A CONCEPTUAL MODEL AND ANALYSIS FRAMEWORK OF SERVICE-SYSTEM CLASSIFICATION

Service Science, Vol. 3, No. 1, June 2012 1 A CONCEPTUAL MODEL AND ANALYSIS FRAMEWORK OF SERVICE-SYSTEM CLASSIFICATION Shari S. C. Shang Department ...
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Service Science, Vol. 3, No. 1, June 2012

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A CONCEPTUAL MODEL AND ANALYSIS FRAMEWORK OF SERVICE-SYSTEM CLASSIFICATION Shari S. C. Shang Department of Management Information Systems National Chengchi University, Taipei, Taiwan, R.O.C [email protected] Angela J. Y. Wu Department of Management Information Systems National Chengchi University, Taipei, Taiwan, R.O.C [email protected] ABSTRACT A service system is a resource structure that illustrates the components and capabilities available to realize the services for customers. Given the complex configuration of people, technologies, knowledge, activities, processes, intentions, organizations, and the wide-ranging types of service systems, the modeling of service systems is still in its initial stage. This paper identified four components and five capabilities of service systems from the extant literatures. The four components are service provider, service client, service collaborator, and service supporter; the five service systems capabilities are integration, customization, technology optimizing, innovation, and learning. By examining various kinds of service system, we regarded client contact and customization as two main dimensions to construct the classification of service systems and further formed 24 types of services systems. The study provides a structural framework for researchers to build a conceptual understanding of service systems. It is also expected that practitioners can benefit from the framework to achieve excellent service operations and continuous service innovation. Keywords: Service systems, Service-system components, Service-system capabilities, Service-system classification

1. Introduction The growth of the service sector has resulted in changes in the specialization and outsourcing of service activities performed inside manufacturing firms [Spohrer et al. 2007]. Firms have placed their focus on core competencies and have increased their investment in intangibles, including more knowledge-intensive processes and activities, and they are outsourcing low-revenue activities such as the manufacturing of products to low-cost areas [Weissen-berger-Eibl and Koch 2007]. For example, Nike, Inc., the world-famous sportswear and equipment manufacturer, has changed its strategy in order to expand its competencies from a global manufacturing supply chain to product design, brand management, and customer relationship management [Lusch et al. 2008]. The reason for companies to change their focuses from working processes and production-related activities to customer-centric services might be that the margins with service activities are about twice the margins of products sold [Weissenberger-Eibl and Koch 2007]. In addition to manufacturing, the IT industry has experienced a similar transformation in gross profit margins. One IT service provider, in its annual report, described gross profit margins for different parts of its business. Software had gross profit margins of nearly 90%, whereas services had margins of only 25%. When they analyzed the report on costs and benefits, they found that doubling service productivity would result in gross profit margins of 60%, and improving productivity by ten folds would result in gross profit margins of over 90% [Spohrer and Maglio 2006]. The discussion above implies that the service business has considerable potential for revenue. With regard to this issue, the demand for better service and service innovations is going to grow significantly. Therefore, finding out how to provide service and continue service innovation have become urgent goals of businesses. A systematic approach is needed for the design and production/delivery of services [Tien and Berg 2003]. Service is provided through the application of service systems, which consist of clients and service providers that interact to co-produce value [Spohrer and Maglio 2006]. In terms of increasing productivity in service and service innovation, the re-configuration of service systems can become a major source of service innovation and create competitive advantage within a firm’s industry [Lusch et al. 2008]. However, because of the complexity of the management and the modeling of people, technologies, knowledge, activities, processes, intentions, organizations, and the wide-ranging types of service systems, the formal representation and modeling of service systems is still in its initial stage [Maglio et al. 2006]. In recent studies, scholars have discussed topics mainly related to service innovation, value creation, service science, service management, service-dominant logic, trends of service, and so on [Fitzsimmons and Fitzsimmons 2006; Maglio et al. 2006; Weissenberger-Eibl and Koch 2007; Lusch et al. 2008; Vargo et al., 2008]. Knowledge about service systems’ components, capabilities, and taxonomies is still scattered. There is

