Customer switching intention from home delivery to smart locker delivery: Evidence from Vietnam
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Author(s)Nguyet NguyenLink to ORCID Index: https://orcid.org/0009-0000-8127-1125
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Minh Trang NguyenLink to ORCID Index: https://orcid.org/0009-0009-5380-3281
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Thi Thuy Chung Nguyen
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Manh Hung NguyenLink to ORCID Index: https://orcid.org/0000-0002-2460-6205
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DOIhttp://dx.doi.org/10.21511/im.20(2).2024.12
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Article InfoVolume 20 2024, Issue #2, pp. 140-151
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181 Downloads
This work is licensed under a
Creative Commons Attribution 4.0 International License
The purpose of this study is to uncover evidence on the factors influencing switching intention from home delivery to smart lockers in the last-mile delivery service. The research model is constructed based on the Pull-Push-Mooring Theory and the Customer Perceived Value Theory using structural equation modelling to analyze data collected from 557 smart locker users in Vietnam. The results indicated a significantly positive influence of pull factors (convenience, environmental friendliness, and security) and push factors (delivery failure experience and risk), and confirmed that mooring factors (habit and switching cost) negatively impacted customers’ intention to switch from home delivery to smart lockers. The study also revealed that mooring factors moderate the relationship between pull factors and the intention to switch. Moreover, gender, age and frequency of shopping online are significant to switching intention, and usefulness mediates between them and switching intention. Several managerial implications were suggested for stakeholders in order to enhance customers’ switching intentions to use smart lockers, thereby improving the quality, efficiency, and sustainability of the last-mile delivery service in the future.
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- Keywords
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JEL Classification (Paper profile tab)D12, L87, O14, M31
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References50
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Tables4
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Figures2
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- Figure 1. Research framework
- Figure 2. Structural model
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- Table 1. Research sample characteristics
- Table 2. Results of evaluating composite reliability, outer loadings, and AVE of first-order items
- Table 3. Discriminant validity
- Table 4. Hypothesis testing results
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- 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.
- Barua, Z., Aimin, W., & Hongyi, X. (2018). A perceived reliability-based customer satisfaction model in self-service technology. Service Industries Journal, 38(7-8), 446-466.
- Buldeo Rai, H., Verlinde, S., & Macharis, C. (2021). Unlocking the failed delivery problem? Opportunities and challenges for smart locks from a consumer perspective. Research in Transportation Economics, 87.
- Campos, J. G. F. de, & Mello, A. M. de. (2017). Transaction costs in environmental purchasing: analysis through two case studies. Journal of Operations and Supply Chain Management, 10(1), 87.
- Chen, Y. H., & Keng, C. J. (2019). Utilizing the Push-Pull-Mooring-Habit framework to explore users’ intention to switch from offline to online real-person English learning platform. Internet Research, 29(1), 167-193.
- Chen, Y., Yu, J., Yang, S., & Wei, J. (2018). Consumer’s intention to use self-service parcel delivery service in online retailing: An empirical study. Internet Research, 28(2), 500-519.
- Cheng, S., Lee, S. J., & Choi, B. (2019). An empirical investigation of users’ voluntary switching intention for mobile personal cloud storage services based on the push-pull-mooring framework. Computers in Human Behavior, 92, 198-215.
- Chiu, H. C., Hsieh, Y. C., Roan, J., Tseng, K. J., & Hsieh, J. K. (2011). The challenge for multichannel services: Cross-channel free-riding behavior. Electronic Commerce Research and Applications, 10(2), 268-277.
- Chuong, H. N., Uyen, V. T. P., Ngan, N. D. P., Tram, N. T. B., Tran, L. N. B., & Ha, N. T. T. (2024). Exploring a new service prospect: customer’ intention determinants in light of utaut theory. Cogent Business and Management, 11(1).
