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Based on generic reviews of research on school leadership, this study aims to conceptualize an emerging leadership competence model for further prioritizing school leadership training needs by decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP). Targeting at a specific group of junior high school principals in Taiwan, the synthesized prioritization of core competences and competence indicators computed by DEMATEL-based ANP can be used as a blueprint for systematically developing school principal preparation programs elsewhere based on contextually specific needs and concerns.

For the purpose of detecting the priority of competences extracted from a plethora of literature in relation to school leaders’ skills, abilities and knowledge, a hybrid MCDM model, known as DEMATEL-based ANP, is used to snapshot critical leadership competences for tailoring the intended junior high school principal preparation program.

Results of global weight computations by DEMATEL-based ANP show that the overall prioritization of the five dimensions in ranking order are “Redesigning the organization,” “Related leadership practices,” “Setting Directions,” “Personal Characteristics” and “Developing People.” Factor-level analysis indicated that “Legality,” “Consensus Building,” “Shared Vision,” “Strategic Management,” “Authoritarianism,” “Modeling Behavior” and “High Performance Emphasis” were prioritized factors to be included in developing the intended school principal preparation program.

Contextually based findings yielded from DEMATEL-based ANP would only be applicable to the target context under investigation. Generalizing the findings to junior high school principals elsewhere might not be appropriate. Methods introduced in this study are extensible to further studies aiming at shaping leadership trainings in other school settings to achieve maximum impact based on contextually specific needs. Limitations associated with sophisticated mathematical computations involved in performing high-leverage MCDM models would shed light on the importance of interdisciplinary collaborations between scholars, practitioners and methodologists.

To efficiently deliver training for junior high school principals, the prioritization of core competences and competence indicators solicited by DEMATEL-based ANP can be used as a scenario-based reference for planning the intended school principal preparation program planning, as well as a mechanism for selecting and evaluating potential and incumbent school principals with desired leadership competences.

This study has used DELATEL-based ANP as a decision-making tool to disclose a plethora of competences extracted from different threads in the literature into a prioritized competence framework that differs from past one-size-fit-all approach to design and plan school principal preparation programs.

Carbon reduction in the construction supply chain can critically affect the construction industry’s transition to an environmentally sustainable one. However, implementing carbon reduction in all parties is restricted because of the poor understanding of the drivers influencing the low-carbon construction supply chain (LCCSC). The purpose of this paper is to systematically identify the drivers of LCCSC, analyze their causality, and prioritize the importance of their management.

A decision-making analysis process was developed using an integrated decision-making trial and evaluation laboratory (DEMATEL)–analytical network process (ANP). First, the hierarchical drivers of the LCCSC were identified through a literature review. The DEMATEL method was subsequently applied to analyze the interactions between the drivers, including the direction and strength of impact. Finally, the ANP analysis was used to obtain the drivers’ weights; consequently, their priorities were established.

Various factors with complex interactions drive LCCSC. With respect to their influence relationships, incentive policy, regulatory policy, consumers’ low-carbon preference, market competition, supply chain performance, and managers’ low-carbon awareness have more significant center degrees and are cause drivers. Their strong correlations and influence on other drivers should be noticed. In terms of weights in the driver system, regulatory policy, consumers’ low-carbon preference, supply chain performance, and incentive policy are the key drivers of LCCSC and require primary attention. Other drivers, such as supply chain collaboration, employee motivation, and public participation, play a minor driving role with less management priority.

Despite some contributing studies with localized perspectives, the systematic analysis of LCCSC drivers is limited, especially considering their intricate interactions. This paper establishes the LCCSC driver system, explores the influence relationships among the drivers, and determines the key drivers. Hence, it contributes to the sustainable construction supply chain domain by enabling decision-makers and practitioners to systematically understand the drivers of LCCSC and gain management implications on priority issues with limited resources.

The purpose of this paper is to apply a multi-criteria decision-making (MCDM) framework to evaluate distribution strategies for an e-tailer. An application of MCDM method, the hybrid DANP–VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) model, is used for e-tailers’ distribution strategy evaluation. The choice of distribution strategies under various dimensions is evaluated.

The authors used a hybrid MCDM model to solve the decision-making framework, which combines Decision-Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based analytic network process and VIKOR method. Data were collected from the experts (e-tail manager, logistics manager, operations manager and distribution center (DC) manager) using two questionnaires, first for the influential relationship among the criteria and dimensions and second for a performance rating of each alternative (distribution strategies) against each criterion.