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a need for a comprehensive understanding of the service systems and their classification. The objectives of this study are: (1) understanding the required components and capabilities of service systems, and (2) examining service systems from different classifications. It is expected that the result of this study can provide a structural framework for service systems. 2. Concept Building for Service Systems To develop a more comprehensive understanding of the service system, we explore extant scholarship and collect the definitions and the characteristics of the researchers. The term “service system” is derived from the domain of operations research, which had invested huge efforts in the early 20th century. The previous research focused on the problem of queuing and was devoted to resolving the optimization of the “waiting line.” As the related research has evolved, researchers have started to examine the configuration of whole service systems and have transferred to a focus on service system design and management [Fitzsimmons and Fitzsimmons 2006]. The concept of a service system has been extensively studied over the past several decades, but there is still inconsistent. Generally, scholars have identified the service system as a resource structure that illustrates the resources available to the service process for realizing the service [Edvardsson and Olsson 1996]. The resources (i.e., the components and the capabilities) that compose the service system do not give a comprehensive understanding yet, so we will widely discuss those resources in this session and then establish a service classification based on the discussion. 2.1. Components of Service Systems We examined the configuration of service systems from extant scholars. Referring to the value-creation configuration [Vargo et al. 2008], the service system is basically made up of providers and clients. To ensure a consistent quality, a service system may include collaborators and supporters. Because of the complex and overlapping characteristics of service systems, we use service providers, service controllers, service-supporting components, and service clients here to cover all of these similar characteristics. However, it is still necessary to go deeply into each part of the service system configuration to construct components of service systems in detail. Service providers. Service providers are responsible for designing and realizing the contacting interface with service clients in service systems. By means of the service system, providers create service experience, get customer feedback, identify new markets, and so on [Glushko and Tabas 2008; Basole and Rouse 2008]. In addition, providers should manage the service process to ensure service quality. Service providers might be influenced by culture to resist or be willing to provide better service, innovate in service, and take their customers into account [Lush et al. 2008; Basole and Rouse 2008; Alter 2008]. Most of the service providers are companies or other organizations. While service systems integrate the front-service stage and the back-service stage to create a contact interface with the service client, the front stage is realized by the employees [Glushko and Tabas 2008]. Enhancing the abilities of employees can improve service creation and service delivery in service systems [Glushko and Tabas 2008; Lusch 2008; Vargo et al. 2008]. This involves emphasizing knowledge and skills used in service systems when talking about scaling up service systems, forming human capabilities infrastructure, and using competencies to benefit service clients [Spohrer et al. 2007; Lusch 2008; Vargo et al. 2008]. Service clients. Service clients are the core of service system and be divided into internal and external customers. A service system can serve internal customers in businesses through such things as workflow systems, and service providers can also gain experience and knowledge from these internal service processes [Basole and Rouse 2008; Glushko and Tabas 2008; Vargo et al. 2008]. In terms of the above characteristics, there is an important customer-centric concept inside service systems. Service systems must include service clients and take their needs into account to provide and co-produce value. Service collaborators. Service collaborators mean the external entities (c.f., the organization itself) that can ensure that all of the actors and components in the service system act well and are under control. The need for this is based on the facts that (1) some service systems might not have all of the required knowledge and skills to provide value, or (2) it might be impossible for a service system to perform the service independently at its current technology or competency level [Spohrer et al. 2007]. Service collaborators can be government, third parties, suppliers, internal service systems, or external service systems. Service supporters. In addition to the basic components, there are also resources, technologies, and information that need to be considered. When a service provider provides or co-produces a service, service systems might supply service delivery through technologies, or a service provider might be supported by technologies during the processes of service creation. In addition, connections between internal and external service systems are dependent upon technologies because of the instant information exchange. As for the information, it can be information requirements, information flows and dependencies, or feedback loops within service systems [Glushko and Tabas 2008]. The last part, resources, which are utilized in the processes of service creation, can be intangible or tangible, such as knowledge, skills, tangible capital, and so on. Finally, we combine all of these together into an interactive configuration and then make up a service system. So the definition of a service system could be that “a service system is an interactive configuration that comprises service provider, related service controller, service supporting components, the service client, technology, information, and resources dynamically to create value for internal or external customers.” 2.2. Capabilities of Service System In this section, five major service system capabilities are identified based on a collective review of the relevant literature. The

