics and Management,20(5),860–877
  • KOCK, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10.
  • LEE, E.-B., LEE, S.-G., & YANG, C.-G. (2017). The influences of advertisement attitude and brand attitude on purchase intention of smartphone advertising. Industrial Management & Data Systems, 117(6), 1011–1036.
  • LEE, C. T., & HSIEH, S. H. (2019). Engaging consumers in mobile instant messaging: the role of cute branded emoticons. Journal of Product & Brand Management, 28(7), 849–863.
  • LEI, P. W., & WU, Q. (2007). Introduction to structural equation modeling: Issues and practical considerations. Educational Measurement: Issues and Practices, 26(3),33–43.
  • LIU, F., ZHAO, X., CHAU, P. Y. K., & TANG, Q. (2015). Roles of perceived value and individual differences in the acceptance of mobile coupon applications. Internet Research, 25(3), 471–495.
  • LIU, Y., CUI, F., SU, X., DU, X., (2019). How Social Support Motivates Trust and Purchase Intentions in Mobile Social Commerce, Review of Business Management, 21(4), 839-860.
  • MAHAPATRA, S. (2017). Mobile shopping among young consumers: an empirical study in an emerging market. International Journal of Retail & Distribution Management, 45(9), 930–949.
  • MARRIOTT, H.R., WILLIAMS, M.D. and DWIVEDI, Y.K. (2017). What do we know about consumer m-shopping behaviour? International Journal of Retail & Distribution Management, 45(6), 568–586.
  • MOLINILLO, S., NAVARRO-GARCÍA, A., ANAYA-SÁNCHEZ, R., & JAPUTRA, A. (2019). The impact of affective and cognitive app experiences on loyalty towards retailers. Journal of Retailing and Consumer Services, 54(C), 1-10.
  • NAKUZE, C., HELEN, D., GUJRAL, I. (2019). Meenakshi Generation Y's brand satisfaction, continuance intention and loyalty to branded mobile apps, .Management Dynamics; Stellenbosch, (28)3, 30-43.
  • NEL, J., and BOSHOFF, C. (2019). The psychological processes underlying online customers' mobile purchasing 'cognitive effort – resistance' behaviour, Management Dynamics; Stellenbosch, 28(4), 15-28.
  • NEL, J. and BOSHOFF, C (2020). Status quo bias and shoppers’ mobile website purchasing resistance, European Journal of Marketing, 54(6), 1433-1466.
  • NUNNALLY, J.C. and BERNSTEIN, I.H. (1994) Psychometric Theory, 3rd ed., McGraw-Hill, New York, NY.
  • OWUSU KWATENG, K., OSEI ATIEMO, K. A., & APPIAH, C. (2018). Acceptance and use of mobile banking: an application of UTAUT2. Journal of Enterprise Information Management, 32(1), 118-151
  • REINARTZ, W., HAENLEIN, M., and HENSELER, J. (2009), "An empirical comparison of the efficacy of covariance-based and variance-based SEM," International Journal of Research in Marketing, 26 (4), 332 – 44
  • REZAEI, S., AMIN, M., MOGHADDAM, M. and MOHAMED, N. (2016), "3G post adoption users experience with telecommunications services: A partial least squares (PLS) path modelling approach", Nankai Business Review International, Vol. 7 No. 3, pp. 361-394.
  • REZAEI, S., & VALAEI, N. (2017). Crafting experiential value via smartphone apps channel. Marketing Intelligence & Planning, 35(5), 688–702.
  • RIGDON, E.E. (1994). “Demonstrating the Effects of Unmodeled Random Measurement Error,” Structural Equation Modeling 1(4), pp. 375-380.
  • RIGDON, E. E. (1998). Structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 251–294). Mahwah: Erlbaum.
  • RINGLE, C., WENDE, S. and BECKER, J. (2015) SmartPLS 3 (Version 3.2.3), SmartPLS GmbH, Boenningstedt, Germany.
  • RÖNKKÖ, M., MCINTOSH, C. N., ANTONAKIS, J., & EDWARDS, J. R. (2016). Partial least squares path modeling: Time for some serious second thoughts. Journal of Operations Management 47-48, 9-27.
