A Model for Strategic Supplier Selection

A comprehensive theoretical framework for sustainable network contracts: Contracting dimensions and Contract classification

Disruptions in the supply chains/networks result in both performance failures and a poor return on investment (ROI) of network assets. We propose that addressing this situation requires the governance of exchange relationships through contracts guided by sustainability principles. Specifically, we refer to these contracts in the supply and distribution context as "sustainable network contracts", and the overall framework as the "sustainable contracting framework (SCF)/theory". Despite the critical role of sustainable network contracts for all key stakeholders in the network, we identify a gap in the existing literature regarding the theory of sustainable network contracts. We bridge this gap by extending the extant dimensions of contracts, as described in Transaction Cost Economics and Relational Exchange Theory, to include sustainability dimensions - constituting the 'what' of theory building. To inform sustainable contracts, we propose and employ three factors: costs, benefits, and risks (CBR). We present the 'how' of the theory building, outlined in a five-step approach along with an analytical tool, to demonstrate the practical application of our framework. Additionally, we provide a rationale for adopting sustainable network contracts (the 'why' of the theory building). Our research methodology involves collecting interview-based data from senior executives (CXOs) (secondary and primary), collecting primary and secondary cost data (objective), integrating behavioral elements (subjective), and employing constrained optimization techniques to determine quantity allocation under various contract policies. Further, we map the proposed eight distinct contract types onto the CBR-space, thereby highlight the relevance of the contract types to real-world practices. This mapping considers network externalities, risks, and allows for a coordinated sustainable approach to contracting from the buyer's (retailer's) perspective. For managers, our framework would serve as an important tool that would inform the contract evaluation process, facilitate local versus global decision-making, safeguard network investments, and help align the interests of buyers and suppliers in each contracting cycle.

Supplier Selection through Multicriteria Decision-Making Algorithmic Approach Based on Rough Approximation of Fuzzy Hypersoft Sets for Construction Project

The suppliers play a significant role in supply chain management. In supplier selection, factors like market-based exposure, community-based reputation, trust-based status, etc., must be considered, along with the opinions of hired experts. These factors are usually termed as rough information. Most of the literature has disregarded such factors, which may lead to a biased selection. In this study, linguistic variables in terms of triangular fuzzy numbers (TrFn) are used to manage such kind of rough information, then the rough approximations of the fuzzy hypersoft set (FHS-set) are characterized which are capable of handling such informational uncertainties. The FHS-set is more flexible as well as consistent as it tackles the limitation of fuzzy soft sets regarding categorizing parameters into their related sub-classes having their sub-parametric values. Based on these rough approximations, an algorithm is proposed for the optimal selection of suppliers by managing experts’ opinions and rough information collectively in the form of TrFn-based linguistic variables. To have a discrete decision, a signed distance method is employed to transform the TrFn-based opinions of experts into fuzzy grades. The proposed algorithm is corroborated with the help of a multi-criteria decision-making application to choose the best supplier for real estate builders. The beneficial facets of the put forward study are appraised through its structural comparison with few existing related approaches. The presented approach is consistent as it is capable to manage rough information and expert’s opinions about suppliers collectively by using rough approximations of FHS-set.

Evaluation of the Efficiency in Public Health Centers in Greece Regarding the Human Resources Occupied: A Bootstrap Data Envelopment Analysis Application

In this paper, the overall efficiency of health centers in Greece is measured by applying the input-oriented model of Data Envelopment Analysis. In addition, four different models were subjected to the input-oriented Data Envelopment Analysis to investigate the contribution of each category of human resources to the efficiency results of the health centers. The bootstrap technique was performed to generate confidence intervals for the models. Data for 155 health centers in Greece were provided by the Ministry of Health. The health centers submitted in the analysis obtained an average efficiency value of 0.932. The average results of the partial models in terms of each input show that the efficiency values achieved by the health centers are mostly influenced by the number of physicians and the number of managers employed. The second factor influencing the efficiency values of the health centers are the number of nursing staff occupied in the health centers. Non-medical staff employed in the health centers had the least contribution to the efficiencies measured. This paper provides important information for the stakeholders and the Government of Greece so as to better allocate the personnel employed in primary health care according to the efficiencies attained by the health centers.

Total productivity change of Health Centers in Greece in 2016-2018: a Malmquist index data envelopment analysis application for the primary health system of Greece

BACKGROUND

This paper attempts to evaluate the primary health care system by evaluating health centres in Greece.

