Multi‐criteria supplier selection using fuzzy AHP

A decision model for selecting a safety data sheet management system using fuzzy TOPSIS

Purpose

Safety data sheets are documents developed by chemical manufacturers to identify and label hazardous materials. The occupational safety and health administration regulations state that employers must make safety data sheets available for employees. When firms use hundreds of chemicals, tracking their safety data sheets becomes difficult. Safety Data Sheet Management Systems are developed to track safety data sheets. This paper aims to propose a multi-attribute decision-making framework for selecting a Safety Data Sheet Management System.

Design/methodology/approach

A total of 12 attributes are proposed based on a real-life project conducted at a firm in New York and the software selection models existed in the literature. Fuzzy technique for order of preference by similarity to ideal solution is used to assess the proposed attributes and alternatives. A case study and sensitivity analysis are conducted to show the robustness of the proposed model. Fuzzy analytical hierarchy process is used for validation.

Findings

Safety Data Sheet Management System is important for firms to track and manage safety data sheets. The proposed framework is practical and easy to implement.

Practical implications

The proposed decision model is useful for firms to select a proper Safety Data Sheet Management System. The system developers can use the model to update their systems.

Originality/value

This paper develops a new multi-attribute decision-making model for selecting a Safety Data Sheet Management System. To the best of the authors’ knowledge, no previous study has developed such a model.

An Extended GRA Method Integrated with Fuzzy AHP to Construct a Multidimensional Index for Ranking Overall Energy Sustainability Performances

In an age of rapid technological advancement, the increasing need for energy and its related services to satisfy economic and social development has become a critical concern of national governments worldwide. This has triggered researchers to work on metrics for tracking and tracing energy sustainability in order to provide monitoring mechanisms for policy makers. In this regard, multicriteria decision-making (MCDM) methods are becoming more popular to deal with the multidimensional and complex nature of sustainability. We have proposed an extended and revised version of the grey relational analysis (GRA) method, which is integrated with the fuzzy analytic hierarchy process (AHP), to develop a new composite index for comparing the overall energy sustainability performances of 35 OECD member countries. Our case study revealed the performances of selected countries by providing their strengths and weaknesses based on determined criteria as well as the level of change in performances with different criteria weights. The proposed GRA model can be used in different applications of sustainability due to its flexible nature, which provides benefits from goal-oriented extensions in order to adequately capture different aspects of sustainability.

Multi-criteria of wind-solar site selection problem using a GIS-AHP-based approach with an application in Igdir Province/Turkey

Sustainable sources like wind, solar, and geothermal power are defined as a clean source of renewable energy which has a less harmful impact on the environment than other energy sources such as coal, natural gas and oil. Turkey is one of the energy-importing countries where air pollution has been become an inevitable environmental concern. Thus, investments on sustainable sources have been developed rapidly in recent years in Turkey. This paves the way for studying a site selection problem considering both solar and wind energy in Igdir Province located in the east part of Turkey. In the literature, there are many studies on solar-wind energy to select a desirable site for both energy sources, and many solution techniques have been proposed dealing with this problem. In this study, one of multi-criteria decision-making methods named analytical hierarchy process (AHP) and geographical information systems (GIS) are used to determine suitable site selection for solar-wind energy investigating four counties of Igdir: Tuzluca, Igdir Central, Karakoyunlu and Aralik. The aim of this work is first to investigate possible locations for solar-wind power plant installation using a mapping method, GIS, and then, AHP is applied to the problem to obtain optimum areas for both solar-wind energy. Also, more accurate results are provided comparing results of two methods, GIS and AHP. The results reveal that 524.5 km² for solar power plant and 147.2 km² for wind turbine are suitable while only 49.1 km² is suitable for solar-wind power plan installation.

