IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt06f195pf.html
   My bibliography  Save this paper

Personal Vehicle Ownership and Operating Cost Calculator

Author

Listed:
  • Kim, Daejin
  • Zhao, Yingping
  • Rodgers, Michael O.
  • Guensler, Randall

Abstract

The goal of this research is to develop a tool that can help students and the public better understand the total cost of owning and operating a personal vehicle over the lifetime of that vehicle, from vehicle purchase to vehicle disposal. Lifetime vehicle operating cost consists of the vehicle purchase cost, as well as costs that are less obvious to the user (e.g., financing, fuel, maintenance, insurance, etc.). Underestimating the hidden costs embedded in lifetime vehicle operating cost can lead people to choose vehicles that are unaffordable for their financial situations. Hence, educating transportation planners, students, and the public about lifetime vehicle operating costs is important. To provide a more personalized calculation approach, the National Center for Sustainable Transportation (NCST) research team developed the Lifetime Vehicle Ownership and Operating Cost Calculator. The NCST website provides users with data entry flexibility and a clear, intuitive, and interactive user-interface through which users can better understand their vehicle ownership costs. Vehicle ownership costs are calculated using lookup data and user input for such elements as: purchase price, down payment, interest rates, loan term, annual insurance, maintenance, tire, smog check, parking, tolls, etc. All lookup data can be modified as desired by the user. The NCST website is designed to provide students and the public with a tool that can be used in research and also at any educational level. Users can calculate the cent/mile and total cost of vehicle ownership over the life of the vehicle, with cost estimates for each component specifically identified so that users can weigh the impact of each cost element in their vehicle purchase and use decisions. From an educational perspective, this tool can be used as an instructional aid to specific courses. For example, the tool has been used in the urban transportation planning course at Georgia Tech, where the students are asked to compare different vehicle choices based on a real-life case study. In addition, the NCST team plans to introduce this tool to high school consumer economics classes to help students make reasonable vehicle purchase decisions and to assess vehicle operating costs over entire vehicle life cycles. The Lifetime Vehicle Ownership and Operating Cost Calculator is available at http://costcalculator.ce.gatech.edu/ . View the NCST Project Webpage

Suggested Citation

  • Kim, Daejin & Zhao, Yingping & Rodgers, Michael O. & Guensler, Randall, 2018. "Personal Vehicle Ownership and Operating Cost Calculator," Institute of Transportation Studies, Working Paper Series qt06f195pf, Institute of Transportation Studies, UC Davis.
    • Handle: RePEc:cdl:itsdav:qt06f195pf
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/06f195pf.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dumortier, Jerome & Siddiki, Saba & Carley, Sanya & Cisney, Joshua & Krause, Rachel M. & Lane, Bradley W. & Rupp, John A. & Graham, John D., 2015. "Effects of providing total cost of ownership information on consumers’ intent to purchase a hybrid or plug-in electric vehicle," Transportation Research Part A: Policy and Practice, Elsevier, vol. 72(C), pages 71-86.
    Full references (including those not matched with items on IDEAS)

