Construction Mechanism of Data-driven New Retail Business Model Loop: A Case Study of Hema

Abstract

As the development driving force and new production factor in the era of digital economy, data plays an important role in new retail business model innovation that begins to show the characteristic of closed loop, a term we define as data-driven new retail business model loop, however, we know little about this process and the mechanism behind. In this paper, grounded in an in-depth case study of Hema, a fresh new retail enterprise in China, we systematically explore the construction mechanism of data-driven new retail business model loop through data network effects theory. The findings reveal that the construction of data-driven new retail business model loop includes three phases, namely start, expansion, and reinforcement, they are manifested in the dynamic cycle of “experience optimization of all touchpoints ? value network expansion ? competitive advantage realization”, with the boosting logic of data network effects behind. Specifically, according to the data network effects theory, start, expansion, and reinforcement three phases can be respectively refined as “scene matching”, “connection synergy”, and “value-adding efficiency”, the boosting logic of data network effects theory behind the construction of data-driven new retail business model loop can be realized through the dynamic cycle of “scene matching ? connection synergy ? value-adding efficiency”. The final theoretical model built in this paper can not only contribute to the existing research gaps on the loop innovation of data-driven business model and new retail business model, but also expand data network effects by its theoretical boundary and research context.