IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v40y2012i3p302-313.html
   My bibliography  Save this article

Investigating a long tail in retail vehicle sales

Author

Listed:
  • Brabazon, Philip G
  • MacCarthy, Bart

Abstract

The concept of the long tail in demand distributions has generated significant research interest because of its potential importance for producers, distributors and retailers. Studies to date have focused on information goods sold through internet channels. Here we study long tail effects in vehicle sales sold through conventional car dealerships. The willingness of customers to compromise on, and/or wait for their requested vehicle specifications are identified as critical factors in vehicle purchases. An extensive empirically based simulation study is conducted to investigate these demand-side factors. The results show how the characteristics of the customer population affect the observed pattern in vehicle sales. The interaction effects of supply-side factors are also highlighted, in particular the effect of the replenishment policy used in the fulfillment system. The study also analyzes the distortion of the underlying demand signal in the sales distribution and the lead time and degree of compromise experienced by different customer populations. Significant managerial implications are highlighted, including the dangers of using the sales distribution as a definitive indicator of demand, the need for the order fulfillment process to align with the characteristics of the market, and the negative effects of focusing replenishment on a small subset of the most popular variants.

Suggested Citation

  • Brabazon, Philip G & MacCarthy, Bart, 2012. "Investigating a long tail in retail vehicle sales," Omega, Elsevier, vol. 40(3), pages 302-313.
    • Handle: RePEc:eee:jomega:v:40:y:2012:i:3:p:302-313
    DOI: 10.1016/j.omega.2011.07.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048311001198
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2011.07.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Bentley, R. Alexander & Madsen, Mark E. & Ormerod, Paul, 2009. "Physical space and long-tail markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(5), pages 691-696.
    2. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    3. Paul E. Green & Abba M. Krieger, 1985. "Models and Heuristics for Product Line Selection," Marketing Science, INFORMS, vol. 4(1), pages 1-19.
    4. Vijay Mahajan & Eitan Muller & Frank M. Bass, 1995. "Diffusion of New Products: Empirical Generalizations and Managerial Uses," Marketing Science, INFORMS, vol. 14(3_supplem), pages 79-88.
    5. Erik Brynjolfsson & Yu (Jeffrey) Hu & Michael D. Smith, 2003. "Consumer Surplus in the Digital Economy: Estimating the Value of Increased Product Variety at Online Booksellers," Management Science, INFORMS, vol. 49(11), pages 1580-1596, November.
    6. Daniel Corsten & Thomas Gruen, 2005. "On Shelf Availability: An Examination of the Extent, the Causes, and the Efforts to Address Retail Out-of-Stocks," Springer Books, in: Georgios J. Doukidis & Adam P. Vrechopoulos (ed.), Consumer Driven Electronic Transformation, pages 131-149, Springer.
    7. 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.
    8. A. Gürhan Kök & Marshall L. Fisher, 2007. "Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application," Operations Research, INFORMS, vol. 55(6), pages 1001-1021, December.
    9. Fenner, Trevor & Levene, Mark & Loizou, George, 2010. "Predicting the long tail of book sales: Unearthing the power-law exponent," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(12), pages 2416-2421.
    10. Meyr, H., 2004. "Supply chain planning in the German automotive industry," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 36062, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    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. MacCarthy, Bart L. & Ovutmen, Tamer, 2015. "Using a central Vehicle Holding Compound (VHC) in an open pipeline automotive order fulfilment system: A simulation study," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 590-601.
    2. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.

    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. 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.
    2. Tolotti, Marco & Yepez, Jorge, 2020. "Hotelling-Bertrand duopoly competition under firm-specific network effects," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 105-128.
    3. Ryo Iwata & Kaoru Kuramoto & Kenyuu Matsumoto & Satoshi Kumagai, 2020. "Extracting Innovative Buyers by Scoring Using Innovator Theory," International Review of Management and Marketing, Econjournals, vol. 10(5), pages 92-102.
    4. 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.
    5. Negahban, Ashkan & Smith, Jeffrey S., 2018. "Optimal production-sales policies and entry time for successive generations of new products," International Journal of Production Economics, Elsevier, vol. 199(C), pages 220-232.
    6. Elmar Kiesling & Markus Günther & Christian Stummer & Lea Wakolbinger, 2012. "Agent-based simulation of innovation diffusion: a review," 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. 20(2), pages 183-230, June.
    7. 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.
    8. Constanza Fosco, 2012. "Spatial Difusion and Commuting Flows," Documentos de Trabajo en Economia y Ciencia Regional 30, Universidad Catolica del Norte, Chile, Department of Economics, revised Sep 2012.
    9. Daria Dzyabura & Srikanth Jagabathula, 2018. "Offline Assortment Optimization in the Presence of an Online Channel," Management Science, INFORMS, vol. 64(6), pages 2767-2786, June.
    10. Edouard Civel & Marc Baudry, 2018. "The Fate of Inventions. What can we learn from Bayesian learning in strategic options model of adoption ?," EconomiX Working Papers 2018-47, University of Paris Nanterre, EconomiX.
    11. Langley, David J. & Hoeve, Maarten C. & Ortt, J. Roland & Pals, Nico & van der Vecht, Bob, 2014. "Patterns of Herding and their Occurrence in an Online Setting," Journal of Interactive Marketing, Elsevier, vol. 28(1), pages 16-25.
    12. Qin, Ruwen & Nembhard, David A., 2012. "Demand modeling of stochastic product diffusion over the life cycle," International Journal of Production Economics, Elsevier, vol. 137(2), pages 201-210.
    13. Yujuico, Emmanuel, 2015. "Considerations in the diffusion of a public traffic app for Metro Manila," Journal of Transport Geography, Elsevier, vol. 42(C), pages 48-56.
    14. Toka, Agorasti & Iakovou, Eleftherios & Vlachos, Dimitrios & Tsolakis, Naoum & Grigoriadou, Anastasia-Loukia, 2014. "Managing the diffusion of biomass in the residential energy sector: An illustrative real-world case study," Applied Energy, Elsevier, vol. 129(C), pages 56-69.
    15. Oded Koenigsberg & Rajeev Kohli & Ricardo Montoya, 2011. "The Design of Durable Goods," Marketing Science, INFORMS, vol. 30(1), pages 111-122, 01-02.
    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. Delre, Sebastiano A. & Panico, Claudio & Wierenga, Berend, 2017. "Competitive strategies in the motion picture industry: An ABM to study investment decisions," International Journal of Research in Marketing, Elsevier, vol. 34(1), pages 69-99.
    18. Ruiz-Conde, Enar & Wieringa, Jaap E. & Leeflang, Peter S.H., 2014. "Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 49-63.
    19. Kocaman, Barış & Gelper, Sarah & Langerak, Fred, 2023. "Till the cloud do us part: Technological disruption and brand retention in the enterprise software industry," International Journal of Research in Marketing, Elsevier, vol. 40(2), pages 316-341.
    20. Fibich, Gadi & Levin, Tomer, 2020. "Percolation of new products," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).

    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:eee:jomega:v:40:y:2012:i:3:p:302-313. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.