How Does the Contingent Sustainability–Risk–Cost Relationship Affect the Viability of CSR? An Emerging Economy Perspective

Sustainability has become a core strategic initiative for firms in the global economy. Its key benefits aside, sustainability may increase a firm’s risks, undermining its prospective value. The intricate relationship among sustainability’s impact on various dimensions of firm risk is poorly understood, particularly for firms operating in emerging economies. The purpose of this study is to address this gap by developing a nuanced framework for the sustainability–risk relationship in various industries in emerging economies. A multi-method approach was used to collect both quantitative and qualitative data through interviews and site visits for supply chain members of four industries. A fuzzy AHP method was used to illustrate cross-industry differences in sustainability-induced firm risks. These differences are further illustrated through inductive, interpretive analysis of semi-structured interviews. Sustainability behaves as a limits-to-growth system and engenders different risk profiles across four industries. For all firms in emerging economy, sustainability initiatives increase various unanticipated risks. Thus, these firms must saliently tailor sustainability initiatives uniquely suitable for their industry to avoid compromising their value proposition. Insights gleaned from this study may assist both buyers from multinational corporations in the developed economy to propagate sustainability initiatives and suppliers in the emerging economy to implement sustainability initiatives more saliently.

A Decision-making Model for Supplier Selection in Indian Pharmaceutical Organizations

Supplier selection is the process by which firms identify, evaluate and contract with suppliers. The supplier selection process deploys a tremendous amount of a firm’s operational and financial resources and is considered as an important determinant of the success of its supply chain. In spite of being strategically important to organizations, the decision for supplier selection is often complex and unstructured. Furthermore, it is inherently a multi-criterion decision-making (MCDM) problem, which pertains to structuring and solving decision problems involving multiple criteria. The paper provides a framework to analyze and evaluate supplier selection in Indian pharmaceutical sector (IPS) using MCDM technique of fuzzy analytic hierarchy process. It intends to improve managerial decision-making in the IPS in developing a supplier selection strategy based on multi-criteria evaluation technique.

Traffic Accident Spatial Simulation Modeling for Planning of Road Emergency Services

The appropriate locations of road emergency stations (RESs) can help to decrease the impact of traffic accidents that cause around 50 million injuries per year worldwide. In this research, the appropriateness of existing RESs in the Khuzestan province, Iran, was assessed using an integrated fuzzy analytical hierarchy process (FAHP) and geographic information system (GIS) approach. The data used in this research were collected from different sources, including the department of roads, the department of health, the statistics organization, forensics, police centers, the surveying and geological department, remotely-sensed and global positioning system (GPS) data of accident high crash zones. On the basis of previous studies and the requirements of the Ministry of Health and Medical Education, as well as the department of roads of Iran for the location of RESs, nine criteria and 19 sub-criteria were adopted, including population, safety, environmental indicators, compatible area in RES, incompatible area in RES, type of road, accident high crash zones, traffic level and performance radius. The FAHP yielded the criteria weights and the ideal locations for establishing RESs using GIS analysis and aggregation functions. The resulting map matched the known road accident and high crash zones very well. The results indicated that the current RES stations are not distributed appropriately along the major roads of the Khuzestan province, and a re-arrangement is suggested. The finding of the present study can help decision-makers and authorities to achieve sustainable road safety in the case study area.

Supporting Europe’s Energy Policy Towards a Decarbonised Energy System: A Comparative Assessment

The European Union (EU) aims to prepare its strategy and infrastructure for further decarbonisation of its energy system in the longer term towards 2050. Recent political discussions and research interest focus on ways to accelerate the development and deployment of low-carbon technologies with respect to the targets set for 2030 and 2050. However, the diverse options available that are to be implemented, are policy sensitive and need careful comparative assessment. This paper presents a multi-criteria approach based on an extension of the Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) method for group decision-making that incorporates fuzzy set theory in order to evaluate alternative transformation pathways for achieving a sustainable energy system in EU. This assessment aims at providing a direction towards a most preferable pathway concept that should be taken into account by a future model-based analysis of the necessary transformation of our energy sector. The results obtained could support policymakers in drawing effective recommendations based on the findings. The added value of this analysis to policymakers is its contribution to plan climate and energy strategies towards a low-carbon transition pathway by using the information of this approach and prioritizing uncertainties through an environmental and energy perspective.

