Do Shipping Incentives and Platform Trust Reduce Customer Switching Behaviour? Empirical Evidence from E-Commerce Platforms in Malaysia

Authors

Nor Irwani Abdul Rahman

Faculty of Business & Communication, Universiti Malaysia Perlis (UniMAP) (Malaysia)

Maisarah Misbu

Faculty of Business & Communication, Universiti Malaysia Perlis (UniMAP) (Malaysia)

Muhammad Alif Ikhmal Mohd Azlan

Faculty of Business & Communication, Universiti Malaysia Perlis (UniMAP) (Malaysia)

Article Information

DOI: 10.47772/IJRISS.2025.91200117

Subject Category: Marketing

Volume/Issue: 9/12 | Page No: 1558-1573

Publication Timeline

Submitted: 2025-12-17

Accepted: 2025-12-24

Published: 2026-01-01

Abstract

The rapid expansion of e-commerce has heightened competition among online platforms, driving the use of shipping discounts as a key promotional tool. While such incentives aim to attract and retain customers, frequent switching across platforms raises concerns about their effectiveness in sustaining loyalty. This study investigates the effects of platform trust and shipping discounts on platform switching behaviour and repurchase intention among Malaysian online shoppers, employing the Push-Pull-Mooring (PPM) framework. Platform trust is conceptualized as a mooring factor that discourages switching, whereas shipping discounts act as pull factors encouraging migration. A quantitative research approach with 208 respondents was analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that platform trust significantly reduces switching behaviour, while shipping discounts exert no significant influence. Moreover, platform switching behaviour negatively impacts repurchase intention and mediates the relationship between platform trust and repurchase intention, but not between shipping discounts and repurchase intention. These results extend trust theory within the PPM framework and underscore the limitations of price-based incentives in fostering loyalty. Practically, the study suggests that e-commerce platforms should focus on trust-building strategies alongside innovative service enhancements to improve customer retention in Malaysia’s competitive digital marketplace.

Keywords

Shipping incentives; platform trust; customer switching behaviour

Downloads

References

1. Ahmad, S. N. (2018). “FREE SHIPPING” OR “DOLLAR OFF”? THE MODERATING EFFECTS OF LIST PRICE AND E-SHOPPING EXPERIENCE ON CONSUMER PREFERENCE FOR ONLINE DISCOUNT. International Journal of Electronic Commerce Studies, 9(1). https://doi.org/10.7903/ijecs.1542 [Google Scholar] [Crossref]

2. Akhmedova, A., Vila-Brunet, N., & Mas-Machuca, M. (2021). Building trust in sharing economy platforms: trust antecedents and their configurations. Internet Research, 31(4), 1463–1490. https://doi.org/10.1108/INTR-04-2020-0212 [Google Scholar] [Crossref]

3. Al-Kfairy, M., Shuhaiber, A., Al-Khatib, A. W., & Alrabaee, S. (2024). Social Commerce Adoption Model Based on Usability, Perceived Risks, and Institutional Trust. IEEE Transactions on Engineering Management, 71, 3599–3612. https://doi.org/10.1109/TEM.2023.3341900 [Google Scholar] [Crossref]

4. Bansal, H. S., & Taylor, S. F. (1999). The Service Provider Switching Model (SPSM). Journal of Service Research, 2(2), 200–218. https://doi.org/10.1177/109467059922007 [Google Scholar] [Crossref]

5. Bansal, H. S., Taylor, S. F., & James, Y. S. (2005). “Migrating” to new service providers: Toward a unifying framework of consumers’ switching behaviors. Journal of the Academy of Marketing Science, 33(1), 96–115. https://doi.org/10.1177/0092070304267928 [Google Scholar] [Crossref]

6. Bernama. (2024, December 9). Syarikat kecil, sederhana berdepan tekanan kenaikan kos logistik. BH Online. https://www.bharian.com.my/bisnes/lain-lain/2024/12/1334653/syarikat-kecil-sederhana-berdepan-tekanan-kenaikan-kos-logistik [Google Scholar] [Crossref]

7. Chaffey, D., & Smith, P. (2022). Digital Marketing Excellence. Routledge. https://doi.org/10.4324/9781003009498 [Google Scholar] [Crossref]

8. Chang, I., Liu, C., & Chen, K. (2014). The push, pull and mooring effects in virtual migration for social networking sites. Information Systems Journal, 24. [Google Scholar] [Crossref]

