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PLS-SEM or CB-SEM method for customer loyalty towards mobile service providers data

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General Information Cached
Title
PLS-SEM or CB-SEM method for customer loyalty towards mobile service providers data
Type
Article
Main Author
Nurulhayah Muhamad
Additional Authors
  • Nurul Hila Zainuddin
Subject
HF Commerce
ISSN
2289-7070 / e-ISSN 2462-2451
Language Code
eng
Bibliographic Details
Place of Production
Tanjong Malim
Publisher
UPSI Press
Year of publication
2025
Notes
EDUCATUM JSMT Vol. 12 SPECIAL ISSUE (2025)
Degree Type
Others
Corporate Name
Perpustakaan Tuanku Bainun

Abstract

This study compares two commonly used Structural Equation Modeling (SEM) methods_Partial Least Squares SEM (PLS-SEM) and Covariance-Based SEM (CB-SEM)_to assess customer loyalty data in the telecommunications industry. The comparison was conducted using a dataset of 448 mobile service users in Melaka, where service providers have faced challenges in meeting performance standards. Findings reveal that PLS-SEM outperforms CBSEM in terms of Average Variance Extracted (AVE) and Composite Reliability (CR), with AVE values exceeding 0.68 compared to CB-SEM's 0.58, and CR values above 0.89 compared to CB-SEM's 0.84. These results highlight PLS-SEM_s superior construct reliability and validity, particularly for complex models and smaller sample sizes. This study provides valuable insights into selecting appropriate SEM techniques for customer loyalty research. Keywords: PLS-SEM, CB-SEM, customer loyalty, telecommunications, construct validity.

References

Afthanorhan, W. M. A. B. W. (2013). A Comparison Of Partial Least Square Structural Equation

Modeling (PLS-SEM) and Covariance Based Structural Equation Modeling (CB-SEM) for

Confirmatory Factor Analysis. International Journal of Engineering Science and Innovative

Technology (IJESIT), 5 (2), 198 - 205.

 

Ahmed, R.R., Štreimikienė, D., Streimikis, J., & Siksnelyte-Butkiene, I. (2024). A comparative

analysis of multivariate approaches for data analysis in management sciences. E+M Ekonomie a

Management.

 

Akbar, M. M., & Parvez, N. (2009). Impact of service quality, trust & customer satisfaction on

customer loyalty. ABAC Journal, 29(1), 24-38.

 

Amaro, S., Duarte, P. (2015). Travel Social Media Involvement: A Proposed Measure. In: Tussyadiah,

I., Inversini, A. (eds) Information and Communication Technologies in Tourism 2015. Springer, Cham.

https://doi.org/10.1007/978-3-319-14343-9_16

 

Awang, Z., Ahmad, J. H., & Zin, N. M. (2010). Modelling job satisfaction and work commitment

among lecturers: a case of UITM Kelantan. Journal of Statistical Modeling and Analytics, 1(2), 45-59.

 

Awang, Z. (2012). Research Methodolgy and data analysis second edition. UiTM Press.

 

Aydin, S., & Ozer, G. (2005). The analysis of antecedents of customer loyalty in the Turkish mobile

telecommunication market. European Journal of Marketing, 39(7/8), 910-925.

http://dx.doi.org/10.1108/03090560510601833

 

Batra, S. (2024). Exploring the application of PLS-SEM in construction management research:

a bibliometric and meta-analysis approach. Engineering, Construction and Architectural Management.

 

Chan, K.H., Ng, T.H., Tay, L.Y. & The, C.Y. (2021). Antecedents of generation Z towards

digitalisation. A PLS-SEM analysis.

 

Dhasan, D., Kowathanakul, S. & Theingi (2017). Building Customer Loyalty Through Service Quality,

Customer Engagement and Commitment: The Case of Mobile Network Providers in Thailand. XVI

International Business & Economy Conference (IBEC) - Chile 2017.