Service Supplier Selection Decision Based on Dempster–Shafer Synthesis Rule

Service supplier selection is a multi-criteria decision-making problem and becomes incredibly profound as it helps to reduce cost to the bottom line. According to the unique characteristics of the service supply chain and service, we summed up the service provider’s evaluation criteria, and then deeply profile the basic principles of the Dempster–Shafer synthesis rule. Finally, there is a case to show that the Dempster–Shafer synthesis rule is efficient as it can guarantee that the multi-criteria evaluation could find accurate and effective service providers on the service supply chain, and it also helps the service business decision-maker.

A Spatial Fuzzy Multicriteria Analysis of Accessibility: A Case Study in Brazil

Accessibility is a well-established concept in sustainable transportation literature; however, it is often measured through accessibility models that are still being developed. This article presents an accessibility evaluation model that applies multiple attributes, fuzzy functions, and spatial analysis tools. The model determines indices that reflect an average level of attractiveness for each potential destination (deemed a location of interest—LI). Each destination has different weights based on its degree of importance. Moreover, the model was developed in two phases: The first considered cost–distance metrics, and the second incorporated ground friction factors. The application of the model provides great contribution to the region under study (Campos do Jordão, a city located in a mountainous region of the state of São Paulo), thus presenting some implications for sustainable urban planning and mobility policies, especially in segregated areas with mixed inhabitant populations between tourists and local residents. The results have shown that special attention should be paid to planning new school facilities and city transportation systems. Most of these services are currently concentrated in the city’s downtown area, making access to urban facilities inefficient and unfair. Using the results in urban projects, the allocation of future urban facilities or the reallocation of current urban facilities contributes to reduced impacts on urban mobility caused by individual motorized transportation in daily activities.

Fuzzy Multi-Criteria Decision-Making Model for Supplier Evaluation and Selection in a Wind Power Plant Project

In order to meet ambitious growth targets in the medium term, Vietnam must continue exploiting traditional energy sources. In the longer term, Vietnam has to develop a strategy and roadmap for the development of new energy sources. In these new energy sources, wind energy has emerged as a viable option. Given the geographic conditions of a locality with a long coastline and high winds that are fairly distributed all year, many wind-power plants are being built in Vietnam. One of the most important pieces of equipment in a wind-power plant is the wind turbine. The wind turbine suppliers’ selection is a complex and multicriteria decision-making (MCDM) process that can reduce the costs of procuring equipment and aid in receiving products on time. Many studies have applied the MCDM model to various fields of science and engineering. One of the fields that the MCDM approaches have been applied to is the supplier selection problem. Supplier selection is an important issue of the MCDM model. Especially in a renewable energy project, decision-makers have to evaluate both natural and society factors. Although some researchers have reviewed the applications of the MCDM model in wind turbine supplier selection, limited work has focused on this problem in a fuzzy environment. Therefore, in this work, the authors propose a fuzzy MCDM model for the wind turbine supplier selection process under fuzzy environment conditions. In the first step, all factors for wind turbine supplier selection are identified by supply chain operations reference (SCOR) metrics and the results from a review of the literature. A fuzzy analytic network process (FANP) model is applied for determining the weight of all the criteria in the second stage, and the technique for order preference by similarity to an ideal solution (TOPSIS) model is used to rank all the potential suppliers in the final stage. As a result, Decision-Making Unit 010 (DMU010) becomes an optimal option for the wind turbine supplier selection processes. The contribution of this research is to develop new hybrid fuzzy MCDM approaches for wind turbine supplier selections. Furthermore, this work presents useful guidelines for wind turbines as well as provides a guideline for supplier selection in other industries.

Demand prediction in health sector using fuzzy grey forecasting

Purpose

The purpose of this paper is to apply GM (1, 1) and TFGM (1, 1) models on the healthcare sector, which is a new area, and to show TFGM (1, 1) forecasting accuracy on this sector.

