IDEAS home Printed from https://ideas.repec.org/a/taf/tprsxx/v55y2017i13p3862-3885.html
   My bibliography  Save this article

An integrated framework for product line design for modular products: product attribute and functionality-driven perspective

Author

Listed:
  • Mohit Goswami
  • Yash Daultani
  • M.K. Tiwari

Abstract

The purpose of this research is to facilitate original equipment manufacturers operating in a single market segment to frame their product line design strategy that pertains to offering right product attributes with right attribute level in the right product profile within a market segment. Through this research, we attempt to establish a link between functional level design of product attributes with commercial objectives of the enterprise. Initially, by deriving the functional importance of product attribute levels of individual product attributes within a product profile, demand and functional importance data are generated. Utilising the function-based cost estimating framework and multi-linear regression methodology, we determine the cost and product development time coefficients for respective product attributes. Finally, a mixed integer quadratic programming-based mathematical formulation is developed that includes maximisation of product premium and minimisation of various costs as major objectives under the assumption that manufacturer seeks to offer optimal number of product profiles within the market segment. Employing the commercial solver LINGO, the integrated framework is solved. The entire framework is illustrated using the operator cabin of heavy construction machinery.

Suggested Citation

  • 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.
    • Handle: RePEc:taf:tprsxx:v:55:y:2017:i:13:p:3862-3885
    DOI: 10.1080/00207543.2017.1314039
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207543.2017.1314039
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207543.2017.1314039?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. Michalek, Jeremy J. & Ebbes, Peter & Adigüzel, Feray & Feinberg, Fred M. & Papalambros, Panos Y., 2011. "Enhancing marketing with engineering: Optimal product line design for heterogeneous markets," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 1-12.
    2. Gregory Dobson & Shlomo Kalish, 1988. "Positioning and Pricing a Product Line," Marketing Science, INFORMS, vol. 7(2), pages 107-125.
    3. Albritton, M. David & McMullen, Patrick R., 2007. "Optimal product design using a colony of virtual ants," European Journal of Operational Research, Elsevier, vol. 176(1), pages 498-520, January.
    4. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    5. Hans Sebastian Heese & Jayashankar M. Swaminathan, 2006. "Product Line Design with Component Commonality and Cost-Reduction Effort," Manufacturing & Service Operations Management, INFORMS, vol. 8(2), pages 206-219, May.
    6. G. E. Fruchter & A. Fligler & R. S. Winer, 2006. "Optimal Product Line Design: Genetic Algorithm Approach to Mitigate Cannibalization," Journal of Optimization Theory and Applications, Springer, vol. 131(2), pages 227-244, November.
    7. 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.
    8. Liang Guo & Juanjuan Zhang, 2012. "Consumer Deliberation and Product Line Design," Marketing Science, INFORMS, vol. 31(6), pages 995-1007, November.
    9. Kyle D. Chen & Warren H. Hausman, 2000. "Technical Note: Mathematical Properties of the Optimal Product Line Selection Problem Using Choice-Based Conjoint Analysis," Management Science, INFORMS, vol. 46(2), pages 327-332, February.
    10. Richard D. McBride & Fred S. Zufryden, 1988. "An Integer Programming Approach to the Optimal Product Line Selection Problem," Marketing Science, INFORMS, vol. 7(2), pages 126-140.
    11. Rajeev Kohli & R. Sukumar, 1990. "Heuristics for Product-Line Design Using Conjoint Analysis," Management Science, INFORMS, vol. 36(12), pages 1464-1478, December.
    12. A. Ye(scedilla)im Orhun, 2009. "Optimal Product Line Design When Consumers Exhibit Choice Set-Dependent Preferences," Marketing Science, INFORMS, vol. 28(5), pages 868-886, 09-10.
    13. John E. Ettlie, 1995. "Product-Process Development Integration in Manufacturing," Management Science, INFORMS, vol. 41(7), pages 1224-1237, July.
    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. Gauss, Leandro & Lacerda, Daniel P. & Cauchick Miguel, Paulo A., 2022. "Market-Driven Modularity: Design method developed under a Design Science paradigm," International Journal of Production Economics, Elsevier, vol. 246(C).
    2. Leandro Gauss & Daniel P. Lacerda & Paulo A. Cauchick Miguel, 2021. "Module-based product family design: systematic literature review and meta-synthesis," Journal of Intelligent Manufacturing, Springer, vol. 32(1), pages 265-312, January.

