A complexity theory approach to IT-enabled services (IESs) and service innovation: Business analytics as an illustration of IES
Introduction
Firms in the business-to-business (B-to-B) market now increasingly view services, rather than traditional products, as the main source of their revenue and competitive advantage [18], [20], [54], [67], [77]. To this end, there are several streams of research and practice in what is now called “service innovation”, from economics [26], operations [49], marketing [54], strategy [18], and organization science [20]. Particularly, information systems (IS) literature discusses information technology (IT), along with services and service innovation, as a primary driver for economic growth and firms' competitive advantage [51], [76], [77]. Previous studies have suggested many roles for IT in service innovation [14], [22], [23], [34]. What is most evident is that IT (e.g., the Internet) has profoundly changed the ways customers interact with service providers [25]. Many traditional services (e.g., healthcare) are now delivered through IT (e.g., IT-enabled healthcare) [22], [74], often increasing operational efficiency. However, the role of IT does not stop here: certain new services, such as digitized services [76], remote diagnostic decision services [31] and cloud-based decision support services [19], are simply not possible without ubiquitous IT and big data management platforms. Thus, not only is IT (re)combined with traditional services and goods, but emerging technologies also enable the emergence of a new generation of services. Simply put, IT is integral to a growing number of services [33].
We call these services IT-enabled services (IESs). IESs differ from traditional IT products, such as word processors and email software, for which production (producer) and consumption (user) tend to be separable. These products often stand alone and support pre-defined requirements, such as storing texts and transmitting messages. IESs also differ from traditional business consulting services, through which a customer gets a master plan (e.g., strategic roadmaps) as the final deliverable from a service provider. Instead, IESs emerge through combining IT and other organizational resources (e.g., processes, skills, work practices) [20], [74], which are sourced from beyond organizational boundaries, including traditional providers, customers and even third-parties (e.g., developers). Related concepts are integrated solutions [18], servitization [66] and resource configurations [69]. An example is business analytics (BA) service, which combines various tangible and intangible resources, such as high-quality data, analytical talents, processes, analytical software, powerful hardware and data management platforms, and other organizational resources from providers, customers, and others [17]. There is considerable potential for researchers in IS to make contributions to the emerging debates and challenges in IES and service innovation [6], [7], [51].
In the literature, there are potentially useful perspectives and theories [67] for the research and practice of service and service innovation in general. Both research and practice are growing in these areas. Compared to product innovation, however, there is still a very limited understanding about service and service innovation in general: relevant theory and empirical work are quite limited [55], [75]. This lack of understanding is especially significant in IES and their innovation [7], [13]. Much work is needed to understand the contemporary trend of integrating diverse material and social resources to address complex organizational and individual needs.
This article aims to respond by developing a novel theoretical perspective on IES and IES innovation. The proposed perspective draws upon the tenet of complexity theory and conceptualizes IES as complex adaptive systems (CAS) and IES innovation as a co-evolutionary process. From this perspective, IESs are viewed as internally complex, dynamic, adaptive, and emergent. They are co-evolving with a wide network of technologies, organizational and individual needs, rules and regulations, institutional arrangements, etc., through variation, selection, and retention (VSR). Through this, this paper broadly covers two important topics in both IES research and practice: what IESs are; and, how such services emerge and evolve. How something (e.g., IT artifacts) is conceptualized influences our way of studying, analyzing, designing, delivering, and changing it [47]. Thus, the inquiry into IES conceptualizations is important, since it reveals what constitutes an IES and the interaction of its internal elements, and thus affects the way “various research priorities for the science of service” [49] are examined. However, focusing on “entities” may not be sufficient: understanding process is also necessary [24]. Thus, studying IES-related service innovation is necessary, since it is the process by which IES comes to life and evolves. We use BA service, as an example of IES, to illustrate the proposed perspective throughout this paper.
