Decision Making Trial And Evaluation Laboratory Approach Research Articles

Application of the DEMATEL approach to analyse the root causes of building defects

AbstractBuilding defects are a common phenomenon in the construction industry. The negative consequences of building defects are not limited to waste generation or low resource efficiency. This challenge can have several direct and indirect implications such as cost overruns, unforeseen delays in project completion time, building occupants’ dissatisfaction and health and safety risks. Despite the increase in the number of studies investigating building defects in recent years, little is known about the prioritisation of their causes by considering the interaction among the causes of defects. Therefore, this study employed the decision-making trial and evaluation laboratory (DEMATEL) method to bridge this gap. Experts' opinion was sought using a questionnaire developed in the form of a matrix and semi-structured interview questions. Thereafter, the interactions among the causes of building defects were analysed and the most prominent causes are identified. The study showed that materials, workmanship and design are the major causes of building defects. Despite being specific context, the findings can be the basis for further research in this area with a focus on a range of different building typologies. Furthermore, the recommendations provided will act as a facilitator to minimise the occurrence of building defects. Lastly, the research findings can be considered in the planning stage of any construction project, to ensure the construction quality, reduce potential waste and enhance the circular economy and resource efficiency in the built environment sector.

A duo-theme cloud model DEMATEL approach for exploring the cause factors of green supply chain management.

Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods identify cause factors in green supply chain management (GSCM). This study argues that the target method treats affecting factors as unique themes; however, various factors may be mutually antagonistic (i.e., mutually positive or negative) or encompass other meaningful information (e.g., gain/risk, intensify/depress). The factor affecting GSCM implicitly encompasses the economy and ecology (greenness), which may conflict. This new approach can be integrated into the analysis, dividing affecting factors into "cause" and "effect" groups. The organization should focus on affecting factors in the cause group. The findings provide strategic guidance for organizations to practice GSCM. A duo-theme cloud model DEMATEL approach was proposed to divide these affecting factors of GSCM into "economy" and "greenness." The cloud model was applied to overcome the ambiguity and randomness in the concept of uncertainty and allow the integration of mutual qualitative and quantitative mapping. Six factors in the economic aspect and four in the greenness aspect should be classified as the cause group. Organizations should prioritize these ten factors in their GSCM practices. Doing so makes the GSCM problem relatively straightforward and allows for efficacious decision-making. This study proposes a duo-theme cloud model DEMATEL approach to identify cause factors in GSCM.

Analysis of the Barriers to Smart City Development Using DEMATEL

This study analyzes the barriers to developing smart cities (SCs) using the decision-making trial and evaluation laboratory (DEMATEL) approach. The primary objective is to identify, classify, and assess the main barriers hindering the progress of SCs. Through an extensive literature review, twelve main barriers were identified. The DEMATEL approach models and analyzes the relationships among these barriers based on expert input. The results reveal that technical problems, a lack of infrastructure, and high costs are classified as cause barriers. Security and privacy concerns and the absence of coordinated planning are classified as effect barriers. This study emphasizes the need for established criteria and iterative development requirements. Although the influence of knowledge and skills gaps and a lack of awareness is less significant, these aspects still require attention. The findings suggest that a comprehensive approach focusing on technical solutions, infrastructure development, strategic planning, and cybersecurity measures can effectively overcome barriers. Regular evaluation of barrier dynamics is crucial for implementing adaptive measures. The results provide decision-makers with a valuable model to address the challenges and foster the efforts of SC stakeholders.

A DEMATEL Analysis of The Complex Barriers Hindering Digitalization Technology Adoption In The Malaysia Agriculture Sector

This study investigates the challenges to the digitalization technology adoption in Malaysia agriculture sector by using the DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach, which will give a complete knowledge of the interdependencies among the barriers. The research objectives are to determine the cause and effect of digital agriculture using DEMATEL and to recommend the best way to overcome the obstacles in using digital technology. The findings from this study reveals the cause and effect from the barriers which is lack of skills, lack of technology, high cost, infrastructure and connectivity, and resistance to change are in the cause group while limited locality, data privacy and security concerns, low level of education, market access and regulatory and policy are in the effect group. The research findings are utilized to give policymakers and stakeholders with practical recommendations aimed at addressing the identified barriers and promoting the adoption of digital technologies in Malaysian agriculture. Thus, this study offers recommendations for the most important obstacles found, which are an improvement in infrastructure and the implementation of financial assistance mechanisms. All things considered, this research makes a significant contribution to the subject of agriculture and sheds light on the difficulties associated with implementing new technologies in Malaysia's agriculture industry.

