Barriers to implementing digitalization in the Indian construction industry

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Avirag Bajpai ◽  
Subhas C. Misra

PurposeThis research paper aims to analyze the critical barriers to implementing digitalization in the Indian construction industry as Indian construction companies are lagging in the implementation of digital technologies in the work environment.Design/methodology/approachIn this research paper, a qualitative research approach is adopted, and multiple detailed interviews are conducted with industry and academic experts. Further, multi-criteria decision-making (MCDM) techniques are used to finalize the prioritization among various alternatives. The fuzzy-decision-making trial and evaluation laboratory (Fuzzy-DEMATEL) and interpretive structural modeling (ISM) techniques are employed to find the exact relationship among the identified alternatives.FindingsThis study identifies 14 critical barriers from an extensive literature review and multiple interviews with industry professionals, and further driving and critical barriers are identified.Research limitations/implicationsIn this research paper, an exploratory study with a limited number of respondents from a large Indian construction company is carried out. Further, a detailed longitudinal analysis can be done to assess the subjectivity of the participants with more advanced statistical tools. However, this research discusses several points pertaining to the implementation of digitalization in the construction industry. The research further identifies the critical barriers to digitalization in the Indian construction industry.Practical implicationsThe finding of the study has two-pronged implications. First, it provides a road-map to the construction industry by highlighting the engagement of top management as the key focus area for successful digitalization. Second, the finding also shows similarity of the digitalization process to the adoption of process improvement techniques like lean and total quality management (TQM), wherein the top management plays a crucial role in ushering in the implementation of a disruptive change.Originality/valueThe research is unique in two ways. First, this is one of the very few attempts to understand digitalization in the Indian context. Second, the research also demonstrates that the combination of fuzzy DEMATEL and ISM techniques can be successfully employed in the emerging field of construction digitalization research.

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
S Vinodh ◽  
Vishal Ashok Wankhede

PurposeThe aim of this study is to analyze workforce attributes related to Industry 4.0 using fuzzy decision-making trial and evaluation laboratory (DEMATEL) and fuzzy combinative distance-based assessment (CODAS).Design/methodology/approachTechnological trends stipulate various revolution in industries. Industry 4.0 is a vital challenge for modern manufacturing industries. Workforce adoption to such challenge is gaining vital importance. Therefore, such workforce-related attributes need to be identified for enhancing their performance in Industry 4.0 environment. In this context, this article highlights the analysis of 20 workforce attributes for Industry 4.0. Relevant criteria are prioritized using fuzzy DEMATEL. Workforce attributes are prioritized using fuzzy CODAS.FindingsThe key attributes are “Skills/training in decision-making (WA2)”, “Competences in complex system modelling and simulation (WA1)” and “Coding skills (WA20)”.Research limitations/implicationsIn the present study, 20 workforce attributes are being considered. In future, additional workforce attributes could be considered.Practical implicationsThe study has been conducted based on inputs from industry experts. Hence, the inferences have practical relevance.Originality/valueThe analysis of workforce attributes for Industry 4.0 using MCDM methods is the original contribution of the authors.


2019 ◽  
Vol 29 (3) ◽  
pp. 335-354
Author(s):  
Hasan Dinçer ◽  
Tuba Bozaykut-Buk ◽  
Şenol Emir ◽  
Serhat Yuksel ◽  
Nicholas Ashill

