Title
A private sustainable partner selection model for green public-private partnerships and regional economic development
Document Type
Article
Publication Date
10-1-2022
DOI
10.1016/j.seps.2021.101189
Abstract
Many cities are struggling to keep pace with limited budgets and rapid growth. Economic development models involving public-private partnerships (P3s) can help drive economic revitalization. The choice of partners plays a vital role in the success or failure of sustainable P3 initiatives. In this study, we propose a novel integrated sustainable private partner selection framework in P3s. The proposed model is composed of the best-worst method (BWM), the weighted influence non-linear gauge system (WINGS), and the technique of order preference similarity to the ideal solution (TOPSIS). The BWM is used to identify the importance weights of the economic, environmental, social, and technological criteria. The WINGS method uses ideographic causal maps to analyze the intertwined criteria and their causal relations. TOPSIS is used to rank and select the private partners that will bring the “best value” to the partnership. We demonstrate the proposed method's applicability in a P3 initiative for sustainability, gentrification and neighborhood revitalization, and economic development in a northeastern US city. In this initiative, low density, low cost, and biodegradable agricultural waste and mushroom fibers are grown in vacant buildings to be used as a Styrofoam packaging replacement.
Language
English
Recommended Citation
Tavana, Madjid; Nasr, Arash Khalili; Mina, Hassan; and Michnik, Jerzy, "A private sustainable partner selection model for green public-private partnerships and regional economic development" (2022). Business Systems and Analytics Faculty Work. 16.
https://digitalcommons.lasalle.edu/bsa_faculty/16
Comments
Tavana, M., Khalili Nasr, A., Mina, H. and Michnik, J. (2022) ‘A Private Sustainable Partner Selection Model for Green Public-Private Partnerships and Regional Economic Development,’ Socio-Economic Planning Sciences, Vol. 83, Article 101189.