Personalized service product family design optimization considering crowdsourced service operations

Abstract

Facing an increasing demand and market competition for personalization, more and more service enterprises need to offer personalized service products to enhance customer satisfaction and the service level in a cost-effective manner. Service products are inherently coupled with service operations in order to leverage service satisfaction upon operations costs. This requires that design of personalized service products must be coordinated with service operations planning (SOP) within a coherent framework of joint optimization. This study proposes a hierarchical joint optimization (HJO) model for personalized service product family (SPF) design considering crowdsourcing of service operations by taking advantage of service resource family (SRF). A nested genetic algorithm (NGA) is developed to solve the HJO model and find a scheme of a personalized service product, based on which SPF design is derived along with the corresponding SRF. A case study of personalized tourism product family design and tourism operations planning is reported to illustrate the feasibility and potential of the proposed joint optimization method.