Dynamic supply chain integration optimization in service mass customization

Optimization of supply chain integration (SCI) is a key issue for traditional service firms which are seeking transition towards service mass customization (SMC). However, conventional research disregards the characteristics of SMC and the dynamic nature of SCI optimization triggered by the service firm's renewals of its strategy and operational decisions in the transition process. To address this challenge effectively, this study firstly proposes a resource evaluation method from a dynamic and integration process-oriented perspective. It then elaborates the impacts of service firm's strategic renewals, as well as the operational decisions, namely the resource scheduling decisions, on the evolution of the resource's integration value. On this basis, it illustrates the mechanism of the dynamic SCI optimization in SMC, and further designs a novel SCI optimization model along with a corresponding genetic algorithm. In particular, tradeoff between customized demands and scale effects, which is the paradox of SMC, is regarded as an essential optimization objective besides SCI performance. The feasibility and validity of the model and algorithm are verified by applying them to a numerical example. By incorporating the perspective of service operations, strategic change and the methodology of operations research, this study contributes to the literature of SCI in SMC by developing a dynamic resource evaluation method and a novel optimization model.