Abstract
Service design is a multidisciplinary area that helps innovate services by bringing new ideas to customers through a design-thinking approach. Services are affected by multiple factors, which should be considered in designing services. In this paper, we propose the multi-factor service design (MFSD) method, which helps consider the multi-factor nature of service in the service design process. The MFSD method has been developed through and used in five service design studies with industry and government. The method addresses the multi-factor nature of service for systematic service design by providing the following guidelines: (1) identify key factors that affect the customer value creation of the service in question (in short, value creation factors), (2) define the design space of the service based on the value creation factors, and (3) design services and represent them based on the factors. We provide real stories and examples from the five service design studies to illustrate the MFSD method and demonstrate its utility. This study will contribute to the design of modern complex services that are affected by varied factors.
Highlights
A factor is ‘‘one of the things that affects an event, decision, or situation’’ (Collins Cobuild 2009), and understanding key factors that affect the system in question is a prerequisite to its analysis and design (Lim et al 2018b)
The method addresses the multi-factor nature of service for systematic service design by providing the following guidelines: (1) identify key factors that affect the customer value creation of the service in question, (2) define the design space of the service based on the value creation factors, and (3) design services and represent them based on the factors
This paper proposes the multi-factor service design (MFSD) method that helps to consider the multiple factors of the service in question systematically in its design
Summary
A factor is ‘‘one of the things that affects an event, decision, or situation’’ (Collins Cobuild 2009), and understanding key factors that affect the system in question is a prerequisite to its analysis and design (Lim et al 2018b). Serv Sci 4(4):349364 Kim KJ, Lim CH, Heo JY, Lee DH, Hong YS, Park K (2016) An evaluation scheme for product–service system models: development of evaluation criteria and case studies. Serv Sci 6(4):296312 Lim CH, Maglio PP (2018) Data-driven understanding of smart service systems through text mining. J Clean Prod 37:42–53 Lim CH, Kim MJ, Heo JY, Kim KJ (2015) Design of informatics-based services in manufacturing industries: case studies using large vehicle-related databases. J Serv Theor Pract 28(1):128 Lim CH, Kim KH, Kim MJ, Heo JY, Kim KJ, Maglio PP (2018b) Nine factor framework for analyzing and designing data-based value creation in information-intensive services. Serv Bus 11(1):161189 Maglio PP, Lim CH (2016) Innovation and big data in smart service systems.
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