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Previous studies on hospital supply chain performance have attempted to measure the performance of the hospital supply chain either by the measurement of performance indicators or the performance of specific activities. This paper attempts to measure the internal hospital supply chain's performance indicators to find their interdependencies to understand the relationship among them and identify the key performance indicators for each of those aspects of the logistics process toward improvement.

In this research, a systematic assessment and analysis method under vagueness is proposed to assess, analyze and measure the internal health care performance aspects (HCPA). The proposed method combines the group Decision-Making and Trial Evaluation Laboratory (DEMATEL) method and rough set theory.

The study results indicate that the most critical aspects of hospital supply chain performance are completeness of treatment, clinical care process time and no delay in treatment.

The causal relationship from rough-DEMATEL can advise management officials that to improve the completeness of treatment toward patient safety, clinical care process time should be addressed initially and with it, patient safety aspects such as free from error, clinical care productivity, etc. should be improved as well. Improvement of these aspects will improve the other aspects they are related to.

The purpose of this paper is to identify, analyze and model Internet of Things (IoT) enablers essential for the success of Industry 4.0.

IoT enablers for Industry 4.0 are identified from literature and inferable discussions with industry experts. Three different techniques namely, principal component analysis (PCA), interpretive structural modeling (ISM) and decision making trial and evaluation laboratory (DEMATEL) are applied to model IoT enablers. In addition to this, DEMATEL is also applied under two different situations representing the behavioral characteristic of experts involved. These are termed as optimistic (maximum) and pessimistic (minimum).

The integrated approach of PCA-ISM-DEMATEL shows that IoT ecosystem and IoT Big Data are the most influential or driving IoT enablers. These two enablers have been identified as the pillars for Industry 4.0. On the other side, IoT interchangeability, consumer IoT, IoT robustness and IoT interface and network capability have also been identified as the most dependent enablers for Industry 4.0.

The findings enable the industry practitioners to select the most appropriate driving enablers for an effective implementation of Industry 4.0.

The integrated approach-based hierarchical model and cause-effect relationship among IoT enablers are proposed which is a novel initiative for Industry 4.0. Moreover, two different variants of DEMATEL namely, pessimistic and optimistic are applied first time.

Risk factors related delay hinder the schedule performance of most construction projects in the world. It is a critical challenge to realize the advantages of prefabricated construction projects (PCPs) under the negative effect of schedule delay. This paper aims to propose an exhaustive list of risk factors impeding the progress of PCPs and evaluate the collected risk factors based on the cause–effect relations. The ultimate goal is to improve the understanding of the complex relations among various risk factors related delay in PCPs, and also offer managers a reference on aspect of schedule risk management.

This paper proposes a hybrid method of GT–DEMATEL–ISM, that is combing grounded theory, DEMATEL (decision-making trial and evaluation laboratory) and ISM (Interpretative Structural Modeling), to collect, evaluate and structure risk factors related delay for PCPs. The research procedure of this methodology is divided into three stages systematically involving qualitative and quantitative analysis. In the first stage, GT is utilized to implement qualitative analysis to collect the risk factors leading to schedule delay in PCPs. While, the quantitative analysis is to analyze and evaluate the collected risk factors based on the cause–effect relations in the next two stages evaluation by the DEMATEL focuses on quantifying the priority and intensity of the relations between factors. Additionally, ISM is employed to construct the hierarchical structure and graphically represent the pairwise relations between factors.

The outcome of qualitative investigation by grounded theory proposes a theoretical framework of risk factors related delay for PCPs. The framework contains three levels of category, namely, core category, main category and initial category and provides a list of risk factors related delay. Following this finding, evaluation results by the DEMATEL classify factors into cause and effect groups and determine 11 critical delay risk factors. Meanwhile, the findings show that risks referring to organizational management issue foremost impact the progress of PCPs. Furthermore, a systemic multilevel hierarchical structure model is visually constructed by ISM to present the pairwise linkages of critical factors. The model provides the risk transmission chains to map the spread path of delay impact in the system.