METHODS

Malmquist Index Data Envelopment Analysis is applied to study the total productivity of 155 health centres in Greece during 2016-2018. The data were collected from the Ministry of Health and submitted to quality tests to ensure validity and avoid bias.

RESULTS

This paper measures the productivity of each of the 155 health centres in Greece and how it shifted during 2016-2018. In addition, the overall productivity change of the 155 health centres over time is calculated and analysed as being due to technical efficiency or technological efficiency. The analysis of the mean values showed a decrease of 0.9% in the overall productivity factor from 2016 to 2017 and a decrease of 5.2% from 2017 to 2018. The overall decrease in the productivity of the 155 health centres was 3.1%. From 2016 to 2018, 59 health centres changed their productivity mainly due to technological change and 91 changed mainly due to technical efficiency change. One health centre showed regression to its total productivity due to equal regression of its technical efficiency and technology.

CONCLUSIONS

The method used is nonparametric data envelopment analysis along with the Malmquist index to include panel data in the analysis. Meaningful results were extracted by indicating the number of health centres that improved their productivity, regressed in productivity, or remained constant through the period 2016-2018. This paper may contribute to improving health centres' efficiency and productivity. Furthermore, valuable results can be extracted for the National Health Care System to match available resources that correspond to each health centre's needs, as well as for manager planners and stakeholders in primary health care.

Improving logistics supplier selection process using lean six sigma – an action research case study

Purpose

Outsourcing logistical activities have become a widely used approach for firms to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages. Lean six sigma (LSS) has been accepted globally across sectors as a management strategy for achieving process excellence. The purpose of this paper is to feature the application of LSS for improving the supplier selection process (SSP) of outsourced logistics services in a multinational health-care company.

Design/methodology/approach

This study is based on an action research case study conducted on the SSP of the freight and distribution department in a multinational health-care company. This paper reports on the application of the LSS define-measure-analyze-improve-control (DMAIC) approach for reducing supplier selection lead time.

Findings

The study features a real-world case study of the LSS DMAIC application to improve the supplier selection process of a large health-care company. The key issues that were identified are lack of information visibility, top-down changes and unclear communication lines. To counteract these three root causes, the lean six sigma techniques that are implemented are the 5S, stakeholder analysis and standard operating procedure.

Research limitations/implications

This research provided empirical evidence of how practical challenges in SSP can be managed with the use of LSS. It further proposed plausible solutions for reducing and sustaining improved outcomes. As the study is limited to one case, the validity of the results can be improved by including more organisations and more case studies from other similar organisations.

Originality/value

Research in supplier selection processes rarely links continuous improvement ideology such as LSS to support strategic selection and procurement of logistics services. This paper could serve as a resource for both practitioners to derive useful implications and to academicians as it contributes to the LSS body of knowledge for further theory testing.

Analytic Hierarchy Process-Based Airport Ground Handling Equipment Purchase Decision Model

The Airport ground handling services (AGHS) equipment supplier provider selection requires a safety guarantee in terms of the daily operations AGHS provider. AGHS providers seek to avoid aircraft damage and airline delays and ensure the provision of reliable and high-quality services. The primary objective of this paper was to develop purchasing decision model of the analytic hierarchy process (AHP), AHP-fuzzy linear programming (FLP), and AHP-Taguchi loss function (TLF) multi-choice goal programming (MCGP) purchase decision models to help the AGHS purchasing managers in selecting the best AGHS equipment supplier provider. The constructed models were assessed, and results obtained for the AHP-FLP and AHP-TLF-MCGP models were compared. We conducted a real-world example of supplier selection by an AGHS company by using the proposed models. The proposed model provides useful information and has practical value for AGHS providers.

Destruction Decisions for Managing Excess Inventory in E-Commerce Logistics

The Internet has brought about new possibilities for innovation and radically changed business activities. Internet shopping is a prime example of increasing popularity, which is exacerbated due to the recent pandemic. It is expected that e-commerce will accommodate more than a quarter of the total retail sales worldwide in the next few years. Given the characteristics of e-commerce, inventory management is of paramount importance for an effective and timely response to the online customers’ demand. Despite its relevance, the issue of warehouse excess inventory is not sufficiently studied in the operations management literature. This study explores the factors, including sustainability and strategic considerations, that influence the inventory destruction decisions as one of the alternatives for managing excess inventory. Applying the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, the interrelationships between the decision factors are investigated and the decisive considerations are identified. Overall, the outcomes provide insights for the e-commerce practitioners and offer directions for modeling and managing inventory destruction decisions.

