Grey Decision Making Trial And Evaluation Laboratory Research Articles

Analyzing barriers to sustainable healthcare waste disposal: a hybrid decision-making framework

PurposeIn the recent post-pandemic era, the globe has been anxious for the sustainable disposal of healthcare waste to protect public health, protect the environment and enhance future preparedness. Developing countries, in particular, have struggled to dispose of healthcare waste (HCW) to eradicate the hazardous effects of medical waste generated during and after the deadly COVID-19 pandemic. Hence the purpose of the research paper is to develop a hybrid decision-making framework to identify various barriers for sustainable disposal of healthcare waste use of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP).Design/methodology/approachA hybrid framework of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP) has been used to rank barriers and sub-barriers in the disposal of healthcare waste.FindingsThe study’s findings suggest that lack of segregation practices, absence of green procurement policy, obsolete technologies and resistance to adopting change management are the topmost causal barriers influencing the remaining barriers. Lack of commitment among healthcare administrations, lack of standard performance measures and resistance to adopting change appear to be the topmost crucial barriers.Practical implicationsThe study’s finding enables all stakeholders to prioritize the barriers systematically for better performance and save resources during the process. The policymakers can use the results to design a clear regulatory framework.Originality/valueThe literature has highlighted the factors and their association with the disposal of healthcare waste mainly in isolation. The results are validated against the Grey-Analytical Hierarchy Process (G-AHP) to ensure the robustness of the proposed framework. This paper is one of the preliminary attempts to propose a framework of the interrelationships of the factors that have a direct role in survival for management education.

What hinders the implementation of carbon emission reduction in the construction industry: evidence from integrated multi-criteria decision-making in China

PurposeThis research paper aims to establish a comprehensive framework for the barriers to CER in the construction industry, assesses the barriers' relative degrees of hindrance and causal mechanisms.Design/methodology/approachFirstly, 26 carbon emission reduction (CER) barriers in the construction industry were identified based on a systematic literature review (SLR) and categorized into five dimensions: policy, economy, society, technology and organization (PEST + O model). Secondly, the Best–Worst Method (BWM) was used to clarify the degrees of hindrance of the CER barriers. Then, the Grey-Decision-Making Trial and Evaluation Laboratory (Grey-DEMATEL) was used to visualize the directional cause–result relationship network among prominent barriers. Finally, the Boston matrix model was used to propose differentiated strategies to address CER barriers in the construction industry.FindingsThe calculated centrality and causality of the prominent barriers indicated that the lack of relevant legal policies and normative guidelines, the poor binding force and enforcement of existing relevant policies, the lack of effective economic subsidies and incentives and the difficulty in the operation, transformation and upgrading of existing construction CER are the key barriers that CER needs to address first in the construction industry. Considering the order of priority and the optimal path, differentiated countermeasures are proposed to address key, driving, independent and effect barriers.Originality/valueThis study develops a BWM–Grey-DEMATEL integrated multi-criteria decision-making model. An innovative C-shaped strategic map for addressing CER barriers in the construction industry is proposed by integrating the dual dimensions of time and space. This will guide practitioners, policymakers and decision-makers in developing CER strategies.

Multi-Source Monitoring Data Fusion Comprehensive Evaluation Method for the Safety Status of Deep Foundation Pit

Construction of the deep foundation pit (DFP) in subway stations is fraught with significant uncertainties, which may cause project delays due to discrepancies between single-indicator monitoring warning information and actual conditions at the site. Therefore, this article proposes a safety assessment method for DFP based on the Game-Cloud Model. An entirely quantitative assessment index system is established with on-site monitoring projects according to the design safety classification of DFP. Considering the one-sidedness of using a single method to determine the weights of assessment indices, game theory is introduced to calibrate the subjective and objective weights determined by the grey decision-making trial and evaluation laboratory (GDEMATEL) and the entropy method, respectively. Next, we use the forward cloud generator of the cloud model (CM) to generate the safety level membership function of the evaluation indicators. Finally, we quantitatively calculate the synthetic safety level of DFP using the comprehensive evaluation approach. A 19-day dynamic assessment was conducted on the actual engineering project by the proposed method. The results indicated that the synthetic safety level of the assessed area ranged between grades Ⅰ and Ⅱ, corresponding to Negligible and Acceptable in the acceptance criteria. Compared with the single-indicator monitoring warning results, it was more in line with on-site observation, which verified its reliability and practicality.

