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1 – 10 of over 1000Hajar Regragui, Naoufal Sefiani, Hamid Azzouzi and Naoufel Cheikhrouhou
Hospital structures serve to protect and improve public health; however, they are recognized as a major source of environmental degradation. Thus, an effective performance…
Abstract
Purpose
Hospital structures serve to protect and improve public health; however, they are recognized as a major source of environmental degradation. Thus, an effective performance evaluation framework is required to improve hospital sustainability. In this context, this study presents a holistic methodology that integrates the sustainability balanced scorecard (SBSC) with fuzzy Delphi method and fuzzy multi-criteria decision-making approaches for evaluating the sustainability performance of hospitals.
Design/methodology/approach
Initially, a comprehensive list of relevant sustainability evaluation criteria was considered based on six SBSC-based dimensions, in line with triple-bottom-line sustainability dimensions, and derived from the literature review and experts’ opinions. Then, the weights of perspectives and their respective criteria are computed and ranked utilizing the fuzzy analytic hierarchy process. Subsequently, the hospitals’ sustainable performance values are ranked based on these criteria using the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution.
Findings
A numerical application was conducted in six public hospitals to exhibit the proposed model’s applicability. The results of this study revealed that “Patient satisfaction,” “Efficiency,” “Effectiveness,” “Access to care” and “Waste production,” respectively, are the five most important criteria of sustainable performance.
Practical implications
The new model will provide decision-makers with management tools that may help them identify the relevant factors for upgrading the level of sustainability in their hospitals and thus improve public health and community well-being.
Originality/value
This is the first study that proposes a new hybrid decision-making methodology for evaluating and comparing hospitals’ sustainability performance under a fuzzy environment.
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Aniruddh Nain, Deepika Jain and Ashish Trivedi
This paper aims to examine and compare extant literature on the application of multi-criteria decision-making (MCDM) techniques in humanitarian operations (HOs) and humanitarian…
Abstract
Purpose
This paper aims to examine and compare extant literature on the application of multi-criteria decision-making (MCDM) techniques in humanitarian operations (HOs) and humanitarian supply chains (HSCs). It identifies the status of existing research in the field and suggests a roadmap for academicians to undertake further research in HOs and HSCs using MCDM techniques.
Design/methodology/approach
The paper systematically reviews the research on MCDM applications in HO and HSC domains from 2011 to 2022, as the field gained traction post-2004 Indian Ocean Tsunami phenomena. In the first step, an exhaustive search for journal articles is conducted using 48 keyword searches. To ensure quality, only those articles published in journals featuring in the first quartile of the Scimago Journal Ranking were selected. A total of 103 peer-reviewed articles were selected for the review and then segregated into different categories for analysis.
Findings
The paper highlights insufficient high-quality research in HOs that utilizes MCDM methods. It proposes a roadmap for scholars to enhance the research outcomes by advocating adopting mixed methods. The analysis of various studies revealed a notable absence of contextual reference. A contextual mind map specific to HOs has been developed to assist future research endeavors. This resource can guide researchers in determining the appropriate contextual framework for their studies.
Practical implications
This paper will help practitioners understand the research carried out in the field. The aspiring researchers will identify the gap in the extant research and work on future research directions.
Originality/value
To the best of the authors’ knowledge, this is the first literature review on applying MCDM in HOs and HSCs. It summarises the current status and proposes future research directions.
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Satish Kumar, Arun Gupta, Anish Kumar, Pankaj Chandna and Gian Bhushan
Milling is a flexible creation process for the manufacturing of dies and aeronautical parts. While machining thin-walled parts, heat generation during machining essentially…
Abstract
Purpose
Milling is a flexible creation process for the manufacturing of dies and aeronautical parts. While machining thin-walled parts, heat generation during machining essentially affects the accuracy. The workpiece temperature (WT), as well as the responses like material removal rate (MRR) and surface roughness (SR) for input parameters like cutting speed (CS), feed rate (F), depth-of-cut (DOC), step over (SO) and tool diameter (TD), becomes critical for sustaining the accuracy of the thin walls.