  • SAN-MARTÍN, S; JIMÉNEZ, N; PUENTE, N., (2019). Bridging the gap between customer experience management and mobile shopping, Review of Business Management, 21(2), 213-233.
  • SAPRIKIS, V., MARKOS, A., ZARMPOU, T. & MARO, V. (2018). Mobile shopping consumers’ behavior: an exploratory study and review, Journal of Theoretical and Applied Electronic Commerce Research, 13(1),71–90.
  • SARSTEDT, M., HAIR, J. F., RINGLE, C. M., THIELE, K. O., & GUDERGAN, S. P. (2016). Estimation issues with PLS and CB SEM: Where the bias lies! Journal of Business Research, 69(10), 3998-4010.
  • SARSTEDT, M., RINGLE, C.M. and HAIR, J.F. (2017). Partial least squares structural equation modeling, in C., Klarmann, M. and Vomberg, A. (Eds.): Handbook of Market Research, Chapter 15, Springer, Homburg.
  • SCHMITZ, C., BARTSCH, S., & MEYER, A. (2016). Mobile App Usage and its Implications for Service Management – Empirical Findings from German Public Transport. Procedia - Social and Behavioral Sciences, 224, 230–237.
  • SHUKLA, A., & SHARMA, S. K. (2018). Evaluating Consumers’ Adoption of Mobile Technology for Grocery Shopping: An Application of Technology Acceptance Model. Vision: The Journal of Business Perspective, 22(2), 185–198.
  • SINGH, S., & SRIVASTAVA, R. K. (2020). Understanding the intention to use mobile banking by existing online banking customers: an empirical study. Journal of Financial Services Marketing, 25, 86–96.
  • SMITH, T. A. (2020). The role of customer personality in satisfaction, attitude-to-brand and loyalty in mobile services. Spanish Journal of Marketing - ESIC, ahead-of-print(ahead-of-print). doi:10.1108/sjme-06-2019-0036
  • SOUIDEN, N., CHAOUALI, W., & BACCOUCHE, M. (2019). Consumers’ attitude and adoption of location-based coupons: The case of the retail fast food sector. Journal of Retailing and Consumer Services, 47, 116–132.
  • SPEARMAN, C. (1927). The abilities of man. London: MacMillan.
  • SUNG, E (2020). Consumers’ responses to mobile app advertisements during holiday periods, Journal of Consumer Marketing, 37(3), 341–352
  • TAK, P. and PANWAR, S. (2017) ‘Using UTAUT 2 model to predict mobile app-based shopping: evidences from India’, Journal of Indian Business Research, 9(3), 248–264.
  • TAN, G. W.-H., LEE, V.-H., HEW, J.-J., OOI, K.-B., & WONG, L.-W. (2018). The interactive mobile social media advertising: The imminent approach to advertise tourism products and services? Telematics and Informatics, 35(8), 2270-2288
  • TAN, G. W.-H., & OOI, K.-B. (2018). Gender and age: Do they really moderate mobile tourism shopping behavior? Telematics and Informatics, 35(6), 1617–1642.
  • TAN, G. W.-H., LEE, V. H., LIN, B., & OOI, K.-B. (2017). Mobile applications in tourism: the future of the tourism industry? Industrial Management & Data Systems, 117(3), 560–581.
  • TAYLOR, S., & TODD, P. (1995). Assessing IT Usage: The Role of Prior Experience, MIS Quarterly, 19(4),561-570.
  • THAKER, M.T., M. A. B., AMIN, M. F. B., THAKER, H. B. M. T., & ALLAH Pitchay, A. B. (2018). What keeps Islamic mobile banking customers loyal? Journal of Islamic Marketing, 10(2), 525-542
  • THAKUR, R. (2018). The role of self-efficacy and customer satisfaction in driving loyalty to the mobile shopping application. International Journal of Retail & Distribution Management, 46(3), 283–303.
  • THURSTONE, L. L. (1947). Multiple factor analysis. Chicago, IL: The University of Chicago Press.
