From Traditional Purchasing to Supplier Management: A Fuzzy Logic-based Approach to Supplier Selection

An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection

Purpose

Supplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).

Design/methodology/approach

The proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.

Findings

A fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.

Originality/value

QFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

Integrating Fuzzy Multiobjective Programming and System Dynamics to Develop an Approach for Talent Retention Policy Selection: Case on Health-Care Industry

The demand for medical services has been increasing yearly in aging countries. Medical institutions must hire a large number of staff members to provide efficient and effective health-care services. Because of high workload and pressure, high turnover rates exist among health-care staff members, especially those in nonurban areas, which are characterized by limited resources and a predominance of elderly people. Turnover in health-care institutions is influenced by complex factors, and high turnover rates result in considerable direct and indirect costs for such institutions (Lo and Tseng 2019). Therefore, health-care institutions must adopt appropriate strategies for talent retention. Because institutions cannot determine the most effective talent retention strategy, many of them simply passively adopt a single human resource (HR) policy and make minor adjustments to the selected policy. In the present study, system dynamics modeling was combined with fuzzy multiobjective programming to develop a method for simulating HR planning systems and evaluating the suitability of different HR policies in an institution. We also considered the external insurance policy to be the parameter for the developed multiobjective decision-making model. The simulation results indicated that reducing the turnover rate of new employees in their trial period is the most effective policy for talent retention. The developed procedure is more efficient, effective, and cheaper than the traditional trial-and-error approaches for HR policy selection.

Development of questionnaire to assess the supplier evaluation criteria and supplier selection benefits

Purpose

The purpose of this paper is to develop an instrument/questionnaire to assess the supplier evaluation (SE) criteria and supplier selection (SS) benefits with their level of importance.

Design/methodology/approach

This paper develops an instrument/questionnaire based on generally accepted principle of instrument design to assess the SE criteria and SS benefits through the responses collected from 34 automobile industries in India. The SE criteria and SS benefits were derived through extensive literature review and expert’s opinion.

Findings

The reliability, normality and validity of developed instrument/questionnaire were determined through the responses collected from the managers of 34 automobile industries in India and are found to be acceptable for most of the SE criteria and SS benefits. The criterion validity is also found to be fairly good for the developed instrument/questionnaire.

Research limitations/implications

While designing the instrument/questionnaire, SE criteria and SS benefits were considered for automobile sector in India through prequestionnaire sheet. Further, research may be required to corroborate these results from larger data sets.

Practical implications

Now a days, it is essential for organizations to rely on their suppliers for their survival and to gain competitive advantage. The well developed and validated instrument/questionnaire can be used for industry practitioners in Indian automobile industries to assess the SE criteria and SS benefits.

Originality/value

An empirically tested instrument/questionnaire is developed first time to assess the SE criteria and SS benefits for automobile sector in India.

A new goal-directed benchmarking for supplier selection in the presence of undesirable outputs

Purpose

– In this paper, the authors extend the goal-directed benchmarking theory proposed by Stewart for benchmarking and selecting suppliers. This extension is in recognition of the fact that benchmarking for suppliers is more than a pure monitoring process and includes a component of future planning. The paper aims to discuss these issues.

Design/methodology/approach

– In this paper, the proposed model utilizes a goal programming structure to find points on the efficient frontier which are realistically attainable by suppliers in the presence of undesirable outputs, but at the same time achieving a closer method to long-term organizational goals (as distinct from the local performance of individual suppliers).

Findings

– The contributions of the current paper are as follows: the proposed model considers undesirable outputs in the context of goal-directed benchmarking. The proposed model does not demand weights from the decision maker. The proposed model can be easily computerized, enabling it to serve as a decision making tool to assist decision makers. For the first time, the proposed model is applied for the supplier selection and benchmarking.

Originality/value

– To the best of knowledge of the authors, there is not any reference that discusses supplier selection problem and benchmarking in the presence of undesirable outputs in the context of goal-directed benchmarking.