9. Chang, P.-C., & Chiu, Y.-P. (2023). Factors Influencing Switching Intention and Customer Retention of Over-the-Top (OTT) Viewing Behavior in Taiwan: The Push–Pull– Mooring Model. Emerging Media, 1(2), 196–217. https://doi.org/10.1177/27523543231210140 [Google Scholar] [Crossref]

10. Chatzoglou, P., Chatzoudes, D., Savvidou, A., Fotiadis, T., & Delias, P. (2022). Factors affecting repurchase intentions in retail shopping: An empirical study. Heliyon, 8(9), e10619. https://doi.org/10.1016/j.heliyon.2022.e10619 [Google Scholar] [Crossref]

11. Clay, K., Krishnan, R., & Wolff, E. (2001). Prices and Price Dispersion on the Web: Evidence from the Online Book Industry. The Journal of Industrial Economics, 49(4), 521–539. https://doi.org/10.1111/1467-6451.00161 [Google Scholar] [Crossref]

12. Cohen, J. (1988). Statistical power analysis for the behavioral sciences. L. Erlbaum Associates. [Google Scholar] [Crossref]

13. F. Hair Jr, J., Sarstedt, M., Hopkins, L., & G. Kuppelwieser, V. (2014). Partial least squares structural equation modeling (PLS-SEM). European Business Review, 26(2), 106–121. https://doi.org/10.1108/EBR-10-2013-0128 [Google Scholar] [Crossref]

14. Fernandez, C. (2024, December 9). Addressing the hidden costs of adaptability in Southeast Asia’s e-commerce and logistics. The Edge Malaysia. https://theedgemalaysia.com/node/737088 [Google Scholar] [Crossref]

15. Frischmann, T., Hinz, O., & Skiera, B. (2012). Retailers’ Use of Shipping Cost Strategies: Free Shipping or Partitioned Prices? International Journal of Electronic Commerce, 16(3), 65–88. https://doi.org/10.2753/JEC1086-4415160303 [Google Scholar] [Crossref]

16. Gefen, Karahanna, & Straub. (2003). Trust and TAM in Online Shopping: An Integrated Model. MIS Quarterly, 27(1), 51. https://doi.org/10.2307/30036519 [Google Scholar] [Crossref]

17. Gu, J. (2024). Research on Influencing Factors of Brand Loyalty. Advances in Economics, Management and Political Sciences, 114(1), 1–4. https://doi.org/10.54254/2754-1169/114/2024BJ0138 [Google Scholar] [Crossref]

18. Hahn, E. D., & Ang, S. H. (2017). From the editors: New directions in the reporting of statistical results in the Journal of World Business. Journal of World Business, 52(2), 125–126. https://doi.org/10.1016/j.jwb.2016.12.003 [Google Scholar] [Crossref]

19. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Springer International Publishing. https://doi.org/10.1007/978-3-030-80519-7 [Google Scholar] [Crossref]

20. Hair., J. F., M. Hult, G. T., M. Ringle, C., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Second Edition (Second Edition). SAGE Publications, Inc. [Google Scholar] [Crossref]

21. 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 [Google Scholar] [Crossref]

22. 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. https://doi.org/10.1007/s11747-014-0403-8 [Google Scholar] [Crossref]

23. Hou, A. C. Y., Chern, C.-C., Chen, H.-G., & Chen, Y.-C. (2011). ‘Migrating to a new virtual world’: Exploring MMORPG switching through human migration theory. Computers in Human Behavior, 27(5), 1892–1903. https://doi.org/10.1016/j.chb.2011.04.013 [Google Scholar] [Crossref]

24. Hsieh, J.-K., Hsieh, Y.-C., Chiu, H.-C., & Feng, Y.-C. (2012). Post-adoption switching behavior for online service substitutes: A perspective of the push–pull–mooring framework. Computers in Human Behavior, 28(5), 1912–1920. https://doi.org/10.1016/j.chb.2012.05.010 [Google Scholar] [Crossref]

25. Huang, Z., & Benyoucef, M. (2015). User preferences of social features on social commerce websites: An empirical study. Technological Forecasting and Social Change, 95, 57–72. https://doi.org/10.1016/j.techfore.2014.03.005 [Google Scholar] [Crossref]

26. Javed, M. K., & Wu, M. (2020). Effects of online retailer after delivery services on repurchase intention: An empirical analysis of customers’ past experience and future confidence with the retailer. Journal of Retailing and Consumer Services, 54, 101942. https://doi.org/10.1016/j.jretconser.2019.101942 [Google Scholar] [Crossref]