  • TRAN, H. T. T., & CORNER, J. (2016). The impact of communication channels on mobile banking adoption. International Journal of Bank Marketing, 34(1), 78–109.
  • TSENG, T.H. (2020), "Facilitation of “strong” branded application outcomes – the self-concept perspective", Journal of Product & Brand Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JPBM-03-2020-2783
  • VERKIJIKA, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics, 35(6), 1665–1674.
  • WILLABY, H.W., COSTA, D.S.J., BURNS, B.D., MACCANN C., ROBERTS R.D. (2015). Testing complex models with small sample sizes: A historical overview and empirical demonstration of what Partial Least Squares (PLS) can offer differential psychology, Personality and Individual Differences, 84,73-78.
  • WOLD, H.O.A. (1982). Soft modeling: The basic design and some extensions. In K. G. Jöreskog, & H. O. A. Wold (Eds.), Systems under indirect observations: Part II (pp. 1–54). Amsterdam: North-Holland.
  • WU, J. and WANG, S. (2005) ‘What drives mobile commerce? An empirical evaluation of the revised technology acceptance model’, Information & Management, 42(5), 719–729.
  • WU, Y., TAO, Y. and YANG P. (2008) ‘The use of unified theory of acceptance and use of technology to confer the behavioral model of 3G mobile telecommunication users’, Journal of Statistics & Management Systems, 11(5), 919–949.
  • YANG, K. (2012) ‘Consumer technology traits in determining mobile shopping adoption: an application of the extended theory of planned behavior’, Journal of Retailing and Consumer Services, 19(5), 484–491.
  • YANG, H.C. (2013) ‘Bon Apetit for Apps: young American consumers’ acceptance of mobile applications’, Journal of Computer Information Systems, 53(3), 85–95.
  • YANG, H. and ZHOU, L. (2011) ‘Extending TPB and TAM to mobile viral marketing: an exploratory study on American young consumers’ mobile viral marketing attitude, intent and behavior’, Journal of Targeting, Measurement and Analysis for Marketing, 19(2), 85–98.
  • YILDIZ, O. (2021). A PLS-SEM approach to the consumer adoption of shopping via mobile apps, International Journal of Marketing (Forthcoming). DOI: 10.1504/IJMC.2021.10032505
  • ZHANG, L., ZHU, J. and LIU, Q. (2012) ‘A meta-analysis of mobile commerce adoption and moderating effect of culture’, Computers in Human Behavior, 28(5), 1902–1911.
  • ZHU, G., So, K.K.F. and HUDSON, S. (2017). Inside the sharing economy: understanding consumer motivations behind the adoption of mobile applications, International Journal of Contemporary Hospitality Management, 29(9), 2218–2239.

Mobil Alışveriş Düzleminde Consistent PLS-SEM ve CB-SEM Yöntemlerinin Karşılaştırılması

Yıl 2023, Cilt: 10 Sayı: 2, 649 - 667, 25.10.2023
https://doi.org/10.17336/igusbd.1014138

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.
  • GASKIN, J. (2016). MasterValidity, Gaskination's Statistics. http://statwiki.kolobkreations.com
  • GASKIN, J. (2017). Common Method Bias (CMB) in PLS (partial least squares), Gaskination's Statistics. http://youtube.com/Gaskination
  • GHAZALI, E. M., MUTUM, D. S., CHONG, J. H., & NGUYEN, B. (2018). Do consumers want mobile commerce? A closer look at M-shopping and technology adoption in Malaysia. Asia Pacific Journal of Marketing and Logistics, 30(4), 1064-1086.
  • GEFEN, D., STRAUB, D. W., & RIGDON, E.E. (2011). An Update and Extension to SEM Guidelines for Administrative and Social Science Research, MIS Quarterly (35:2), pp. iii-xiv.
  • GOH, M. L., ANG, H. C. TAN, S. H., OUN, W. L. ()2020. Examining the Determinants of Consumer Purchase Intention towards Mobile Advertising, Global Business and Management Research; Boca Raton, 12(2), 89-103.