Design/methodology/approach

GM (1, 1) and TFGM (1, 1) models are presented. A hospital’s nine months (monthly) demand data is used for forecasting. Models are applied to the data, and the results are evaluated with MAPE, MSE and MAD metrics. The results for GM (1, 1) and TFGM (1, 1) are compared to show the accuracy of forecasting models. The grey models are also compared with Holt–Winters method, which is a traditional forecasting approach and performs well.

Findings

The results of this study indicate that TFGM (1, 1) has better forecasting performance than GM (1, 1) and Holt–Winters. GM (1, 1) has 8.01 per cent and TFGM (1, 1) 7.64 per cent MAPE, which means excellent forecasting power. So, TFGM (1, 1) is also an applicable forecasting method for the healthcare sector.

Research limitations/implications

Future studies may focus on developed grey models for health sector demand. To perform better results, parameter optimisation may be integrated to GM (1, 1) and TFGM (1, 1). The demand may be predicted not only for the total demand on hospital, but also for the demand of hospital departments.

Originality/value

This study contributes to relevant literature by proposing fuzzy grey forecasting, which is used to predict the health demand. Therefore, the new application area as the health sector is handled with the grey model.

Analyzing Workforce 4.0 in the Fourth Industrial Revolution and proposing a road map from operations management perspective with fuzzy DEMATEL

Purpose

The purpose of this paper is threefold: first, to present a structural competency model; second, to remark new criteria for personnel selection in Industry 4.0 environment; and third, to contribute to the operations management literature by focusing on recruitment process in Industry 4.0 environment and supporting human resources activities with Industry 4.0 related criteria and point out a new research field in Industry 4.0.

Design/methodology/approach

Fuzzy DEMATEL has been used in the implementation. The study is conducted in a high-tech firm, which has started to modify its processes according to Industry 4.0, and introduces a new specific department that is responsible of this transformation. In total, 11 personnel selection criteria were presented and then assessed by experts through a fuzzy linguistic scale. Both importance order and causal relation between criteria are presented at the end of the study.

Findings

According to the results, the most important criteria in the selected firm are the ability of dealing with complexity and problem solving, thinking in overlapping process, and flexibility to adapt new roles and work environments. While cause group includes criteria such as knowledge on IT and production technologies, awareness of IT security and data protection, and ability of fault and error recovery, effect group includes flexibility to adapt new roles and work environments, organizational and processual understanding, and the ability to interact with modern interfaces.

Practical implications

Analytical thinking and system approach are the key topics for new supporting personnel selection criteria, which lead to the need for the skills and qualifications in decision making and process management. Results of the cause group criteria also indicate the importance of technical abilities such as coding, IT security and human-machine interfaces. On the other hand, effect group of the study emphasizes on the flexibility and interdisciplinary working structure that suggests the suitability of matrix organization in the companies which follow the Industry 4.0 trends. Moreover, team work comes forward as another key concept for organizations transforming to Industry 4.0.

Originality/value

The originality of this study appears on modeling of a competency structural model for Workforce 4.0 which is proposed as a road map, including the suggested set of related criteria and the fuzzy MCDM-based methodology for companies which alter their organizations according to Industry 4.0.

Ranking criteria for selection of certification bodies for ISO 9001 through the Analytic Hierarchy Process (AHP)

Purpose

The purpose of this paper is to present a framework to assist the selection of certification bodies in the implementation of quality management system (QMS) based on ISO 9001 taking into account a set of criteria organized in a multi-level hierarchical form. To deal with this complexity, the multi-criteria decision-making method (MCDM) analytic hierarchy process (AHP) was used in this research.

Design/methodology/approach

The research was conducted in small and medium-sized companies certified to ISO 9001. The MCDM method AHP was used as a method for developing the model to support the selection of certification bodies.

Findings

This paper provides a framework for companies seeking to hire certification bodies, mainly for ISO 9001 certification, which help identify the companies that best fit the certification objectives. Additionally, a ranking of the main criteria to select certification bodies for ISO 9001 was obtained.

Research limitations/implications

The decision-making method was applied to Brazilian companies from different sectors. As the results can vary between regions and sectors, this is a limitation of the research. In addition, the number of ten respondents could be higher to increase the robustness of the results.