- Collier, J. E., & Sherrell, D. L. (2010). Examining the influence of control and convenience in a self-service setting. Journal of the Academy of Marketing Science, 38(4), 490-509.
- Demoulin, N. T. M., & Djelassi, S. (2016). An integrated model of self-service technology (SST) usage in a retail context. International Journal of Retail and Distribution Management, 44(5), 540-559.
- Featherman, M. S., Miyazaki, A. D., & Sprott, D. E. (2010). Reducing online privacy risk to facilitate e-service adoption: The influence of perceived ease of use and corporate credibility. Journal of Services Marketing, 24(3), 219-229.
- Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human Computer Studies, 59(4), 451-474.
- Forsythe, S., Liu, C., Shannon, D., & Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of Interactive Marketing, 20(2), 55-75.
- 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.
- Halpern, N., & Mwesiumo, D. (2021). Airport service quality and passenger satisfaction: The impact of service failure on the likelihood of promoting an airport online. Research in Transportation Business and Management, 41.
- Haridasan, A. C., Fernando, A. G., & Balakrishnan, S. (2021). Investigation of consumers’ cross-channel switching intentions: A push-pull-mooring approach. Journal of Consumer Behaviour, 20(5), 1092-1112.
- Henseler, J., Ringle, C., & Sarstedt, M. (2015). A New Criterion for Assessing Discriminant Validity in Variance-based Structural Equation Modeling. Journal of the Academy of Marketing Science, 43, 115-135.
- 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.
- Huong, T. T., & Thiet, B. N. (2020). Smart locker- A sustainable urban delivery solution: Benefits and challenges in implementing in Vietnam. 12th NEU-KKU International Conference Socio-Economic And Environmental Issues In Development, (pp. 1123-1135).
- Issock Issock, P. B., Roberts-Lombard, M., & Mpinganjira, M. (2020). The importance of customer trust for social marketing interventions: a case of energy-efficiency consumption. Journal of Social Marketing, 10(2), 265-286.
- Iwan, S., Kijewska, K., & Lemke, J. (2016). Analysis of Parcel Lockers’ Efficiency as the Last Mile Delivery Solution – The Results of the Research in Poland. Transportation Research Procedia, 12, 644-655.
- Lee, E. S. (1966). A Theory of Migration. Demography, 3(1), 47-57.
- Lemke, J., Iwan, S., & Korczak, J. (2016). Usability of the Parcel Lockers from the Customer Perspective - The Research in Polish Cities. Transportation Research Procedia, 16, 272-287.
- Lim, S. F. W. T., Jin, X., & Srai, J. S. (2018). Consumer-driven e-commerce: A literature review, design framework, and research agenda on last-mile logistics models. International Journal of Physical Distribution and Logistics Management, 48(3), 308-332.
- Liu, Q., Xue, B., & Huang, S. (2021). Investigating users switching intention for mobile map services: An extension of the push-pull-mooring model. International Journal of Mobile Communications, 19, 99-120.
- Marriott, H. R., & Williams, M. D. (2018). Exploring consumers perceived risk and trust for mobile shopping: A theoretical framework and empirical study. Journal of Retailing and Consumer Services, 42, 133-146.
- McKinnon, A. C., & Tallam, D. (2003). Unattended delivery to the home: An assessment of the security implications. International Journal of Retail & Distribution Management, 31(1), 30-41.
- Moon, B. (1995). Paradigms in migration research: exploring “moorings” as a schema. Progress in Human Geography, 19(4), 504-524.
- Nimako, S., Ntim, B. A., & Nimako, S. G. (2013). Construct Specification and Misspecification within the Application of Push-Pull-Mooring Theory of Switching Behaviour. Construct Specification and Misspecification within the Application of Push-Pull-Mooring Theory of Switching Behaviour. Journal of Business and Management Sciences, 1(5), 83-95.
- Quan, N. H., Binh, N. T., & Ly, B. T. (2022). Impact of smart locker use on customer satisfaction of online shoppers in Vietnam. Humanities and Social Sciences Communications, 9(1).