  • GONG, X., LIU, Z., ZHENG, X., & WU, T. (2018). Why are experienced users of WeChat likely to continue using the app? Asia Pacific Journal of Marketing and Logistics, 30(4), 1013-1039
  • GROß, M. (2014) ‘Exploring the acceptance of technology for mobile shopping: an empirical investigation among smartphone users’, The International Review of Retail, Distribution and Consumer Research, 25(3), 215–235.
  • GROß, M. (2016). Impediments to mobile shopping continued usage intention: A trust-risk-relationship. Journal of Retailing and Consumer Services, 33, 109–119.
  • GUPTA, K. and ARORA, N. (2019), "Investigating consumer intention to accept mobile payment systems through unified theory of acceptance model: An Indian perspective", South Asian Journal of Business Studies, Vol. 9 No. 1, pp. 88-114.
  • GUPTA, A., DOGRA, N., & GEORGE, B. (2018). What determines tourist adoption of smartphone apps? Journal of Hospitality and Tourism Technology, 9(1), 50–64.
  • HAIR, J. F., BLACK, W. C., BABIN, B. J., & ANDERSON, R. E. (2010). Multivariate data analysis (7th ed.). NJ: Prentice Hall
  • HAIR, J. F., RINGLE, C. M., & SARSTEDT, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 18(2), 139–152
  • HAIR, J.F., HULT, G.T.M., RINGLE, C.M. & SARSTEDT, M. (2014), A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), Sage, Thousand Oaks.
  • HAIR, J., HOLLINGSWORTH, C.L., RANDOLPH, A.B. & CHONG, A.Y.L. (2017). An updated and expanded assessment of PLS-SEM in information systems research, Industrial Management & Data Systems, 117(3),442-458
  • HARIGUNA, T., ADIANDARI, A.M. and RUANGKANJANASES, A. (2020), "Assessing customer intention use of mobile money application and the antecedent of perceived value, economic trust and service trust", International Journal of Web Information Systems, Vol. 16 No. 3, pp. 331-345.
  • HENSELER, J., RINGLE, C.M., RUDOLF R. & SINKOVICS, R.R. (2009), “The Use of Partial Least Squares Path Modeling in International Marketing,” Advances in International Marketing, vol. 20, Rudolf R. Sinkovics and Pervez N. Ghauri, eds., Bingley, UK: Emerald Group, 277–320.
  • HENSELER, J., DIJKSTRA, T. K., SARSTEDT, M., RINGLE, C. M., DIAMANTOPOULOS, A., STRAUB, D. W., ...CALANTONE, R. J. (2014). Common beliefs and reality about partial least squares: Comments on Rönkkö & Evermann (2013). Organizational Research Methods, 17(2),182–209.
  • HENSELER, J., RINGLE, C.M. & SARSTEDT, M. (2015) ‘A new criterion for assessing discriminant validity in variance-based structural equation modeling’, Journal of the Academy of Marketing Science, 43(1), 115–135.
  • HONG, H., MUKUN, C., WANG, G. A., (2017) THE EFFECTS OF NETWORK EXTERNALITIES AND HERDING ON USER SATISFACTION WITH MOBILE SOCIAL APPS, Journal of Electronic Commerce Research, 18(1), 18-31.
  • HSIEH, S. H., & LEE, C. T. (2020). Traces of mobility: Examining location disclosure on social networks with mobile location tagging. Telematics and Informatics, 49, 1-14.
  • INFORMATION AND COMMUNICATION TECHNOLOGIES AUTHORITY ICTA Quarterly Market Report) (2020) Electronic Communications Market in Turkey Market Data (2020 Q2) [online] https://www.btk.gov.tr/uploads/pages/pazar-verileri/turkiye-haberlesme-raporu-002.pdf (accessed 19 Jan 2021).
  • JIMENEZ, N., SAN-MARTIN, S., & PUENTE, N. (2018). The path to mobile shopping compatibility. The Journal of High Technology Management Research, 30(1), 1-12.
  • KLINE, R.B. (2016). Principles and Practice of Structural Equation Modeling, Fourth Edition, NY: The Guilford Press.