Practical implications

The model assists companies looking for certification, mainly ISO 9001, in the selection of certification bodies contributing in the search for deeper implementations of QMS.

Originality/value

This work has the originality of the application of a decision-making method in the final process of ISO 9001 certification, scarce in the literature. In addition, it defines weights for the criteria involved in the process of selecting certification bodies.

Pythagorean fuzzy CODAS and its application to supplier selection in a manufacturing firm

Purpose

The purpose of this paper is to develop the Pythagorean fuzzy extension of CODAS method.

Design/methodology/approach

Supplier selection is a critical issue for manufacturing companies since it is a multidimensional problem including several conflicting criteria. A suitable multi criteria decision making (MCDM) method that could consider vagueness and impreciseness in the assessments should be used for this kind of problems. Pythagorean fuzzy sets (PFSs) are characterized by a membership degree and a non-membership degree satisfying the condition that their square sum is equal to or less than 1. PFSs extend the concept of intuitionistic fuzzy sets (IFSs). COmbinative Distance-based Assessment (CODAS) method is relatively a new MCDM technique introduced by Keshavarz Ghorabaee et al. (2016).

Findings

Pythagorean fuzzy CODAS gives better results than ordinary fuzzy CODAS since it considers the hesitancy of decision makers and presents a larger space for membership and non-membership definition.

Originality/value

The value of this paper is the proposal of a new method to use for the solutions of MCDM problems under vagueness and impreciseness. To show validity and effectiveness of the proposed method, an application to the supplier selection problem is given.

Facilitating quality project manager selection for Indian business environment using analytical hierarchy process

Purpose

The purpose of this paper is to develop criteria for project manager selection based on desired skills of a project manager and facilitate the selection of a suitable candidate from a pool of potential candidates for the implementation of projects in the Indian context.

Design/methodology/approach

The study utilizes three major skills, namely human skill, conceptual and organizational skills; technical skill along with their sub-skills to develop criteria for project manager selection. Based on the responses of project professionals from industry, the study uses analytical hierarchy process to prioritize and identify the relative importance of different skills in the criteria in order to develop a hierarchical structure for project manager selection.

Findings

The study finds that at the first level of project manager selection criteria, conceptual and organizational skills are the most important selection criteria followed by human skills and technical skills. At the second level of project manager selection criteria, planning, delegating authority and understanding methods, processes, and procedures are some of the important sub-selection criteria. The weights indicating the relative importance of major selection criteria and sub-selection criteria can be used to evaluate the relative weight of a given candidate for selection as a project manager.

Research limitations/implications

The results in this study are derived from specific demographic conditions in India. Future research with larger samples from other countries is needed for generalizations of the proposed criteria.

Practical implications

The proposed method quantifies the intangible qualitative criteria to select a project manager, which can aid decision-makers in a multi-criteria decision-making environment.

Originality/value

This research paper is focused on the identification of critical skills for the selection of a project manager, which is almost neglected by the researchers.

A multi-objective approach to design strategic supply chains and develop responsiveness- efficiency frontiers

Purpose

The purpose of this paper is twofold. Initially, a multi-objective binary integer programming model is proposed for designing an appropriate supply chain that takes into consideration both responsiveness and efficiency. Then, a responsiveness-cost efficient frontier is generated for the supply chain design that can help organizations find the right balance between responsiveness and efficiency, and hence achieve a strategic fit between organizational strategy and supply chain capabilities.

Design/methodology/approach

The proposed SC design model used both cross-functional and logistical SC drivers to build a binary integer programming model. To this end, various alternative solutions that correspond to different SC design portfolios were generated and a responsiveness-cost efficient frontier was constructed.

Findings

Various alternative solutions that correspond to different SC designs were generated and a responsiveness-cost efficient frontier was constructed to help the decision makers to design SC portfolios to achieve a strategic fit between organizational strategy and SC capabilities.

Practical implications

The proposed methodology enables the decision makers to incorporate both qualitative and quantitative judgements in SC design. The methodology is easy to use and it can be readily implemented by a software.