An analysis of critical factors for adopting machine learning in manufacturing supply chains

This study identifies and examines the critical factors for adopting machine learning technologies in manufacturing supply chains. Initially, a thorough literature review was employed to identify 13 critical factors, and then the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology was used to analyse their cause–effect relationship. Next, a qualitative analysis concluded that ‘Technology Integration’ and ‘Forecasting’ are essential for adopting machine learning in manufacturing supply chains, ‘Risk Management’ is unaffected by causal factors, and ‘Manufacturing Processes’ is minor in adopting machine learning. The research findings aim to guide the practitioners in understanding the influence of one factor over the other and the ‘cause–effect’ relation among them. The strategies for the effective implementation of machine learning technologies may be deduced. It is a pioneering study in which novel and crucial determinants have been identified and examined in the multi-criteria environment using the DEMATEL approach.

An integrated method for complex heterogeneous multi-attribute group decision-making and application to photovoltaic power station site selection

This paper abstracts the complex heterogeneous multi-attribute group decision-making (CHMAGDM) characterized by two-layer decision-makers (DMs), individual attribute sets, complex relationships among attributes and heterogeneous evaluation information. DMs are composed by internal decision-makers (IDMs) and external decision-makers (EDMs). The evaluation information is represented by linguistic variables (LVs), intervals and real numbers. To handle such CHMAGDM, this paper puts forward an integrated method of prospect theory, DEMATEL (decision-making trial and evaluation laboratory) and QUALIFLEX (qualitative flexible). Firstly, a novel reference point determining approach is proposed based on three special indicators. A linguistic variable inverse prospect value function is designed and introduced to the transformation process from LVs to clouds to reduce the impacts of DMs’ psychological behaviors on decision-making. Secondly, a cloud-based DEMATEL approach is proposed to determine the attribute weights, where LVs are employed to judge the relationships among attributes. A new linguistic scale function is initiated and introduced to another transformation process from clouds to LVs. A representative indicator of cloud is designed for facilitating the normalization of direct relation matrix. Moreover, a linear programming model is built to calculate the attribute weights. Thirdly, an extended QUALIFLEX approach is developed to obtain the optimal ranking and EDM weights, where adoption coefficient is provided by IDMs. Another linear programming model is constructed to calculate the optimal collective concordance/discordance index of each permutation. The optimal ranking is generated by the maximum collective concordance/discordance index. Finally, a photovoltaic power station site selection example validates the proposed method. The advantages are demonstrated with sensitivity and comparison analyses.

Analyzing the relationship between digitalization and energy sustainability: A comprehensive ISM-MICMAC and DEMATEL approach

The objective of this study is to develop a comprehensive framework for evaluating the interconnectivity of digital measurements that significantly contribute to energy sustainability in the European energy domain. Our research aims to clarify the challenges presented by the digital era and its influence on sustainable energy solutions. To achieve this, we employ the DEMATEL (Decision Making Trial and Evaluation Laboratory) approach and the MICMAC (Matrice d'Impacts Croisés-Multiplication Appliquée, à un Classement) methodology through a survey-based taxonomy of digital measurements. The resulting hierarchy and contextual linkages among critical measurements in Europe's energy domain shed light on ten key dimensions of digitalization for energy sustainability, including the “decision-making process” the “sustainable value chain,” the “sustainable supply chain,” “sustainable product life cycle,” and “interconnection of diverse equipment”. However, the “transformation of the energy market and ”smart manufacturing technologies“ play a significant role in energy sustainability. By prioritizing these dimensions, we aim to enhance convenience and effectiveness and diminish preservation in energy products. The practical implications of our framework can support institutions, experts, and academics in forecasting essential energy dimensions and complement ongoing research on digitalization and sustainable energy. Our research contributes novel insights into the analysis of digitalization dimensions within the European energy industry, leveraging a cohesive ISM (Interpretive Structural Modeling), MICMAC, and DEMATEL framework.