The contribution of the study involves twofold issues. Methodologically, this research proposes a hybrid method GT–DEMATEL–ISM used to identify and analyze factors for a complex system. It is also applicable to other fields facing similar problems that require collecting, evaluating and structuring certain elements as a whole in a comprehensive perspective. The theoretical contribution is to fill the relevant research gap of the existing body of knowledge. To the best knowledge of the authors, this paper is the first attempt to integrate qualitative and quantitative research for risk analysis related delay and take the insight into the whole process of PCPs covering off-site manufacture and on-site construction. Furthermore, the analysis of findings provided both a micro view focusing on individual risk factor and a managerial view from a systematic level. The findings also contribute the effective information to improve the risk management related schedule delay in PCPs.

The Healthcare sector is one of the important sectors of the Service Industry. It is believed that in this sector, the customer server relationship is very critical, and even the slightest gap in the people quality may have a huge impact on the delivered service quality. Some of these enablers are doctors, nursing staff and support staff. Furthermore, the nonpeople quality enablers such as diagnostic services, facilities, hygiene levels and so on are also likely to impact the delivered service quality. It was also felt that the degree of impact each enabler has on the service quality could vary. Therefore there is a need for structured and deep analysis. The paper attempts to identify, analyze and prioritize the enablers that impact the delivered service quality.

The enablers have been identified through literature review and inputs from experts in the healthcare fraternity. The authors have explored different decision-making tools such as analytic hierarchy process (AHP), analytic network process (ANP), stepwise weight assessment ratio analysis, Hybrid Model and DEMATEL (Decision-Making Trial and Evaluation Laboratory) for the analysis of data in this paper. Based on the strengths of the approach and careful considerations by focus group discussions, DEMATEL was chosen as the best option. It is simple, unique, sparingly used in the healthcare sector, effective in prioritizing and gives meaningful insights on importance, cause and effect factors. DEMATEL approach converts the complex problem with interrelated factors into a clear structure that makes simple interrelationships among factors in the form of cause and effects digraph, and hence, the authors chose to use it. A case study in one of the hospitals has also been conducted to demonstrate the applicability of the developed index. The case study very strongly validates the developed index.

This research paper has found that there are people quality enablers such as the doctor, nursing staff, support staff and nonpeople quality enablers such as facilities, diagnostic services and hygiene levels maintenance, which impact the delivered service quality. It also concludes that the delivered service quality depends not only on the quality but also on the availability of these enablers. The inputs received from the experts have been run through the DEMATEL methodology and importance computed for each. The top five priority enablers are Quality of Doctor, Availability of Doctor, Quality of Support Staff, Quality of Nursing Staff and Availability of Support Staff.

The weights of the enablers have been obtained using the DEMATEL tool. These weights have been calculated using the inputs from 22 experts, which meets the statistical requirement (Skulmoski, 2007). However, a larger group of experts can be reached, and based on the inputs received from them, the tool can be revalidated for repeatability and reproducibility. Using Fuzzy DEMATEL can also be explored for further analysis.

The proposed framework to assess the service quality level of a healthcare organization is based on a sound approach of DEMATEL. The service index arrived, thereafter, can be used to rate the delivered service quality by any healthcare organization. It can be used to compare the similar type of healthcare organizations across locations. This Index can facilitate improvements in the healthcare organization through internal and external benchmarking. It also helps the organization to know the gaps, understand the root cause, improve upon them and become the best in class. This Index uses the inputs from the end customers to calculate the rating, which makes it more reliable and accurate. The overall scores obtained from the Index can provide the ranking to the healthcare providing organizations and options to customers to choose from best. The service quality index can be used by an organization to continuously monitor their delivered service quality scores and improve them to become the best in class. The research paper highlights the significant role played by the people quality and its strong impact/contribution on the delivered service quality. Hence, it is believed that it will encourage the healthcare organizations to prioritize the improvement and upgrade of the people quality over the nonpeople quality aspect.

Putting people and nonpeople quality enablers in one single model and assigning weights to them using the DEMATEL approach is a new application in healthcare. Developing an Index to measure the delivered service quality in the healthcare sector is also different and new.

To develop a fuzzy causal model of enterprise flexibility dimensions in a case study of Indian pharmaceutical industry.

