Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause-effect chain components of a complex system. It deals with evaluating interdependent relationships among factors and finding the critical ones through a visual structural model. Over the recent decade, a large number of studies have been done on the application of DEMATEL and many different variants have been put forward in the literature. The objective of this study is to review systematically the methodologies and applications of the DEMATEL technique. We reviewed a total of 346 papers published from 2006 to 2016 in the international journals. According to the approaches used, these publications are grouped into five categories: classical DEMATEL, fuzzy DEMATEL, grey DEMATEL, analytical network process- (ANP-) DEMATEL, and other DEMATEL. All papers with respect to each category are summarized and analyzed, pointing out their implementing procedures, real applications, and crucial findings. This systematic and comprehensive review holds valuable insights for researchers and practitioners into using the DEMATEL in terms of indicating current research trends and potential directions for further research.
Based on the DEMATEL methods adopted, the selected publications are roughly grouped into five categories: the ones using classical DEMATEL (105 articles), the ones using fuzzy DEMATEL (63 articles), the ones using grey DEMATEL (12 articles), the ones combining analytical network process (ANP) and DEMATEL (154 articles), and the ones based on other DEMATEL methods (12 articles). The classification scheme of the DEMATEL articles is shown in Figure 1. Most of the papers on ANP and DEMATEL hybridization are included in a review paper of DEMATEL approaches for criteria interaction handling with ANP by Gölcük and Baykasoğlu [7]. Therefore, in the following sections, we will not discuss the studies which apply the DEMATEL in conjunction with ANP to deal with interactions among criteria.
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Table 1 summarizes all the classical DEMATEL studies based on the particular purpose of using DEMATEL, the topic of decision making, and other methods combined. According to the distinct usage of the DEMATEL method, the current classical DEMATEL researches can be classified into three types: the first type is merely clarifying the interrelationships between factors or criteria; the second type is identifying key factors based on the causal relationships and the degrees of interrelationship between them; the third type is determining criteria weights by analyzing the interrelationships and impact levels of criteria.
In Table 1, we have provided an overview on the existing applications of the classical DEMATEL for solving complicated and intertwined problems in many fields, based on which we now point out some critical steps added to the original approach.
Step 6 (calculate the importance weights for criteria). In some studies, the classical DEMATEL technique was used to compute the weights of criteria. Normally, the criteria weights are determined based on the prominence () through a normalization procedure as follows [27, 28]:
Analyzing the data contained in Table 1, we can observe that the crisp DEMATEL has been combined with a variety of other methods or tools to solve the management decision problems effectively, and the methods most frequently integrated with the DEMATEL include AHP, balanced scorecard (BSC), TOPSIS, and quality function deployment (QFD). Generally, the classical DEMATEL are applied to the following circumstances in combination with other methods. First, it can be used to identify the interdependency among dimensions or perspectives. For example, the DEMATEL was applied to determine the interrelationships between four BSC perspectives [16] and to unveil the implicit interrelationships of customer requirements [210]. Second, it can be used to calculate the weights of evaluation criteria. For instance, the DEMATEL was employed to resolve criteria interdependency relationship weights and then the TOPSIS is utilized to evaluate the service quality of hot spring hotels [122]. Third, it can be used to determine critical factors or criteria via analyzing their dependent relations. For example, the DEMATEL method was applied first to select the most important sustainable criteria, and fuzzy AHP is constructed next to rank end-of-life vehicle management alternatives [108].
Step 5. Produce the IRM.Once the total-influence fuzzy matrix is obtained, then and can be calculated easily in which and are the sum of rows and the sum of columns within the matrix , respectively. Next, the fuzzy numbers of and are converted into crisp numbers by using a defuzzification method. A causal diagram can be drawn like the classical DEMATEL by mapping the ordered pairs of and .
(2) Weighting Methods. As shown in Table 2, many studies have applied the fuzzy DEMETAL to determine the weights of criteria considering their hierarchies, and a variety of weighting methods have been suggested. In addition to those methods already mentioned in the classical DEMETAL studies, that is, those based and dependency weights, some new weighting methods have been developed.