 

Fornell, C. & Larcker, D.F. (1981). Structural Equation Models with Unobservable Variables and

Measurement Error: Algebra and Statistics. Journal of Marketing Research. 18 (3).

https://doi.org/10.1177/002224378101800313

 

Gefen, D., Straub, D., & Boudreau, M. (2000). Structural Equation Modeling and Regression:

Guidelines for Research Practice. Communications of the Association for Information Systems, 4.

https://doi.org/10.17705/1CAIS.00407

 

Hair, J.F., Hult, G.T., Ringle, C.M., Sarstedt, M., Danks, N.P., & Ray, S. (2021). An Introduction to

Structural Equation Modeling. Classroom Companion: Business.

 

Hair, J.F., Risher, J.J., Sarstedt, M. & Ringle, C.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

 

Hair, J.F., Matthews, L.M., Matthews, R.L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated

guidelines on which method to use.

 

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2016). A Primer on Partial Least Squares

Structural Equation Modeling (PLS-SEM). Sage Publications.

 

Hair, J. F., Gabriel, M. & Patel, V. (2014) AMOS Covariance-Based Structural Equation Modeling

(CB-SEM): Guidelines on Its Application as a Marketing Research Tool . Brazilian Journal of

Marketing. 13(2).

 

Hair, J. F., Ringle, C. M., & 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

 

Im, K. S. & Grover, V. (2004). The Use of Structural Equation Modeling in IS Research: Review and

Recommendations. The Handbook of Information Systems Research

 

Mia, M., Majri, D.Y., & Rahman, I.K. (2019). Covariance Based-Structural Equation Modeling(CBSEM)

UsingAMOS in Management Research.

 

Nitzl, C. (2018). Management Accounting and Partial Least Squares-Structural Equation Modelling

(PLS-SEM): Some Illustrative Examples.

 

Nitzl, C. (2016). Partial Least Squares Structural Equation Modelling (PLS-SEM) in Management

Accounting Research: Directions for Future Theory Development. Econometrics: Multiple Equation

Models eJournal.

 

Nunally, J.C. & Bernstein, I.H. (1994). Psychometric Theory. McGraw-Hill. New York.

 

Richter, N.F., Sinkovics, R.R., Ringle, C.M., & Schlägel, C. (2014). A Critical Look at the Use of

SEM in International Business Research. Econometrics: Single Equation Models eJournal.

 

Ringle, C.M., Sarstedt, M. & Straub, D.W. (2012). A Critical Look at the Use of PLS-SEM. MIS

Quarterly. 36 (1)

 

Sarstedt, M., Hair, J. F., Pick, M., Liengaard, B. D., Radomir, L., Ringle, C.M. (2022) Progress in

partial least squares structural equation modeling use in marketing research in the last decade.

Psychology & Marketing. 39 (5). 1035 - 1064. https://doi.org/10.1002/mar.21640

 

Sinkovics, R.R., Ringle, C.M., & Schlägel, C. (2017). University of Southern Denmark A critical look

at the use of SEM in International Business research.

 

Suwanamas, C., Trimetsoontorn, J., & Fongsuwan, W. (2015). The effect of perceived service quality

on customer emotions, customer satisfaction and customer loyalty: a PLS-SEM approach towards a

luxury hotel in Bangkok, Thailand. Journal for Global Business Advancement, 8(4), 374-398.

 

Tenenhaus, M. (2007). Structural Equation Modelling for small samples. HEC Research Papers Series

885, HEC Paris.

 

Zeng, N., Liu, Y., Gong, P., Hertogh, M., & König, M. (2021). Do right PLS and do PLS right: A

critical review of the application of PLS-SEM in construction management research. Frontiers of

Engineering Management, 8, 356 - 369.

 

Zhang, M.F., Dawson, J.F., & Kline, R.B. (2020). 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.

 

Zhang, Y. (2009). A Study of Corporate Reputation’s Influence on Customer Loyalty Based on PLSSEM

Model. International Business Research. 2 (3). 28 - 35.


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