Originality/value

The proposed methodology allows for subjective value judgements of the decision makers to be considered in SC design and the efficiency-responsiveness frontier generated by the methodology provides a trade-off to be used when choosing between speed and cost efficiency in SC design.

Effective factors on not using the N95 respirators among health care workers: Application of Fuzzy Delphi and Fuzzy Analytic Hierarchy Process (FAHP)

Using respiratory protective equipment (RPE) including N95 respirators is one of the most important ways to protect health care workers (HCWs) against respiratory hazards. The aim of this study was to identify and prioritize the problems and obstacles in using N95 respirators among HCWs in Iran. In this cross-sectional study, problems and obstacles in using N95 respirators were identified and ranked by experts, using Fuzzy Delphi and Fuzzy Analytic Hierarchy Process (FAHP). Additionally, HCWs were asked to give their opinions about obstacles in using N95 respirators in order to form an opinion. Of 15 important obstacles in using N95 respirators identified by Fuzzy Delphi method, 6 factors were entered into the FAHP model: heat around the face, inaccessibility to respirator, difficulty breathing, pressure on the nose, trouble communicating with patients and colleagues, and no one does it. Identified problems and obstacles in using N95 respirators could be controlled during the selection of respirators, as well as by training and administrative measures.

A fuzzy goal programming approach for selecting sustainable suppliers

Purpose

Due to the ever increasing concern toward sustainability, suppliers nowadays are evaluated on the basis of environmental performances. The data on supplier’s performance are not always available in quantitative form and evaluating supplier on the basis of qualitative data is a challenging task. The purpose of this paper is to develop a framework for the selection of suppliers by evaluating them on the basis of both quantitative and qualitative data.

Design/methodology/approach

Literature on sustainability, green supply chain and lean practices related to supplier selection is critically reviewed. Based on this, a two phase fuzzy goal programming approach integrating hyperbolic membership function is proposed to solve the complex supplier selection problem.

Findings

Results obtained through the proposed approach are compared to the traditional models (Jadidi et al., 2014; Ozkok and Tiryaki, 2011; Zimmermann, 1978) of supplier selection and were found to be optimal as it achieves higher aspiration level.

Practical implications

The proposed model is adaptive to solve real world problems of supplier selection as all criteria do not possess the same weights, so the managers can change the criteria and their weights according to their requirement.

Originality/value

This paper provides the decision makers a robust framework to evaluate and select sustainable supplier based on both quantitative and qualitative data. The results obtained through the proposed model achieve greater satisfaction level as compared to those achieved by traditional methods.

A novel GIS-based approach to assess beekeeping suitability of Mediterranean lands

Honeybees are critically important for the environment and to the economy. However, there are in substantial decline worldwide, leading to serious threat to the stability and yield of food crops. Beekeeping is of pivotal importance, combining the wide economical aspect of honey production and the important ecological services provided by honeybees. In this scenario, the prompt identification of beekeeping areas is strategic, since it maximised productivity and lowered the risks of colony losses. Fuzzy logic is an ideal approach for problem-solving tasks, as it is specifically designed to manage problems with a high degree of uncertainty. This research tested a novel GIS-based approach to assess beekeeping suitability of lands located in Calabria (Southern Italy), without relying to Analytic Hierarchy Process – Multiple Criteria Decision Making (AHP-MCDM), thus avoiding the constraints due to the technique and decision makers’ influences. Furthermore, the data used here were completely retrieved from open access sources, highlighting that our approach is characterized by low costs and can be easily reproduced for a wide arrays of geographical contexts. Notably, the results obtained by our experiments were validated by the actual beekeeping reality. Besides beekeeping, the use of this system could not only be applied in beekeeping land suitability evaluations, but may be successfully extended to other types of land suitability evaluations.