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five capabilities are integration, learning, customization, innovation, and technology optimizing. Integration. When talking about integration, the emphasis is on integrating internal and external service systems, integrating inter-functional processes and activities, and optimizing the resources of the service provider [Spohrer et al. 2007; Lusch et al. 2008; Glushko and Tabas 2008; Alter 2008; Vargo et al. 2008]. Most discussion about service systems will point out these implications because delivering better service to meet customers’ requirements necessitates that all competencies across the organization contribute to the processes and activities of value creation. Integration involves people, technology, and other service systems, as well as more components of service systems. Once a service system is consistently integrating and optimizing scattered resources, systems, processes, and activities, it will have increasing productivity in the service and effective service delivery, and it will provide a better service experience for customers. Learning. A service system can obtain service clients’ feedback through a well-designed front stage of the system [Glushko and Tabas 2008]. Then the service system can adjust its components and configurations to provide better service based on that information. This dynamic cycle increases the learning ability of service systems. Another aspect of learning capability is focusing on the process of investing in some components of service systems. Businesses can improve the competencies of people and technologies and can create an adaptive environment within a service system; consequently, the entire service system and business are learned and benefited from at the same time [Spohrer and Maglio 2006; Spohrer et al. 2007]. Customization. Understanding insights regarding customers and meeting their needs can facilitate making appropriate decisions and aligning organizational efforts to make the best use of every part of service systems to provide quick responses to the requirements of customers [Glushko and Tabas 2008; Basole and Rouse 2008; Lusch et al. 2008]. By means of bridging the front and back stages in service systems, a comprehensive, end-to-end conception of services that treats the entire network of services will enable quick responses to customers. Also, introducing some technologies in service systems, such as customer relationship management (CRM) or business intelligence (BI), will help in identifying potential consumers and new markets and in promoting and customizing the service offerings. Innovation. According to the literature, the boundaries of service systems are not limited to only one type, but rather can be viewed in an infinite number of ways. The configuration of service systems can become a major driving force for innovation and competitive advantage for services [Lusch et al., 2008]. In other words, enhancing and diversifying the competencies of each component in a service system will stimulate more innovation opportunities. Technology Optimization. Most scholars have noted that service systems must comprise technologies as part of the system [Tien and Berg 2003; Spohrer and Maglio 2006; Spohrer et al. 2007; Lusch et al. 2008; Glushko and Tabas 2008; Alter 2008; Vargo et al. 2008]. Broadly speaking, many component linkages of service systems are supported, communicated, facilitated, and driven by information and communication technology (ICT). For example, CRM, supply chain management (SCM), and enterprise resources planning (ERP) applications provide a business-to-business (B2B) mode of service systems that provide an integrated and instant view of critical information during the process of value creation. This helps to promote greater flexibility, agility, and quick responses for all service providers and service clients. In addition to facilitation and support of the interconnections between service providers and service clients, or processes and activities, the technologies can provide an instant, convenient, effective way to deliver service. A correct adoption of technologies can benefit the delivery of services to customers.

Figure 1. The conceptual model of the service system 2.3. Classification of Service Systems Although the development of the service-system classification is one of the major difficulties in service research [Wemmerlöv 1990], the intent of such classifications allow better understanding of the characteristics differentiating service organizations [Cook et al. 1999]. For practitioners, it could help them to identify differentiating factors from other companies and to design services,

