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As competition motivates firms to exploit their core competencies, outsourcing takes on greater significance. Increased reliance on supplier capabilities and technologies, however, increases the impact that supplier selection and assessment can have on the buying firm and in particular, its performance. While prior studies of supply management provide considerable evidence of the criteria used by firms to select and assess suppliers, they provide little insight into the relationships between selection and assessment and the buying firm's performance. This research describes an empirical study of attitudes towards supplier selection and assessment of American and European companies and their impact on business performance. Results illustrate that while both American and European managers consider objective selection and assessment criteria such as cost and price to be more important than subjective criteria such as supplier commitment, it is the more subjective criteria that have a greater impact on firm performance. Moreover, while for American companies there are strong relationships between attitudes towards supply management and performance, similar relationships do not appear to hold for European companies.

Very often, manufacturing companies have been faced with the problem of assessment and selection of suppliers for their product development. Some methods and techniques have been developed to assist these companies in performing the assessment. However, these methods and techniques lack tge capability to deal with the instrumental and conceptual uncertainties that are involved in the supplier assessment and selection. Fuzzy expert system is an alternative approach from which the heuristics and knowledge of supplier assessment can be captured and the impreciseness and uncertainties due to the human subjectivity, that are common in the process of the supplier assessment, can be handled. In this paper, a combined scoring method with fuzzy expert systems approach is introduced to perform the supplier assessment. With the use of the fuzzy concept, the error due to human judgement in the scoring method could be minimized. First, current methods and techniques of supplier assessment are reviewed in this paper. There follows the description of a case study of combined scoring method and fuzzy expert systems approach to supplier assessment. Some results of the prototype system trial‐run are discussed in the final part of this paper.

This paper aims to evaluate and prioritize the key supplier selection indicators and to establish the relationship between available alternatives and selected indicators by using step-wise weight assessment ratio analysis (SWARA) and weighted aggregated sum product assessment (WASPAS).

Authors have extracted the supplier selection criteria from literature and used a combined SWARA-WASPAS method to evaluate and rank the criteria’s. SWARA is applied for evaluating and weighting selection criteria, whereas WASPAS helped in evaluating different available alternatives based on supplier selection indicators.

Finding from SWARA suggests that supplier management is the high weighted criteria followed by information sharing and joint actions. WASPAS was used to evaluate the available alternatives and supplier A1 got the highest priority. Additionally, sensitivity analysis indicates the different scenarios for the best supplier selection.

Working executives can use the SWARA for assessment of weights of finalized indicators for their firm in the cement industry. Further, the calculated weights can be used for product and sum weightage through WASPAS to finalize the best supplier.

The originality of the manuscript lies in the sector and methodology. Author(s) applied the SWARA and WASPAS method for supplier selection in the Indian cement industry that will help working executives to evaluate their supply chain partners.

Ground-handling services are important for effective aircraft operations in the air transportation system. Airlines often outsource these services to ground-handling agents through business-to-business (B2B) marketing decisions. Therefore, this paper aims to address the problem of ground-handling agent selection in the airline industry.

A real-world case study was carried out to demonstrate the applicability of the integrated best worst method and fuzzy multi-attribute ideal real comparative analysis (F-MAIRCA) approach to solve ground-handling agent selection problems under uncertainty and imprecision. A two-stage sensitivity analysis was also conducted to ensure the credibility and validity of the application.

In the weighting stage, “Quality” was determined as the most important criterion in terms of supplier performance. With regard to the performance of the ground-handling agents, A2 was found as the optimal supplier in terms of both credibility and validity.

This study enumerated several criteria that ground-handling agents must meet in order to effectively supply services for the airlines. In addition, this study provides a novel framework from which managers can gain additional benefits from their businesses. Finally, it is concluded that this approach will help airline managers quantitatively in choosing the most appropriate ground-handling agent.

The contributions of this study to the existing literature are twofold. First, we propose a novel multiple attribute decision-making approach to address the problem of supplier selection for airlines under uncertainty and imprecision. Second, the selection of ground-handling agents from the B2B perspective is addressed for the first time in literature.

Faced with increasing pressure to improve responsiveness to rapidly changing market needs, firms must respond to the challenge of how to improve supply reliability and quality, while simultaneously reducing costs. This has led to an increase in outsourcing and the adoption of supplier alliances with key suppliers. While much has been written about when and how to form such alliances and the benefits of doing so, little evidence exists of how alliance adopters differ from non‐adopters in their attitudes towards managing suppliers and their efforts to manage quality in the supply process. This study presents results of a survey of supply management professionals that examines attitudes of adopters and non‐adopters of supplier alliances to supplier and quality management. Results indicate that significant differences in attitudes exist between alliance adopters and non‐adopters, and that differences have a direct and significant impact on key measures of a buying firm's business performance.