Key factors influencing mass willingness to use CESPs under green concept: ECOCO smart recyclers as a case study

In promoting green life and environmental protection, encouraging mass participation in environmental protection activities and increasing mass willingness to use circular economy service platforms (CESPs) are of high importance. In light of this stance and other several dimensions, including green concept, hedonic value, and user benefits, the multiple attribute decision-making technique was used to develop an evaluation model that assesses the influential factor of one's willingness to use CESPs. By employing the decision-making trial and evaluation laboratory (DEMATEL) approach, the degree of mutual influence between different evaluation dimensions and criteria was first determined to generate an influential network relation map (INRM). Next, the weights of influence of varying evaluation dimensions and criteria were calculated by combining the DEMATEL approach with analytic network process. Finally, an empirical analysis of comprehensive performance of different evaluation dimensions and criteria was carried out based on the modified VIKOR technique. Referring to the INRM, green information emerged as the primary aspect that should be improved and adjusted, followed by green management, hedonic value, user benefits, green appeal, and green participation in order of priority. These outcomes may serve as reference regarding ways to enhance mass willingness to use the ECOCO CESPs and its smart recyclers.

Local Food Entrepreneurship in Rural India: Modelling the Challenges

Local food entrepreneurship plays a vital role in promoting and distributing regional foods. To link local food with the market, there is a need to develop local food systems that promote and support local food, its distribution and consumption. Local food entrepreneurs are constrained due to various factors prevailing in the entire rural ecosystem, which hinders their prospects of business expansion. This study focussed on identifying the commercially feasible local food products that can be produced and marketed by local entrepreneurs. Also, this study is an effort towards identifying and analysing the challenges perceived by local food entrepreneurs in rural India. The challenges were identified through a literature review and the personal interviews of the rural entrepreneurs and were then modelled through the DEMATEL (decision-making trial and evaluation laboratory) approach. The modelling of challenges helped in identifying the priority areas, based on which focused strategies were suggested for the promotion of local food entrepreneurs. From this study, it emerged that product quality issues, lack of buyers and inconsistent government policies are the most significant challenges perceived by entrepreneurs. This study also includes resource mapping for the local entrepreneurs to present a comprehensive scenario of the prevailing ecosystem.

Barriers to immigrant entrepreneurship: A causal relationship analysis of the Asian immigrant entrepreneurs in Germany employing the DEMATEL approach

Research background: Entrepreneurship and migration are top priorities on many national and international agendas. As a result, entrepreneurship is one of the most popular strategies immigrants use to avoid unemployment in a host country. However, studies lack to discuss causal relationships among key barriers to immigrant entrepreneurs. Purpose of the article: This study attempts to fill the knowledge gap and investigate the causal relationship between the primary obstacles faced by Asian immigrant entrepreneurs in Germany. Methods: A predesigned questionnaire was used in face-to-face interviews with Asian business owners in Germany for the study, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method of data analysis was used. Findings & value added: The findings reveal that lack of sufficient financial resources to establish a business, high market competition, and a lack of knowledge of the local language of the host country are the most significant barriers, among others, which may severely hamper Asian immigrant business performance and have a considerable impact on their entrepreneurial decision. At the same time, lack of professional knowledge & skills, problems with rules & regulations, and cultural differences are among the least essential obstacles for Asian immigrant entrepreneurs. The findings show that unfamiliarity with the local language, problems with rules and regulations, cultural differences, and lack of international business experience are associated with the causer category. However, lack of enough capital to establish a venture, lack of professional knowledge and skills, difficulty in access to financial resources, and high market competition relate to the receiver category. This research generates value for policymakers, particularly those participating in migration studies. One of the study's novelties is using the DEMATEL framework for decision-making on barriers to immigrant entrepreneurship in the European context.

Enhancing Sustainability in Belize’s Ecotourism Sector: A Fuzzy Delphi and Fuzzy DEMATEL Investigation of Key Indicators

Sustainable ecotourism has become a strategy to balance tourism growth with environmental and sociocultural considerations. This study aims to propose an integrated approach of the Delphi technique and the decision-making trial and evaluation laboratory (DEMATEL) based on fuzzy set theory to investigate sustainable ecotourism indicators in Belize. The study covers six dimensions: environmental, social, cultural, economic, political, and intrinsic. Firstly, the Fuzzy Delphi technique constructs a comprehensive set of indicators with expert consensus, resulting in 51 relevant and representative indicators out of the initial 63. Secondly, the Fuzzy DEMATEL approach is then applied to analyze the interdependencies among indicators and identify their causal relationships, providing insights into the complex dynamics of sustainable ecotourism in Belize. The results provide a structured decision-making framework to prioritize actions, allocate resources effectively, and promote sustainable practices in the ecotourism sector. Therefore, these findings enhance the understanding of indicator interconnections across dimensions, enabling informed decision making for policymakers, industry practitioners, and researchers. Policymakers can develop policies and regulations that foster sustainable practices, while industry practitioners can enhance visitor experiences, engage with local communities, and ensure the industry’s long-term viability. Researchers can further investigate specific dimensions and indicators to advance the knowledge and implementation of sustainable ecotourism. Finally, this investigation supports the goal of achieving a harmonious and sustainable balance between tourism development and environmental preservation in Belize. By safeguarding the natural and cultural heritage of the region, sustainable ecotourism can benefit present and future generations.