  • KUO T., HUANG, K., NGUYEN Q.T., NGUYEN, P.H. (2019). Adoption of mobile applications for identifying tourism destinations by travellers: an integrative approach, Journal of Business Economics and Management,20(5),860–877
  • KOCK, N. (2015). Common method bias in PLS-SEM: A full collinearity assessment approach. International Journal of e-Collaboration, 11(4), 1-10.
  • LEE, E.-B., LEE, S.-G., & YANG, C.-G. (2017). The influences of advertisement attitude and brand attitude on purchase intention of smartphone advertising. Industrial Management & Data Systems, 117(6), 1011–1036.
  • LEE, C. T., & HSIEH, S. H. (2019). Engaging consumers in mobile instant messaging: the role of cute branded emoticons. Journal of Product & Brand Management, 28(7), 849–863.
  • LEI, P. W., & WU, Q. (2007). Introduction to structural equation modeling: Issues and practical considerations. Educational Measurement: Issues and Practices, 26(3),33–43.
  • LIU, F., ZHAO, X., CHAU, P. Y. K., & TANG, Q. (2015). Roles of perceived value and individual differences in the acceptance of mobile coupon applications. Internet Research, 25(3), 471–495.
  • LIU, Y., CUI, F., SU, X., DU, X., (2019). How Social Support Motivates Trust and Purchase Intentions in Mobile Social Commerce, Review of Business Management, 21(4), 839-860.
  • MAHAPATRA, S. (2017). Mobile shopping among young consumers: an empirical study in an emerging market. International Journal of Retail & Distribution Management, 45(9), 930–949.
  • MARRIOTT, H.R., WILLIAMS, M.D. and DWIVEDI, Y.K. (2017). What do we know about consumer m-shopping behaviour? International Journal of Retail & Distribution Management, 45(6), 568–586.
  • MOLINILLO, S., NAVARRO-GARCÍA, A., ANAYA-SÁNCHEZ, R., & JAPUTRA, A. (2019). The impact of affective and cognitive app experiences on loyalty towards retailers. Journal of Retailing and Consumer Services, 54(C), 1-10.
  • NAKUZE, C., HELEN, D., GUJRAL, I. (2019). Meenakshi Generation Y's brand satisfaction, continuance intention and loyalty to branded mobile apps, .Management Dynamics; Stellenbosch, (28)3, 30-43.
  • NEL, J., and BOSHOFF, C. (2019). The psychological processes underlying online customers' mobile purchasing 'cognitive effort – resistance' behaviour, Management Dynamics; Stellenbosch, 28(4), 15-28.
  • NEL, J. and BOSHOFF, C (2020). Status quo bias and shoppers’ mobile website purchasing resistance, European Journal of Marketing, 54(6), 1433-1466.
  • NUNNALLY, J.C. and BERNSTEIN, I.H. (1994) Psychometric Theory, 3rd ed., McGraw-Hill, New York, NY.
  • OWUSU KWATENG, K., OSEI ATIEMO, K. A., & APPIAH, C. (2018). Acceptance and use of mobile banking: an application of UTAUT2. Journal of Enterprise Information Management, 32(1), 118-151
  • REINARTZ, W., HAENLEIN, M., and HENSELER, J. (2009), "An empirical comparison of the efficacy of covariance-based and variance-based SEM," International Journal of Research in Marketing, 26 (4), 332 – 44
  • REZAEI, S., AMIN, M., MOGHADDAM, M. and MOHAMED, N. (2016), "3G post adoption users experience with telecommunications services: A partial least squares (PLS) path modelling approach", Nankai Business Review International, Vol. 7 No. 3, pp. 361-394.
  • REZAEI, S., & VALAEI, N. (2017). Crafting experiential value via smartphone apps channel. Marketing Intelligence & Planning, 35(5), 688–702.
  • RIGDON, E.E. (1994). “Demonstrating the Effects of Unmodeled Random Measurement Error,” Structural Equation Modeling 1(4), pp. 375-380.
  • RIGDON, E. E. (1998). Structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 251–294). Mahwah: Erlbaum.