The eight dimensions of enterprise flexibility were identified based on literature review. Fermatean fuzzy decision-making trail and evaluation laboratory (FF-DEMATEL) technique is applied to develop the cause-and-effect interrelationship model among various enterprise flexibility dimensions.

The information technology flexibility, supply chain flexibility, technical flexibility and marketing flexibility are found to be causing/influencing other flexibilities and contributing to overall enterprise flexibilities. Therefore, more attention needs to be paid to develop and sustain them for competitive advantage.

Fermatean fuzzy sets offer more flexibility and more accurate handling complex uncertain group decision making. FF-DEMATEL is a more accurate method to develop inter-dependencies and causal model than ISM, TISM. Ratings from the limited number of decision experts (DEs) from few pharmaceutical firms were done. Future study should take bigger sample of firms and more number of DEs to generalize the findings.

The model will help managers in pharmaceutical industry to prioritize the dimensions of enterprise flexibility to achieve agility, responsiveness, resilience and competitive advantage.

To the best knowledge of the authors, causal modeling enterprise flexibility dimensions using FF-DEMATEL has been studied for the first time in a developing economy context.

Subway systems are highly susceptible to external disturbances from emergencies, triggering a series of consequences such as the paralysis of the internal network transportation functions, causing significant economic and safety losses to cities. Therefore, it is necessary to analyze the factors affecting the resilience of the subway system to reduce the impact of disaster incidents.

Using the interval type-2 fuzzy linguistic term set and the K-medoids clustering algorithm, this paper improves the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to construct a subway resilience factor analysis model for emergencies. Through comparative analysis, this study confirms the superior performance of the proposed approach in enhancing the precision of the DEMATEL method.

The results indicate that the operation and management level of emergency command organizations is the key resilience factors of subway operations in China. Furthermore, based on real case analyses, the corresponding suggestions and measures are put forward to improve the overall operation resilience level of the subway.

This paper identifies four emergency scenarios and 15 resilience factors affecting subway operations through literature review and expert consultation. The improved fuzzy DEMATEL method is applied to explore the levels of influence and causal mechanisms among the resilience factors of the subway system under the four emergency scenarios.

Green Lean concepts offer methods for managing manufacturing organizations with the goal of improving organizational performance. Green Lean practices are good options to increase the environmental and operational performance of manufacturing industries. However, there are some barriers to implement Green Lean in manufacturing industries. This paper aims to identify these barriers by reviewing the literature and analyze inter-relationships amongst selected barriers.

This paper deals with the identification of barriers to the adoption of Green Lean practices in manufacturing industries. Using the DEMATEL approach and using the insights of experts, a cause and effect relationship diagram was generated through which the effect of barriers was analyzed.

Twelve barriers were categorized in terms of cause and effect, and the interrelationships of barriers were also analyzed. Threshold value is calculated as 0.134 and the values lower than a were eliminated to obtain the digraph. “Resistance to change,” “lack of top management commitment” and “lack of training to employees” are the most prominent barriers on the basis of their prominent score.

Analysis in the research is highly dependent on expert judgments and opinions may be biased. However, the initial matrix obtained from the experts is hindered by the ambiguity about some relationships. But this can be improved by using fuzzy and grey set theories. The barriers used for the analysis are not from a specific type of manufacturing industry.

The findings will help the manufacturing organizations to simplify the most important barriers, the least significant barriers and the relationships between these barriers. This Berlin knowledge will enable administrators to increase awareness of the barriers in Green Lean implementation. “The top management commitment” and “government support” are most important for the removal of barriers to Green Lean strategies.

Very few scholars have used the DEMATEL approach to examine the sequence of the barriers to Green Lean implementation. The present study attempts to incorporate the DEMATEL model to assess the sequence of barriers to the implementation of Green Lean. This study investigates the degree of influence of barriers on each other and categorizes the barriers into cause and effect groups. This study is also intended to pave the way for future research in the path of the elimination of barriers to Green Lean strategies.

The risk of adverse events in a hospital evaluation is an important process in healthcare management. It involves several technical, social, and economical aspects. The purpose of this paper is to propose an integrated approach to evaluate the risk of adverse events in the hospital sector.

