Practice and promise of formal supplier selection: a study of four empirical cases

Structural transformation of fuzzy analytical hierarchy process: a relevant case for Covid-19

Covid-19 has posed difficult and challenging situations to the supply chains and companies are in fix how to choose the vendors under the uncertainty and complexity in recent years. Therefore, this research aims to incorporate structural transformation of the fuzzy analytical hierarchy process (FAHP) that is most appropriate for the uncertainty and disruption caused by Covid-19 like situation for ensuring supplies from vendors. The conventional approaches for vendor selection and evaluation use numerous multi-criteria decision-making tools that may not ensure reliability in a dynamic situation caused due to Covid-19. In this research, Fleiss’ Kappa method ensures the reliability of responses from eight respondents by using pairwise comparisons and assigning weights as envisaged in FAHP. In addition to determine the reliability of responses, a step under FAHP has been altered. This alteration is demonstrated in the vendor selection case in the Covid-19 scenario. The research suggests a plausible system required to address the uncertainties associated with Covid-19 to select and evaluate vendors by modifying a FAHP. The proposed altered mechanism can be incorporated in a similar type of other decision-making circumstances such as Covid-19, where the decision-makers are more than one, and the situation is very dynamic. The study is likely to facilitate information management, algorithmic development in decision making, or machine-driven decisions in uncertain conditions. The study offers managerial implications to purchase managers to accommodate and combine multiple factors and responses concerning the vendor performances for their evaluation, thus making a process more reliable.

Integrated Multicriteria Decision-Making Methods to Solve Supplier Selection Problem: A Case Study in a Hospital

In supply chain literature, supplier evaluation and selection problem is one of the most studied subjects because of the significant roles of suppliers in terms of the chain's sustainability and profitability. Therefore, it is important for organizations to adopt a systematic way to evaluate and select the best supplier according to their respective criteria in today's competitive environment. Multicriteria decision-making methods provide for this need of organizations because determination of an appropriate supplier selection is a multicriteria decision-making (MCDM) problem essentially. Although a lot of applications of these methods for supplier evaluation and selection can be seen in the literature, studies in the health-care sector are insufficient. Hospitals in the health-care sector also have to consider their supplier-related decisions to decrease risks and threads which affect their effectiveness. The aim of this study was to fill this gap by providing different hybrid models for selecting the best supplier for hospitals. Supplier evaluation and selection process start with recognizing the related criteria according to the studies in the literature. Analytic hierarchy process (AHP) method is deployed to weight the criteria, and suppliers are listed via technique for order preference by similarity to ideal solution (TOPSIS), elimination and choice translating reality English (ELECTRE), grey relational analysis (GRA), and simple additive weighting (SAW) methods. The main aim of this study was to present different hybrid MCDM methods and show their efficiency and consistency with each other. In this study, hybrid multicriteria decision-making models (AHP-TOPSIS, AHP-ELECTRE, AHP-GRA, and AHP-SAW) are presented and compared. The results show that the presented hybrid methods in this study are consistent with each other and give the same ranking for the selection of the best supplier. It can be considered as a useful guideline for hospitals.

Supplier selection using grey theory: a case study from Indian banking industry

Purpose

– As the suppliers of any organization are considered as the strategic partners and taken as the integral part of the supply chain network, hence it is very crucial decision to select the suppliers in order to get the competitive edge. Whenever, any organization select its suppliers then organization evaluates every supplier with respect to certain criteria, which are already listed in the organization’s policies. Since supplier selection is based on the evaluation of various attributes of each alternative; therefore this problem is a multi-attribute decision-making (MADM) problem. The purpose of this paper is to propose a model for selecting the best supplier.

Design/methodology/approach

– This paper reports the implementation of grey theory to choose the appropriate supplier with uncertain information. Grey values have been used to give the ratings and weightage to various criteria which are being used to evaluate the different supplier alternatives. And finally the grey possibility degree has been calculated to rate the various alternatives.

Findings

– This paper proposed a MADM model based on grey theory to select the optimal supplier and finally, the proposed model has been applied to select the best supplier for “optimizing digital banking” in the Indian context.

Research limitations/implications

– The selection criteria selected here through literature review may not fit the whole industry and moreover this paper can be extended into the field where multiple-supplier selection is required, like in manufacturing sector where the authors cannot rely always on single supplier. So, in that case the authors need to pick more than one best alternatives.

Practical implications

– The grey theory approach can be applied almost all the services industries, where the exact information about the suppliers in quantitative terms is very difficult to find. So the authors can use the grey numbers to rate the suppliers.

Social implications

– Since, the coming generation is more dependent on the internet banking, so it becomes very much necessary for the banking sector to update the existing system. Due to lack in technical skills, outsourcing the information technology and software development is the best option. Hence, Grey theory based model can be used in selecting the best supplier under uncertain information.

Originality/value

– Very few studies have been done in India using grey theory approach for supplier selection and moreover, to the best knowledge of the authors’ this is the first study which employs grey theory for selecting the best supplier in banking industry. Moreover the digital banking system is the future of banking industry, so every player should provide the digital banking structure in order to survive in the market.

TECHNOLOGY SELECTION FROM ALTERNATIVES: A SCORING MODEL FOR SCREENING CANDIDATES IN EQUIPMENT PURCHASING

This paper presents a technique to aid decision-making in certain technology selection projects. It describes a scoring model for screening and selecting candidates, suitable for simple cases such as equipment purchase projects. This model considers for each possible alternative its technological performance together with commercial aspects, and analyzes the results on a single "score". The main advantage of the proposed technique is that it is easy to understand and use, while not very time and effort consuming. An example of a real technology selection project from the iron and steel industry is also presented to illustrate the proposed framework.