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.

Modeling supplier selection in the era of Industry 4.0

Purpose

The problem of evaluating potential suppliers has always been based on finding an optimal tradeoff between supplier’s performance consistently meeting firms’ needs and acceptable cost. The purpose of this paper is to propose a hybrid multi-criteria decision framework to quantify this qualitative judgment and reduce ambiguity in selection of suppliers in the era of Industry 4.0.

Design/methodology/approach

A hybrid intuitionistic fuzzy entropy weight-based multi-criteria decision model with TOPSIS is proposed. The authors make use of the intuitionistic fuzzy weighted approach operator for aggregating individual decision maker’s opinions regarding each alternative over every criterion. Additionally, the authors employ the concept of Shannon’s entropy to calculate the criteria weights.

Findings

Results obtained on the basis of the proposed hybrid methodology are analyzed against two more cases wherein the authors try to showcase the relevance of using IFS and entropy-based decision framework and find out the uniqueness of the proposed framework in supplier selection process.

Practical implications

The proposed model is apposite to solve management problem of supplier selection in two ways: aggregating individual decision maker’s opinion for each of the predefined criteria along with individual decision maker’s importance and ranking the suppliers based on both positive and negative ideal solutions using TOPSIS.

Originality/value

A robust framework incorporates not only suppliers’ performance but also provides weightage to key decision makers. Especially in the context of MCDMs wherein both qualitative and quantitative data is evaluated simultaneously, the proposed framework is unique in its practical implementation of reducing ambiguity in the supplier selection process.

Solar Panel Supplier Selection for the Photovoltaic System Design by Using Fuzzy Multi-Criteria Decision Making (MCDM) Approaches

The period of industrialization and modernization has increased energy demands around the world. As with other countries, the Taiwanese government is trying to increase the proportion of renewable energy, especially solar energy resources. Thus, there are many solar power plants built in Taiwan. One of the most important components of a solar power plant is the solar panel. The solar panel supplier selection process is a complex and multi-faceted decision that can reduce the cost of purchasing equipment and supply this equipment on time. In this research, we propose fuzzy MCDM approach that includes fuzzy analytical hierarchy process model (FAHP) and data envelopment analysis (DEA) for evaluation and selection of solar panel supplier for a photovoltaic system design in Taiwan. The main objective of this work is to design a fuzzy MCDM approach for solar panel supplier selection based on qualitative and quantitative factors. In the first step of this research, FAHP is applied to define the priority of suppliers. The AHP combined with fuzzy logic (FAHP) can be used to rank suppliers; however, the disadvantages of the FAHP model is that input data, expressed in linguistic terms, depends on experience of experts and the number of suppliers is practically limited, because of the number of pairwise comparison matrices. Thus, we applied several DEA models for ranking potential suppliers in the final stages. As the result, decision making unit 1 (DMU 1) is the optimal solar panel supplier for photovoltaic system design in Taiwan. The contribution of this research is a new fuzzy MCDM for supplier selection under fuzzy environment conditions. This paper also lies in the evolution of a new approach that is flexible and practical to the decision maker. It provides a useful guideline for solar panel supplier selection in many countries as well as a guideline for supplier selection in other industries.

An Integrated Sustainable Supplier Selection Approach Based on Hybrid Information Aggregation

With a great emphasis on both social and environmental responsibilities, sustainable supply chain management has gradually been adopted and promoted as an innovative business model. In sustainable supply chain practice, the choice of sustainable suppliers relates to the long-term development of a company. While the environmental performance of suppliers has been commonly considered, the social dimension has not yet received enough attention. This paper first proposes a novel criteria system for evaluating sustainable suppliers from three aspects and six dimensions, and then introduces an integrated evaluation model with a novel hybrid information aggregation. To verify the applicability and effectiveness of the proposed method, a real case of a large supermarket is introduced and analyzed. The research results show that (1) the indicator system based on Triple Bottom Line theory can serve as a framework of sustainable supplier selection for manufacturing and circulation enterprises; (2) the introduction of hybrid information aggregation can effectively handle the uncertainties of indicator scores under the realistic fuzzy environment and objectively reflect the intentions of the scorers; and (3) in comparison with the TOPSIS algorithm, the priority order finally obtained is consistent, but the proposed model shows more robustness in the sensitivity test.

