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1 – 10 of 347
Article
Publication date: 10 July 2020

Morteza Yazdani, Ali Ebadi Torkayesh and Prasenjit Chatterjee

In this study, an integrated decision-making model consisting of decision-making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and a modified version of…

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Abstract

Purpose

In this study, an integrated decision-making model consisting of decision-making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and a modified version of evaluation based on distance from average solution (EDAS) methods is proposed for supplier selection problem in a public procurement system considering sustainable development goals.

Design/methodology/approach

DEMATEL and BWM methods are used to determine weights of the criteria that are defined for the supplier selection problem. Weight aggregation method is applied to combine the weights obtained from these two methods. A modified version of EDAS method is then used in order to rank the alternative suppliers.

Findings

The proposed decision-making model is investigated for a supplier selection problem for a hospital in Spain. The validity of the results is checked using comparison with other decision-making methods and several performance analysis tests.

Practical implications

The proposed multi-criteria decision-making (MCDM) model contributes to the healthcare supply chain management (SCM) and aims to lead the policy makers in selecting the best supplier.

Originality/value

There is no such study that combines DEMATEL and BWM together for weight generation. The application of the modified EDAS method is also new. In real time situations, the decision experts may confront to the difficulty of using BWM while identifying the best and the worst criteria choices. The idea of using DEMATEL is to aid the experts to make them enable in distinguishing between the best/worst criteria and handle BWM easily.

Details

Journal of Enterprise Information Management, vol. 33 no. 5
Type: Research Article
ISSN: 1741-0398

Keywords

Article
Publication date: 18 September 2019

Faisal Talib, Mohammad Asjad, Rajesh Attri, Arshad Noor Siddiquee and Zahid A. Khan

Recent years have witnessed a significant rise in Indian healthcare establishments (HCEs) which indicate that there is a constant need to improve the healthcare quality services…

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Abstract

Purpose

Recent years have witnessed a significant rise in Indian healthcare establishments (HCEs) which indicate that there is a constant need to improve the healthcare quality services through the adoption and implementation of TQM enablers. The purpose of this paper is to identify such enablers and then propose a ranking model for TQM implementation in Indian HCEs for improved performance.

Design/methodology/approach

The study identifies 20 TQM enablers through comprehensive literature survey and expert’s opinion, and classifies them into five main categories. The prominence of these enablers is established using a recently developed novel multi-criteria decision making (MCDM) method, i.e. best-worst method (BWM). The importance of the various main category and sub-category enablers is decided on the basis of their weights which are determined by the BWM. In comparison to other MCDM methods, such as analytical hierarchy process, BWM requires relatively lesser comparison data and also provides consistent comparisons which results in both optimal and reliable weights of the enablers considered in this paper. Further, a sensitivity analysis is also carried out to ensure that the ranking (based on the optimal weights) of the various enablers is reliable and robust.

Findings

The results of this study reveal that out of five main category enablers, the “leadership-based enablers (E1)” and the “continuous improvement based enablers (E5)” are the most and the least important enablers, respectively. Similarly, among the 20 sub-category enablers, “quality leadership and role of physicians (E14)” and “performing regular survey of customer satisfaction and quality audit (E52)” are the most and the least dominating sub-category enablers, respectively.

Research limitations/implications

This study does not explore the interrelationship between the various TQM enablers and also does not evaluate performance of the various HCEs based on the weights of the enablers.

Practical implications

The priority of the TQM enablers determined in this paper enables decision makers to understand their influence on successful implementation of the TQM principles and policies in HCEs leading to an overall improvement in the system’s performance.

Originality/value

This study identifies the various TQM enablers in HCEs and categorizes them into five main categories and ranks them using the BWM. The findings of this research are quite useful for management of the HCEs to properly understand the relative importance of these enablers so that managers can formulate an effective and efficient strategy for their easy and smooth implementation which is necessary for continuous improvement.

Details

The TQM Journal, vol. 31 no. 5
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 4 February 2022

Vimal K.E.K., Simon Peter Nadeem, Siddharth Meledathu Sunil, Gokul Suresh, Navaneeth Sanjeev and Jayakrishna Kandasamy

Improving the medical oxygen supply chain (MOSC) is important to cope with the uneven demand and supply seen in the MOSC when India faced the second wave of COVID-19. This…

Abstract

Purpose

Improving the medical oxygen supply chain (MOSC) is important to cope with the uneven demand and supply seen in the MOSC when India faced the second wave of COVID-19. This improvisation increases the supply chain (SC) maturity and consequently the efficiency and resiliency to tackle oxygen shortage across the country and to prevent another similar scenario from ever happening. The purpose of this study is to identify and prioritize the solutions to overcome the issues faced by the MOSC during the second wave of COVID-19 cases in India and in turn reduce the extent of casualties in the expected third wave.

