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Article Dans Une Revue Computers & Industrial Engineering Année : 2022

A 2-phase interdependent methodology for sustainable project portfolio planning in the pharmaceutical industry

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Résumé

In response to the increasing awareness of sustainability issues, companies have reevaluated their approach to research and development (R&D). Taking into account the long-term effects and consequences of R&D projects on social, economic, and environmental conditions, this research has presented a comprehensive methodology for planning pharmaceutical holding company project portfolios by considering both sustainability dimensions and profitability objectives. The first phase of the developed methodology consists of a new combined MCDM method that is used to determine the sustainability score of each project. The following phase focuses on developing a bi-level bi-objective optimization model that is designed to take into account the decentralized structure of pharmaceutical holdings to optimize the budgeting, selection, and scheduling of projects. This optimization model proposes that the head office of the holding company as leader allocates R&D budgets between subsidiaries as followers to maximize the holding company's profit and sustainability. In contrast, the followers are responsible for selecting and scheduling research projects. We examine the optimal strategy of each actor using an illustrative case to validate the methodology. Based on experimental results, an approach focusing on sustainability versus profitability (or vice versa) has a significant impact on decisions made at each level of operation. The results reveal that the proposed approach can be adopted by the holding companies to improve the performance of portfolio planning from the sustainability perspective.
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Dates et versions

hal-03895283 , version 1 (12-12-2022)

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Citer

Faraz Salehi, S. Mohammad J. Mirzapour Al-E-Hashem, S. Mohammad Moattar Husseini. A 2-phase interdependent methodology for sustainable project portfolio planning in the pharmaceutical industry. Computers & Industrial Engineering, 2022, 174, pp.108794. ⟨10.1016/j.cie.2022.108794⟩. ⟨hal-03895283⟩
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