Author(s)

Shirin Noei¹, Arman Sargolzaei², Kang Yen³, Saman Sargolzaei^4,5, Nansong Wu⁶

¹Department of Civil and Environmental Engineering, University of Florida, Gainesville, FL, USA.
²Department of Electrical Engineering, Florida Polytechnic University, Lakeland, FL, USA.
³Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA.
⁴Rancs Group LLC, Wilmington, DE, USA.
⁵Department of Neurosurgery, University of California at Los Angeles, Los Angeles, CA, USA.
⁶Department of Electrical Engineering, Arkansas Tech University, Russellville, AR, USA.

A supply chain network coordinates flow of components from different suppliers to enhance a product that meets customers’ value expectations. Traditionally, companies consider price, quality, and lead time for selecting appropriate suppliers. Increasing environmental concerns, government regulations, and long-term profitability have forced companies to reduce pollution. In addition, in a complex business environment, supply managers should have flexibility skills to act entrepreneurially. Being ecopreneur is a paradigm modification from being a green supplier and entrepreneur toward global economy and sustainability. Although ecopreneur selection is a strategic key to project success, construction industry lacks a systematic approach for decision-making processes. When historical data are not available or adequate, subjective judgment of experts is the only source of information for decision. Fuzzy logic helps decision makers to translate qualitative terms into quantitative information, whereas TOPSIS method ranks alternatives according to their relative distance to the ideal solution. This paper aims to rank ecopreneurs according to the criteria for green entrepreneur selection. In this case, construction-related experts are interviewed to first rate the importance of each criterion as their point of view, and then rate performance of each candidate in accordance to the most important criteria for ecopreneur selection. The final response is expressed based on the average of new variants of fuzzy TOPSIS each using a different fuzzy similarity measure. A numerical example is also presented to illustrate the process in detail.

Supply Chain Management, Ecopreneur Selection, New Variants of Fuzzy TOPSIS, Similarity Measure

Noei, S. , Sargolzaei, A. , Yen, K. , Sargolzaei, S. and Wu, N. (2017) Ecopreneur Selection Using Fuzzy Similarity TOPSIS Variants. American Journal of Industrial and Business Management, 7, 864-880. doi: 10.4236/ajibm.2017.77061.