Purpose The purpose of this paper is to present a multidimensional evaluation of brand equity performance incorporating dimensions adopted from the balance scorecard (BSC) approach to business performance. Design/methodology/approach In this study, text mining is used for automatic extraction of valuable information from textual data such as the financial reports of firms. Instead of expert opinions, linguistic scales built upon outcomes of text mining are used as inputs for decision-making. The proposed model combines fuzzy DEMATEL (FDEMATEL), fuzzy ANP (FANP), fuzzy TOPSIS (FTOPSIS) and fuzzy VIKOR (FVIKOR) methods for weighting criteria and ranking alternatives. Findings Using data from five privatized firms in Turkey, the study’s findings demonstrate that the customer is the most important dimension of brand equity performance evaluation. Cash flow and brand loyalty are identified as the most important criteria in the measurement of brand equity performance. Practical implications Findings highlight the importance of firms taking action to increase consumer perceptions, attitudes and behaviors in the privatization processes. For this purpose, privatized firms need to understand the expectations of customers to increase customer satisfaction and loyalty and therefore improve brand equity. Originality/value The paper contributes to literature in several important ways. First, by adopting the BSC approach, it proposes a holistic and a multidimensional model for measuring brand equity performance. Second, the study offers a novel methodology using a hybrid multi-criteria decision-making model designed for the fuzzy environment. Third, the study uses the knowledge extraction tool of text mining in the fuzzy decision-making process. Finally, the study evaluates the brand equity performance of privatized firms in an emerging country context.


2020 ◽  
Vol 13 (5) ◽  
pp. 1025-1050
Author(s):  
Reyhane Hashemi ◽  
Reza Kamranrad ◽  
Farnoosh Bagheri ◽  
Iman Emami

PurposeThe aim of this paper is to predict and minimize the risks of oil, gas and petrochemical projects. Besides, reducing the likelihood of occurrence and minimizing risks impact on the projects to reduce the probable costs and improve the economic situation is another purpose of this paper.Design/methodology/approachThis paper provides a fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) – a technique that assist to solve decision-making problems – and IP (Impact & Probability) table methods to identify and analyze critical risks in energy projects, and then fuzzy Binary Logistic Regression (BLR) in order to predict the probability of each level of risk for more efficient risk management in projects. Furthermore, in this paper, the fuzzy BLR (FBLR) is optimized such that the probability of a high level of risk for the implementation of the project has been minimized using meta-heuristic algorithm.FindingsThe results from the point of view of experts show that combination of fuzzy DEMATEL with FBLR approach as well as using SA algorithm, in order to optimize the high level of risks, can provide a smart approach to managing risks with more success.Practical implicationsThe application of the proposed method is illustrated via a real data set from energy projects.Originality/valueWe propose combined fuzzy DEMATEL and FBLR methods to predict and optimize the risks of the energy projects, which is the innovation of this paper.


Kybernetes ◽  
2019 ◽  
Vol 49 (4) ◽  
pp. 1103-1126
Author(s):  
Negar Shaaban ◽  
Majid Nojavan ◽  
Davood Mohammaditabar

Purpose The purpose of this paper is to investigate a fuzzy hybrid approach for ranking the flare gas recovery methods and allocating to refineries. Design/methodology/approach The proposed approach is containing four stages: in the first stage, experts' assessment is applied to identify relevant criteria and sub-criteria in the evaluation of flare gas recovery methods. In the second stage, the corresponding weights of criteria and sub-criteria are determined via fuzzy decision-making trial and evaluation (DEMATEL)-analytical network process (ANP) (DANP) method. In the third stage, the flare gas recovery methods are ranked using fuzzy weighted aggregated sum product assessment method (WASPAS) multi-criteria decision-making (MADM) technique. In the fourth stage, an optimization model is developed to allocate gas recovery methods to refineries while maximizing the total utility of allocations based on model constraints. Findings According to the results of fuzzy DANP method, technical and operational criterion was the most important followed by economic, political, managerial and environmental criteria. With respect to sub-criteria, international sanctions and political stability were the most important. The results of fuzzy WASPAS method indicated that gas injection was the first ranked alternative. Finally, the mathematical modeling allocated the recovery methods to five refineries of South Pars gas field in Iran based on budget and time constraints. Originality/value The proposed approach provides a systematic tool in the selection of flare recovery methods and allocation to refineries. This approach uses a new combination of fuzzy DEMATEL-ANP (DANP) method, fuzzy WASPAS method and mathematical programming. The approach is effectively implemented in a case study for ranking the flare gas recovery methods and allocating to refineries of South Pars gas field in Iran.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Justin Zuopeng Zhang ◽  
Praveen Ranjan Srivastava ◽  
Prajwal Eachempati