Using a sample of executing agency executives, donor agency executives and supplying organisation executives, this study aims to identify the critical criteria for the assessment of suppliers in foreign-aid funded procurement in Bangladesh.

An instrument with 32-seven-point (1 – rarely, 7 – mostly) Likert-scaled items was employed to gather data on the level of importance assigned by both buyers and suppliers on each supplier assessment criterion. The importance-performance matrix analysis was conducted to assess the gap in expectations between buyers and suppliers and to organise the assessment criteria into four categories such as “low priority”, “possible killer”, “concentrate here”, and “keep up the good work”.

The results indicate that, to provide better service, suppliers must assign tasks to the knowledgeable sales personnel, provide better warranties with well-known branded products, and ensure a reliable level of quality. The supplier organisations should implement a high calibre management system that allows prompt responses to enquiries and the provision of services without buyers having to follow up.

With careful considerations, the methodology and results of the study could be adapted to design supplier assessment procedure in other developing countries.

This research employs a simple and practical method which purchasing executives will find easy to apply and interpret the findings.

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).

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.

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.

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.

This paper seeks to describe the development of a web‐based system for managing and assessing suppliers, presenting the system design and interface of the prototype and discussing the applicability of the system.

In this paper critical assessment criteria and factors for managing supplier quality (MSQ) were identified through literature review and a mail survey of manufacturers in Hong Kong. Using the Analytic Hierarchy Process methodology, a self‐assessment model comprising these criteria and factors was developed. Industry experts were invited to determine the relative weighting of these criteria and factors. A software was developed to support the assessment system.

The findings in this paper identified criteria addressed strategic alliance, supplier development and supplier monitoring. The critical factors encompassed buyer‐supplier partnership, technology and information sharing, sourcing strategies, supplier evaluation and motivation, and issues on performance measurement and improvement. A self‐assessment model comprising these criteria and factors was developed.

The paper shows that in future work, more best practices of supplier management will be identified to enrich the knowledge base of the system in order to further develop the assessment system to an expert system.

The findings in this paper were incorporated to develop a prototype web‐based system for self‐assessment with promising industrial validation results.

In this paper, a novel self‐assessment system was developed for supplier quality management. It is of great value for quality management theory and practice.

The purpose of this paper is to develop a new composite model using structural equation modelling (SEM) and analytic hierarchy process (AHP) for the selection of suppliers.

In this paper the authors have made an attempt to arrive at the supplier selection score using SEM and AHP. An attempt has been made to develop a new composite model using SEM and AHP technique, based on the survey of 151 respondents. Attributes' weightage are found out using cluster analysis.

Based on the output from the composite model, cluster analysis has been carried out to find out the strengths and weakness of each supplier on the influencing factors. Based on these findings, the supplier can improve on factors where they lag and can maintain the factors where they excel.

In this paper the authors have made an attempt to arrive at the supplier selection score using SEM and AHP.

Industrial organizations often face difficulties in finding out the methods to meet ever increasing customer expectations and to remain competitive in the global market while maintaining controllable expenses. An effective and efficient green supply chain management (GSCM) can provide a competitive edge to the business. This paper focusses on the selection of green suppliers while simultaneously balancing economic, environmental and social issues.

In this study, it is assumed that two types of decision-makers (DMs), namely, the first level and second-level DMs operate at two separate groups in GSC. The first-level DMs always empathise to optimize carbon emissions, per unit energy consumption per product and per unit waste production, while the second-level DMs seek to optimize ordering costs, number of rejected units and number of late delivered units in the entire GSCM. In this paper, fuzzy goal programming (FGP) approach has been adopted to obtain compromise solution of the formulated problem by attaining the uppermost degree of each membership goal while reducing their deviational variables. Furthermore, demand has also been forecasted using exponential smoothing analysis. The model is verified on a real-time industrial case study.

This research enables DMs to analyse uncertainty scenarios in GSCM when information about different parameters are not known precisely.

The proposed model is restricted to vagueness only, however, DMs may need to consider probabilistic multi-choice scenarios also.

The proposed model is generic and can be applied for large-scale GSC environments with little modifications.

No prior attempt is made till date to present interval type-2 fuzzy sets in a multi-objective GSC environment where the DMs are at hierarchical levels. Interval type-2 fuzzy sets are considered as better ways to represent inconsistencies of human judgements, its incompleteness and imprecision more accurately and objectively. Also, crisp or deterministic forms of uncertain parameters have been obtained by taking expected value of the fuzzy parameters.