Similar to the fuzzy DEMATEL, there are mainly two types of grey DEMATEL methods, that is, the grey theory and DEMATEL and the grey-based DEMATEL. Fu et al. [187] first introduced the grey theory and DEMATEL methodology to investigate the importance of green supplier development programs at a telecommunications systems provider. The proposed method involves assessing interdependency relationships among factors by a grey linguistics scale, transforming grey numbers into single real numbers using a modified CFCS process, and eventually executing the classical DEMATEL steps to obtain an IRM with associated analysis. Later, the grey theory and DEMATEL method was applied by Dou and Sarkis [188] to evaluate the barriers of implementing China RoHS (the restriction of the use of hazardous substances in electrical and electronic equipment) regulations from a multiple stakeholder perspective, by Zhu et al. [189] to identify the supply chain-based barriers for truck-engine remanufacturing in China, by Rajesh and Ravi [190] to ascertain the major enablers of supply chain risk mitigation in electronic supply chains, by Shao et al. [191] to analyze the barriers between environmentally friendly products and consumers on the European automobile industry, by Govindan et al. [192] to develop important criteria for third-party logistics provider selection and evaluation, and by Xia et al. [193] to analyze the internal barriers for remanufacturers in the Chinese automotive sector.
Based on the collected papers on the DEMATEL, a bibliometric analysis is conducted in this section regarding quantity of articles published per year, application areas of DEMATEL, and the highly cited papers. The intention of this bibliometric analysis is to find out current research trends, distribution of the articles in different categories, and interactions with other fields, which provide valuable insights for researchers and practitioners working in this field. First, from Figure 4, one can observe that the number of publications on DEMATEL has increased considerably, especially after the year 2009. It can be expected that the studies of utilizing the DEMATEL and its variants will continue to grow at an increased pace in the coming decade. Figure 4 also shows the trend in the number of publications in each category. It can be found that the classical and the fuzzy DEMATEL methods are mostly used for decision making in the earlier literature. It was only after the year 2010 when the focus shifted to employing the combination of ANP and DEMATEL. However, the usage of the classical and the fuzzy DEMATEL methods has continued to grow until more recently when some papers began to deal with the grey and other DEMATEL applications. Normally, if the relationships of systems are given by crisp values in establishing a structural model, the classical DEMATEL can be used for evaluating problems and decision making [217]. For the cases that the human judgments about preferences are unclear and hard to estimate by exact numerical values, the fuzzy DEMATEL is necessary for making better decisions in fuzzy environments. The grey DEMATEL can be applied to the systems with limited data and incomplete information, which may exhibit random uncertainty.
Cussac et al. (2008) reported differential agonist action for a series of serotonergic ligands, including LSD and DOI, and using CHO cells stably expressing the human 5-HT2A receptor. [They also used cells transfected with the human 5-HT2B and 5-HT2C (VSV isoform) receptors, obtaining generally similar results, but the discussion here will focus on their work with the 5-HT2A receptor.] They measured specific activation of Gq/11 proteins using a scintillation proximity assay and used a fluorescent imaging plate reader assay to measure intracellular Ca2+ responses. Serotonin and 5-carboxytryptamine gave a 20- to 50-fold greater potency for Ca2+ release than measured for Gq/11 activation, whereas DOI showed only a modest 2-to 3-fold preference for Ca2+ release. As anticipated, M100907 potently blocked serotonin-stimulated Gq/11 proteins. LSD showed a 20-fold higher potency to stimulate Gq/11 than to induce Ca2+ release. The most striking separation between activities was for the nonhallucinogenic 5-HT2A agonist lisuride, which was as potent as DOI in stimulating Gq/11, more than 1000-fold more potent than at Ca2+ release, and was a partial agonist for the two pathways. Interestingly, Ca2+ mobilization is classically considered to be a downstream consequence of Gq/11 activation and subsequent PLC stimulation. Yet the results presented here suggest that Gq/11 signaling may not be the only determinant of Ca2+ signaling. The main result of this study, however, was the ability of different agonists to differentially activate two signaling pathways in the same cell type. 2ff7e9595c
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