27. Joseph F. Hair, Jr., G. Tomas M. Hult, Christian M. Ringle, & Marko Sarstedt. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Third Edition (Third Edition). SAGE Publications, Inc. [Google Scholar] [Crossref]

28. Kang, I. (2022). A study on switching behavior of social media: from a dynamic perspective. International Trade, Politics and Development, 6(3), 107–120. https://doi.org/10.1108/ITPD-08-2022-0015 [Google Scholar] [Crossref]

29. Kashyap, M. (2024, November 1). Ecommerce in Malaysia: Growth, Trends & Opportunities. Capillary. https://www.capillarytech.com/blog/ecommerce-in-malaysia-growth/#:~:text= Understand %20local%20nuances,the%20power%20of%20customer%20segmentation [Google Scholar] [Crossref]

30. Kim, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), 283–311. https://doi.org/10.1111/j.1365-2575.2007.00269.x [Google Scholar] [Crossref]

31. Kotler, P., & Keller, K. L. (2012). Marketing Management (14th ed.). Pearson, United States. [Google Scholar] [Crossref]

32. Li, C.-Y. (2018). Consumer behavior in switching between membership cards and mobile applications: The case of Starbucks. Computers in Human Behavior, 84, 171–184. https://doi.org/10.1016/j.chb.2017.12.042 [Google Scholar] [Crossref]

33. Likert, R. (1932). A technique for measurement of attitudes. Archives of Psychology, 140, 5–55. [Google Scholar] [Crossref]

34. Ma, S. (2017). Fast or free shipping options in online and Omni-channel retail? The mediating role of uncertainty on satisfaction and purchase intentions. The International Journal of Logistics Management, 28(4), 1099–1122. https://doi.org/10.1108/IJLM-05-2016-0130 [Google Scholar] [Crossref]

35. Ma, X., Bian, W., Yang, X., Niu, S., Cai, Y., Guan, J., & Wang, W. (2022). Online Retailer’s Contingent Free-Shipping Decisions under Large-Scale Promotions Considering Delayed Delivery. Sustainability, 14(17), 10773. https://doi.org/10.3390/su141710773 [Google Scholar] [Crossref]

36. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and Validating Trust Measures for e-Commerce: An Integrative Typology. Information Systems Research, 13(3), 334–359. https://doi.org/10.1287/isre.13.3.334.81 [Google Scholar] [Crossref]

37. milieu. (2024, October 16). Rising costs and service inconsistencies threaten Malaysia’s online retail growth. Milieu. https://www.mili.eu/my/insights/rising-costs-and-service-inconsistencies-threaten-malaysias-online-retail-growth [Google Scholar] [Crossref]

38. Mukherjee, P., & Menon, N. (2024). Digital Migration Infrastructure in return-writing: visualizing the migration landscape of India. Frontiers in Sociology, 9. https://doi.org/10.3389/fsoc.2024.1450773 [Google Scholar] [Crossref]

39. Oyama, Y., Fukuda, D., Imura, N., & Nishinari, K. (2022). E-commerce users’ preferences for delivery options. [Google Scholar] [Crossref]

40. Pertiwi, T. K., Joseph, C., Warmana, G. O., Khoirotunnisa, F., & Hariyana, N. (2025). Exploring Platform Trust, Borrowing Intention, and Actual Use of PayLater Services in Indonesia and Malaysia. Journal of Risk and Financial Management, 18(5), 255. https://doi.org/10.3390/jrfm18050255 [Google Scholar] [Crossref]

41. Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879 [Google Scholar] [Crossref]

42. Qin, L., Qu, Q., Zhang, L., & Wu, H. (2022). Platform trust in C2C e-commerce platform: the sellers’ cultural perspective. Information Technology and Management, 23(4), 233–243. https://doi.org/10.1007/s10799-021-00349-1 [Google Scholar] [Crossref]

43. Ramayah, T., Cheah, J., Chuah, F., Ting, H., & Ali Memon, M. (2018). Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0 : an updated and practical guide to statistical analysis. Pearson Malaysia Sdn. Bhd. [Google Scholar] [Crossref]

44. Rasyid Syamsuri, A. (2022). The Effect of Discounts and Free Shipping on Shopee Marketplace Purchase Decisions with Advertising as Intervening Variable. https://doi.org/10.33258/birci.v5i3.6163 [Google Scholar] [Crossref]

