Classification of Service Model and Value Creation Kanji Ueda and Takeshi Takenaka Research into Artifacts, Center for Engineering, The University of Tokyo, Japan
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[email protected] Abstract Science and technology are expected to establish a new scientific methodology for studies of services to raise service-sector productivity and to support new services. However, no consensus exists on how to study services because of their specific nature. This paper first provides an overview of previous studies of services using an academic database. Then it presents a new classification of service models considering the relationships among service providers, service receivers, and service environments toward value creation. We also discuss scientific strategies to cocreate new service values in the real world.
(search dates: 1945 to February 2007). We categorized articles according to their year of publication, research fields and the country of the authorship using analytical tools provided by the database, and reconstructed the results using spreadsheet software. Using trial-and-error, we searched some additional cooccurring keywords that were thought to be related to service studies. Of course, search techniques using keywords do not necessarily correspond to the contents, as we expected.
2.2 Historical change of service studies
We specifically viewed historical changes of research fields and interests in service studies. Fig. 1 shows the top 10 research fields in each period.
1. Introduction In recent years, service-sector productivity has become increasingly important. Science and technology are also expected to establish a systematic methodology for service studies. The concept of service science (service sciences, management, and engineering: SSME), proposed by IBM, is an interesting challenge to bridge the gap between science and services [1]. However, no consensus exists on how to study services as science because the nature of services differs from that of manufacturing. A specific structure of services is the inseparability of products and processes. Moreover, service providers, service receivers and service environment are also inseparable from the viewpoint of value creation. For those reasons, services are difficult to address separately in respective traditional academic fields such as engineering, economics, and business. Next, we will overview precedent studies of services using an academic database to elucidate the research trends of studies and underlying problems.
2. Overview of service studies 2.1 Research Method Using the Web of Science database (Thomson Scientific, Philadelphia, PA) [2], we searched articles using keywords. The number of publications including “service” in any title or abstract was about 150,000
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Fig. 1. Top 10 research fields in each historical period: 1945–2007 During 1945–1980, service studies were mostly led by medical science, public administration, and library sciences. Their main targets seem to have been social services and public science. In the 1980s, elemental technologies in the fields of telecommunication engineering and computer science entered gradually. Then, engineering (electrical, telecommunication and computer science) grew to become the top research field in service studies in the 1990s. That phenomenon corresponds to the innovation of internet businesses in the 2000s. Additionally, management science, management engineering, and healthcare science entered in the 1990s and grew to serve an important role in service studies. These trends suggest that service studies in those days were not done solely with
each elemental technology or each academic discipline to deal with social needs.
2.3 Key technologies in recent service studies Figure 2 shows the number of articles that include some keywords that co-occurred with “service” during 1990–2006. We specifically examined keywords that might be related to new technologies; other closelylinked keywords (such as mobile, network, internet, web) are excluded for this purpose. Although we can not give details about each keyword, optimization, for instance, was characteristic of academic interest in several years. We can find many papers that use optimization techniques such as genetic algorithms or neural networks to new fields of real services (logistics, medical service, retailing, tourism, etc.) These trends, however, suggest new problems about service studies nowadays. Interests about humans (lifestyle, cognition, brain, etc.), concerns about social or environmental sustainability, and scientific exploration about innovation or service design all might expose uncertainty about objectives or environments of services in the real world. To clarify the problems described above, we classify service models by their relationships among service providers, service receivers, and service environments toward value creation.
Figure 3 shows the proposed new classification of service models considering the relationship among service providers, service receivers, and service environments toward value creation. Service providers and service receivers can be treated as agents in engineering systems such as multi-agent systems. In class I services, difficult problems require optimal solutions, even if information about service value and service environment are given and are perfectly describable. In class II services, difficulty is attributed to the uncertain service environment. In class III, the service providers must be involved mutually with service receivers to co-create the value of service.
Fig. 3. A classification of service models
4. Conclusion
Fig. 2. Number of articles that include some technical keywords related to services (1990–2006)
3. Service model classification Service design is a synthesis problem among decision-making agents. Co-creation is an important concept to clarify and use decision-making agents’ interactions. The authors [3] have proposed emergent synthesis-based co-creation engineering by which bidirectional interaction among humans, artifacts and environments is considered explicitly to dissolve limitations of existing artificial systems.
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Recent interest has been given to two completely opposite phrases: manufacturing-oriented service sector, and service-oriented manufacturing. In our classification described above, the former is trying to make a class II problem into a class I problem in the same manner as manufacturing. The latter addresses class II and class III problems in which providers positively co-create new values with receivers. Both phrases must be true when they treat these problems as scientific problems to be solved. Toward the co-creation of new values in services, it is important to design how decision-making agents mutually interact and to understand the system uncertainty. Emergent synthetic approaches using emergent-based computations, experimental economics, and experimental psychology are thought to be useful approaches to create new service values.
5. References [1] IBM Research: http://www.research.ibm.com/ssme/ [2] Web of Science: http://scientific.thomson.com/products/wos/ [3] Ueda, K. et al. Emergent Synthesis Methodologies for Manufacturing, Annals of the CIRP, 50/2: 535-551. 2001.