  • RINGLE, C., WENDE, S. and BECKER, J. (2015) SmartPLS 3 (Version 3.2.3), SmartPLS GmbH, Boenningstedt, Germany.
  • RÖNKKÖ, M., MCINTOSH, C. N., ANTONAKIS, J., & EDWARDS, J. R. (2016). Partial least squares path modeling: Time for some serious second thoughts. Journal of Operations Management 47-48, 9-27.
  • SAN-MARTÍN, S; JIMÉNEZ, N; PUENTE, N., (2019). Bridging the gap between customer experience management and mobile shopping, Review of Business Management, 21(2), 213-233.
  • SAPRIKIS, V., MARKOS, A., ZARMPOU, T. & MARO, V. (2018). Mobile shopping consumers’ behavior: an exploratory study and review, Journal of Theoretical and Applied Electronic Commerce Research, 13(1),71–90.
  • SARSTEDT, M., HAIR, J. F., RINGLE, C. M., THIELE, K. O., & GUDERGAN, S. P. (2016). Estimation issues with PLS and CB SEM: Where the bias lies! Journal of Business Research, 69(10), 3998-4010.
  • SARSTEDT, M., RINGLE, C.M. and HAIR, J.F. (2017). Partial least squares structural equation modeling, in C., Klarmann, M. and Vomberg, A. (Eds.): Handbook of Market Research, Chapter 15, Springer, Homburg.
  • SCHMITZ, C., BARTSCH, S., & MEYER, A. (2016). Mobile App Usage and its Implications for Service Management – Empirical Findings from German Public Transport. Procedia - Social and Behavioral Sciences, 224, 230–237.
  • SHUKLA, A., & SHARMA, S. K. (2018). Evaluating Consumers’ Adoption of Mobile Technology for Grocery Shopping: An Application of Technology Acceptance Model. Vision: The Journal of Business Perspective, 22(2), 185–198.
  • SINGH, S., & SRIVASTAVA, R. K. (2020). Understanding the intention to use mobile banking by existing online banking customers: an empirical study. Journal of Financial Services Marketing, 25, 86–96.
  • SMITH, T. A. (2020). The role of customer personality in satisfaction, attitude-to-brand and loyalty in mobile services. Spanish Journal of Marketing - ESIC, ahead-of-print(ahead-of-print). doi:10.1108/sjme-06-2019-0036
  • SOUIDEN, N., CHAOUALI, W., & BACCOUCHE, M. (2019). Consumers’ attitude and adoption of location-based coupons: The case of the retail fast food sector. Journal of Retailing and Consumer Services, 47, 116–132.
  • SPEARMAN, C. (1927). The abilities of man. London: MacMillan.
  • SUNG, E (2020). Consumers’ responses to mobile app advertisements during holiday periods, Journal of Consumer Marketing, 37(3), 341–352
  • TAK, P. and PANWAR, S. (2017) ‘Using UTAUT 2 model to predict mobile app-based shopping: evidences from India’, Journal of Indian Business Research, 9(3), 248–264.
  • TAN, G. W.-H., LEE, V.-H., HEW, J.-J., OOI, K.-B., & WONG, L.-W. (2018). The interactive mobile social media advertising: The imminent approach to advertise tourism products and services? Telematics and Informatics, 35(8), 2270-2288
  • TAN, G. W.-H., & OOI, K.-B. (2018). Gender and age: Do they really moderate mobile tourism shopping behavior? Telematics and Informatics, 35(6), 1617–1642.
  • TAN, G. W.-H., LEE, V. H., LIN, B., & OOI, K.-B. (2017). Mobile applications in tourism: the future of the tourism industry? Industrial Management & Data Systems, 117(3), 560–581.
  • TAYLOR, S., & TODD, P. (1995). Assessing IT Usage: The Role of Prior Experience, MIS Quarterly, 19(4),561-570.
