IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v9y2017i2p166-d88694.html
   My bibliography  Save this article

Demand Forecasting for Heavy-Duty Diesel Engines Considering Emission Regulations

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/9/2/166/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/9/2/166/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Keiko Hirota, 2010. "Comparative Studies on Vehicle Related Policies for Air Pollution Reduction in Ten Asian Countries," Sustainability, MDPI, vol. 2(1), pages 1-18, January.
    2. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    3. Li, Ke & Lin, Boqiang, 2016. "Impact of energy conservation policies on the green productivity in China’s manufacturing sector: Evidence from a three-stage DEA model," Applied Energy, Elsevier, vol. 168(C), pages 351-363.
    4. Meng, Fanyi & Su, Bin & Thomson, Elspeth & Zhou, Dequn & Zhou, P., 2016. "Measuring China’s regional energy and carbon emission efficiency with DEA models: A survey," Applied Energy, Elsevier, vol. 183(C), pages 1-21.
    5. Zeger Degraeve & Gert Jan Koopman, 1998. "Achieving Air Quality Standards in the European Union," Operations Research, INFORMS, vol. 46(5), pages 643-654, October.
    6. Gao Xiang Lou & Hai Yang Xia & Jie Qiong Zhang & Ti Jun Fan, 2015. "Investment Strategy of Emission-Reduction Technology in a Supply Chain," Sustainability, MDPI, vol. 7(8), pages 1-25, August.
    7. Christopher J. Easingwood & Vijay Mahajan & Eitan Muller, 1983. "A Nonuniform Influence Innovation Diffusion Model of New Product Acceptance," Marketing Science, INFORMS, vol. 2(3), pages 273-295.
    8. Shihong Zeng & Yan Xu & Liming Wang & Jiuying Chen & Qirong Li, 2016. "Forecasting the Allocative Efficiency of Carbon Emission Allowance Financial Assets in China at the Provincial Level in 2020," Energies, MDPI, vol. 9(5), pages 1-18, May.
    9. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    10. Shihong Zeng & Jiuying Chen, 2016. "Forecasting the Allocation Ratio of Carbon Emission Allowance Currency for 2020 and 2030 in China," Sustainability, MDPI, vol. 8(7), pages 1-28, July.
    11. Park, Sang Yong & Kim, Jong Wook & Lee, Duk Hee, 2011. "Development of a market penetration forecasting model for Hydrogen Fuel Cell Vehicles considering infrastructure and cost reduction effects," Energy Policy, Elsevier, vol. 39(6), pages 3307-3315, June.
    12. Shihong Zeng & Mimi Hu & Bin Su, 2016. "Research on Investment Efficiency and Policy Recommendations for the Culture Industry of China Based on a Three-Stage DEA," Sustainability, MDPI, vol. 8(4), pages 1-15, March.
    13. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    14. Qian, Lixian & Soopramanien, Didier, 2014. "Using diffusion models to forecast market size in emerging markets with applications to the Chinese car market," Journal of Business Research, Elsevier, vol. 67(6), pages 1226-1232.
    15. Sung Yong Chun & Minhi Hahn, 2008. "A diffusion model for products with indirect network externalities," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 27(4), pages 357-370.
    16. Wei Jiang & Jia Liu & Xiang Liu, 2016. "Impact of Carbon Quota Allocation Mechanism on Emissions Trading: An Agent-Based Simulation," Sustainability, MDPI, vol. 8(8), pages 1-13, August.
    17. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Saiah, Saiah Bekkar Djelloul & Stambouli, Amine Boudghene, 2017. "Prospective analysis for a long-term optimal energy mix planning in Algeria: Towards high electricity generation security in 2062," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 26-43.
    2. Velickovic, Stevan & Radojicic, Valentina & Bakmaz, Bojan, 2016. "The effect of service rollout on demand forecasting: The application of modified Bass model to the step growing markets," Technological Forecasting and Social Change, Elsevier, vol. 107(C), pages 130-140.