Design/methodology/approach
Response surface methodology was used to make 46 tests. To convert the multi-character problem into a single-character problem, the weightage was assessed using the entropy approach and the grey relational coefficient (GRC) was determined. To investigate the connection among input parameters and single-objective (GRC), a fuzzy mathematical modelling technique was used. The optimal performance of process parameters was estimated by grey relational entropy grade (GREG)-fuzzy and genetic algorithm (GA) optimization.
Findings
SR was found to be a significant process parameter, with CS, feed and DOC, respectively. Similarly, F, DOC and TD were found to be significant process parameters with MRR, respectively, and F, DOC, SO and TD were found to be significant process parameters with WT, respectively. GREG-fuzzy-GA found more suitable for minimizing the WT with the constraint s of SR and MRR and provide maximum desirability of 0.665. The projected and experimental values have a good agreement, with a standard error of 5.85%, and so the responses predicted by the suggested method are better optimized.
Originality/value
The GREG-fuzzy-GA is a new hybrid technique for analysing Inconel625 behaviour during machining in a 2.5D milling process.
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Miguel Angel Ortíz-Barrios, Stephany Lucia Madrid-Sierra, Antonella Petrillo and Luis E. Quezada
Food manufacturing supply chain systems are the most relevant wheels of the world economy since they provide essential products supporting daily life. Nevertheless, various supply…
Abstract
Purpose
Food manufacturing supply chain systems are the most relevant wheels of the world economy since they provide essential products supporting daily life. Nevertheless, various supply inefficiencies have been reported to compromise food safety in different regions. Sustainable supplier management and digitalization practices have become cornerstone activities in addressing these shortcomings. Therefore, this paper proposes an integrated method for sustainability management in digital manufacturing supply chain systems (DMSCS) from the food industry.
Design/methodology/approach
The Intuitionistic Fuzzy Analytic Hierarchy Process (IF-AHP) was used to weigh the criteria and subcriteria under uncertainty. Second, the Intuitionistic Fuzzy Decision-Making Trial and Evaluation Laboratory (IF-DEMATEL) was applied to determine the main DMSCS sustainability drivers whilst incorporating the expert's hesitancy. Finally, the Combined Compromise Solution (CoCoSo) was implemented to pinpoint the weaknesses hindering DMSCS sustainability. A case study from the pork supply chain was presented to validate this method.
Findings
The most important criterion for DMSCS sustainability management is “location” while “manufacturing capacity” is the most significant dispatcher.
Originality/value
This paper presents a novel approach integrating IF-AHP, IF-DEMATEL, and CoCoSo methods for sustainability management of DMSCS pillaring the food industry.
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Javier Isaac Torres Vergara, Jania Astrid Saucedo Martínez and Daniela Olivo Lucio
In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and…
Abstract
Purpose
In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and sustainability paradigms. In this way, this research aims to identify the attributes that a supply chain (SC) should follow to be resilient and sustainable, and then to evaluate their importance according to industry experts.
Design/methodology/approach
This study suggests a hybrid approach. The authors identified the most commonly used criteria using literature review, and then applied fuzzy Delphi technique (FDT) with the objective of surveying experts to find the attributes used in practice and asked to assess their relevance.
Findings
The resilient-sustainable supply chain (RSSC) is formed by four dimensions: resiliency, economic, environmental and social. A total of 15 criteria are identified, and the most important are visibility, flexibility, supply chain risk management (SCRM) culture, work conditions and communication.
Research limitations/implications
This study used a literature review, so it is subject to a time frame, and the criteria could no longer be relevant as the time and business conditions change. Also, the findings may not be completely applicable throughout different industries, and therefore the finding cannot be replicated to other businesses.
Practical implications
This study will assist decision-makers among other interested parties to construct and/or strengthen an integrated SC that mixes resiliency and sustainability.
Originality/value
This study contributes to the state-of-art by producing a characterization of the resilient and sustainable supply chain for the automotive industry. Also, this research produces a new and holistic framework for resilient and sustainable SCPM supporting the decision-making process.