Sustainability assessment of power generation systems under the objective consideration of criteria interactions

The combination with carbon capture and storage (CCS) can significantly reduce CO2 emission in power generation systems, however, it remains to be clarified whether the CCS combination can make the power generation systems more sustainable by comprehensively taking account of economic, social and environmental effects. In this study, a novel multi-criteria decision-making (MCDM) mathematical framework was developed to evaluate the sustainability of power generation systems using either fossil energy (with or without CCS) or renewable energy sources. In the mathematical framework, interval numbers are used to retain the objective uncertainties, and an improved Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) method is employed to determine the weights of the evaluation criteria, which can avoid subjective uncertainties while considering the interactions between evaluation criteria. According to the affecting factors calculated by G-DEMATEL, the interaction between criteria can be visualized and key criteria can be identified more intuitively. Finally, the interval Vlsekriterijumska Optimizacijia I Kompromisno Resenje (VIKOR) method is employed to rank the sustainability of alternative power generation systems. In order to verify the developed framework, the sustainability of 6 power generation systems was assessed and compared by considering 10 criteria from dimensions of technology, environment, economy and society. The results show that “Wind power” is assessed as the most sustainable technology and the criterion of “Global warming” has the greatest impact on the sustainability of power generation systems, while the sustainability of power generation systems using fossil energy can be significantly improved by combining with CCS.

Blockchain Integrated IoT for Food Supply Chain: A Grey Based Delphi-DEMATEL Approach

The Food Supply Chain (FSC) can be made more efficient, resilient, and transparent by implementing industry 4.0 technologies. In this context, blockchain and the Internet of Things (IoT) become a panacea for several FSC problems. As a result of FSC complexity and their specific needs, the adoption of Blockchain integrated IoT (B-IoT) in FSC is challenging, and further investigation is required. Therefore, this study aims to explore the Critical Success Factors (CSFs) for the adoption B-IoT in FSC. To achieve this objective, a literature review is conducted to identify the CSFs of B-IoT adoption and then a grey Delphi is conducted on finalised CSFs. Ten CSFs finalised that faceplate for the adoption of B-IoT in FSC. Further, these CSFs were analysed through a grey Decision-Making Trial and Evaluation Laboratory (DEMATEL) to determine the importance and causal relationships among them. A grey DEMATEL analysis also categorised these factors into influencing and influenced groups. The findings showed that “top management support”, “knowledge management”, “technology hardware readiness”, “skilled personnel”, and “high investment” were the influencing factors that needed to be addressed for the effective adoption of B-IoT. The FSC partners could benefit from the findings of this study by focusing on high-priority CSFs. The causal relationship among CSFs also helps the managers achieve optimal utilisation of resources. Further, this study encourages the FSC stakeholders to adopt the B-IoT in their supply chain to improve their performance.

Method for a new risk assessment of urban inundation: G-DEMATEL–AHP

Urban flooding disasters caused by frequent heavy rainfall threaten the safety of residents and socioeconomic development. Thus, risk evaluation of urban inundation is a vital component of sustainable urban development. Analytical hierarchical process (AHP) and decision-making trial and evaluation laboratory (DEMATEL) are common methods applied to flood risk evaluation. The former focuses on the relationship among different layers, while the latter reflects the relationship of factors in one layer. Moreover, the ambiguity in the decision-making process can be reduced by the uncertainty system. Therefore, the proposed method integrates grey theory and utilises the characteristics of DEMATEL to establish the AHP comparison matrix, particularly when the scores given by experts’ questionnaires are scattered. The method was applied to the risk assessment of urban inundation in Zhengzhou and verified by its flooding disaster sites that occurred during the 20 July storm in 2021 [1].•Developed approach merges grey theory, DEMATEL, and AHP methods;•Application of G-DEMATEL-AHP method in risk assessment of urban inundation;•The proposed method can increase the reliability of risk assessment results.