Design/methodology/approach

This paper uses best worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution to classify the sub-criteria for solutions to solve major SC issues. BWM is used to determine the weights of the sub-criteria and fuzzy technique for order performance by similarity to ideal solution for the final ranking of the solutions to be adopted.

Findings

The result of this study shows that the Internet of Things based tagging system is the best solution followed by horizontal and vertical integration of SC in making a resilient and digitized MOSC capable of handling general bottlenecks during a possible third wave.

Research limitations/implications

The research provides insights that can enable the personnel involved in MOSC. Proper understanding will help the practitioners involved in the SC to effectively tailor the operations and to allocate the resources available in an effective and dynamic manner by minimizing or eliminating the pre-existing bottlenecks within the SC.

Originality/value

The proposed framework provides an accurate ranking and decision-making tool for the implementation of the solutions for the maturity of the MOSC.

Article
Publication date: 4 July 2023

Priya Ambilkar, Priyanka Verma and Debabrata Das

This research work has developed an integrated fuzzy Delphi and neutrosophic bestworst framework for selecting the sustailient (sustainable and resilient) supplier for an…

Abstract

Purpose

This research work has developed an integrated fuzzy Delphi and neutrosophic bestworst framework for selecting the sustailient (sustainable and resilient) supplier for an additive manufacturing (AM)-enabled industry.

Design/methodology/approach

An integrated fuzzy Delphi method (FDM) and neutrosophic bestworst method (N-BWM) approach is developed. 34 supplier evaluation criteria falling under 4 groups, that is, traditional, sustainable, resilient, and AM specific, are identified and validated using the FDM. Afterward, the weights of each criterion are measured by N-BWM. Later on, the performance evaluation is carried out to determine the best-suited supplier. Finally, sensitivity analysis is performed to know the stability and robustness of the proposed framework.

Findings

The outcome indicates the high performance of the suggested decision-making framework. The analysis reveals that supplier 4 (S4) is selected as the most appropriate for a given firm based on the FDM and N-BWM method.

Research limitations/implications

The applicability of this framework is demonstrated through an industrial case of a 3D-printed trinket manufacturer. The proposed research helps AM decision-makers better understand resiliency, sustainability, and AM-related attributes. With this, the practitioners working in AM business can prioritize the supplier selection criteria.

Originality/value

This is the primitive study to undertake the most critical aspect of supplier selection for AM-enabled firms. Apart from this, an integrated FDM-N-BWM framework is a novel contribution to the literature on supplier selection.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 31 December 2019

Mona Jami Pour, Javad Mesrabadi and Mahnaz Hosseinzadeh

Today, the high cost of e-learning systems’ implementation and the difficulty of managing the infrastructures motivate educational institutions toward application of cloud-based…

Abstract

Purpose

Today, the high cost of e-learning systems’ implementation and the difficulty of managing the infrastructures motivate educational institutions toward application of cloud-based e-learning systems. This new system should be aligned with the academics’ aims and pedagogical principles to be beneficial for learners and instructors. Therefore, the vendor selection of learning systems is one of the most important processes to migrate toward cloud-based e-learning. The purpose of this paper is to develop a new framework to facilitate the vendor selection of cloud-based e-learning systems in the cloud market.

Design/methodology/approach

To identify the initial criteria as to the vendor selection of cloud-based e-learning services, a literature review is done. To enrich the initial criteria, a focus group of experts is investigated, and the framework developed; then, a survey analysis is conducted to validate the proposed framework. The extracted criteria and sub-criteria are weighted and prioritized using best-worst method (BWM).

Findings

The results indicate that the main dimensions of vendor selection framework as regards cloud-based e-learning systems are managerial, technological and pedagogical factors. The rank orders and weights of the mentioned aspects and their sub-criteria are calculated using the BWM.

Practical implications

The proposed framework helps managers to get a big picture of requirements as to cloud-based e-learning and more effectively to select appropriate vendors in this initiative. In the vendor selection process, managers must pay attention to technological issues as well as managerial and pedagogical considerations.

Originality/value

Cloud-based e-learning systems are getting increasingly essential to offer training courses more efficiently in educational institutions. Although the intersection between cloud computing and e-learning has increasingly grown in both practical and academic contexts, there are little studies on how educational institutions and organizations could be able to select appropriate cloud-based e-learning systems. This paper explores the ignored but critically important subject of cloud-based e-learning. The main contribution of this paper is to propose a novel and integrated framework containing the important aspects of vendor selection in cloud-based e-learning services. The proposed framework comprises managerial, technological and pedagogical aspects simultaneously as well as sub-criteria denoting each aspect.