Causal Modelling of the Key Competitiveness Assessment Factors of Wellness Tourism Destinations: A DEMATEL Approach

Objectives: The objectives of this study are 1) to identify and prioritize the significant competitiveness factors that need to be considered in the context of wellness tourism destinations and 2) to identify the causal interrelationships between competitiveness factors that need to be considered in the context of wellness tourism destinations. Methods/Analysis: The theoretical framework of this research began with documentary research of secondary data, followed by semi-structured interviews and quantitative research using questionnaires to collect primary data from wellness tourism clusters and experts. Based on these responses, a multiple-criteria decision-making framework using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was implemented to prioritize wellness tourism destination competitiveness factors and their relationships. Findings: The destination strategy and roadmap for wellness tourism were the most important competitiveness factors for wellness tourism destinations, and the wellness service experience and activities factor was the most significant cause factor, with strategies to improve service and restoration being the most significant source of effect. Novelty/Improvement:This research sheds light on wellness tourism destinations' competitiveness assessment factors and indicators and how to improve them to attract wellness tourists seeking preventive health care or health promotion services. Doi: 10.28991/HEF-2023-04-02-01 Full Text: PDF

Proposing a strategy map based on sustainability balanced scorecard and DEMATEL for manufacturing companies

PurposeThe purpose of this study is to integrate the sustainability balanced scorecard (SBSC) framework with decision-making trial and evaluation laboratory (DEMATEL) for proposing a model and identifying the cause-and-effect relationships between the five perspectives of SBSC and then 23 performance indicators within the SBSC framework in a strategy map.Design/methodology/approachThe DEMATEL approach is used to obtain a matrix including direct and indirect influences between the five perspectives of SBSC and among 23 key performance indicators (KPIs). DEMATEL data are gathered from experts to propose a model and establish reliable relationships between performance metrics. Using DEMATEL and the SBSC framework, a strategy map for the SBSC dimensions and KPIs was built to illustrate strategic cause-and-effect relationships among the various dimensions and performance indicators.FindingsThe outcomes indicated that internal process and financial perspectives play essential outputs. Sustainability is the most critical predictor (causal) in the model, then customer and learning and growth dimensions, indicating that sustainability, learning and growth and customer dimensions all positively affect other dimensions. Additionally, sustainability has bi-directional in its link to the customer and internal processes and bi-directional in its relationship to finance, learning and growth. Numerous additional linkages are observed among the five SBSC perspectives and KPIs.Research limitations/implicationsThe data collected is based on an “average” company in manufacturing sector; thus, companies need to customize this model to ensure that their strategies are clearly translated into KPIs.Practical implicationsThe findings gave valuable information to management about manufacturing companies KPIs. They determined which KPIs are regarded as outcome (effect) variables and which KPIs are considered predictor (casual) variables. Additionally, the findings offer management with SBSC perspectives that should be traded as outcomes and those that should be traded as predictors. Additionally, the findings highlighted the critical KPIs and explained their interrelationships. This enables managers to focus on the significant financial besides non-financial indicators and comprehend the logical connection among them.Social implicationsThe results qualify executives and management to analyze and recognize a strategy map by understanding each objective's impacts, including direct and indirect, on all others. The typical analysis comprises determining the strategic objectives that are “cause” and the objectives considered as “effect”. As this study extends the BSC framework to have sustainability perspectives, the results of DEMATEL provide administrators with exceptional information to blend the conventional BSC perspectives with sustainability as added perspective.Originality/valueThe current study proposed an illustration model for strategy map development and also provide an interrelationship among SBSC perspectives.

Integrated multi-criteria group decision-making methods based on q-rung picture fuzzy sets for the identification of occupational hazards.