This paper aims to provide a decision-making framework to evaluate hospital service. Three well-known methods are applied. More specifically are proposed the following methods: analytic hierarchy process (AHP), a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology developed by Thomas L. Saaty in the 1970s; decision-making trial and evaluation laboratory (DEMATEL) to construct interrelations between criteria/factors and VIKOR method, a commonly used multiple-criteria decision analysis technique for determining a compromise solution and improving the quality of decision making.

The example provided has demonstrated that the proposed approach is an effective and useful tool to assess the risk of adverse events in the hospital sector. The results could help the hospital identify its high performance level and take appropriate measures in advance to prevent adverse events. The authors can conclude that the promising results obtained in applying the AHP–DEMATEL–VIKOR method suggest that the hybrid method can be used to create decision aids that it simplifies the shared decision-making process.

This paper presents a novel approach based on the integration of AHP, DEMATEL and VIKOR methods. The final aim is to propose a robust methodology to overcome disadvantages associated with each method.

The purpose of this article is to identify the critical success factors (CSFs) of knowledge management (KM) adoption in the supply chain (SC) using the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method through an empirical case study.

The paper examines the influencing factors of KM adoption in SC which have been identified through the literature survey and expert opinion. The fuzzy DEMATEL method has been used to evaluate identified influencing factors. Considering the interdependence among factors, the fuzzy DEMATEL method forms a structural model and then visualizes the causal relationships among factors through a cause–effect relationship diagram. On the basis of the cause–effect relationship diagram, CSFs that are extraordinarily essential for KM adoption in SC are identified. Empirical case study of an Indian automobile organization presented to illustrate the fuzzy DEMATEL method and demonstrates its usefulness.

The results gathered from the implementation of the fuzzy DEMATEL method to identify CSFs of KM adoption in SC to the chosen case illustrate that factors such as top management support, employee training and education, integration of knowledge and information flow, communication among the SC members and trustworthy teamwork to exchange knowledge within SC need to be highlighted as critical factors for successful adoption of KM in SC.

The finding not only offers a meaningful base to deepen the understanding with regard to KM adoption in SC, but also provides a clue to develop an effective adoption of KM in SC in a stepwise manner.

The empirical case study contributes to the literature on KM adoption in SC, suggesting how an organization can identify CSFs of KM adoption in SC and implement them progressively to greatly improve the efficiency of the whole SC performance.

Increasing environmental pollution and destruction have damaged sustainability in polluting societies and organizations. For this reason, various environmental management programs have recently been developed by governments and the environmental protection agencies (EPAs) to control and reduce environmental pollution. One of these programs is environmental audit (EA), which has not been fully implemented yet in developing countries and it has many disadvantages. It seems that one of the reasons for the lack of perfect implementation of EA in these countries is the lack of adequate review of the factors affecting its implementation. The purpose of this paper is to identify the factors affecting EA implementation and then analysis of causal relationships between them.

Decision-making trial and evaluation laboratory (DEMATEL) technique was used to identify causal relationships of factors affecting EA implementation. Based on the literature review and interviewing nine experts in EA, 17 factors were identified to influence EA implementation. Six experts were selected for the evaluation using snowball sampling method. Using the DEMATEL approach, a cause and effect relationship diagram was generated through which the effect of factors was analyzed.

Seventeen factors were categorized in terms of cause and effect, and the interrelationships of factors were also analyzed. “Reducing environmental impacts and improving environmental performance,” “obtaining environmental management system certificates” and “contributing to the environmental goals of investment projects” are the most prominent factors on the basis of their prominent score.

Analysis in the research is highly dependent on expert judgments and opinions may be biased. However, the initial matrix obtained from the experts is hindered by the ambiguity about some relationships. But this can be improved by using fuzzy and gray set theories. The factors used for the analysis may not be comprehensive and other researchers may find other factors.

Identifying the factors affecting EA implementation and analyzing causal relationships between them can be a guide and help governments to improve the implementation of EA or even develop this policy by being aware of the effect of the factors analyzed.

To the best of the authors’ knowledge, no comprehensive study of factors affecting EA implementation has been undertaken; this study is the first to identify these factors and analyze them using DEMATEL. Therefore, it is suggested that governments and EPAs in the policies focus on the significant factors.