Architectures for multichannel front-office service delivery models
本文基于运营管理理论，提出了两个维度（渠道冗余和渠道跨度）来区分多渠道前台服务交付模型，并归纳出四种基本架构（通才型、并行型、紧缩型和集中型），探讨了不同架构的运营效能及其与服务战略的匹配。
Purpose Multichannel (MC) service providers have been adopting a wide diversity of front-office service delivery models, i.e. different ways of employing channels to support the delivery of the service activities that involve customer interaction. Despite this, we are still faced with a paucity of concepts to understand the myriad of possible choices. The purpose of this paper is to develop a theoretical framework and basic design architectures to provide a structured understanding of the diversity of operational design choices for MC front-office service delivery models, their efficacy implications, and how they fit with the provider’s service strategy. Design/methodology/approach The study employs the analytical conceptual approach. The authors logically develop the architectures based on the operations management theory and provide corresponding empirical illustrations based on secondary sources, direct observation, and case studies. Findings The authors propose two theoretically meaningful dimensions to characterize and distinguish between delivery models (channel redundancy and channel span) and put forward four anchor architectures for such models: generalist, parallel, constricted, and centralized. The authors identify the operational efficacy implications (effectiveness and efficiency) of the different architectures, and develop a set of propositions and design principles for selecting appropriate architectures. Research limitations/implications Future research should develop empirical measures for the dimensions underlying the architectures. Originality/value The study extends existing service process classifications by capturing the MC traits of front-office processes. The authors offer design principles to assist firms in selecting architectures that are aligned with their service strategy. The framework and architectures provide seminal concepts to support a wealth of future empirical studies.