Practical group decision-making (DM) problems frequently involve challenging circumstances when attempting to assign appropriate values to the data because of the haziness and uncertainty of the surrounding circumstances. In order to address the ambiguity and imprecision that arise in DM issues, q-rung picture fuzzy sets (q-RPFSs) have a more broader structure. In this research, the criteria importance through intercriteria correlation (CRITIC) and the decision-making trial and evaluation laboratory (DEMATEL) techniques are separately integrated with the multi-attributive border approximation area comparison (MABAC) method. The MABAC method, which measures how far each alternative is from the border approximation area, is very stable and useful for resolving real-world problems. The CRITIC technique calculates the criteria weights by taking into account the relationships between attributes, and the DEMATEL methodology is recognized as the best method for determining how several criteria or factors interact with one another. As a result of these justifications, we made the decision to create the CRITIC-MABAC and DEMATEL-MABAC procedures for q-RPFSs. By using the suggested strategies, the primary goal of this article is to determine the occupational risk that has the greatest impact on the health of a hospital's medical staff. We begin by employing the CRITIC technique to determine the criteria weights. In addition, we calculate the weights of the criteria using the DEMATEL approach. The offered methodologies are investigated for their applicability to determine the most serious occupational hazard for hospital employees. We conducted a comparison with three earlier studies to verify the accuracy of the tactics that are offered.

Artificial Intelligence and Smart Cities: A DEMATEL Approach to Adaptation Challenges and Initiatives

This article focused on two main topics currently on among many agendas: smart cities and Artificial Intelligence (AI). The growing interest in the former is due to these cities’ multidimensionality and adaptability in terms of residents’ needs and the requirements of each municipality's reality. AI, in turn, currently plays a transformative, disruptive role in various areas by performing “smart” tasks, thereby facilitating the automation of processes and differentiation initiatives. Smart city strategic planning, especially in the long term, will most likely have to deal with adaptations to AI. Thus, research is needed that can contribute to a more holistic view of these topics and support decision-making processes in these areas. Based on the epistemological principles of the multiple-criteria decision analysis approach (MCDA), this article developed and tested a dynamic analysis system that allows smart city initiatives to address the challenges of adapting to AI. The proposed system highlights the cause-and-effect relationships in this context. The article included an application of the decision-making trial and evaluation laboratory (DEMATEL) technique. The procedural steps followed to implement this methodology were enhanced by close collaboration with an experienced decision maker, who has coordinated various projects in this research context. The proposed system's contributions and limitations were also analyzed in this article.

Developing A Sustainable Balanced Scorecard (SBSC) Model by Integrating EESG (Economic, Environmental, Social, and Governance) Performance Indicators for Private Hospitals in Egypt

This study constructs a model for Sustainable Balanced Scorecard (SBSC) by identifying the critical indicators from eight perspectives (Finance, Internal Business Process, Customer/Patient, Learning and Growth, Economic, Environmental, Social, and Governance). Moreover, in this study, a structural evaluation approach is presented to link the important SBSC indicators to a strategy map for private hospitals in Egypt. The most important metrics for measuring hospital performance are compiled from relevant literature and evaluated by a panel of experts in accordance with the eight SBSC perspectives. Then, using the DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach, a tool to analyze multiple criteria, the study ascertains the causal connections among the indicators, pinpoints the crucial core and deciding factors, and creates a visual strategy map with logical connections to boost hospital performance. To assess sustainable performance of private hospitals, 49 metrics were chosen based on the perspectives of the SBSC. Also, the study reveals that ‘‘Governance Control Activities’’, ‘‘Governance Financial Activities’’, ‘‘Non-compliance with laws and regulations’’, “Return on Investment”, “% of Revenue from repeat business “, “Net Promoter Score (NPS)”, and “Patient Complaints”, are the most essential evaluation indicators for private hospitals’ performance. The strategy map results demonstrate a clear road map to assist hospital leaders in ranking performance metrics and focusing on strategy-related actions for the essential indicators, where they could more effectively direct their limited resources toward areas that need the most improvement.