45. Ridley, G., & Young, J. (2012). Theoretical approaches to gender and IT: examining some Australian evidence. Information Systems Journal, 22(5), 355–373. https://doi.org/10.1111/j.1365-2575.2012.00413.x [Google Scholar] [Crossref]

46. Ringle, C. M., Wende, S., & Becker, J.-M. (2024). SmartPLS 4. SmartPLS. https://www.smartpls.com/ [Google Scholar] [Crossref]

47. Sekaran, U., & Wiley, J. (2002). A Skill-Building Approach Fourth Edition RESEARCH METHODS FOR BUSINESS (4th edition). Wiley. http://www.wiley.com/college [Google Scholar] [Crossref]

48. Semrush. (2025, May). Monthly web visits of major e-commerce platforms in Malaysia . Semrush. https://www.semrush.com [Google Scholar] [Crossref]

49. Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/EJM-02-2019-0189 [Google Scholar] [Crossref]

50. Soleimani, M. (2022). Buyers’ trust and mistrust in e-commerce platforms: a synthesizing literature review. Information Systems and E-Business Management, 20(1), 57–78. https://doi.org/10.1007/s10257-021-00545-0 [Google Scholar] [Crossref]

51. Statista. (2023). Number of Internet and Social Media Users Worldwide as of January 2023. Statista. https://www.statista.com/statistics/617136/digital-population-worldwide/ [Google Scholar] [Crossref]

52. Suhaily, L., & Soelasih, Y. (2017). What Effects Repurchase Intention of Online Shopping. International Business Research, 10(12), 113. https://doi.org/10.5539/ibr.v10n12p113 [Google Scholar] [Crossref]

53. TMO Group. (2025). Southeast Asia eCommerce Outlook 2025. TMO Group. https://www.tmogroup.asia/downloads/southeast-asia-ecommerce-outlook/ [Google Scholar] [Crossref]

54. Tsai, M.-T., Tsai, C.-L., & Chang, H.-C. (2010). The Effect of Customer Value, Customer Satisfaction, and Switching Costs on Customer Loyalty: An Empirical Study of Hypermarkets in Taiwan. Social Behavior and Personality: An International Journal, 38(6), 729–740. https://doi.org/10.2224/sbp.2010.38.6.729 [Google Scholar] [Crossref]

55. Wang, L., & Bae, S. (2020). How to avoid the free shipping pitfall? Changing consumer attitudes from the perspective of information interaction. Electronic Commerce Research and Applications, 42, 100996. https://doi.org/10.1016/j.elerap.2020.100996 [Google Scholar] [Crossref]

56. Widodo, E., Palullungan, D., & Syairudin, B. (2019). Implementing PPM framework to customer’s switching behaviour in dual-channel service supply chain. Journal of Physics: Conference Series, 1367(1), 012043. https://doi.org/10.1088/1742-6596/1367/1/012043 [Google Scholar] [Crossref]

57. Xu, C., Peak, D., & Prybutok, V. (2015). A customer value, satisfaction, and loyalty perspective of mobile application recommendations. Decision Support Systems, 79, 171–183. https://doi.org/10.1016/j.dss.2015.08.008 [Google Scholar] [Crossref]

58. Yin, C., Zhou, Y., He, P., & Tu, M. (2023). Research on the influencing factors of the switching behavior of Chinese social media users: QQ transfer to WeChat. Library Hi Tech, 41(3), 771–787. https://doi.org/10.1108/LHT-09-2020-0234 [Google Scholar] [Crossref]

59. Zhao, Q., Chen, C.-D., Zhou, Z., & Mao, R. (2023). Factors Influencing Consumers’ Intentions to Switch to Live Commerce From Push-Pull-Mooring Perspective. Journal of Global Information Management, 31(1), 1–30. https://doi.org/10.4018/JGIM.319972 [Google Scholar] [Crossref]

60. Zhao, Y. X., & Liu, Z. Y. (2017). User switch behavior in IT adoption and usage: A literature review. Libr. Inf, 5, 86–96. [Google Scholar] [Crossref]

61. Zhou, T. (2011). Examining the critical success factors of mobile website adoption. Online Information Review, 35(4), 636–652. https://doi.org/10.1108/14684521111161972 [Google Scholar] [Crossref]

Metrics

Views & Downloads

Similar Articles