    3. Rodríguez-Huerta, Edgar & Rosas-Casals, Martí & Sorman, Alevgul H., 2017. "A societal metabolism approach to job creation and renewable energy transitions in Catalonia," Energy Policy, Elsevier, vol. 108(C), pages 551-564.
    4. Martin Zsifkovits & Markus Günther, 2015. "Simulating resistances in innovation diffusion over multiple generations: an agent-based approach for fuel-cell vehicles," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(2), pages 501-522, June.
    5. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    6. Barnes, Belinda & Southwell, Darren & Bruce, Sarah & Woodhams, Felicity, 2014. "Additionality, common practice and incentive schemes for the uptake of innovations," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 43-61.
    7. Rao, K. Usha & Kishore, V.V.N., 2010. "A review of technology diffusion models with special reference to renewable energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(3), pages 1070-1078, April.
    8. Hélène Dernis & Mariagrazia Squicciarini & Roberto Pinho, 2016. "Detecting the emergence of technologies and the evolution and co-development trajectories in science (DETECTS): a ‘burst’ analysis-based approach," The Journal of Technology Transfer, Springer, vol. 41(5), pages 930-960, October.
    9. Shi, Xiaohui & Chumnumpan, Pattarin, 2019. "Modelling market dynamics of multi-brand and multi-generational products," European Journal of Operational Research, Elsevier, vol. 279(1), pages 199-210.
    10. Shi, Xiaohui & Li, Feng & Bigdeli, Ali Ziaee, 2016. "An examination of NPD models in the context of business models," Journal of Business Research, Elsevier, vol. 69(7), pages 2541-2550.
    11. Adarsh Anand & Richie Aggarwal & Ompal Singh, 2019. "Using Weibull Distribution for Modeling Bimodal Diffusion Curves: A Naive Framework to Study Product Life Cycle," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(07), pages 1-17, November.
    12. Cambier, Adrien & Chardy, Matthieu & Figueiredo, Rosa & Ouorou, Adam & Poss, Michael, 2022. "Optimizing subscriber migrations for a telecommunication operator in uncertain context," European Journal of Operational Research, Elsevier, vol. 298(1), pages 308-321.
    13. Peres, Renana & Muller, Eitan & Mahajan, Vijay, 2010. "Innovation diffusion and new product growth models: A critical review and research directions," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 91-106.
    14. Krishnan, Trichy V. & Feng, Shanfei & Jain, Dipak C., 2023. "Peak sales time prediction in new product sales: Can a product manager rely on it?," Journal of Business Research, Elsevier, vol. 165(C).
    15. Brito, Thiago Luis Felipe & Islam, Towhidul & Stettler, Marc & Mouette, Dominique & Meade, Nigel & Moutinho dos Santos, Edmilson, 2019. "Transitions between technological generations of alternative fuel vehicles in Brazil," Energy Policy, Elsevier, vol. 134(C).
    16. Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
    17. Stefan N. Groesser & Niklas Jovy, 2016. "Business model analysis using computational modeling: a strategy tool for exploration and decision-making," Journal of Management Control: Zeitschrift für Planung und Unternehmenssteuerung, Springer, vol. 27(1), pages 61-88, February.
    18. Al-Alawi, Baha M. & Bradley, Thomas H., 2013. "Review of hybrid, plug-in hybrid, and electric vehicle market modeling Studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 190-203.
    19. Kurdgelashvili, Lado & Shih, Cheng-Hao & Yang, Fan & Garg, Mehul, 2019. "An empirical analysis of county-level residential PV adoption in California," Technological Forecasting and Social Change, Elsevier, vol. 139(C), pages 321-333.
    20. Yogesh V. Joshi & David J. Reibstein & Z. John Zhang, 2009. "Optimal Entry Timing in Markets with Social Influence," Management Science, INFORMS, vol. 55(6), pages 926-939, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:9:y:2017:i:2:p:166-:d:88694. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.