Supplier selection for a sustainable supply chain

Purpose

The purpose of this paper is to integrate the “triple bottom line (3BL)” approach in the supplier selection decision. It also aims to consider the feedback effect of the decision on strategic factors that determine the future viability of the firm in the market.

Design/methodology/approach

A multi-criteria decision model is developed that considers simultaneously the impact of three dimensions of 3BL approach and their sub-dimensions on the supplier selection decision. The proposed model is evaluated for a large white goods manufacturer using the analytic network process (ANP) approach.

Findings

The ANP considers the impact of variables, sub-variables, and their interdependencies simultaneously. The outcome of the model is the relative priorities for the firms considered as potential suppliers.

Practical implications

This research was conducted in one of the largest developing economies. The impact of integrating sustainability would be widespread due to the huge market in which the company operates. The results of this research can provide support to the decision makers in arriving at an optimal decision considering all sustainability dimensions.

Originality/value

The novelty of the approach lies in the application of multi-criteria model integrating sustainability dimensions with a feedback effect for supplier selection. The case company would benefit by showing its commitment toward environment and social responsibility leading to improved brand image and sustainable business.

Driving green supply chain management performance through supplier selection and value internalisation

Purpose

The purpose of this paper is to apply self-determination theory (SDT) to green supply chain management (GSCM) and explore how green supplier selection (GSS) drives GSCM performance and how realisation of improved GSCM performance is contingent upon SDT mechanisms of autonomy, competence and relatedness.

Design/methodology/approach

This study draws on 18 semi-structured interviews and secondary data from a Germany-based first-tier aircraft interior manufacturer and its six key suppliers. The focal company was selected because it is recognised as having achieved high GSCM standards in the aerospace industry.

Findings

The study draws out the importance of GSS, distinguishing between new and legacy suppliers, and offers significant insights into how suppliers’ motivation and downstream GSCM criteria can be internalised in second-tier suppliers to drive GSCM performance.

Practical implications

GSS should be considered not only for new suppliers but also at an ongoing basis for legacy suppliers. Focal companies must realise the importance of motivating supply chain partners to realise GSCM practices and need to first build-up autonomy before focussing on competence and relatedness sub-dimensions.

Originality/value

The authors make a significant contribution to the GSCM literature by conducting a study of first-tier-second-tier relationships, thus moving beyond the buyer-supplier relationships investigated in extant studies. The results theoretically and empirically draw out key factors in GSS and supplier motivation in engaging with GSCM practices, thus driving GSCM performance.

Introduction to soft-set theoretic solution of project selection problem

Purpose

The purpose of this paper is to introduce a model of decision-making problem in multi-criteria optimization domain for project selection. The model is built by combining the soft set theory and analytic hierarchical model under fuzziness. Soft set model gives us the opportunity to use parameterization properties. Here, the authors have proved that multiple alternatives can be reduced to make the selection process computationally efficient. Here, the authors illustrate the hybrid method by means of an application of the new mathematical model of soft set theory.

Design/methodology/approach

This paper is designed to excel a decision support system with multiple criteria analysis tool, analytic hierarchy process combined with soft set theory under fuzziness.

Findings

In this paper, the authors have taken four projects P1, P2, P3 and P4. As per chosen parameters of softest theory the result of the illustrative example reveals that P2 is the best project. The ranking the authors get is in the order of P2, P3, P4 and P1. The algorithm leads the authors to maximize the proper choice in the environment of imprecise information. The main advantage of this method compare to others is that this hybrid method is very simple in terms of calculation and the computational complexity of the proposed algorithm is low.

Originality/value

This proposed decision support strategy for an intended project manager helped to take decision in the perspective environment.

Multi-criteria supplier selection model using the analytic hierarchy process approach

Purpose

– The purpose of this paper is to propose a supplier selection model for an automobile company using analytic hierarchy process (AHP) approach. Supplier selection is now growing to be an important but complex issue, as it involves a large number of factors and decisions. These factors have complicated operational and financial implications.

Design/methodology/approach

– A case study of an Indian automobile company is used to illustrate and propose a supplier selection model using AHP approach.

Findings

– Key criteria of the supplier selection problem are identified based on the literature review and case study. Then, a model is proposed for supplier selection using AHP approach followed by a detailed sensitivity analysis.

Practical implications

– This paper contributes to supplier selection process, and points out the importance of supplier selection. It proposes a supplier selection model for an automobile industry which often faces heterogeneous supply environments. The proposed model provides key criteria for supplier selection in Indian context. This model may have high acceptability, where a large number of suppliers are available to supply the materials or provide the services.