DANP with VIKOR method prioritizes the distribution strategies in the following order: DC shipment, drop shipment, click and collect, store shipment and click and reserve. Performance gap was calculated based on the VIKOR method to provide distribution strategies to an e-tailer under different situations. The authors infer that in developing country, product characteristics and transportation have a major influence on deciding the distribution strategy.

Decision-making framework will provide e-tail mangers a knowledge-based understanding to select the distribution strategy under the different situations related to the performance, product, e-tailer and external characteristics for smooth order fulfillment process. The insights developed by this research provide a framework for rational decision making in distribution strategy selection in e-business.

This is the first kind of a study which offers a decision framework for e-tail managers on how to choose distribution strategies under different situations which are related to the performance, product, e-tailer and external characteristics.

This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

The purpose of this paper is to select the optimal Lean Six Sigma (LSS) project using hybrid fuzzy-based Multi-Criteria Decision-Making (MCDM) approach for an automotive component manufacturing organization.

The LSS project selection has been formulated as the MCDM problem. Hybrid MCDM method based on Decision-Making Trial and Evaluation Laboratory Model (DEMATEL), Analytical Network Process (ANP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) has been used to select the optimal LSS project. The methodology enabled the practitioners to systematically prioritize LSS projects.

The finding of this study is that, out of five LSS projects, project P3 is the best LSS project. P3 is the optimal LSS project with reduced failure risk, and efforts are being taken to implement the selected project.

The problem formulation and methodology has been tested for a single study. In future, more number of studies could be conducted using the hybrid approach. This method is presently applied for an automotive component manufacturing organization; in future, the approach could be applied in different industrial sectors for improving its effectiveness.

The case study has been conducted in a real-time industrial problem. The practitioners expressed the usefulness of the methodology for prioritizing LSS projects Hence, the inferences derived are found to possess practical relevance.

The original contribution of the study is the selection of optimal LSS project using hybrid MCDM technique.

The concept of sustainable product design (SPD) is gaining significant attention in recent research. However, due to inherent uncertainties associated with new product development and incorporation of multiple qualitative and quantitative criteria; SPD is a complex and challenging task. The purpose of this paper is to introduce a novel approach by integrating quality function deployment (QFD), multi-criteria decision making (MCDM) technique and Six Sigma evaluation for facilitating SPD in the context of Industry 4.0.

The customer requirements are evaluated through the neutrosophic-decision-making trial and evaluation laboratory-analytic network process (DEMATEL-ANP)-based approach followed by utilizing QFD matrix to estimate the weights of the engineering characteristics (EC). The Six Sigma method is then employed to evaluate the alternatives’ design based on the ECs’ values.

The effectiveness of the suggested approach is illustrated through an example. The result indicates that utilization of the neutrosophic MCDM technique with integration of Six Sigma methodology provides a simple, effective and computationally inexpensive method for SPD.

The proposed approach is helpful in upstream evaluation of the product design with limited experimental/numerical data, maintaining a strong competitive position in the market and enhancing customer satisfaction.

This work provides a novel approach to objectively quantify performance of SPD under the paradigm of Industry 4.0 using the integration of QFD-based hybrid MCDM with Six Sigma method.

As wireless penetration continues to increase worldwide, competitors in the mobile telecommunication industry are changing their strategies from a growth model to a value‐added one. The companies that can attract and retain customers in this highly competitive and increasingly saturated market stand poised to make considerable gains, and thus customer retention is an important field of study in this maturing market. Using the Canadian mobile phone market as an example, this work aims to study the major motivators of customer retention and their interrelationships, and assess the value that customers perceive with regard to the related advertising.

Based on a literature review and expert validation, the motivators of customer retention are divided into three dimensions and eight criteria. A systematic hybrid multiple criteria decision‐making (MCDM) method that combines the decision making trial and evaluation laboratory (DEMATEL) technique and the analytic network process (ANP) is used to examine the customer retention framework and to evaluate the promotional strategies used by various market players.

The interdependence relation shows that phone service quality, customer service quality, and phone plan quality are three major motivators in terms of causality with regard to brand image, customer service quality, and complaint management, while phone service quality has become a hygiene factor with regard to customer satisfaction and retention. The findings from an assessment of the promotional strategies used by the major players in the Canadian mobile telecoms industry suggest that well‐financed foreign entrants pose a risk to the major domestic carriers, and that successful promotional strategies will require strong leverage of their existing price and quality advantages.