A Framework for Applying CSFs to ERP Software Selection

The literature review studies on ERP system indicate two main areas of thrust: the study of critical success factors for the risk aversion in ERP implementation projects and the ERP system selection studies. However, ERP system selection is a tedious and a time-consuming activity. The critical success factors (CSFs) serve as vital input ingredients to the ERP selection Models. It is however notable that, that none of the CSFs listing propagated by the researchers find a straightforward application in the selection procedure. The paper bridges the gap between the two thrust areas by proposing a framework for applying the prioritized CSFs listed for direct utilization in the selection process. An exhaustive review on the ERP selection techniques reveals the focus on AHP and/or the Fuzzy Logic approaches to ERP selection problem. A new approach to ERP selection problem with the extensions of the Fuzzy-TOPSIS is subsequently introduced and is illustrated by a solved numerical example. Also, the computational simplicity of the extensions of Fuzzy TOPSIS is demonstrated.

Development of a framework for resilience measurement: Suggestion of fuzzy Resilience Grade (RG) and fuzzy Resilience Early Warning Grade (REWG)

BACKGROUND

Resilience engineering (RE) can be an alternative technique to the traditional risk assessment and management techniques, to predict and manage safety conditions of modern socio-technical organizations. While traditional risk management approaches are retrospective and highlight error calculation and computation of malfunction possibilities, resilience engineering seeks ways to improve capacity at all levels of organizations in order to build strong yet flexible processes.

OBJECTIVES

Considering the resilience potential measurement as a concern in complex working systems, the aim of this study was to quantify the resilience by the help of fuzzy sets and Multi-Criteria Decision-Making (MCDM) techniques. In this paper, we adopted the fuzzy analytic hierarchy process (FAHP) method to measure resilience in a gas refinery plant.

METHODS

A resilience assessment framework containing six indicators, each with its own sub-indicators, was constructed. Then, the fuzzy weights of the indicators and the sub-indicators were derived from pair-wise comparisons conducted by experts. The fuzzy evaluating vectors of the indicators and the sub-indicators computed according to the initial assessment data. Finally, the Comprehensive Resilience Index (CoRI), Resilience Grade (RG), and Resilience Early Warning Grade (REWG) were established.

RESULTS

To demonstrate the applicability of the proposed method, an illustrative example in a gas refinery complex (an instance of socio-technical systems) was provided. CoRI of the refinery ranked as "III". In addition, for the six main indicators, RG and REWG ranked as "III" and "NEWZ", respectively, except for C3, in which RG ranked as "II", and REWG ranked as "OEWZ".

CONCLUSIONS

The results revealed the engineering practicability and usefulness of the proposed method in resilience evaluation of socio-technical systems.

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.

Assessing the economics of processing end-of-life vehicles through manual dismantling

Most dismantling enterprises in a number of developing countries, such as China, usually adopt the "manual+mechanical" dismantling approach to process end-of-life vehicles. However, the automobile industry does not have a clear indicator to reasonably and effectively determine the manual dismantling degree for end-of-life vehicles. In this study, five different dismantling scenarios and an economic system for end-of-life vehicles were developed based on the actual situation of end-of-life vehicles. The fuzzy analytic hierarchy process was applied to set the weights of direct costs, indirect costs, and sales and to obtain an optimal manual dismantling scenario. Results showed that although the traditional method of "dismantling to the end" can guarantee the highest recycling rate, this method is not the best among all the scenarios. The profit gained in the optimal scenario is 100.6% higher than that in the traditional scenario. The optimal manual dismantling scenario showed that enterprises are required to select suitable parts to process through manual dismantling. Selecting suitable parts maximizes economic profit and improves dismantling speed.

A multicriteria model on calculating the Sustainable Business Excellence Index of a firm with fuzzy AHP and TOPSIS

Purpose

– The purpose of this paper is to provide an integrated methodology for benchmarking the sustainability of organizations. The fuzzy analytical hierarchy process (FAHP) and technique for order of preference by similarity to ideal solution (TOPSIS) methods have been used for this purpose. The FAHP is used to determine the weights of the criteria by decision makers, and the rankings of the alternatives are determined by TOPSIS. The proposed instrument is used to calculate the Sustainable Business Excellence Index (SBEI) and its potential impact on the formulation of firm strategy. To demonstrate the applicability of the model, illustrative examples are presented.