Originality/value

– The proposed model can provide guidelines and directions for managers involved in purchasing function to effectively select suppliers on the basis of the identified criteria in the heterogeneous manufacturing environment.

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.

Self-interest or the greater good

Purpose

– The purpose of this paper is to provide an understanding of the influence of political goals and behaviour on the outsourcing decision process and outcomes.

Design/methodology/approach

– The research used an exploratory longitudinal case-based approach. Eight outsourcing projects in three telecommunications companies were analysed from the initial decision to the outcome of the case.

Findings

– The authors show how political goals and behaviours influence the outsourcing decision process and inductively develop four political goals: personal reputation, attainment, elimination and control. The authors also identify three dynamic outsourcing paths: the personal reputation path, which leads to successful outcomes; the short-term attain and eliminate path leading to unsuccessful outcomes; and the destabilised path, which leads to mixed outcomes. All of these can be tested in other empirical settings.

Research limitations/implications

– The implications for outsourcing literature are that political intentions influence the decision process and outcomes. For theorists, the authors provide an understanding of how political and rational goals and behaviour interact to impact outsourcing outcomes: with political and rational goals and behaviour complementary in some instances. The limitations are that with a small sample the findings are generalisable to theoretical propositions rather than to a population.

Practical implications

– The implications for managers are the ability to identify and manage political goals that influence outsourcing decision process and outcomes.

Originality/value

– For the first time, the authors uncover the political goals that impact the outsourcing decision process and outcomes. The authors add to the outsourcing literature, transaction cost theory and resource-based theory by defining and understanding the political goals that complement these theories.

An application of hybrid data envelopment analytical hierarchy process approach for supplier selection

Purpose

– The problem of supplier selection gets complicated when a company looks for various criteria to evaluate different suppliers. The decision criteria used for supplier selection process can be different for different organizations due to a large number of factors. Hence, it can be said that supplier selection is basically, a multiple criteria decision-making (MCDM) problem. The purpose of this paper is to propose a hybrid data envelopment analytical hierarchy process (DEAHP) approach to solve the supplier selection problem for an automobile company.

Design/methodology/approach

– In this study, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. Literature review suggested that majority of researches found it appropriate using DEA and AHP methodologies for supplier selection process; hence it is felt that a hybrid DEAHP would be a useful methodology to offer a MCDM model for supplier selection problem.

Findings

– First, the key criteria of the supplier selection problem for the company are identified. Then a model is developed and implemented for supplier selection using DEAHP approach. This study concluded that quality, cost and service are the most crucial criteria for an automobile company operational in a developing country like India. Sensitivity analysis further helped to evaluate suppliers based on each criterion.

Research limitations/implications

– As this analysis and findings are based on only one case study of an Indian automobile company, and this necessitates caution in interpreting the results. The limited number of interviewed managers in a company restricts the generalizability of the results. Though the company selected for this study is typical of developing country businesses, the findings of the paper may not be readily extensible to other companies. Second, this study used retrospective settings, based on the interviewed feedback after the events had occurred. This method naturally poses limitations due to respondent recall and the accuracy of information provided. Third, the problem chosen for this study is based in a single country context and further additional research will be required to examine if the findings could be extended to other automobile companies in other developing nations. Also in some cases technique used in the study may pose some extra computational efforts.

Practical implications

– This study points out the importance of the supplier selection problem. It provides key criteria for supplier selection in Indian context also proposes a framework to deal with multiple criteria. proposed model deals with two crucial criteria long term relationships and flexibility which were relatively less discussed and considered in the literature in past.

Originality/value

– The proposed MCDM model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment.

Assessment of supplier quality performance of computer manufacturing industry by using ANP and DEMATEL

Purpose

– The purpose of this paper is to establish an integrated model of Analytic Network Process (ANP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL), to assist enterprises to process supplier quality performance rating and comparison and find the core improvement direction to create the value of all supply chain members.

Design/methodology/approach

– This study used the integrated model to process supplier quality performance rating and comparison, which not only improved the order-winners and qualifiers and continued to increase supplier quality performance, but resolved the complex and difficult cause-effect relation issue to find out core improvement items. The cases of Taiwanese industrial computer manufacturers were used to describe the application and benefits of this methodology.

Findings

– The results recommended that the improvement item of supplier A shall focus on design and quality conformance. The recommended improvement item and order for supplier B is design, delivery reliability and delivery speed. This study established ANP and DEMATEL evaluation models, and expanded the application field in the supplier performance evaluation.