Details

Online Information Review, vol. 44 no. 1
Type: Research Article
ISSN: 1468-4527

Keywords

Article
Publication date: 30 July 2021

Sharfuddin Ahmed Khan, Simonov Kusi-Sarpong, Iram Naim, Hadi Badri Ahmadi and Adegboyega Oyedijo

The purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance.

Abstract

Purpose

The purpose of paper is to develop a performance evaluation framework for manufacturing industry to evaluate overall manufacturing performance.

Design/methodology/approach

The best-worst method (BWM) is used to aid in developing a performance evaluation framework for manufacturing industry to evaluate their overall performance.

Findings

The proposed BWM-based manufacturing performance evaluation framework is implemented in an Indian steel manufacturing company to evaluate their overall manufacturing performance. Operational performance of the organization is very consistent and range between 60% and 70% throughout the year. Management performance can be seen high in the 1st and 2nd quarter of the financial year ranging from 70% to 80%, whereas a slight decrease in the management performance is observed in the 3rd and 4th quarter ranging from 60% to 70%. The social stakeholder performance has a peak in first quarter ranging from 80% to 100% as at start of financial year.

Originality/value

This paper utilized BWM, a MCDM method in developing a performance evaluation index that integrates several categories of manufacturing and evaluates overall manufacturing performance. This is a novel contribution to BWM decision-making application.

Details

Kybernetes, vol. 51 no. 10
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 14 March 2022

Sayyid Ali Banihashemi and Mohammad Khalilzadeh

Recognizing the factors affecting employees’ job motivation is one of the necessities that can improve people’s performance and increase their effectiveness. This study aims to…

Abstract

Purpose

Recognizing the factors affecting employees’ job motivation is one of the necessities that can improve people’s performance and increase their effectiveness. This study aims to determine the factors affecting job motivation and to examine effective strategies to increase motivation through identifying internal and external factors.

Design/methodology/approach

In this descriptive study, the statistical population was the employees of the largest petrochemical company in Iran. The questionnaire was randomly distributed to the organization’s employees and managers based on Herzberg’s motivation-hygiene theory. To analyze the obtained data, first, the best and the worst factors were identified using SPSS software and then were ranked using bestworst method (BWM).

Findings

The results demonstrated that the highest rank among the motivational factors of employees is related to working environment conditions and the lowest rank is related to career advancement and development indicator. In the second stage, the best strategies for motivational factors were determined using the fuzzy goal programming method. The findings showed that 12 out of the 17 proposed solutions have the highest motivation among employees, the implementation of which can increase employee productivity in the petrochemical company under study.

Originality/value

Further to the best of the authors’ knowledge, job motivation factors in the petrochemical industry have never been examined and ranked by using the BWM method so far. Also, the goal programming approach has never been applied to determine strategies for increasing job motivation and ultimately productivity.

Details

International Journal of Energy Sector Management, vol. 16 no. 6
Type: Research Article
ISSN: 1750-6220

Keywords

Article
Publication date: 15 March 2022

Vikas Swarnakar, Anthony Bagherian and A.R. Singh

Recent years have seen an increased demand for healthcare services, presenting a need to improve service quality through the deployment of sustainable Lean Six Sigma (LSS). This…

Abstract

Purpose

Recent years have seen an increased demand for healthcare services, presenting a need to improve service quality through the deployment of sustainable Lean Six Sigma (LSS). This study aims to identify critical success factors (CSFs) of sustainable LSS and prioritize them based on their intensity of importance for the effective implementation of sustainable LSS in the healthcare environment.

Design/methodology/approach

The present study identified 33 leading CSFs through a comprehensive literature review and expert experience and classified them into six major categories based on organizational functions. The primacy of these CSFs is established using the best-worst-method (BWM) approach. The significant advantage of this approach is that the decision-maker identifies both the best and worst criteria among alternatives prior to pairwise comparisons, leading to fewer pairwise comparisons and saving time, energy and resources. It also provides more reliable and consistent rankings.

Findings

The findings of the present study highlight the economic and managerial (E&M) CSFs as the most significant CSFs among the major category criteria of sustainable LSS-CSFs, followed by organizational (O), knowledge and learning (K&L), technological (T), social and environmental (S&E), and external factors (EF). Similarly, management involvement and leadership to implement sustainable LSS (E&M1), structured LSS deployment training and education (K&L2), and availability of required resources and their efficient utilization (O2) are ranked as the topmost CSFs among sub-category criteria of sustainable LSS-CSFs.