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enhance services, and innovate in services. For academics, it could provide a foundation for developing theories such as service strategy, service innovation, or service-system design. Regarding to the extant literatures [Maister and Lovelock 1982; Lovelock and Christopher 1983; Schmenner 1986; Bowen 1990; Wemmerlöv 1990; Silvestro et al. 1992; Kellogg and Chase 1995; Kellogg and Nie 1995; Stell and Donoho 1996; Collier and Meyer 1998; Cunningham et al. 2004; Ng et al. 2007], the service system have no identical classification. We try to find out the suitable classification dimensions to construct our own classifications for study. First, we form two-by-two matrixes via possible dimensions and see if all matrixes are meaningful and suitable. For example, a combination of service outlets and customization is meaningless because these two dimensions are irrelevant. Another example concerns the combination of client contact and equipment/people focus. There is no such situation in which there is high client contact and high equipment focus at the same time. Finally, we remove these combinations and iterate the process until we filter out suitable dimensions. After reviewing all possible combinations of dimensions, client contact and customization are retained. The dimensions that are retained are the most meaningful and have clear definitions, and thus they are also the most frequently used by scholars. Level of Client Contact. Chase and Aquilano (1977) asserted that the main feature of the service is “the extent to which the customers must be in direct contact.” Clients participate at different levels in the service process, and value creation [Bowen 1990] is important but hard to identify; Kellogg and Chase (1995) develop an interval scale to measure it. According to this measurement scale model, client contact can be identified by three vice-dimensions—i.e., communication time, information richness, and “intimacy.” First, there is a period of communication time in which clients make contact with the whole service system [Silvestro et al. 1992]. Second, rich information is passed between clients and providers. Finally, with mutual confiding and trust, a service episode can be described as being intimate. Level of Customization. To response to every customer’s specific order, service needs to be customized. Client orientation is the characteristic of service that is most different from manufacturing. Customization brings competitiveness with increased customers’ value [Simon and Dolan 1998]. But with the rising diversity of market requirements and customers’ needs, the approach of customization has increased both cost and operation complexity [Gilmore and Pine, 1997]. Customization is a complicated, heterogeneous phenomenon that cannot be addressed as a whole, but it can (and should) be classified. According to Lampel and Mintzberg (1996), there are five types of customization—pure standardization, segmented standardization, customized standardization, tailored customization, and pure customization. To widen the interval and simplify the dimension measurement, we pick three types from Lampel and Mintzberg’s classification. The service may be fully customized by individuals (pure customization), may be generated by standards (standardization), or may be fabricated with customized assembly (mass customization) [Lampel and Mintzberg 1996; Pine 1993]. 3. An Analysis of Service Systems Classification We extend the classifications by using these further features as dimensions. This classification is a two-dimension matrix by client-contact and customization. Client contact consists of communication time, information richness, and intimacy, and each can be measured as “high” and “low.” Customization is divided into pure customization (PC), standardization (S), and mass customization (MC). Finally, we spread out all dimensions and form a combination of 24 possible ones, as shown in Appendix 1. 4. Discussion Based on the analysis framework, there are 24 classifications of service systems. With the distinct nature of these different classifications, it may influence the configuration, capabilities, and performance of a service system. That is to say, there are specific relationships between the classification dimensions and service-system capabilities. The analysis of future research might focus on the roles, activities, and meanings of the capabilities required for the building of the service systems based on the different classifications. We suggest two approaches to empirically test this framework. One approach is examining the general service industry by quantitative research methodology. By a survey, managers from different service industries could be asked to report the key capabilities that correspond to its classification. Another approach is testing a specific service industry using a multi-case study. By combining the open data and interviewing, further research could try to find out the real case that matches each classification. The cross-case study could further compare the criteria/properties of different classifications. Further, the research could identify the key capabilities that different service systems require. 5. Conclusion This research tried to provide an analysis framework of the service systems. For this propose, we collected the extant literature and identified the components and capabilities of service systems. First, components of service systems from the service provider perspective were organized and divided into four major parts: service provider, service client, service collaborator, and service supporter. “Service provider” comprises employees, strategy, culture, internal service systems, and knowledge and skills; “service client” means customers; “service collaborator” means governing authority, which can control or monitor the service process; and “service supporter” includes technology, infrastructure, external service systems, interfaces, and the information that forms the basic layer underpinning whole service system.