Originality/value

– The ANP model is used to calculate the importance of the evaluation criteria, and the DEMATEL method is introduced to consider the impact of the casual relationship of evaluation items and to adjust the importance of the evaluation item, and to solve the complex and difficult practical causation issue.

An importance-performance analysis for supplier assessment in foreign-aid funded procurement

Purpose

– 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.

Design/methodology/approach

– 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”.

Findings

– 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.

Practical implications

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

Originality/value

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

Pani A. Exploring the importance of different supplier selection criteria

Purpose

– Supplier selection studies have used a wide variety of supplier evaluation criteria, due to the diversity of the purchasing context. The purpose of this study is to identify the critical supplier selection criteria which are important across industries and across purchasing contexts, and subsequently estimate the importance of these criteria to the procurement practitioners.

Design/methodology/approach

– First, a Delphi study has been conducted to identify the critical supplier selection criteria across manufacturing industries. Then, data were collected from 188 firms across 12 industries and analysed with fuzzy analytic hierarchy process for group decision making, to estimate the relative importance of these criteria.

Findings

– Findings indicate that seven criteria are of critical importance to Indian manufacturing industries. Also evaluation criteria like product quality, delivery compliance and price have maximum criticality, while criterion like e-transaction capability is gaining in importance, with the increased adoption of e-procurement platforms.

Research limitations/implications

– The study has been conducted in India, while focusing on Indian manufacturing industries. Similar study conducted in developed economies may produce different results.

Practical implications

– Findings will be useful for practitioners for benchmarking supplier selection processes, not only in India, but also in similar emerging economies. Also, the outcome will provide insights for suppliers for developing systemic improvements.

Originality/value

– There has been no study in recent years which has attempted to estimate the importance of supplier selection criteria, while taking a multi-industry approach. This study identifies the critical evaluation criteria and estimates their relative importance to procurement experts.

Helping the decision maker effectively promote various experts' views into various optimal solutions to China's institutional problem of health care provider selection through the organization of a pilot health care provider research system

BACKGROUND

The main aim of China's Health Care System Reform was to help the decision maker find the optimal solution to China's institutional problem of health care provider selection. A pilot health care provider research system was recently organized in China's health care system, and it could efficiently collect the data for determining the optimal solution to China's institutional problem of health care provider selection from various experts, then the purpose of this study was to apply the optimal implementation methodology to help the decision maker effectively promote various experts' views into various optimal solutions to this problem under the support of this pilot system.

METHODS

After the general framework of China's institutional problem of health care provider selection was established, this study collaborated with the National Bureau of Statistics of China to commission a large-scale 2009 to 2010 national expert survey (n = 3,914) through the organization of a pilot health care provider research system for the first time in China, and the analytic network process (ANP) implementation methodology was adopted to analyze the dataset from this survey.

RESULTS

The market-oriented health care provider approach was the optimal solution to China's institutional problem of health care provider selection from the doctors' point of view; the traditional government's regulation-oriented health care provider approach was the optimal solution to China's institutional problem of health care provider selection from the pharmacists' point of view, the hospital administrators' point of view, and the point of view of health officials in health administration departments; the public private partnership (PPP) approach was the optimal solution to China's institutional problem of health care provider selection from the nurses' point of view, the point of view of officials in medical insurance agencies, and the health care researchers' point of view.

CONCLUSIONS

The data collected through a pilot health care provider research system in the 2009 to 2010 national expert survey could help the decision maker effectively promote various experts' views into various optimal solutions to China's institutional problem of health care provider selection.

The Cluster-Weighted DEMATEL with ANP Method for Supplier Selection in Food Industry

In terms of keeping material costs low and increasing competitive advantage, supplier selection is one of the most important functions of a business. This paper uses an effective solution based on a combined Analytic Network Process (ANP) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach to find the criteria that are key to performance improvement. This paper surveys the multicriteria supplier selection approaches and reveals the most popular criteria and sub-criteria. Based on experts’ suggestions and the most popular criteria, the key factors in the selection of food industry suppliers are identified. Then, the causal relationships and relative importance weights of the criteria in the system are computed using the cluster-weighted DEMATEL with ANP method. This paper compares the results of experts and purchasing managers and discovers a cognitive gap. The managers agree that cost and delivery are very important; they need to keep material costs down and increase the company’s competitive advantage. The experts value customer satisfaction and Corporate Social Responsibility (CSR), so they feel that quality and service are the most important criteria.