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A bi-objective game-theoretic model for collaboration formation between software development firms

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  • Muhammad Fahimullah
  • Yasir Faheem
  • Naveed Ahmad

Abstract

Requirement for formation of collaborations has been on increase for the software development industry, especially for smaller to medium sized firms, due to rapid technological advancements, requirements for diversified skills, ever enhancing demands for innovation and fierce competition. Collaborative product development in an alliance enables the firms to benefit from each other’s diversified skills and the experience as a result of which they can develop products more rapidly and of better quality as well resulting in a higher payoff. Also, the development costs decrease. However, to avoid undesired results, selection of an appropriate partner firm for collaboration is of utmost importance keeping in view the objectives of alliance formation of both the strategic partners. One-way partner selection techniques available in the literature are impractical as they enable a firm to rank potential partners only from its own perspective while ignoring their objectives. This problem is addressed by the two-way partner selection techniques, however, they either ignore the payoff distribution criteria or the proposed criteria is unfair. More importantly, existing techniques consider that firm collaborate only with the objective to enhance their financial payoff which might not always be the case. The fact that collaborating firms may have one but different objectives for collaboration, or, each may have multiple objectives is largely neglected. To address the scenarios in which firms may collaborate due to multiple and possibly different objectives, this work proposes a bi-objective game-theoretic model that enables a firm to select an appropriate partner based on the individual preferences of both on the following two objectives: 1) learning and 2) financial revenue. Moreover, this model calculates the pay-off that each firm should get whether only monetary, only in the form of learning or both. The calculation of payoff share is based on the following parameters: 1) individual goals of collaboration of partner selecting firms on the said two objectives, 2) their level of cost contribution, 3) cooperation ratio and 4) knowledge investment difference. Comprehensive analysis of various scenarios is done for the proposed Nash Bargaining payoff distribution model to find the optimum strategy of collaborating firms for each scenario.

Suggested Citation

  • Muhammad Fahimullah & Yasir Faheem & Naveed Ahmad, 2019. "A bi-objective game-theoretic model for collaboration formation between software development firms," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-19, July.
  • Handle: RePEc:plo:pone00:0219216
    DOI: 10.1371/journal.pone.0219216
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    References listed on IDEAS

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    1. Sreekumar R. Bhaskaran & V. Krishnan, 2009. "Effort, Revenue, and Cost Sharing Mechanisms for Collaborative New Product Development," Management Science, INFORMS, vol. 55(7), pages 1152-1169, July.
    2. Feng, Bo & Fan, Zhi-Ping & Ma, Jian, 2010. "A method for partner selection of codevelopment alliances using individual and collaborative utilities," International Journal of Production Economics, Elsevier, vol. 124(1), pages 159-170, March.
    3. Goyal, Sanjeev & Joshi, Sumit, 2003. "Networks of collaboration in oligopoly," Games and Economic Behavior, Elsevier, vol. 43(1), pages 57-85, April.
    4. Robin Cowan & Nicolas Jonard & Jean-Benoit Zimmermann, 2007. "Bilateral Collaboration and the Emergence of Innovation Networks," Management Science, INFORMS, vol. 53(7), pages 1051-1067, July.
    5. Cai, Gangshu & Kock, Ned, 2009. "An evolutionary game theoretic perspective on e-collaboration: The collaboration effort and media relativeness," European Journal of Operational Research, Elsevier, vol. 194(3), pages 821-833, May.
    6. Jafar Rezaei, 2015. "A two-way approach to supply chain partner selection," International Journal of Production Research, Taylor & Francis Journals, vol. 53(16), pages 4888-4902, August.
    7. Wilfred Amaldoss & Richard Staelin, 2010. "Cross-Function and Same-Function Alliances: How Does Alliance Structure Affect the Behavior of Partnering Firms?," Management Science, INFORMS, vol. 56(2), pages 302-317, February.
    8. Jing Li & Wei Liu & He Zhang, 2016. "Profit-sharing and investment strategies of a one-leader-one-follower R%D alliance with industrialisation risks," International Journal of Product Development, Inderscience Enterprises Ltd, vol. 21(2/3), pages 175-189.
    9. Masao Nakamura & Mariko Sakakibara, 2003. "Knowledge sharing in cooperative research and development," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 24(2-3), pages 117-132.
    10. Keeeun Lee & Inchae Park & Byungun Yoon, 2016. "An Approach for R&D Partner Selection in Alliances between Large Companies, and Small and Medium Enterprises (SMEs): Application of Bayesian Network and Patent Analysis," Sustainability, MDPI, vol. 8(2), pages 1-18, January.
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