Design of Public Services Using Operational Data Analysis: A Case Study on Public Bus Services in South Korea

Design of Public Services Using Operational Data Analysis: A Case Study on Public Bus Services in South Korea

Min-Jun Kim (Samsung Electronics, South Korea), Chiehyeon Lim (Ulsan National Institute of Science and Technology (UNIST), South Korea) and Kwang-Jae Kim (Pohang University of Science and Technology (POSTECH), South Korea)
DOI: 10.4018/978-1-5225-7591-7.ch002
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Various types and massive amounts of data are collected in public sectors, such as transportation, healthcare, and security. Such proliferation of big data facilitates and improves the strategic decision making in the context of public service design. However, the application of big data to public service design, understanding on this topic still remains limited. This chapter presents a case study on designing a service concept for enhancing the driving safety of bus drivers by using their behavior data. Based on this case study, the application of big data for designing public services was empirically identified and various managerial issues facing data-driven service design were recognized. This study extends the research on public service design by revealing how big data can be utilized for public service design.
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Given recent advances in data collection technologies, various types and massive amounts of data were collected in public sectors, such as transport, health care, security, and civic infrastructure (Munné, 2016). The proliferation of public data facilitates and improves analytics in the improvement of public service design. For example, the government can collect information from public transportation systems (i.e., bus operations) to identify areas that cause traffic and thereby propose new routes (Rudin et al., 2014). Real-time operational data can also be used to determine the time when passengers wait for buses. In the health care industry, the government can collect health-related data, such as patient behavior data, clinical data from hospitals, accident reports, and data from disease centers (Rudin et al., 2014). Health-related data can be helpful in improving public health care services, such as disease pattern identification, high-risk patient identification, health care policy development, insurance management, and detection of potential places to obtain medical or social services and ambulatory and emergency services.

This context indicates the importance of utilizing big data in developing and widening public services, which explains the importance of this research topic. However, our understanding of this field remains limited despite its obvious significance. Moreover, existing studies primarily discussed the benefits of big data in advancing public services. Empirical studies should be increased to utilize big data for public service design. Insights from these empirical studies can be used as foundation for increasing the value of big data in public services.

This chapter shows how big data can contribute to the design of public services. More specifically, the chapter presents a case study of the design of a new public service. This service aims to enhance the safety of bus drivers using their driving behavior data (i.e., operational data) from the Korea Transportation Safety Authority (TS) of the South Korean government. TS is tasked to supervise buses and minimize accidents. The safety management strategy of TS involves using driving records, accident history, and driving history to obtain relevant data. This study analyzed the driving record data of 278 buses and accident history data of 4,289 bus drivers to understand and improve the driving behavior of bus drivers. The results were used to identify target drivers who need to improve their driving behavior in terms of driving safety, generate service contents, and design a new service to enhance the driving safety of bus drivers. This chapter also reports the insights gained from the case study. The insights derived from the case study include the use of big data for conceptualizing public services and identifying issues in public service design using big data.

The next section of this chapter, RESEARCH BACKGROUND, reviews related studies. The third and fourth sections of this chapter, CASE STUDY and DISCUSSION, present the results of case study and the findings from the case study results, respectively. The last section of this chapter, CONCLUSION, concludes this chapter.

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