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Assessing the key enablers for industry 4.0 adoption using MICMAC analysis: a case studyThe aim of this research is to assess the key enablers of Industry 4.0 (I4.0) in the context of the Indian automobile industry. It is done to apprehend their comparative effect on executing Industry 4.0 concepts and technology in manufacturing industries, in a developing country context. The progression to Industry 4.0 grants the opportunity for manufacturers to harness the benefits of this industry generation. Literature related to Industry 4.0 has been reviewed for the identification of key enablers of Industry 4.0. The enablers were further verified by academic professionals. Additionally, key executive insights had been revealed by using interpretive structural modelling (ISM) model for the vital enablers unique to the Indian scenario. We have also applied MICMAC analysis, to group the enablers of I4.0. The analysis of our data from respondents using ISM provided us with 7 levels of enabler framework. Our study adds to the existing literature on industry 4.0 enablers and findings highlight the specificities of the territories in India context. Our results show that top management is the major enabler to I4.0 implementation. Infact, it occupies the 7th layer of the ISM framework. Subsequently, government policies enable substantial support to develop smart factories in India. The findings of our work provides implementers of I4.0 in the automobile industry in the form of a robust framework. This framework can be followed by the automobile sector in enhancing their competency in the competitive market and ultimately provide a positive outcome for the Indian economic development led by these businesses. Furthermore, our work will guide decision-makers in enabling strategic integration of Industry 4.0, opening doors for the development of new business opportunities as well. The study proposes a framework for Indian automobile industries. The automobile sector was chosen for this study as it covers a large percentage of the market share of the manufacturing industry in India. Existing literature does not address the broader picture of I4.0 and most papers do not provide validation of the data collected. Our study thus addresses this research gap.
Exploration and Prioritization of Just in Time Enablers for Sustainable Healthcare: An Integrated GRA-Fuzzy TOPSIS ApplicationThe increased healthcare costs, improved service quality, and sustainability-oriented customer demand have forced the healthcare sector to relook their current process. The present work deals with the identification, analysis, and prioritization of Just in Time (JIT) enablers in the healthcare sector. JIT leads to waste reduction, improves productivity, and provides high quality patient care. The practical implementation of JIT depends on vital factors known as enablers. The enablers have been found through the comprehensive literature review and prioritized using responses from different healthcare facilities of national capital region of India. Grey Relational Analysis (GRA) has been used in the present study to rank enablers and ranks were further validated using fuzzy TOPSIS and sensitivity analysis. It has been found that top management support, teamwork, and real-time information sharing are the most significant enablers of JIT in healthcare with grey relational grades 0.956, 0.832, and 0.718, respectively. The corresponding closeness coefficients of the fuzzy TOPSIS for the enablers were found as 0.875, 0.802, and 0.688, respectively. The findings of the present research work will facilitate the healthcare organizations to implement a comprehensive JIT approach that further leads to improved patient care at low cost. The present study is unique in terms of the exploration of the readiness measures or enablers of JIT using GRA and fuzzy TOPSIS. The findings of the present research work will facilitate the healthcare organizations to optimize their resources for better patient care.
Mapping the human resource focused enablers with sustainability viewpoints in Indian power sector.Sustainability is defined a triple bottom line approach, which concentrates on economic, social and environment growth of any organisation. In order to achieve sustainability objective, the human resource focused enablers are playing a significant role in optimising expenses, improving productivity and quality of work. Therefore, the present study seeks to build a model for the enablers of human resource development for sustainability in India power sector. The study findings help the sector to improve the productivity of their workers and establish all the enablers, which can be seen to improve quality of work life in the Indian power sector. Improved human resource capabilities and work conditions provide not only much needed motivation to power sector employees to improve their efficiency but also assist to accomplish social-ecological-economic organizational sustainability. Total Interpretive Structural Modelling with Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) analysis has been applied to build a structural model and to identify the driving force and dependence power of enablers. Validation of relationships among the enablers and managerial implications are also discussed. According to the findings, the enablers ‘work safety and healthy working conditions’ have the highest driving power. The outcomes of this study can help the power sector to enhance human resource capabilities and quality of work life within the organization through provision of a benchmark model and help to accomplish sustainable development initiatives in its business.