- Quynh, T. T. D., Phu, T. T., Anh, T. D., Trang, N. Q., & Giang, H. H. (2023). Research overview of research attractions in last-mile delivery (FTU Working Paper Series).
- Rahman, M. A., Islam, M. A., Esha, B. H., Sultana, N., & Chakravorty, S. (2018). Consumer buying behavior towards online shopping: An empirical study on Dhaka city, Bangladesh. Cogent Business and Management, 5(1), 1-22.
- Roy, S. K., Shekhar, V., Lassar, W. M., & Chen, T. (2018). Customer engagement behaviors: The role of service convenience, fairness and quality. Journal of Retailing and Consumer Services, 44, 293-304.
- Shan, H., Tong, Q., Shi, J., & Zhang, Q. (2021). Risk assessment of express delivery service failures in China: An improved failure mode and effects analysis approach. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2490-2514.
- Song, L., Cherrett, T., Mcleod, F., & Guan, W. (2009). Addressing the Last Mile Problem: Transport Impacts of Collection/Delivery Points. Transportation Research Record, 2097(1), 9-18.
- Sun, Y., Liu, D., Chen, S., Wu, X., Shen, X. L., & Zhang, X. (2017). Understanding users’ switching behavior of mobile instant messaging applications: An empirical study from the perspective of push-pull-mooring framework. Computers in Human Behavior, 75, 727-738.
- Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203-220.
- Tsai, Y. Te, & Tiwasing, P. (2021). Customers’ intention to adopt smart lockers in last-mile delivery service: A multi-theory perspective. Journal of Retailing and Consumer Services, 61.
- Tuu, H. H., Olsen, S. O., Thao, D. T., & Anh, N. T. K. (2008). The role of norms in explaining attitudes, intention and consumption of a common food (fish) in Vietnam. Appetite, 51(3), 546-551.
- Van Duin, J. H. R., De Goffau, W., Wiegmans, B., Tavasszy, L. A., & Saes, M. (2016). Improving Home Delivery Efficiency by Using Principles of Address Intelligence for B2C Deliveries. Transportation Research Procedia, 12, 14-25.
- Verplanken, B. (2006). Beyond frequency: Habit as mental construct. British Journal of Social Psychology, 45(3), 639-656.
- Wang, X., Zhan, L., Ruan, J., & Zhang, J. (2014). How to choose “last mile” delivery modes for E-fulfillment. Mathematical Problems in Engineering, 2014.
- Xie, W., Chen, C., & Sithipolvanichgul, J. (2022). Understanding e-commerce customer behaviors to use drone delivery services: A privacy calculus view. Cogent Business and Management, 9(1).
- Xu, H., Dinev, T., Smith, J., & Hart, P. (2011). Information Privacy Concerns: Linking Individual Perceptions with Institutional Privacy Assurances. Journal of the Association for Information Systems, 12(12).
- Yang, H. L., & Lin, S. L. (2015). User continuance intention to use cloud storage service. Computers in Human Behavior, 52, 219-232.
- Yuen, K. F., Wang, X., Ma, F., & Wong, Y. D. (2019). The determinants of customers’ intention to use smart lockers for last-mile deliveries. Journal of Retailing and Consumer Services, 49, 316-326.
- Zarei, M. M., Chaparro-Pelaez, J., & Agudo-Peregrina, Á. F. (2020). Identifying consumer’s last-mile logistics beliefs in omni-channel environment. Economic Research-Ekonomska Istrazivanja, 33(1), 1796-1812.
- Zeithaml, V. A. (1988). Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of Marketing, 52(3), 2-22.
- Zhang, Y., Fan, X., & Zhou, L. (2019). Analysis and Research on the “last mile” distribution innovation model of e-commerce express delivery. Journal of Physics: Conference Series, 1176(4).