PurposeThe paper aims to build a customized hybrid multi-criteria model to identify the top three utilities of drones at both personal and community levels for two use cases: firefighting in high-rise buildings and logistic support.Design/methodology/approachA hybrid multi-criterion model that integrates fuzzy analytical hierarchy process (AHP), Best Worst, fuzzy analytical network process (ANP), fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) is used to compute the criteria weights. The weights are validated by a novel ensemble ranking technique further whetted by experts at the community and personal levels to two use cases.FindingsDrones' fire handling and disaster recovery utilities are the most important to fight fire in high-rise buildings at both personal and community levels. Similarly, drones' urban planning, municipal works and infrastructure inspection utilities are the most important for providing logistics support at personal and community levels.Originality/valueThe paper presents a novel multi-criteria approach, i.e. ensemble ranking, by combining the criteria ranking of individual methods – fuzzy AHP, Best-Worst, fuzzy ANP and fuzzy DEMATEL – in the ratio of optimal weights to each technique to generate the consolidated ranking. Domain experts also validate this ranking for robustness. This paper demonstrates a viable methodology to quantify the utilities of drones and their capabilities. The proposed model can be recalibrated for different use case scenarios of drones.


Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Riddhi Rajendra Thavi ◽  
Vaibhav S. Narwane ◽  
Rujuta Hemal Jhaveri ◽  
Rakesh D. Raut

PurposeThe paper focuses on reviewing and theorizing the factors that affect the adoption of cloud computing in the education sector narrowing the focus to developing countries such as India.Design/methodology/approachThrough an extensive literature survey, critical factors of cloud computing for education were identified. Further, the fuzzy DEMATEL approach was used to define their interrelationship and its cause and effect.FindingsA total of 17 factors were identified for the study based on the literature survey and experts' input. These factors were classified as causes and effects and ranked and interrelated. “Required Learning Skills and Attitude,” “Lack of Infrastructure,” “Learners' Ability” and “Increased Investment” are found to be the most influential factors.Practical implicationsThe resultant ranking factors can be used as a basis for managing the process of cloud adoption in several institutions. The study could guide academicians, policymakers and government authorities for the effective adoption of cloud computing in education.Originality/valueThe study investigates interdependency amongst the factors of cloud computing for education in context with developing economy. This is one of first study in higher education institutes of India.


2019 ◽  
Vol 14 (1) ◽  
pp. 153-174 ◽  
Author(s):  
Shahbaz Khan ◽  
Mohd Imran Khan ◽  
Abid Haleem

PurposeHigher level of customer satisfaction for halal products can be achieved by the effective adoption of halal certification through assessment and accreditation (HCAA). There are certain issues that seem detrimental towards the adoption of HCAA. The purpose of this paper is to identify the major barriers towards the adoption of HCAA and evaluate inter-relationships among them for developing the strategies to mitigate these barriers.Design/methodology/approachThe barriers towards the adoption of HCAA are identified through an integrative approach of literature review and expert’s opinion. The inter-relationship among the identified barriers is evaluated using fuzzy-based decision-making trial and evaluation laboratory (fuzzy DEMATEL) technique, which categorises them into influential and influenced group.FindingsThe evaluation of inter-relationship among barriers using fuzzy DEMATEL indicates four influencing barriers and six influenced barriers towards the adoption of HCAA. Further, findings suggest an extensive government, and management support is vital in terms of commitment, resources and actions to realise the benefits attributed with HCAA.Research limitations/implicationsThe inter-relationship among barriers is contextual and based on the perception of experts which may be biased as per their background and area of expertise. This study pertains to a specific region and can be extended to the generalised certification system.Originality/valueThe empirical base of the research provides the inter-relationship among the barriers towards the adoption of HCAA which can be effectively used as input in the decision-making process by producers, manufacturers and distributor. The policy maker can analyse the cause group and effect group of barriers to formulate policies that would help in the adoption of HCAA.


