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Demand Forecasting for Heavy-Duty Diesel Engines Considering Emission Regulations

Author

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  • Yoon Seong Kim

    (Department of Information & Industrial Engineering, Yonsei University, 134 Shinchon-dong, Seoul 120-749, Korea)

  • Eun Jin Han

    (Department of Information & Industrial Engineering, Yonsei University, 134 Shinchon-dong, Seoul 120-749, Korea)

  • So Young Sohn

    (Department of Information & Industrial Engineering, Yonsei University, 134 Shinchon-dong, Seoul 120-749, Korea)

Abstract

Makers of heavy-duty diesel engines (HDDEs) need to reduce their inventory of old-generation products in preparation for the demand for next-generation products that satisfy new emission regulations. In this paper, a new demand forecasting model is proposed to reflect special conditions raised by the technological generational shift owing to new emission regulation enforcement. In addition, sensitivity analyses are conducted to better accommodate uncertainty involved at the time of prediction. Our proposed model can help support manufacturers’ production and sales management for a series of products in response to new emission regulations.

Suggested Citation

  • Yoon Seong Kim & Eun Jin Han & So Young Sohn, 2017. "Demand Forecasting for Heavy-Duty Diesel Engines Considering Emission Regulations," Sustainability, MDPI, vol. 9(2), pages 1-16, January.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:166-:d:88694
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    References listed on IDEAS

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    Cited by:

    1. Eun Jin Han & So Young Sohn, 2017. "Firms’ Negative Perceptions on Patents, Technology Management Strategies, and Subsequent Performance," Sustainability, MDPI, vol. 9(3), pages 1-15, March.
    2. Won Sang Lee & So Young Sohn, 2017. "Identifying Emerging Trends of Financial Business Method Patents," Sustainability, MDPI, vol. 9(9), pages 1-21, September.
    3. Bo Kyeong Lee & Eun Jin Han & So Young Sohn & Yong Sun Kim & Jong Young Yoon & Jun Yeol Choi, 2017. "A Cost–Benefit Analysis to Assess the Effectiveness of Frontal Center Curtain Airbag," Sustainability, MDPI, vol. 9(10), pages 1-17, September.
    4. Won Sang Lee & Hyo Shin Choi & So Young Sohn, 2018. "Forecasting new product diffusion using both patent citation and web search traffic," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-12, April.

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