IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v54y2016i23p6997-7013.html
   My bibliography  Save this article

An integrated Bayesian-Game theoretic approach for product portfolio planning of a multi-attributed product in a duopolistic market

Author

Listed:
  • Mohit Goswami
  • Saurabh Pratap
  • S.K. Kumar

Abstract

The focus of this paper is to develop a Bayesian-Game theoretic framework for product portfolio planning problem thereby aiding the manufacturers operating across variety of product industries to offer the right product portfolio set. The problem is modelled for a duopolistic market and the product type considered is characterised by multiple product attributes having varying attribute levels. Initially, feasible product portfolio candidates are generated in terms of combinations of different product attributes and their attribute levels employing the attribute compatibility constraint. Different product portfolio sets thus generated function as different product offering strategies of the two manufacturers. Thereafter, employing the function-based cost-estimating framework and multi-linear regression methodology, manufacturing costs and product premiums, respectively, are estimated for different product portfolios. Utilising the Bayesian risk network, the purchase probabilities are estimated in high, medium and low-risk states for various product portfolios. The purchase probability is made a function of price and functionality. The purchase probabilities thus obtained acts as an input to the final pay-off calculation. Finally, employing these pay-off values, product offering scenarios are populated for the two manufacturers both in equilibrium and non-equilibrium state.

Suggested Citation

  • Mohit Goswami & Saurabh Pratap & S.K. Kumar, 2016. "An integrated Bayesian-Game theoretic approach for product portfolio planning of a multi-attributed product in a duopolistic market," International Journal of Production Research, Taylor & Francis Journals, vol. 54(23), pages 6997-7013, December.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:23:p:6997-7013
    DOI: 10.1080/00207543.2016.1150614
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2016.1150614
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2016.1150614?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.

    Citations

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


    Cited by:

    1. Van den Broeke, Maud & Boute, Robert & Cardoen, Brecht & Samii, Behzad, 2017. "An efficient solution method to design the cost-minimizing platform portfolio," European Journal of Operational Research, Elsevier, vol. 259(1), pages 236-250.
    2. Mohit Goswami & Yash Daultani & M.K. Tiwari, 2017. "An integrated framework for product line design for modular products: product attribute and functionality-driven perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 55(13), pages 3862-3885, July.
    3. Yuskevich, Ilya & Smirnova, Ksenia & Vingerhoeds, Rob & Golkar, Alessandro, 2021. "Model-based approaches for technology planning and roadmapping: Technology forecasting and game-theoretic modeling," Technological Forecasting and Social Change, Elsevier, vol. 168(C).
    4. Thyago Celso Cavalcante Nepomuceno & Késsia Thais Cavalcanti Nepomuceno & Thiago Poleto & Victor Diogho Heuer de Carvalho & Ana Paula Cabral Seixas Costa, 2022. "When Penalty Fails: Modeling Contractual Misincentives With Evidence From Portugal ITO Agreements," SAGE Open, , vol. 12(4), pages 21582440221, December.

    More about this item

    Statistics

    Access and download statistics

    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:taf:tprsxx:v:54:y:2016:i:23:p:6997-7013. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TPRS20 .

    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.