The Digital Transformation of the Marketing Mix in the Food and Beverage Service Supply Chain: A Grey DEMATEL Approach

Over the last decade, digital marketing and technology have gradually penetrated the food and beverage industry, redefining its marketing mix. However, the urgency caused by the COVID-19 pandemic spurred the digital transformation of the industry, as businesses were forced to adapt to many changes and restrictions, reshape their operational models, and find ways to survive in an unstable marketplace. The purpose of this paper is to examine the transformation of the marketing mix in the food and beverage service supply chain due to the emergence of digital marketing. To this end, critical success factors for the digital transformation of the food and beverage service supply chain were identified based on the literature. These factors were assessed by experts from the Greek market using a grey decision-making trial and evaluation laboratory (DEMATEL) approach because of the complexity and interdependence of the factors interfering in the decision-making process. After a screening process, eight experts were selected to participate based on their experience and their acknowledged presence in the sector. DEMATEL is a multi-criterion decision-making method used to assist in addressing practical assessment issues. Its main advantage is that it can detect and observe the interdependence among the primary components and their relevance in the decision-making process. Additionally, it facilitates the visual display of the results, assisting in the analysis of the causal influence of factors. The combination of DEMATEL with grey system theory is useful because it makes it easier to analyze ambiguities brought on by uncertainties, lack of knowledge, or inadequate human actions. Fourteen critical success factors were identified, and they were grouped into three broad categories: technology-driven, consumer-driven, and industry-driven. Seven factors were classified as causes, and seven factors were classified as effects. In addition, with the use of the DEMATEL approach, the factors were grouped into core, driving, independent, and prominent factors.

Inundation risk assessment based on G-DEMATEL-AHP and its application to Zhengzhou flooding disaster

• Proposed G-DEMATEL-AHP method to assess inundation risk. • A new nine-score questionnaire was developed for G-DEMATEL-AHP method. • The five-year average precipitation scenario was set as the benchmark. • Validated by inundation of traffic system during 7.20 storm in Zhengzhou. • G-DEMATEL-AHP can effectively identify the most critical risk areas. This study proposed an integrated approach to investigate the flooding risk in urban areas of mega-cities. The new method integrated the grey decision-making trial and evaluation laboratory (Grey-DEMATEL) into analytical hierarchical process (AHP) (simplified as G-DEMATEL-AHP). The risk distribution was mapped using geographic information system (GIS). A nine-score questionnaire was adopted in Grey-DEMATEL to analyse the inundation risk. Zhengzhou was selected as a case study with different rainfall scenarios, including flooding disaster induced by heavy storm on July 20, 2021 (i.e., “7.20 Storm”) and average rainfall of five years (i.e., “5-Yr Average”). The results showed that the proposed method can assess the flood risk distribution effectively in Zhengzhou. Comparison between the results from different scenarios showed that the impact of the “7.20 Storm” was much stronger than that of the “5-Yr Average” scenario. Moreover, an existing method, fuzzy AHP (FAHP), was also used to assess the same scenario. The results indicated that the G-DEMATEL-AHP method could more effectively identify the most critical risk areas when compared to the FAHP.

Modeling Impacts of COVID-19 in Supply Chain Activities: A Grey-DEMATEL Approach

The purpose of this study was to identify and exhibit the interrelationships among COVID-19’s impacts on supply chain activities. Based on a literature review and the manager’s input, twenty COVID-19 impacts were collected. An integrated approach of exploratory factor analysis (EFA) and grey-decision-making trial and evaluation laboratory (G-DEMATEL) was used to reveal the causal interrelationships among the COVID-19 impacts. Initially, a questionnaire survey was administered among 220 respondents for EFA. Based on the outcome of EFA, the twenty COVID-19 impacts were categorized into seven critical areas. Then, based on the experts’ inputs, G-DEMATEL was utilized to reveal the causal interrelationships among various COVID-19 impacts. The results indicate that disruption management, relationship management, and production management are the top three critical areas that need to be addressed in the COVID-19 crisis. Disruption in supply, ripple effect on supply chain operations, and obsolescence of machines were found to be the most influential impacts while disproportionateness between supply and demand, difficulty in demand forecasting, and reduced cash inflow were found to be the most influenced impacts. This study’s outcomes will help policymakers and supply chain managers develop strategies to restructure supply chain networks. This study is an original contribution to the analysis of COVID-19 impacts in the supply chain activities in India due to the use of EFA and G-DEMATEL. This study considers India only, and hence, the outcomes lack generalizability. A study considering multiple developing countries could generalize these findings.