2014 ◽  
Vol 4 (1) ◽  
pp. 95-103 ◽  
Author(s):  
Li Li ◽  
Guo-hui Hu

Purpose – At present, financial agglomeration tendency in domestic and foreign countries is increasingly evident. Therefore, from a comparative perspective, this paper aims to assess and predict the financial agglomeration degree in central five cities. Design/methodology/approach – According to the diversity of evaluating indexes and the uncertainty of financial agglomeration, this paper constructs a set of indexes of evaluating the financial agglomeration degree, comprehensively evaluates the financial agglomeration degree of the five cities – Wuhan, Changsha, Zhengzhou, Nanchang and Hefei – in China's middle region from 2001 to 2010 by using the multiple dimension grey fuzzy decision-making model, and predicts their development tendency by using the GM (1, 1, β) model. Findings – The results show that the multiple dimension grey fuzzy decision-making pattern cannot only be used to determine the weights of evaluating indexes, but also get the fuzzy partition and ranking order of the financial agglomeration in central five cities. The grey prediction results can objectively reflect the development tendency of the financial agglomeration in central five cities. Practical implications – From the results, it is necessary for any competitive city to clarify their relative strengths and weaknesses in order for the accurate location and scientific development, and it also provides a reference for the government decision-making. Originality/value – The paper succeeds in using the multiple dimension grey fuzzy decision-making model to measure the financial agglomeration degree of the five central cities and the grey prediction model to predict future trends.


2018 ◽  
Vol 25 (5) ◽  
pp. 1528-1547 ◽  
Author(s):  
Anil Kumar ◽  
Amit Pal ◽  
Ashwani Vohra ◽  
Sachin Gupta ◽  
Suryakant Manchanda ◽  
...  

Purpose Supplier selection for capital procurement is a major strategic decision for any automobile company. The decision determines the success of the company and must be taken systematically with the utmost transparency. The purpose of this paper is to construct capital procurement decision-making model to optimize supplier selection in the Indian automobile industry. Design/methodology/approach To achieve the stated objective, a combined approach of fuzzy theory and AHP-DEMATEL is applied. Evaluation parameters are identified through an extensive literature review and criteria validation has been introduced through a Fuzzy Delphi method by using fuzzy linguistic scales to handle the vagueness of information. AHP is employed to find the priority weight of criteria, although an inter-relationship map among criteria is not possible through AHP alone since it considers all criteria as independent. To overcome this, DEMATEL is used to establish cause-effect relationships among criteria. Findings The results show that the total cost of ownership (TOC) is the first weighted criterion in supplier selection for capital procurement, followed by manufacturing flexibility and maintainability, then conformity with requirement. The cause-effect model shows that supplier profile, TOC, service support and conformity with requirement are in the cause group and are considered to be the most critical factors in selecting the supplier. Originality/value The study’s outcome can help the automobile industry to optimize their selection process in selecting their suppliers for capital procurement; the proposed model can provide guidelines and direction in this regard.


Author(s):  
Gayani Karunasena ◽  
Kosala Rajagalgoda Gamage

Purpose The construction industry in many developing countries is reluctant to apply value engineering (VE) due to uncertainty of outcomes. The purpose of this paper is to examine the existing practices of VE techniques and make recommendations to organisations and national construction regulatory bodies, to standardise VE practices. A decision-making formula is introduced to determine profitability of VE applications prior to implementation. Design/methodology/approach A broad literature review and six case study projects that applied VE were selected. Thirty-nine semi-structured interviews were conducted to gather data within cases. Six expert interviews were conducted as confirmatory interviews to clarify and validate research outcome. Content analysis and cognitive mapping were used to analyse data among case studies. Findings Application, knowledge and experience on VE techniques among construction professionals are unsatisfactory. Recommendations include reducing contractor’s design responsibility, introducing proper VE guidelines and statutory regulations. A framework is introduced to assist authorities to standardise application of VE techniques. A decision-making formula is suggested to determine margins of contractor’s portion due to VE techniques and original profits gained. Originality/value The formula can be used as a decision-making tool by construction industry practitioners to determine successfulness of proposed VE techniques, and the proposed framework can be used to guide construction professional bodies to standardise VE practices.


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