    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. Al-Alawi, Baha M. & Coker, Alexander D., 2018. "Multi-criteria decision support system with negotiation process for vehicle technology selection," Energy, Elsevier, vol. 157(C), pages 278-296.
    2. Bireswar Dutta & Hsin-Ginn Hwang, 2021. "Consumers Purchase Intentions of Green Electric Vehicles: The Influence of Consumers Technological and Environmental Considerations," Sustainability, MDPI, vol. 13(21), pages 1-23, October.
    3. Shanjun Li & Xianglei Zhu & Yiding Ma & Fan Zhang & Hui Zhou, 2022. "The Role of Government in the Market for Electric Vehicles: Evidence from China," Journal of Policy Analysis and Management, John Wiley & Sons, Ltd., vol. 41(2), pages 450-485, March.
    4. Szinai, Julia K. & Sheppard, Colin J.R. & Abhyankar, Nikit & Gopal, Anand R., 2020. "Reduced grid operating costs and renewable energy curtailment with electric vehicle charge management," Energy Policy, Elsevier, vol. 136(C).
    5. Aparna Venugopal & Dhirendra Shukla, 2019. "Identifying consumers' engagement with renewable energy," Business Strategy and the Environment, Wiley Blackwell, vol. 28(1), pages 53-63, January.
    6. Kirkizoğlu, Zeynep & Karaer, Özgen, 2022. "After-sales service and warranty decisions of a durable goods manufacturer," Omega, Elsevier, vol. 113(C).
    7. Schücking, Maximilian & Jochem, Patrick & Fichtner, Wolf & Wollersheim, Olaf & Stella, Kevin, 2017. "Charging strategies for economic operations of electric vehicles in commercial applications," MPRA Paper 91599, University Library of Munich, Germany.
    8. Guo, Yuntao & Souders, Dustin & Labi, Samuel & Peeta, Srinivas & Benedyk, Irina & Li, Yujie, 2021. "Paving the way for autonomous Vehicles: Understanding autonomous vehicle adoption and vehicle fuel choice under user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 364-398.
    9. Wei Wei & Ming Cao & Qianling Jiang & Sheng-Jung Ou & Hong Zou, 2020. "What Influences Chinese Consumers’ Adoption of Battery Electric Vehicles? A Preliminary Study Based on Factor Analysis," Energies, MDPI, vol. 13(5), pages 1-15, February.
    10. Hardman, Scott & Shiu, Eric & Steinberger-Wilckens, Robert, 2016. "Comparing high-end and low-end early adopters of battery electric vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 88(C), pages 40-57.
    11. Carley, Sanya & Zirogiannis, Nikolaos & Siddiki, Saba & Duncan, Denvil & Graham, John D., 2019. "Overcoming the shortcomings of U.S. plug-in electric vehicle policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    12. Scorrano, Mariangela & Danielis, Romeo & Giansoldati, Marco, 2020. "Dissecting the total cost of ownership of fully electric cars in Italy: The impact of annual distance travelled, home charging and urban driving," Research in Transportation Economics, Elsevier, vol. 80(C).
    13. Stadelmann, Marcel & Schubert, Renate, 2018. "How Do Different Designs of Energy Labels Influence Purchases of Household Appliances? A Field Study in Switzerland," Ecological Economics, Elsevier, vol. 144(C), pages 112-123.
    14. Ji, Dandan & Gan, Hongcheng, 2022. "Effects of providing total cost of ownership information on below-40 young consumers’ intent to purchase an electric vehicle: A case study in China," Energy Policy, Elsevier, vol. 165(C).
    15. Munshi, Talat & Dhar, Subash & Painuly, Jyoti, 2022. "Understanding barriers to electric vehicle adoption for personal mobility: A case study of middle income in-service residents in Hyderabad city, India," Energy Policy, Elsevier, vol. 167(C).
    16. Kim, Jae Hun & Lee, Gunwoo & Park, Ji Young & Hong, Jungyeol & Park, Juneyoung, 2019. "Consumer intentions to purchase battery electric vehicles in Korea," Energy Policy, Elsevier, vol. 132(C), pages 736-743.
    17. Jon Martin Denstadli & Tom Erik Julsrud, 2019. "Moving Towards Electrification of Workers’ Transportation: Identifying Key Motives for the Adoption of Electric Vans," Sustainability, MDPI, vol. 11(14), pages 1-19, July.
    18. Wenbo Li & Ruyin Long & Hong Chen & Jichao Geng, 2017. "Household factors and adopting intention of battery electric vehicles: a multi-group structural equation model analysis among consumers in Jiangsu Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(2), pages 945-960, June.
    19. Zirogiannis, Nikolaos & Duncan, Denvil & Carley, Sanya & Siddiki, Saba & Graham, John D., 2019. "The effect of CAFE standards on vehicle sales projections: A Total Cost of Ownership approach," Transport Policy, Elsevier, vol. 75(C), pages 70-87.
    20. Gábor Horváth & Attila Bai & Sándor Szegedi & István Lázár & Csongor Máthé & László Huzsvai & Máté Zakar & Zoltán Gabnai & Tamás Tóth, 2023. "A Comprehensive Review of the Distinctive Tendencies of the Diffusion of E-Mobility in Central Europe," Energies, MDPI, vol. 16(14), pages 1-29, July.

    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:cdl:itsdav:qt06f195pf. 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: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    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.