Shaping the handicraft cluster through innovation capability

There are several enablers to the innovation capability in the exisiting literature, but they all are considered with equal importance. Researchers believe ranking will advance the understanding of academicians and practitioners further. Hence, we started by recognizing the enablers from the available literature and exploring the possible causal relationship among them. A framework based on the causal relationship among the enablers is proposed. Grey DEMATEL (Decision-making trial and evaluation laboratory) has been used to establish this causal relationship. This study identifies nine of the fifteen enablers as causal factors. They are as follows: Knowledge Exploration, Ideation and Organizational Structure, Organizational Climate, Risk Taking Ability, Collaboration and Networking, Institutional Support, Rejuvenation and Upgrading, Leadership Practices, Technological Adaptation. Practitioners, academicians, and policymakers will have a better understanding of this causal relationship among enablers. Knowledge of these enablers will help in fostering a more conducive environment for escalating the process of innovation in the handicraft cluster.

To select suitable supplier for complex equipment military-civilian collaborative design based on fuzzy preference information that from matching perspective

Combine complex equipment collaborative development in military-civilian integration context not only fulfils actual development requirement, but also beneficial to the national economy. Design procedure as first stage of complex equipment military-civilian collaborative development process, select suitable design supplier is significant to whole development process of complex equipment. In order to select suitable design supplier for complex equipment, two aspects done in this paper. One is comprehensive analysis of evaluated influencing factors that affect complex equipment military-civilian collaborative design process, corresponding evaluation indicator constructed and a combination of grey correlation, entropy, DEMATEL (Decision-making Trial and Evaluation Laboratory) and VIKOR analysis theory to obtain grey entropy-DEMATEL-VIKOR, then the combined method is utilized to acquire matching attributes for followed research content. Meanwhile, satisfaction degree for matching side obtained with the help of information aggregation based on power generalized Heronian mean which on the basis of fuzzy preference information. Then, through constructed matching model, suitable design supplier obtained. Finally, a corresponding illustrative example given.

Supply chain management during and post-COVID-19 pandemic: Mitigation strategies and practical lessons learned

The COVID-19 pandemic has affected global supply chains at an unprecedented speed and scale. This paper investigates the supply chain challenges that manufacturing organizations have faced due to the COVID-19 outbreak, particularly in emerging economies. We present a conceptual framework under the dynamic capability theory to analyze challenges and their pertinent mitigation strategies. Ten major challenges are identified based on a literature review, evaluation of several news articles, and discussions with experts. Further, the Grey-Decision-making Trial and Evaluation Laboratory (Grey-DEMATEL) method is applied to analyze the relationships between various supply chain challenges. Scarcity of Labor (PSL) emerges as the most significant challenge, closely followed by Scarcity of Material (SSM). The results also suggest that Inconsistency of Supply (PIS) is the challenge that correlates the most with other factors. Finally, in this paper we also provide guidelines and strategies for practitioners and scholars to better address supply chain challenges post-COVID-19 outbreak.

Towards agility in international high-tech SMEs: Exploring key drivers and main outcomes of dynamic capabilities

• Explores the drivers that foster agility in international high-tech small and medium-sized enterprises • Takes advantage of the wealth of dynamic capabilities to evaluate causation and effectuation relationships that boost agility in internationaliser SMEs • Builds on MCDM method and employs G-DEMATEL and DANP. In the era of digitalisation, agility is considered a crucial factor for the successful operations of small and medium businesses in the intricate international markets. That is, this research aims to explore and evaluate the drivers that foster agility in international high-tech small and medium-sized enterprises (SMEs). In this regard, building on dynamic capabilities, a total of nine capabilities have been identified that assist high-tech SMEs to become agile in their cross-border activities. Taking advantage of an expert-based method, we relied on Multi-Criteria Decision-Making (MCDM) approach to synthesise the opinion of six Italian international entrepreneurs (experts). In doing so, Grey DEcision-MAking Trial and Evaluation Laboratory (G-DEMATEL) method has been employed to investigate the cause-effect relationship between capabilities and propose conceptual frameworks for agility in international high-tech SMEs. This is followed by the DEMATEL based Analytical Network Process (DANP) to assess the importance and ranking of explored factors. Consequently, the research proposes several theoretical and practical contributions.