    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. Michalek, Jeremy J. & Ebbes, Peter & Adigüzel, Feray & Feinberg, Fred M. & Papalambros, Panos Y., 2011. "Enhancing marketing with engineering: Optimal product line design for heterogeneous markets," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 1-12.
    2. Winfried Steiner & Harald Hruschka, 2002. "A Probabilistic One-Step Approach to the Optimal Product Line Design Problem Using Conjoint and Cost Data," Review of Marketing Science Working Papers 1-4-1003, Berkeley Electronic Press.
    3. Bechler, Georg & Steinhardt, Claudius & Mackert, Jochen & Klein, Robert, 2021. "Product line optimization in the presence of preferences for compromise alternatives," European Journal of Operational Research, Elsevier, vol. 288(3), pages 902-917.
    4. Dimitris Bertsimas & Velibor V. Mišić, 2017. "Robust Product Line Design," Operations Research, INFORMS, vol. 65(1), pages 19-37, February.
    5. Pantourakis, Michail & Tsafarakis, Stelios & Zervoudakis, Konstantinos & Altsitsiadis, Efthymios & Andronikidis, Andreas & Ntamadaki, Vasiliki, 2022. "Clonal selection algorithms for optimal product line design: A comparative study," European Journal of Operational Research, Elsevier, vol. 298(2), pages 585-595.
    6. Hongmin Li & Scott Webster & Gwangjae Yu, 2020. "Product Design Under Multinomial Logit Choices: Optimization of Quality and Prices in an Evolving Product Line," Manufacturing & Service Operations Management, INFORMS, vol. 22(5), pages 1011-1025, September.
    7. Kraus, Ursula G. & Yano, Candace Arai, 2003. "Product line selection and pricing under a share-of-surplus choice model," European Journal of Operational Research, Elsevier, vol. 150(3), pages 653-671, November.
    8. Schön, Cornelia, 2010. "On the product line selection problem under attraction choice models of consumer behavior," European Journal of Operational Research, Elsevier, vol. 206(1), pages 260-264, October.
    9. Day, Jamison M. & Venkataramanan, M.A., 2006. "Profitability in product line pricing and composition with manufacturing commonalities," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1782-1797, December.
    10. Dimitris Bertsimas & Velibor V. Mišić, 2019. "Exact First-Choice Product Line Optimization," Operations Research, INFORMS, vol. 67(3), pages 651-670, May.
    11. Sarangi, Subrat & Chakraborty, Abhishek & Triantis, Konstantinos P., 2021. "Multimarket competition effects on product line decisions – A multi-objective decision model in fast moving consumer goods industry," Journal of Business Research, Elsevier, vol. 133(C), pages 388-398.
    12. Tallys H. Yunes & Dominic Napolitano & Alan Scheller-Wolf & Sridhar Tayur, 2007. "Building Efficient Product Portfolios at John Deere and Company," Operations Research, INFORMS, vol. 55(4), pages 615-629, August.
    13. Dimitris Bertsimas & Velibor V. Mišić, 2017. "Robust Product Line Design," Operations Research, INFORMS, vol. 65(1), pages 19-37, February.
    14. Wilhelm, Wilbert E. & Xu, Kaihong, 2002. "Prescribing product upgrades, prices and production levels over time in a stochastic environment," European Journal of Operational Research, Elsevier, vol. 138(3), pages 601-621, May.
    15. 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.
    16. Xinfang (Jocelyn) Wang & Jeffrey D. Camm & David J. Curry, 2009. "A Branch-and-Price Approach to the Share-of-Choice Product Line Design Problem," Management Science, INFORMS, vol. 55(10), pages 1718-1728, October.
    17. Evan Rash & Karl Kempf, 2012. "Product Line Design and Scheduling at Intel," Interfaces, INFORMS, vol. 42(5), pages 425-436, October.
    18. Miller, Christopher M. & Smith, Stephen A. & McIntyre, Shelby H. & Achabal, Dale D., 2010. "Optimizing and Evaluating Retail Assortments for Infrequently Purchased Products," Journal of Retailing, Elsevier, vol. 86(2), pages 159-171.
    19. Andrade, Xavier & Guimarães, Luís & Figueira, Gonçalo, 2021. "Product line selection of fast-moving consumer goods," Omega, Elsevier, vol. 102(C).
    20. Tan Wang & Genaro Gutierrez, 2022. "Robust Product Line Design by Protecting the Downside While Minding the Upside," Production and Operations Management, Production and Operations Management Society, vol. 31(1), pages 194-217, January.

    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:55:y:2017:i:13:p:3862-3885. 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: 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.