The contribution of this paper is multi-faceted. First, there is a recognition that complexity theory can be useful for service science [69] and IS research [61]. This research offers complexity theory as the basis for explaining IES and service innovation. Second, there is not yet consensus on service, in general, and IES, in particular. Many existing studies tend to offer a product-oriented view of service, which undoubtedly leads to a static view of IES, or an intangible view in which IT is either absent or treated as passive. The proposed CAS framework offers a dynamic view that IES are the emergent structures from the interaction of diverse adaptive elements (tangible and intangible). This helps properly explain the properties and behaviors of IES in practice, and further formulate ways to take advantage of such properties and behaviors. Third, innovation in the CAS view is evolutionary. Thus, IES innovation is formulated as a co-evolutionary process of VSR, through which IES and the environment are co-evolving. This is a novel framework that can help develop strategies for designing and managing IES by taking advantage of the evolutionary nature of IES innovation.
In what follows, we briefly review the literature on BA as an example of IES. The next section summarizes existing views of service and service innovation and suggests the need for a perspective to explain complex properties and dynamic behaviors inherent in BA service and other IESs, and the co-evolutionary process in IES innovation. Then, we introduce complexity theory and propose a novel framework for IES and IES innovation. Drawn from the proposed framework, theoretical propositions are developed and several implications for theory and practice are discussed. This discussion includes what strategies are effective for IES innovation.
Section snippets
Business analytics services: an example of IT-enabled services
BA service is neither a single IT product nor a set of non-IT resources. Rather, this emerging service is a configuration of organizational resources with diverse ITs, which aims to enable more efficient and effective decision-making by organizations and individuals. A typical BA service involves complex data and analytics technologies (e.g., in-memory analytics, parallel programming), enabling “the creation, modification, and manipulation of digital artifacts in the process of converting input
Literature review on (IT-enabled) service and service innovation
This review will suggest the need for a perspective to explain dynamic properties and behaviors inherent in IES and IES innovation.
Complex adaptive systems (CAS), environment, and co-evolution
In this section, we present a brief overview of CAS. A CAS is defined as “a system in which large networks of components with no central control and simple rules of operation give rise to complex collective behavior, sophisticated information processing, and adaptation via learning or evolution” [42]. There are many examples of CAS, from biological organisms to economies [9]. While they differ in details, in general there are three coherent dimensions to discuss CAS1
A complexity theory framework for IES and IES innovation
As presented, extant conceptualizations of service have evolved from physical goods or intangible supplements for products to integrated solutions or configurations of resources. Recent views (e.g., service system) are drawn from systems thinking. The previous section offers an overview of CAS. This section presents a complexity theory framework for IES and IES innovation (see Table 4 for summary).
Theoretical propositions
The previous section presented a novel perspective on IES and IES innovation, using BA as an illustration. From this complexity perspective, this section develops theoretical propositions related to IES as CAS, and IES innovation as a co-evolutionary process.
Theoretical and practical implications
The previous section presented a novel perspective on IES and IES innovation and developed theoretical propositions. This section offers several implications for the theory and practice of IES and IES innovation.
Conclusion
While the economies of many countries are shifting from manufacturing to service, understanding of service and service innovation is quite limited [75]. This lack of understanding is especially significant in IES and IES innovation, where IT plays important roles as core or peripheral elements. Drawn upon the tenet of complexity theory, this article has developed a novel framework for understanding IES as CAS and IES innovation as a co-evolutionary process of variation, selection, and
Bongsug (Kevin) Chae is Associate Professor in Information & Operations Management at Kansas State University. He has published papers in such areas as business analytics, supply chain management, service innovation, and knowledge discovery. He has made presentations in universities and global companies in several countries, primarily on the topic of business analytics and intelligence, supply chain management, and service innovation. He is a recipient of the Ralph Reitz Teaching Award and has
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Bongsug (Kevin) Chae is Associate Professor in Information & Operations Management at Kansas State University. He has published papers in such areas as business analytics, supply chain management, service innovation, and knowledge discovery. He has made presentations in universities and global companies in several countries, primarily on the topic of business analytics and intelligence, supply chain management, and service innovation. He is a recipient of the Ralph Reitz Teaching Award and has been nominated for several teaching awards at Kansas State University.