Design/methodology/approach

– After a careful literature review, a sustainable business excellence framework is created and a fuzzy system is developed to assess firms’ sustainability. Finally, the SBEI is computed.

Findings

– The results indicate that the suggested fuzzy approach is feasible for benchmarking the sustainability of organizations. It allows the decision makers to express their opinion regarding the importance of criteria and evaluate each alternative and then have this input coordinated in a quantitative fashion.

Research limitations/implications

– Practitioners and consultants can use the instrument for conducting quality management benchmarking within and across organizations. Researchers can use the instrument in future studies for further theory development in this area.

Originality/value

– As far as the authors are aware, no previous study research has assessed the SBEI of an organization with fuzzy sets. As such, it responds to a number of contemporary challenges in the business excellence theory, most importantly the broad need to identify agile organizations.

Multi-criteria decision framework for supplier classification in collaborative supply chains

Purpose

– Buyer companies’ engagement with suppliers varies according to their specific business needs. Prior models of supplier classification are based on the dimensions like product specification or criticality of purchase. As the supply chains are embracing collaboration among partners to respond to the dynamic market conditions, it is prudent to study the changes adopted by buyer companies for supplier classification. The paper aims to discuss these issues.

Design/methodology/approach

– This is an exploratory research for identifying the criteria used for supplier classification based on the interviews of practitioners from buyer multinational manufacturing companies operating in India. The content analysis of the subjective responses led to the identification of distinctive criteria.

Findings

– Although, many of the practitioners were unaware of the model per se, they labelled their suppliers as per the types stated in the Kraljic model. They mentioned twenty six criteria for supplier classification; five of which do not have any reference in the extant literature. The degree of presence of these criteria provides a multi-criteria framework for supplier classification that has been further extended based on prior models.

Research limitations/implications

– The exploratory nature of the study, its confinement to Indian milieu and small sample size could limit the generality and exhaustiveness of the findings.

Practical implications

– The framework and its extension can be used by practitioners in assessing and classifying their suppliers for strengthening supply chain collaboration.

Originality/value

– This research unveils five new criteria used by buyer companies for supplier classification. The multi-criteria framework for supplier classification and its extension give new insights into the supplier characteristics significant for supply chain collaboration.

Supplier selection in closed loop supply chain by an integrated simulation-Taguchi-DEA approach

Purpose

– Reverse logistics refer to processes related to the reuse of products. The role of suppliers’ performance is crucial in achieving quality, cost, service and delivery aims of a supply chain. The selection of suppliers is regarded as one of the critical issues encountered by purchasing and operations managers in a supply chain to enhance organization’s global marketplace competitiveness. Most of the supply chain models are rather complex problems. Consequently, it is impossible to propose systematic models to handle them. Therefore, in this paper a new integrated approach based on experimental design and computer simulation is proposed for supplier selection. The paper aims to discuss these issues.

Design/methodology/approach

– In this study, a simulation approach is implemented to determine certain equivalent of parameters values in a CLSC network design which cannot be computed through mathematical model. Suppliers’ order quantities are investigated by Taguchi method for planning time horizon. Moreover, data envelopment analysis (DEA) is applied to assess suppliers based on quality, cost, delivery time, production capabilities, services and technology.

Findings

– In the numerical example, there are three suppliers for different regions. Purchase value of each supplier is measured in three years successively. According to the proposed method, the authors find the minimum level of costs together with the maximum number of high-quality products.

Practical implications

– The objective functions of model are minimizing the costs and maximizing number of high-quality products. The integrated approach introduced in this paper enables managers to select their suppliers effectively in their real system.

Originality/value

– Most supply chain models are complex and the identification of proper and optimal solutions in complex real-world systems often requires the solution of multi-objective problems involving multiple stochastic variables. Therefore, the paper introduces a new integrated approach for supplier selection in closed loop supply chain. To the best of the authors knowledge, this is the first study that integrates DEA, computer simulation and Taguchi method for supplier selection in closed loop supply chains.

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.