Analysis of Customization Strategy for E‐Commerce Operation Based on Big Data

Abstract

In order to improve the efficiency of customization and reduce the cost of customization under Big data environment, this paper uses cost‐sharing contract, pricing mechanism, Hotelling model, and game theory tools and research methods, for C2B Electronic Commerce (e‐commerce) mode of Supply Chain Pricing Strategy for in‐depth discussion. This paper first gives the architecture of the customization service system based on big data. The paper studies the game equilibrium of supply chain members under four scenarios: centralized decision‐making, decentralized decision‐making, C2B‐dominated decision‐making, and traditional enterprise‐dominated decision‐making in a supply chain composed of a supplier and C2B e‐commerce enterprises with horizontal price competition, and examines the cross‐price. Important parameters such as impact coefficient, impact coefficient of effort degree of personalized customization, and so on have an impact on variables such as effort degree of personalized customization, retail price, and profit of supply chain members of C2B e‐commerce enterprises. Research shows that with the increase of cross‐price impact coefficient, C2B e‐commerce will enhance its personalized customization efforts in different situations in order to pursue higher profits.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 33 citations exist upstream.