Key motivational factors behind Asian immigrant entrepreneurship: A causal relationship analysis employing the DEMATEL approach for Germany

Research background: Immigrant entrepreneurship remains a key issue for researchers, politicians, and policymakers. It has been widely discussed from different angles among various researchers in recent studies ? particularly in Europe. However, there is a lack of studies to present the motivation of the causal relationship between immigrant entrepreneurs. Purpose of the article: This study aims to fill the gap and analyze the causal relationship between the motivations of Asian immigrant entrepreneurs in Germany. Methods: The study was conducted through a face-to-face interview using a predesigned questionnaire from Asian business owners in Germany and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach was applied to analyze the data. Findings & value added: The results show that capital acquisition, employment, financial problems in the family, and existence opportunities in the market are the factors that have higher priority, and may highly impact the Asian immigrant entrepreneurial decision. On the other hand, relatives or social networks remain the lowest priority factor that encourages Asian immigrants towards self-employment. The study has also found that entrepreneurship in the family, the state support policy for immigrants, low level of education, unfamiliarity with the local language, and dissatisfaction with the previous job belong to the cause group. However, some of the motivating factors relate to the effect group, such as capital acquisition, opportunity in the market, immigrant community ties or social networks, unemployment, and financial problems in the family. The most affected factor among the effect group is unemployment, while immigrant community ties or social network is the least affected factor. This study includes a novel interpretation of the DEMATEL approach that researchers have not yet addressed; therefore, it is highly relevant for policymakers, especially those interested in migration studies. Finding out the main driving forces behind Asian immigrant entrepreneurs in a developed European nation like Germany and how these drivers affect cause-and-effect interactions between them are the contributions that add value to the field.

Application of fuzzy DEMATEL approach in maritime transportation: A risk analysis of anchor loss

Vessels are exposed to various operational risks throughout their service life. Anchor loss, which is one of the operational risks, may lead to grounding, collision and even total loss of vessel afterwards. Accidents due to loss of anchor may lead to serious consequences such as pollution, injury, loss of life and property. Therefore, it is very important to minimize the risk of anchor loss. In this study, a comprehensive literature review including accident and incident reports, technical reports and expert views was conducted to determine the factors that may cause anchor loss of ships. In order to analyze and define the cause-effect relationship between the determined factors, combination of the fuzzy logic and the DEMATEL (Decision Making Trial and Evaluation Laboratory) method was used. The aim of this study is to mitigate the risk of anchor loss by developing an alternative risk analysis tool. Environmental factors at anchorage area, training and competency of crew, the number of shackles paid out, anchoring method and selection of anchor are identified as the most critical factors for anchor loss. According to the results, a risk analysis model based on cause-effect relationship between the factors has been presented for the shareholders in maritime industry.

A fuzzy DEMATEL decision modeling framework for identifying key human resources challenges in start-up companies: Implications for sustainable development

Human resources (HR) management is vital in developing organizational performance and profit maximization. Small and medium-sized enterprises (SMEs) and emerging start-ups struggle to establish a functioning HR department, while larger organizations tend to reinvent their HR functions with updated visions and strategies. The role of HR practice yields more attention in SMEs and growing start-ups because of their increased failure rate. However, hindered by various challenges, selecting suitable HR practices for start-up companies has become difficult. This study investigates key challenges when choosing appropriate HR practices for start-ups based on a fuzzy decision-making trial and evaluation laboratory (DEMATEL) method. Firstly, 43 challenges were identified through a literature survey and consultation with experts. Later, considering the imprecise and subjective nature of the DEMATEL method on human judgments, the fuzzy DEMATEL approach is proposed to investigate the significance of identified challenges and the cause–effect relationships among them. From these findings, we identified that 21 challenges are causal factors that influence HR practice developments more. When selecting the best HR practices for their business, these cause factors will help management understand which challenges need to be removed and assist them in controlling their HR activities.

An integrated machine learning and DEMATEL approach for feature preference and purchase intention modelling

This article models the purchasing intention of young Indian consumers for branded smartphones by analysing their individual preferences for the different features of the smartphone. This article selects thirteen features for analysis, and the respondents are asked to rate, which are further used to model the mentioned purchasing intention. The features are selected using three quantitative methods: uncertainty calculation, correlation and Decision-Making Trial and Evaluation Laboratory (DEMATEL). The uncertainty indicates the variance in the respondents’ preference for a particular feature. So, the features with highly uncertain preference values are undesired. The correlation analysis indicates the feature preferences impacting the buying intention of a branded smartphone. The hierarchy and the causality for the impact of feature preferences on the branded smartphone preference are identified based on DEMATEL. The selected features are used to model the purchasing intention based on K nearest neighbour (KNN), a machine learning technique. The result is compared with the other three machine learning techniques for classification, namely, C4.5, CART, and logistic regression. The result indicates the superiority of KNN based model, which is further used for building a brand switching intention model.