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To acquire and develop core capabilities more precisely, the five service systems capabilities are proposed with integration, customization, technology optimizing, innovation, and learning. Integration capability indicates integration of internal service systems, external service systems, and resources. Customization capability means gaining customer’s insights and meeting their needs through employees or IT. Technology optimizing capability means using IT to facilitate the service process or help on service delivery. Innovation capability means re-configuration and enhancement of service system components such as enhancing employees’ knowledge and skills or innovating in technology. Learning capability means acquiring feedback from customers and retaining customer knowledge through employees or IT. After establishing a comprehensive conceptual model of the service systems, we picked up four dimensions from the characteristics of the service to find out the criteria and properties. We also gave some suggested approaches to further research. The finding of the relationship between service-system capabilities and service-system classifications will bring up new business opportunities and management techniques for delivering services effectively, increasing productivity in services, and finding the path to achieving new and different capabilities. Limitation. Although this study provided an understanding of service-system capabilities in terms of different classifications, the cases that we chose are still limited and need to be increased in width for each classification. In addition, the findings of the study are still in the preliminary stage. Industry experts have not examined our results yet, but they form a basis for further studies. We hope that our research will encourage more exploration in the area of service systems in the future, including measuring the required capabilities, determining the effects of service strategies on different classifications, investigating relationships between different service systems, and adopting more classifying dimensions. REFERENCES Alter, S., “Service system fundamentals: Work system, value chain, and life cycle,” IBM Systems Journal, Vol. 47, No. 1: 71-85, Jan. 2008. Basole, R. C. and W. B. Rouse, “Complexity of service value networks: Conceptualization and empirical investigation,” IBM Systems Journal, Vol. 47, No. 1, 53-70, 2008. Bowen, J. “Development of a Taxonomy of Services to Gain Strategic Marketing Insights,” Journal of the Academy of Marketing Science, Vol. 18, No. 1, 43-49, 1990. Chase, R. B. and N. J. Aquilano, Production and Operations Management: A Life Cycle Approach, 1st edition, Homewood, IL, Richard D. Irwin, Inc., 1977. Collier, D. A. and S. M. 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Tabas, “Bridging the “Front Stage” and “Back Stage” in Service System Design,” Proceedings of the 41st Annual Hawaii International Conference on System Sciences, 106, January 2008. Kellogg, D. L. and R. B. Chase, “Constructing an empirically derived measure for customer contact,” Management Science, Vol. 41, No. 11, 1734-1749, 1995. Kellogg, D. L. and W. Nie, “A framework for strategic service management,” Journal of Operations Management, Vol. 13, No. 4, 323-337, 1995. Lampel, D. and H. Mintzberg, “Customizing Customization,” Sloan Management Review, Vol. 38, No. 1, 21-30, 1996. Lovelock, C. H. and H. Christopher, “Classifying Services to Gain Strategic Marketing Insights,” Journal of Marketing, Vol. 47, No. 3, 9-20, 1983. Lusch, R. F., S. L. Vargo, and G. Wessels, “Toward a conceptual foundation for service science: Contributions from service-dominant logic,” IBM Systems Journal, Vol. 47, No. 1, 5-14, 2008. Maglio, P. P., S. Srinivasan, and J. T. Kreulen, “Service systems, service scientists, SSME, and innovation,” Communications of the ACM, Vol. 49, No. 7, 81-85, 2006. Maister, D. H. and C. H. Lovelock, “Managing Facilitator Services,” Sloan Management Review, Vol. 23, No. 4, 19-31, 1982. Ng, S., R. B. Bennett, and T. Dagger, “A typology of mass services: the role of service delivery and consumption purpose in classifying service experiences,” Journal of Services Marketing, Vol. 21, No. 7, 471-480, 2007. Pine, B. J. II. “Making mass customization happen: Strategies for the new competitive realities,” Strategy and Leadership, Vol. 21, No. 5, 23-24, 1993. Schmenner, R. W. “How Can Service Businesses Survive and Prosper?” Sloan Management Review, Vol. 27, No. 3, 21-32, 1986.

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Silvestro, R., L. Fitzgerald, R. Johnston, and C. Voss, “Towards a Classification of Service Processes,” International Journal of Service Industry Management, Vol. 3, No. 3, 62-75, 1992. Simon, H. and R. J. Dolan, “Price Customization,” Marketing Management, Vol. 7, No. 4, 10-17, 1998. Spohrer, J. and P. P. Maglio, “The emergence of service science: towards systematic service innovations to accelerate the coproduction of value,” Production and Operations Management, Vol.17, No. 3, 238-246, 2006. Spohrer, J., P. P. Maglio, J. Bailey, and D. Gruhl, “Steps Toward a Science of Service Systems,” IEEE Computer Society, Vol. 40, No. 1, 71-77, 2007. Stell, R. and C. L. Donoho, “Classifying services from a consumer perspective,” Journal of Services Marketing, Vol. 10, No. 6, 33-44, 1996. Tien, J. M. and D. Berg, “A case for service systems engineering,” Journal of Systems Science and Systems Engineering, Vol. 12, No. 1, 13-38, 2003. Vargo, S. T., P. P. Maglio, and M. A. Akaka, “On value and value co-creation: A service systems and service logic perspective,” European Management Journal, Vol. 26, No. 3, 145-152, 2008. Weissenberger-Eibl, M. and D. J. Koch, “Importance of industrial services and service innovations,” Journal of Management and Organization, Vol. 13, No. 2, 88-101, 2007. Wemmerlöv, U. “A taxonomy of service processes and its implications for system design,” International Journal of Service Industry Management, Vol. 1, No. 3, 20-40, 1990.

Appendix 1: The Analysis Framework of the Service-System Classifications Type 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Communication Time H H H H H H H H H H H H L L L L L L L L L L L L

Level Of Client-Contact Information Richness H H H H H H L L L L L L H H H H H H L L L L L L

Intimacy H H H L L L H H H L L L H H H L L L H H H L L L

Level of Customization PC MC S PC MC S PC MC S PC MC S PC MC S PC MC S PC MC S PC MC S

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