Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators

Hsin Hsin Chang, Kit Hong Wong, Shi Yu Li

Research output: Contribution to journalArticlepeer-review

127 Citations (Scopus)


The push-pull-mooring model was applied in this study to investigate consumer channel switching intention related to physical and mobile stores. Push effects include mobile information search behavior (with the perceived benefit and cost of search as antecedents) and perceived value (with perceived service quality and perceived price as antecedents) of products and services obtained at a physical store. Pull effects were consumers’ evaluations of the mobile store attractiveness (with mobile characteristics and perceived quality of mobile store as antecedents). Additionally, mobile shopping self-efficacy and switching cost were hypothesized as the mooring effects that intervene in the push and pull effects. A total of 403 valid questionnaires were collected from Taiwanese m-shopping consumers, and structural equation modeling was adopted for quantitative analysis and hypotheses testing. The results indicated that push and pull effects have direct impacts on switching intention, with the exception of the perceived cost of the search. Mooring effects, including m-shopping self-efficacy, procedural and relational switch costs, have a varying degree of moderating effect on the information search behavior, perceived value, mobile store attractiveness and switch intention. This study concluded that retailers should pay more attention to raising consumer value on both physical and mobile channels to diversify their businesses. This not only offers more channel options for consumers to come into contact with retailers (cross-channel retention), but also prevents consumer cross-channel free-riding behavior, and ultimately reduce switching to other retailers.

Original languageEnglish
Pages (from-to)50-67
Number of pages18
JournalElectronic Commerce Research and Applications
Publication statusPublished - 2017 Jul

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Networks and Communications
  • Marketing
  • Management of Technology and Innovation


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