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Mershack Opoku Tetteh, Albert P.C. Chan, Amos Darko, Beliz Özorhon and Emmanuel Adinyira
International construction joint ventures (ICJVs) will fully realize their potential for success and effectively monitor performance when an adequate and suitable performance…
Abstract
Purpose
International construction joint ventures (ICJVs) will fully realize their potential for success and effectively monitor performance when an adequate and suitable performance benchmark is established. However, existing studies fall short of adequately providing a mutually acceptable benchmark for assessing the performance of ICJVs. This study aims to develop an adequate and suitable performance measurement framework for ICJVs.
Design/methodology/approach
A twofold structured questionnaire survey, supplemented by semi-structured interviews, was used to collect data from the practitioners of ICJVs hosted in the developing country of Ghana. The data were analyzed by using descriptive statistics, confirmatory factor analysis (CFA) and a hybrid-fuzzy logic approach.
Findings
A list of 30 performance indicators (PIs), defined by project performance, perceived satisfaction, company/partner performance, socio-environmental performance and performance of ICJV management, was validated and proved to be significant. Only 22 out of the 30 PIs, focusing on project efficiency, societal improvement and organizational goals are realized by the ICJV practitioners. Further, suitable determinants and viable quantitative ranges for measuring each PI are established to prevent different interpretations of the meanings of PIs and objectively express the level of success in quantitative terms. The results call for further investigation of the convergence between the practice of and research into some PIs (e.g. socio-environmental performance) and a range of different performance levels (PLs) in a more scientific manner.
Practical implications
This study not only advances the knowledge base and practice of performance measurement in ICJVs but could also assist stakeholders and decision-makers to assess, compare and monitor the performance of different ICJV projects on common grounds objectively.
Originality/value
This study not only comprehensively assessed PIs – what to measure – but also systematically determined suitable determinants – how to measure – for each PI.
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Sumanta Das, Akhilesh Barve, Naresh Chandra Sahu and Devendra K. Yadav
This paper aims to identify, analyze and evaluate the major enablers for the sustainable public distribution system (PDS) supply chain in India in lessening food insecurity by…
Abstract
Purpose
This paper aims to identify, analyze and evaluate the major enablers for the sustainable public distribution system (PDS) supply chain in India in lessening food insecurity by distributing essentials food grains at a subsidized rate.
Design/methodology/approach
The major enablers for the sustainable PDS supply chain were explored by conducting the literature survey and discussion with academic and warehouse experts. Then, the fuzzy-DEMATEL (decision-making trial and evaluation laboratory) technique was applied to develop a causal model that analyses the interaction among the identified enablers.
Findings
This study recognizes fifteen enablers through literature survey and experts' opinions. The present work concludes that “proper identification of the PDS beneficiaries” and “willingness and commitment of the top management and policymaker” are the two major enablers for the sustainable PDS supply chain.
Research limitations/implications
This work would be helpful for profoundly understanding the major enablers, and how they are affecting the entire PDS supply chain. The study would be beneficial for the general people and the entire society straightforwardly by providing suggestions for food security.
Originality/value
Identifying and analyzing the major enablers for the sustainable PDS supply chain helps to visualize the problem more effectively and efficiently. Besides, the causal model explains a comprehensive perspective on the identified enablers.
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Ahmet Aytekin, Ömer Faruk Görçün, Fatih Ecer, Dragan Pamucar and Çağlar Karamaşa
Pharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and…
Abstract
Purpose
Pharmaceutical supply chains (PSCs) need a well-operating and faultless logistics system to successfully store and distribute their medicines. Hospitals, health institutes, and pharmacies must maintain extra stock to respond requirements of the patients. Nevertheless, there is an inverse correlation between the level of medicine stock and logistics service level. The high stock level held by health institutions indicates that we have not sufficiently excellent logistics systems presently. As such, selecting appropriate logistics service providers (drug distributors) is crucial and strategic for PSCs. However, this is difficult for decision-makers, as highly complex situations and conflicting criteria influence such evaluation processes. So, a robust, applicable, and strong methodological frame is required to solve these decision-making problems.