Supply chain recovery challenges in the wake of COVID-19 pandemic

The COVID-19 pandemic has revealed the fragility of global supply chains arising from raw material scarcity, production and transportation disruption, and social distancing. Firms need to carefully anticipate the difficulties during recovery and formulate appropriate strategies to ensure the survival of their businesses and supply chains. To enhance awareness of the issues, this research aims to identify and model recovery challenges in the context of the Bangladeshi ready-made garment industry. A Delphi-based grey decision-making trial and evaluation laboratory (DEMATEL) methodology was used to analyze the data. While the Delphi method helped identify the major supply chain recovery challenges from the impacts of the COVID-19 pandemic, the grey DEMATEL approach helped categorize the causal relationships among these challenges. Of the 23 recovery challenges finalized, 12 are causal challenges. The study’s findings can assist decision-makers in developing strategic policies to overcome the recovery challenges in the post-COVID-19 era.

Sustainable Sports Tourism Performance Assessment Using Grey-Based Hybrid Model

The development of sports tourism is gaining momentum around the world, with many tourism industries combining sports events and programs to attract more domestic and overseas customers to promote economic and culture. Sustainability awareness has been gaining attention from many international organizations, resulting in the rise of sports tourism that incorporates sustainability. Therefore, the development of a valid and applicable sustainable sports tourism (SST) assessment model is an important task. In this study, a hybrid Multiple Attribute Decision-Making (MADM) model is proposed to measure the development performance of SST. The aims of this study include developing a SST assessment framework, identifying the mutual influential relationships among attributes, generating attribute influence weights, and calculating the performance of the evaluated items. The proposed model is divided into three stages. First, a cause-and-effect diagram is generated using the Grey Decision-Making Trial and Evaluation Laboratory (GDEMATEL) to describe the interactions and feedback among the attributes. Then, the GDEMATEL-based Analytic Network Process (GDANP) is applied to generate the influence weights of the attributes and their rankings. Finally, the expanded Probability-based Grey Relational Analysis (expanded PGRA) was applied to calculate the performance of the evaluated items and to determine the gap between evaluated items and the aspiration level. This study improves the original PGRA technique by introducing the concept of aspiration level into the PGRA calculation process, thereby replacing the traditional concept of “relative satisfaction” with “aspiration level”. In addition, the expanded PGRA can assess a single rated item without being limited to at least two items. We used the Sun Moon Lake Scenic Area in Taiwan as a model demonstration. The results show that the top three attributes that need to be strengthened are disease prevention and treatment, local social welfare and protection, and sports diversity. In the Sun Moon Lake, intersection control should be set up to ensure the health status of visitors and local residents. In addition to epidemic prevention, more measures and behaviors should be developed to deal with tourism diseases. We suggested that subsidies be provided to local residents to rebuild the fences around their homes to avoid disturbances caused by the influx of tourists. Moreover, the local government can create more sports events with special characteristics that can attract tourists to come again and again.

Pattern classification using tolerance rough sets based on non-additive grey relational analysis and DEMATEL

PurposeIt is challenging to derive an appropriate tolerance relation for tolerance rough set-based classifiers (TRSCs). The traditional tolerance rough set employs a simple distance function to determine the tolerance relation. However, such a simple function does not take into account criterion weights and the interaction among criteria. Further, the traditional tolerance relation ignores interdependencies concerning direct and indirect influences among patterns. This study aimed to incorporate interaction and interdependencies into the tolerance relation to develop non-additive grey TRSCs (NG-TRSCs).Design/methodology/approachFor pattern classification, this study applied non-additive grey relational analysis (GRA) and the decision-making trial and evaluation laboratory (DEMATEL) technique to solve problems arising from interaction and interdependencies, respectively.FindingsThe classification accuracy rates derived from the proposed NG-TRSC were compared to those of other TRSCs with distinctive features. The results showed that the proposed classifier was superior to the other TRSCs considered.Practical implicationsIn addition to pattern classification, the proposed non-additive grey DEMATEL can further benefit the applications for managerial decision-making because it simplifies the operations for decision-makers and enhances the applicability of DEMATEL.Originality/valueThis paper contributes to the field by proposing the non-additive grey tolerance rough set (NG-TRS) for pattern classification. The proposed NG-TRSC can be constructed by integrating the non-additive GRA with DEMATEL by using a genetic algorithm to determine the relevant parameters.