This work adopted a hybrid MCDM approach to examine a major strategic issue in mobile telecoms, – i.e. customer retention – and demonstrated the strengths of using this method to investigate rapidly changing markets. The relative importance of the motivators of satisfaction and retention is investigated, and a strategy for customer retention in the mobile telecoms industry is provided to managers.

The purpose of this study is to measure the R&D performance of 81 cities in Turkey by using a scientific approach.

A four-step solution approach is developed for this problem. In the first step, a hierarchical structure of 14 indicators (including number of patents, publications, R&D expense, etc.) in three dimensions is constructed. In the second step, explicitly and implicitly spatial indicators such as university location and R&D manpower are mapped by using geographic information system (GIS). In the third step, a hybrid multi-criteria decision making model, namely, DANP that combines decision-making trial and evaluation laboratory (DEMATEL) and analytic hierarchy process (ANP) techniques is applied to assign different level of importance to the indicators. In the last step, Višekriterijumska Optimizacijai kompromisno Rešenje (VIKOR) method is used to rank the performance of 81 cities. Obtained results are visualized using GIS to show the pros and cons of each city in terms of R&D performance.

Results of the paper show that Istanbul, Ankara and Konya are ordered as contenders of best R&D performances and on the contrary, Igdir, Sirnak and Tunceli are ordered as the worst R&D performances among 81 cities.

One limitation of the study can be the considered criteria. However, all the criteria are obtained from literature and experts; thus, the paper covers as much criteria as possible.

The proposed study may allow Ministry of Science, Industry and Technology of Turkey to formulate more effective strategies to improve cities’ R&D performance. In addition, any country can apply the same methodology for measuring the R&D performance of their cities by using their related data. As the worst R&D city performances belong to the eastern part of Turkey, it can be deducted that the socio-cultural structure of the eastern part of the country needs improvement.

To the best of the author’s knowledge, this is the first study which applies a GIS-based MCDM approach for R&D performance measurement. Thus, the value of this paper belongs to both literature and real life.

The aim of this paper was to investigate the criteria and sub-criteria with the most impact on determining a suitable location for refugee camps. This paper also analysed the relationships between the main criteria used in the selection process.

This study applied a combination of fuzzy methods and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) methods as tools for multiple-criteria decision analysis. A questionnaire was distributed to field workers in an international humanitarian organization team.

Five main criteria and twenty sub-criteria were defined. Between them, the highest ranked sub-criteria were long-term planning, optimal distribution and opportunity for growth. These findings were specific to the interviewed respondents of presented research at the time the data were collected and offer a potential research design for future research examining different organizations and teams.

The methods and evaluation were based on human opinions that were potentially biased.

The results of this study could be useful to government organizations, UN agencies, humanitarian organizations and other decision-making parties in selecting camp locations for refugees or internally displaced people according to how the importance of particular sub-criteria is understood.

New sub-criteria were included in this research. To date, the combination of fuzzy, DEMATEL and ANP methods has not been previously used in relation to these issues. Scientific knowledge concerning refugee camp siting problems is limited. This research extends this knowledge with the involvement of humanitarian workers as respondents. This paper also offers organizations a process for solving complex decision-making problems with long-term results or effect.

Many organizations failed to generate profits after investing considerable money and time in Enterprise Resource Planning (ERP) systems. This study, therefore, sought to identify the challenges encountered by pharmaceutical firms during the post-implementation of ERP systems.

A case-based study followed by general survey-based research was carried out in pharmaceutical firms to determine the critical post-implementation challenges of ERP systems. DANP (DEMATEL-based ANP) and Wilcoxon Signed Rank test were used to find the causal/critical challenges and rank them.

After analyzing a pharmaceutical case company and conducting a general survey among pharmaceutical companies, statistical analysis was performed to identify the most significant challenges, namely, “Inefficient troubleshooting mechanism”, “Lack of training during post-implementation stage” and “Difficulty in identifying invalid data when entered into the ERP system”. Furthermore, organization-wide challenges are considered to be the most important.

The paper identifies the challenges faced during the post-implementation phase of ERP systems. This work brings out the issues with ERP systems' performance after their implementation, which is related to the quality of the ERP systems. This work will support the risk identification and mitigation during ERP implementation to eradicate the problems after its implementation. This work may trigger the ERP system developers to improve its features and performance for better manufacturing and supply chain management system in pharmaceutical firms.

This study is uniquely conducted in pharmaceutical firms to study the benefits and challenges of adopted ERP systems. A pilot case study served as the foundation for the generalizability of other pharmaceutical firms' findings through a non-parametric test.