  • THAKER, M.T., M. A. B., AMIN, M. F. B., THAKER, H. B. M. T., & ALLAH Pitchay, A. B. (2018). What keeps Islamic mobile banking customers loyal? Journal of Islamic Marketing, 10(2), 525-542
  • THAKUR, R. (2018). The role of self-efficacy and customer satisfaction in driving loyalty to the mobile shopping application. International Journal of Retail & Distribution Management, 46(3), 283–303.
  • THURSTONE, L. L. (1947). Multiple factor analysis. Chicago, IL: The University of Chicago Press.
  • TRAN, H. T. T., & CORNER, J. (2016). The impact of communication channels on mobile banking adoption. International Journal of Bank Marketing, 34(1), 78–109.
  • TSENG, T.H. (2020), "Facilitation of “strong” branded application outcomes – the self-concept perspective", Journal of Product & Brand Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JPBM-03-2020-2783
  • VERKIJIKA, S. F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon. Telematics and Informatics, 35(6), 1665–1674.
  • WILLABY, H.W., COSTA, D.S.J., BURNS, B.D., MACCANN C., ROBERTS R.D. (2015). Testing complex models with small sample sizes: A historical overview and empirical demonstration of what Partial Least Squares (PLS) can offer differential psychology, Personality and Individual Differences, 84,73-78.
  • WOLD, H.O.A. (1982). Soft modeling: The basic design and some extensions. In K. G. Jöreskog, & H. O. A. Wold (Eds.), Systems under indirect observations: Part II (pp. 1–54). Amsterdam: North-Holland.
  • WU, J. and WANG, S. (2005) ‘What drives mobile commerce? An empirical evaluation of the revised technology acceptance model’, Information & Management, 42(5), 719–729.
  • WU, Y., TAO, Y. and YANG P. (2008) ‘The use of unified theory of acceptance and use of technology to confer the behavioral model of 3G mobile telecommunication users’, Journal of Statistics & Management Systems, 11(5), 919–949.
  • YANG, K. (2012) ‘Consumer technology traits in determining mobile shopping adoption: an application of the extended theory of planned behavior’, Journal of Retailing and Consumer Services, 19(5), 484–491.
  • YANG, H.C. (2013) ‘Bon Apetit for Apps: young American consumers’ acceptance of mobile applications’, Journal of Computer Information Systems, 53(3), 85–95.
  • YANG, H. and ZHOU, L. (2011) ‘Extending TPB and TAM to mobile viral marketing: an exploratory study on American young consumers’ mobile viral marketing attitude, intent and behavior’, Journal of Targeting, Measurement and Analysis for Marketing, 19(2), 85–98.
  • YILDIZ, O. (2021). A PLS-SEM approach to the consumer adoption of shopping via mobile apps, International Journal of Marketing (Forthcoming). DOI: 10.1504/IJMC.2021.10032505
  • ZHANG, L., ZHU, J. and LIU, Q. (2012) ‘A meta-analysis of mobile commerce adoption and moderating effect of culture’, Computers in Human Behavior, 28(5), 1902–1911.
  • ZHU, G., So, K.K.F. and HUDSON, S. (2017). Inside the sharing economy: understanding consumer motivations behind the adoption of mobile applications, International Journal of Contemporary Hospitality Management, 29(9), 2218–2239.
Toplam 101 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Dijital Pazarlama
Bölüm Makaleler
Yazarlar

Oğuz Yıldız 0000-0003-2164-975X

Alpaslan Kelleci 0000-0003-1589-2905

Erken Görünüm Tarihi 25 Ekim 2023
Yayımlanma Tarihi 25 Ekim 2023
Kabul Tarihi 7 Nisan 2022
Yayımlandığı Sayı Yıl 2023 Cilt: 10 Sayı: 2

Kaynak Göster

APA Yıldız, O., & Kelleci, A. (2023). (Consistent) PLS-SEM vs. CB-SEM in Mobile Shopping. İstanbul Gelişim Üniversitesi Sosyal Bilimler Dergisi, 10(2), 649-667. https://doi.org/10.17336/igusbd.1014138

Creative Commons Lisansı
İstanbul Gelişim Üniversitesi Sosyal Bilimler Dergisi Creative Commons Atıf-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.