A robust hybrid decision model to evaluate critical factors of reverse logistics implementation using Grey-DEMATEL framework

The rising electronics waste (e-waste), increased pollution, disposal issues and exploitation of natural resources have augmented ecological and resource scarcity problems. These problems can be abate by adopting reverse logistics (RL) implementation so, the environmental protection and resource recovery options such as reuse, refurbish, recycle, remanufacturing and proper disposal can be executed to deal and manage with the e-waste. The goal of this research work is to identifies, evaluate and analyze the factors for successful implementation of RL practices. Fifteen critical RL factors are recognized from pertinent literature and endorsed by industry professionals. This paper utilized Grey based Decision Making Trial and Evaluation Laboratory (DEMATEL) approach to sort the identified factors into cause and effect clusters. Grey DEMATEL resolves the problem of data uncertainty and impreciseness involves in decision making in analyzing the factors. The results of the study found that 11 RL factors came into causal cluster as vital factors and 4 RL factors into the effect cluster as fundamental problems factors. Among causal cluster, the highest ranked four influential factors are Top management commitment (RLF1) with weightage value 0.7604, RLF2 i.e. enforced government regulations with weightage value 0.6549, RLF6 i.e. environmental/green concerns factor with weightage value 0.5678 and RLF8 i.e. Waste minimization (especially e-waste) factor with weightage value 0.5113 are respectively. Similarly, among effect cluster, the most easily influenced two factors are “Market and competition factors” (RLF15) with weightage value (− 1.1207) and “Increased e-commerce” (RLF13) with weightage value (− 1.2855) respectively. A case example of an Indian electronics firm is taken to showcase the application of the proposed model. This paper can help supply chain managers and analysts in superior understanding of critical factors and increase the chances of practicing more effective and successful RL implementation in electronics industry. At the end, few key country and industry-specific recommendations are offered to support major decision for management and policy makers to embrace and successfully accomplish the reverse supply chain practices in India.

Evaluation of the Impacting Factors on Sustainable Mining Development, Using the Grey-Decision Making Trial and Evaluation Laboratory Approach

Due to great effect of mining operation on environment and dependent sides, paying attention to the aspects of sustainable development (SD) is important. A conjugation of Grey theory and Decision-Making Trial and Evaluation Laboratory (DEMATEL) is able to find out cause and effect relations among the triple mining SD components and their effective factors. Grey–DEMATEL approach has been used in order to effectively quantify indicators of sustainable development of a copper mine located in south east Iran. This systematic approach transformed the quantitative and qualitative information into a analogous scale and measured the interrelationships among the SD components and their factors. Hierarchical Grey-based DEMATEL compensated the incomplete and uncertain environmental and socio-economic information. The obtained results indicated that social component with an R value of 10 is relatively strong direct influencer on the other components and the economic component is the least direct influencer with R= 8.49. Among the social impacting factors, employment of local work forces is the most important factor that needs to be consider with sustainable development objectives.

An Integrated Multi-Criteria Decision Making Approach to Location Planning of Electric Vehicle Charging Stations

Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle, which, however, is a complicated multiple criteria decision making (MCDM) problem involving many conflicting criteria. Therefore, this work aims to propose a novel integrated MCDM approach by a grey decision making trial and evaluation laboratory (DEMATEL) and uncertain linguistic multi-objective optimization by ratio analysis plus full multiplicative form (UL-MULTIMOORA) for determining the most suitable EVCS site in terms of multiple interrelated criteria. Specifically, the grey DEMATEL method is used to determine criteria weights and the UL-MULTIMOORA model is employed to evaluate and select the optimal site. Finally, an empirical example in Shanghai, China, is presented to demonstrate the applicability and effectiveness of the proposed approach. The results show that the proposed approach is a useful, practical, and effective way to find the optimal location of EVCSs.

Critical Success Factors for Humanitarian Supply Chain Management: A Grey DEMATEL Approach

Abstract Humanitarian Supply Chain Management (HSCM) is an emerging field and has gained prominence in recent past. The increasing demand for proper planning has made disaster relief operations (DRO) a complex phenomenon. Moreover, the success of humanitarian supply chain is dependent on various factors which hold different degrees of importance for every DRO. This study considers the case study of floods in India and explores the critical success factors (CSF) for implementation of effective HSCM. The study also models the factors and classifies them into cause and effect using grey decisionmaking trial and evaluation laboratory (DEMATEL) method. The study then adopts a sensitivity analysis by considering four scenarios and awarding different weights to the experts to validate the robustness of the results. The results are further validated with a set of experts. The study explored 10 causal enablers and 8 effect-based enablers. Both causal and effect enablers are further clustered using principal component analysis which extracts three factors each. The study proposes a conceptual model which could further be tested using empirical data.