Min-Jun Kim

Design of informatics-based services in manufacturing industries: case studies using large vehicle-related databases

Numerous companies in manufacturing industries have “servitized” their value propositions to address issues on product commoditization and sustainability. A key component of servitization is informatics, which transforms product and customer data into information for customers. In this study, informatics-based service is defined as a type of service wherein informatics is crucial to customer value creation. Despite the importance of this concept, studies on the design of informatics-based services in manufacturing industries are rare. This paper reports on two case studies on such designs. Informatics-based services have been designed for a major Korean automobile manufacturer and the Korea Transportation Safety Authority (TS) based on their large vehicle-related databases. The first case study with the automobile manufacturer aims to design vehicle operations and health management services for passenger vehicle drivers while the second study with TS focuses on the design of driving safety enhancement services for commercial vehicle (i.e., bus, taxi, and truck) drivers. Based on the case studies, this paper discusses various aspects of informatics-based service design in manufacturing industries. This study would assist researchers and practitioners in designing new informatics-based services and contribute to promoting and inspiring research on intelligent services in manufacturing industries under the current information economy.

From data to value: A nine-factor framework for data-based value creation in information-intensive services

Abstract Service is a key context for the application of IT, as IT digitizes information interactions in service and facilitates value creation, thereby contributing to service innovation. The recent proliferation of big data provides numerous opportunities for information-intensive services (IISs), in which information interactions exert the greatest effect on value creation. In the modern data-rich economy, understanding mechanisms and related factors of data-based value creation in IISs is essential for using IT to improve such services. This study identified nine key factors that characterize this data-based value creation: (1) data source, (2) data collection, (3) data, (4) data analysis, (5) information on the data source, (6) information delivery, (7) customer (information user), (8) value in information use, and (9) provider network. These factors were identified and defined through six action research projects with industry and government that used specific datasets to design new IISs and by analyzing data usage in 149 IIS cases. This paper demonstrates the usefulness of these factors for describing, analyzing, and designing the entire value creation chain, from data collection to value creation, in IISs. The main contribution of this study is to provide a simple yet comprehensive and empirically tested basis for the use and management of data to facilitate service value creation.

Using data to advance service: managerial issues and theoretical implications from action research

Purpose n n n n nThe proliferation of (big) data provides numerous opportunities for service advances in practice, yet research on using data to advance service is at a nascent stage in the literature. Many studies have discussed phenomenological benefits of data to service. However, limited research describes managerial issues behind such benefits, although a holistic understanding of the issues is essential in using data to advance service in practice and provides a basis for future research. The purpose of this paper is to address this research gap. n n n n nDesign/methodology/approach n n n n n“Using data to advance service” is about change in organizations. Thus, this study uses action research methods of creating real change in organizations together with practitioners, thereby adding to scientific knowledge about practice. The authors participated in five service design projects with industry and government that used different data sets to design new services. n n n n nFindings n n n n nDrawing on lessons learned from the five projects, this study empirically identifies 11 managerial issues that should be considered in data-use for advancing service. In addition, by integrating the issues and relevant literature, this study offers theoretical implications for future research. n n n n nOriginality/value n n n n n“Using data to advance service” is a research topic that emerged originally from practice. Action research or case studies on this topic are valuable in understanding practice and in identifying research priorities by discovering the gap between theory and practice. This study used action research over many years to observe real-world challenges and to make academic research relevant to the challenges. The authors believe that the empirical findings will help improve service practices of data-use and stimulate future research.

Toward smarter service systems through service-oriented data analytics

Various types and massive amounts of data are being collected through physical and social sensing. In many cases of data use, the results and value of data analytics are conveyed to specific beneficiaries (e.g., individuals and organizations) within a service system, such as a transportation, energy supply, or healthcare service system. Thus, data-use can be directed and improved based on considerations of the relevant service system. In this paper, we suggest that effective use of data analytics can be guided by the question, “How does data analytics contribute to the creation of a smarter service system?” To facilitate answers to this question, we define a smart service system from a data application perspective, and propose a specific approach, serviceoriented data analytics, based on eight case studies related to smart service systems. We introduce an ongoing case study to demonstrate the applicability and utility of our proposals.

Data-driven Approach to New Service Concept Design

Various types and massive amounts of data are collected in multiple industries. The proliferation of data provides numerous opportunities to improve existing services and develop new ones. Although data utilization contributes to advancing service, studies on the design of new service concepts using data are rare. The present study proposes a data-driven approach to designing new service concepts. The proposed approach is aimed at helping service designers to understand customer behaviors and contexts through data analysis and then generate new service concepts efficiently on the basis of such understanding. A case using bus driving data is introduced to illustrate the process of the proposed approach. The proposed approach provides a basis for the systematic design of new service concepts by enabling efficient data analysis. It also holds the potential to create a synergetic effect if incorporated into existing approaches to designing new service concepts.

Identifying Service Opportunities for Enhancing Driving Safety of Intra-City Buses Based on Driving Behavior Analysis

The purpose of this research is to identify new service opportunities for enhancing driving safety of intra-city buses based on driving behavior analysis. Service opportunity identification involves finding target customers of service (to whom), motivations for service (why), service contents (what), and service delivery process (when, where). This paper presents an analysis of driving behaviors using the operational data of intra-city buses in conjunction with traffic accident data and drivers’ driving history data. This paper also presents four identified service opportunities based on the data analysis results. This research would contribute to enhancing driving safety of intra-city buses in Korea and serve as a basis for developing new services for driving safety enhancement.The purpose of this research is to identify new service opportunities for enhancing driving safety of intra-city buses based on driving behavior analysis. Service opportunity identification involves finding target customers of service (to whom), motivations for service (why), service contents (what), and service delivery process (when, where). This paper presents an analysis of driving behaviors using the operational data of intra-city buses in conjunction with traffic accident data and drivers’ driving history data. This paper also presents four identified service opportunities based on the data analysis results. This research would contribute to enhancing driving safety of intra-city buses in Korea and serve as a basis for developing new services for driving safety enhancement.