Intelligent evaluation of suppliers using extent fuzzy TOPSIS method: A case study of an Indian manufacturing SME

Abstract

Purpose

In a developing economy like India, the contribution of small- and medium-sized enterprises (SMEs) to the national gross domestic product is significant. This sector creates immense employment opportunities and produces economic products and services. To survive in the globalized marked condition, it is essential for SMEs to be competitive on several fronts such as quality, cost, delivery, lead time, flexibility, etc. Hence, it is imperative for them to have a sound supplier base. Therefore, supplier selection problem (SSP) has a vital role to play in supply chain management of SMEs. The paper aims to discuss these issues.

Design/methodology/approach

However, SSP has now become a significant challenge to address due to the complexity, vagueness and various criteria involved in it. Recently, fuzzy Technique for Order Performance by Similarity to Ideal Solution method has been widely used to tackle such problems.

Findings

The present paper aims at developing an intelligent system for SSP, which can consider the multiple criteria and the uncertainty aspects in the decision process. A case study of a small-scale manufacturing company has been presented.

Practical implications

This study provides a guideline for SME sector to implement intelligent systems for supplier selection decision-making problems. Case application concludes that this model improves firm’s decision making and suppliers’ performance.

Originality/value

The proposed intelligent model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment. And it also provides an opportunity for supplier improvement.

Citation

Yadav, V., Sharma, M.K. and Singh, S. (2018), "Intelligent evaluation of suppliers using extent fuzzy TOPSIS method: A case study of an Indian manufacturing SME", Benchmarking: An International Journal, Vol. 25 No. 1, pp. 259-279. https://doi.org/10.1108/BIJ-07-2016-0114