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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185 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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