Practical implications

The prioritization of sustainable LSS-CSFs determined in this study can provide healthcare managers, researchers and decision-makers with a better understanding of the influence on effective deployment of sustainable LSS, resulting in improved service quality in hospitals.

Originality/value

This paper is an original contribution to the analysis of CSFs in an Indian healthcare institute, utilizing the BMW method for ranking the sustainable LSS-CSFs. The advantage of utilizing and distinguishing the performance of this approach compared to other MCDA approaches in terms of (1) least pairwise comparison and violation, (2) consistency (3) slightest deviation and (4) conformity.

Details

The TQM Journal, vol. 35 no. 3
Type: Research Article
ISSN: 1754-2731

Keywords

Article
Publication date: 17 January 2023

M. Puviarasu, P. Asokan, S. Umar Sherif, K. Mathiyazhagan and P. Sasikumar

Increased demand for new batteries and strict government protocols have stressed the battery industries to collect and recycle used batteries for economic and environmental…

Abstract

Purpose

Increased demand for new batteries and strict government protocols have stressed the battery industries to collect and recycle used batteries for economic and environmental benefits. This scenario has forced the battery industries to collect used batteries and establish the formal battery recycling plant (BRP) for effective recycling. The starting of BRP includes several strategic decisions, one of the most critical decisions encountered is to find the best sustainable location for BRP. Hence, this paper aims to address the complexity of the issues faced during the BRP location selection through a hybrid framework.

Design/methodology/approach

In this study, the criteria are identified under socio-cultural, technical, environmental, economic and policy and legal (STEEP) dimensions through literature review and experts' opinions. Then, the hybrid methodology integrating fuzzy decision making trial and evaluation laboratory (DEMATEL), best worst method (BWM) and technique for order preference by similarity to an ideal solution (TOPSIS) has been proposed to find the inter-relationship between criteria, the weights of criteria and the best alternative.

Findings

The identified five main criteria and 26 sub-criteria have been analyzed through fuzzy DEMATEL, and found that the policy and legal criteria have more inter-relationship with other criteria. Then from BWM results, it is found that the support from government bodies has attained the maximum weightage. Finally, the second alternative has been identified as a more suitable location for establishing BRP using TOPSIS. Further, it is found from the results that the support from government bodies, the impact of emissions, availability of basic facilities and community health are the essential criteria under STEEP dimensions for establishing BRP.

Originality/value

In addition to the various existing sustainable criteria, this study has also considered a set of policy and legal criteria for the evaluation of locations for BRP. Further, the hybrid MCDM method has been proposed in this study for selecting the best alternative. Thus, this study has yielded more insights to the decision-makers in choosing a sustainable location for BRP.

Details

Journal of Advances in Management Research, vol. 20 no. 2
Type: Research Article
ISSN: 0972-7981

Keywords

Article
Publication date: 15 September 2020

Amir Karbassi Yazdi, Peter Fernandes Wanke, Thomas Hanne and Eleonora Bottani

This paper aims to assess and prioritize manufacturing companies in the healthcare industry based on critical success factors (CSFs) of their reverse logistics (RL). The research…

Abstract

Purpose

This paper aims to assess and prioritize manufacturing companies in the healthcare industry based on critical success factors (CSFs) of their reverse logistics (RL). The research involves seven medical device companies located in the Tehran Province, Iran.

Design/methodology/approach

To identify and prioritize companies based on CSFs of RL, the study proposes a three-phase decision-making framework that integrates the Delphi method, the best-worst method (BWM) and the Additive Ratio Assessment (ARAS) method with Z-numbers. The weights required for this method are obtained by a variant of the BWM based on Z-numbers, denoted as Z-numbers Best-Worst Method, or ZBWM. Since decision-makers face an uncertain environment, Z-numbers, which are a kind of fuzzy numbers, are applied.

Findings

First, after customizing CSFs by the Delphi method and obtaining 15 CSFs of RL, these are ranked by the hybrid BWM-ARAS method with Z-numbers. Results reveal which company appears to perform best with respect to their RL implementations. Based on this result, healthcare device companies should choose the highest priority company based on the selected RL CSFs and results from using the BWM-ARAS method with Z-numbers.

Originality/value

The contribution of this paper is using a hybrid ARAS-BWM method based on Z-numbers. Each of these methods has some merits compared to other similar methods. The combination of these methods contributes a new approach for prioritizing companies based on RL CSFs with high accuracy and reliability.

Details

Journal of Enterprise Information Management, vol. 33 no. 5
Type: Research Article
ISSN: 1741-0398

Keywords

1 – 10 of 347