Key Success Factors Analysis of Integration of O2O into 7-Eleven Convenient Store
As information technology becomes more varied, the era of the Internet has come. The connection among the retailing industry, the Internet and online/offline integration is centered surrounded the consumers. The pattern of Internet management across all channel integration called consumer behavior. The dependence of full-path retailing on the use of Wi-Fi has become heavier and heavier as days go by, with the consumers being the core and connecting the management pattern of the Internet. It integrates critical factors in a cross-channel fashion. It develops Apps for 7–11 convenience stores and can solve future online Internet and offline store integration and create the best management values. This study combine the views that the literature in Taiwan on real/virtual integration, supported by the results of the questionnaires devised by AHP experts. It can test the crucial factors involved in the success of real/virtual integration.
The weighted average of the development of APP is 26.1%, ranking first.
The weighted average of full-path retailing pattern is 12.7%, ranking second.
The weighted average of automatic cashier is 8.1%, ranking third.
The weighted average of finance technology is 7.7%, ranking fourth.
It is hoped that via this study retailing 4.0 and big data online-offline integration ideas or practice; driving APP development transformation and the connection between the internal convenience store with seamless virtual market and offline equipment real store. It provides experience in full-path purchase.
Keywords7-Eleven O2O Retailing industry Key success factors Analytic hierarchy process analysis
- 1.APCA, Online Payments: What’s Next? In: A payments industry discussion paper (2009)Google Scholar
- 3.Hofer, C.W., Schendel, D.: Strategy formulation: Analytical concepts 1978: West Publ (1978)Google Scholar
- 4.Althoff, T., Jindal, P., Leskovec, J.: Online actions with offline impact: how online social networks influence online and offline user behavior. In: Proceedings of the Tenth ACM International Conference on Web Search and Data Mining. ACM (2017)Google Scholar
- 5.Chang, C.-Y.: The Mysterious Third-Party on Mobile Phone (2016) Google Scholar
- 7.Vuckovac, D., et al.: From Shopping Aids to Fully Autonomous Mobile Self-checkouts-A Field Study in Retail (2017)Google Scholar
- 9.Li, Q., et al.: The impact of big data analytics on customers’ online behaviour. In: Proceedings of the International Multi Conference of Engineers and Computer Scientists (2017)Google Scholar
- 10.Jui-Mei, Y.: Key factors of bank evaluation: a case study of small and medium enterprises (2016)Google Scholar
- 11.Lazar, J., Preece, J.: Classification schema for online communities. In: AMCIS 1998 Proceedings, p. 30 (1998)Google Scholar