Design/methodology/approach
To achieve this challenging issue, the authors develop and apply an integrated entropy-WASPAS methodology with Fermatean fuzzy sets for the first time in the literature. The evaluation process takes place in two stages, as in traditional multi-criteria problems. In the first stage, the importance levels of the criteria are determined by the FF-entropy method. Afterwards, the FF-WASPAS approach ranks the alternatives.
Findings
The feasibility of the proposed model is also supported by a case study where six companies are evaluated comprehensively regarding ten criteria. Herewith, total warehouse capacity, number of refrigerated vehicles, and personnel are the top three criteria that significantly influence the evaluation of pharmaceutical distribution and warehousing companies. Further, a comprehensive sensitivity analysis proves the robustness and effectiveness of the proposed approach.
Practical implications
The proposed multi-attribute decision model quantitatively aids managers in selecting logistics service providers considering imprecisions in the multi-criteria decision-making process.
Originality/value
A new model has been developed to present a sound mathematical model for selecting logistics service providers consisting of Fermatean fuzzy entropy and WASPAS methods. The paper's main contribution is presenting a comprehensive and more robust model for the ex ante evaluation and ranking of providers.
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Mohd Imran Khan, Shahbaz Khan, Urfi Khan and Abid Haleem
Big Data can be utilised for efficient use of resources and to provide better services to the resident in order to enhance the delivery of urban services and create sustainable…
Abstract
Purpose
Big Data can be utilised for efficient use of resources and to provide better services to the resident in order to enhance the delivery of urban services and create sustainable build environment. However, the adoption of Big Data faces many challenges at the implementation level. Therefore, the purpose of this paper is to identify the challenges towards the efficient application of Big Data in smart cities development and analyse the inter-relationships.
Design/methodology/approach
The 14 Big Data challenges are identified through the literature review and validated with the expert’s feedback. After that the inter-relationships among the identified challenges are developed using an integrated approach of fuzzy Interpretive Structural Modelling (fuzzy-ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (fuzzy-DEMATEL).
Findings
Evaluation of interrelationships among the challenges suggests that diverse population in smart cities and lack of infrastructure are the significant challenges that impede the integration of Big Data in the development of smart cities.
Research limitations/implications
This study will enable practitioners, policy planners involved in smart city projects in tackling the challenges in an optimised manner for the hindrance free and accelerated development of smart cities.
Originality/value
This research is an initial effort to develop an interpretive structural model of Big Data challenges for smart cities development which gives a clearer picture of how the identified challenges interact with each other.
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Asli Pelin Gurgun, Kerim Koc and Handan Kunkcu
Completing construction projects within the planned schedule has widely been considered as one of the major project success factors. This study investigates the use of…
Abstract
Purpose
Completing construction projects within the planned schedule has widely been considered as one of the major project success factors. This study investigates the use of technologies to address delays in construction projects and aims to address three research questions (1) to identify the adopted technologies and proposed solutions in the literature, (2) to explore the reasons why the delays cannot be prevented despite disruptive technologies and (3) to determine the major strategies to prevent delays in construction projects.
Design/methodology/approach
In total, 208 research articles that used innovative technologies, methods, or tools to avoid delays in construction projects were investigated by conducting a comprehensive literature review. An elaborative content analysis was performed to cover the implemented technologies and their transformation, highlighted research fields in relation to selected technologies, focused delay causes and corresponding delay mitigation strategies and emphasized project types with specific delay causes. According to the analysis results, a typological framework with appropriate technological means was proposed.
Findings
The findings revealed that several tools such as planning, imaging, geo-spatial data collection, machine learning and optimization have widely been adopted to address specific delay causes. It was also observed that strategies to address various delay causes throughout the life cycle of construction projects have been overlooked in the literature. The findings of the present research underpin the trends and technological advances to address significant delay causes.
Originality/value
Despite the technological advancements in the digitalization era of Industry 4.0, many construction projects still suffer from poor schedule performance. However, the reason of this is questionable and has not been investigated thoroughly.
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