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Diversification and Efficiency Assessment of Japanese Major Private Railways Using Data Envelopment Analysis and the Malmquist Index

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  • Tadaaki Tomikawa

    (Department of Innovation Science, School of Environment and Society, Institute of Science Tokyo, 3-3-6, Shibaura, Minato-ku, Tokyo 108-0023, Japan)

  • Mika Goto

    (Department of Innovation Science, School of Environment and Society, Institute of Science Tokyo, 3-3-6, Shibaura, Minato-ku, Tokyo 108-0023, Japan)

Abstract

Passenger transportation in Japan’s main metropolitan areas is operated by the JR companies, which were privatized and divested from Japan National Railways (JNR) in 1987 and by 16 major private railway companies with large-scale operations. Although their core business is transportation, the major private railway companies have adopted a strategy of diversification, and they engage, e.g., in real estate and distribution businesses. This study examines the relationship between the degree of business diversification and the production efficiency of Japan’s major private railway companies from the perspective of a future business model. To this aim, this study applies data envelopment analysis combined with the Malmquist index to the data of the railway companies from 1987 to 2019. We focus on four phases of activities: cost, operational resource, operational output, and total revenue. This study is the first to analyze the diversified management of Japanese railroad companies by evaluating their production efficiency and its changes over time. The results of the analysis reveal that, while all companies’ earnings have generally increased, the less diversified they are, the more they struggle to optimize personnel and other overhead expenses and resources, lowering production efficiency.

Suggested Citation

  • Tadaaki Tomikawa & Mika Goto, 2025. "Diversification and Efficiency Assessment of Japanese Major Private Railways Using Data Envelopment Analysis and the Malmquist Index," Economies, MDPI, vol. 13(2), pages 1-21, February.
    • Handle: RePEc:gam:jecomi:v:13:y:2025:i:2:p:40-:d:1585206
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    References listed on IDEAS

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    1. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    2. Sueyoshi, Toshiyuki & Yuan, Yan & Goto, Mika, 2017. "A literature study for DEA applied to energy and environment," Energy Economics, Elsevier, vol. 62(C), pages 104-124.
    3. Fare, Rolf & Shawna Grosskopf & Mary Norris & Zhongyang Zhang, 1994. "Productivity Growth, Technical Progress, and Efficiency Change in Industrialized Countries," American Economic Review, American Economic Association, vol. 84(1), pages 66-83, March.
    4. Utton, M A, 1977. "Large Firm Diversification in British Manufacturing Industry," Economic Journal, Royal Economic Society, vol. 87(345), pages 96-113, March.
    5. Niu, Yanliang & Li, Xin & Zhang, Jiangxue & Deng, Xiaopeng & Chang, Yuan, 2023. "Efficiency of railway transport: A comparative analysis for 16 countries," Transport Policy, Elsevier, vol. 141(C), pages 42-53.
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