• Developing textile entrepreneurial inclination model by integrating experts mining and ISM-MICMAC

      Kapse, Chanduraj Pious; Kumar, Anil; Dash, Manoj Kumar; Zavadskas, Edmundas Kazimieras; Luthra, Sunil; Government Polytechnic, Nagpur, India; BML Munjal University; Indian Institute of Information Technology and Management; Vilnius Gediminas Technical University; State Institute of Engineering & Technology,Nilokheri, India; et al. (Taylor and Francis, 2018-03-05)
      The Indian textile industry is lacking in an entrepreneurial inclination of a skilled young generation; because of this, the industry is facing a challenge to achieve sustainable development and growth. To overcome this problem, the goal of this work is to build an entrepreneurial inclination model in the context of the textile industry. For achieving this goal, a combined approach of an extensive literature review and experts mining has been used to establish the entrepreneurial inclination factors in phased of the study. In the second phase, an Interpretive Structural Modelling (ISM) with Matrice d'Impacts Croisés Multiplication Appliqués à un Classement (MICMAC) has been applied to build a structural model and to find the driving force factors and dependence power. The results show that effective entrepreneurship courses, institutional policy, training and internship, institutional corporation and the involvement of institutional heads play a very significant role in encouraging youth towards entrepreneurship. The outcomes of the study can help both the government and academic institutes to draw up effective policy and develop an entrepreneurial culture which can help to create more entrepreneurs in the textile field.
    • Evaluating the human resource related soft dimensions in green supply chain management implementation

      Kumar, Anil; Kumar Mangla, S; Luthra, Sunil; Ishizaka, Alessio; University of Derby; University of Plymouth; Government Polytechnic, Jhajjar-124103; University of Portsmouth (Taylor and Francis, 2019-04-25)
      Due to increased carbon emissions, environmental protection initiatives have gained significant attention at global level. One of the major initiatives taken by the industrial sector to minimise the negative environmental effect of the value chain activities is Green Supply Chain Management (GSCM). In industry, soft (human resource-related) dimensions influence the implementation of GSCM process greatly. In the literature, relatively less discussion is provided on assessing the significance of soft dimensions in efficient GSCM acceptance in industry. The present work is an attempt to construct a structural framework for assessing the significance of the soft dimensions in adopting GSCM concepts by taking a case of automotive company in India. A hybrid approach of Best Worst Method (BWM) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is employed in this work. BWM is used to prioritize the GSCM oriented soft dimensions, and DEMATEL is employed to extract interrelationships among them. The result shows that ‘Top management commitment’, ‘Employee involvement’, ‘Organizational culture’ and ‘Teamwork’ are the highly prioritized causal soft dimensions in efficient GSCM adoption. This research work would help industry managers and practitioners to decide where to concentrate for GSCM concepts in context of soft dimensions for sustainable business development.
    • Lean Manufacturing and Internet of Things – A Synergetic or Antagonist Relationship?

      Anosike, Anthony; Alafropatis, Konstantinos; Garza-Reyes, Jose Arturo; Kumar, Anil; Luthra, Sunil; Rocha-Lona, Luis; University of Derby; University of Warwick; London Metropolitan University; Ch. Ranbir Singh State Institute of Engineering & Technology, Jhajjar-124103, Haryana, India; et al. (Elsevier, 2021-04-13)
      This paper explores the relationship between five LM methods (JIT, TPM, Autonomation, VSM and Kaizen) and three IoT technologies (RFID, WSN and Middleware) and the implications that arise from their combination. Four hypotheses and four complimentary research questions were formulated and tested. 136 responses were obtained through a questionnaire survey and analysed using descriptive statistics, 2-Sample proportion, Kruskal-Wallis, ANOVA and Pairwise comparison tests. The findings indicate that IoT can significantly improve the operational performance of manufacturing organisations. The findings advocate that all LM methods, apart from Kaizen, benefit from improved effectiveness by combining them with IoT. The results suggest that this can be attributed to the general perception about IoT, which despite the support and benefits it provides to people, is seen to be reducing human involvement whereas Kaizen is seen to be more people-focused. Improvements in information flow, decision-making and productivity were also found to be the most important motivations and benefits of combining LM methods with IoT. The findings of this research can be used by LM organisations that wish to embark into the new digitalised manufacturing era and businesses seeking to improve their performance through the combination of traditional efficiency-based methods and I4.0 technologies.
    • Mapping the human resource focused enablers with sustainability viewpoints in Indian power sector.

      Yadav, Mohit; Kumar, Anil; Mangla, Sachin Kumar; Luthra, Sunil; Bamel, Umesh; Garza-Reyes, Jose Arturo; Jindal Global University; University of Derby; University of Plymouth; Government Engineering College, Nilokheri, India; et al. (Elsevier, 2018-11-15)
      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.
    • Measuring and improving customer retention at authorised automobile workshops after free services.

      Kumar, Anil; Luthra, Sunil; Khandelwal, Dinesh Kumar; Mehta, Rajneesh; Chaudhary, Nityanand; Bhatia, Sukhdev; BML Munjal University; Government Engineering College, Nilokheri, India (Elsevier, 2017-07-29)
      Customer retention is vital for businesses with much research literature now available. But nothing has been investigated regarding measuring and improving customer retention at authorised automobile workshops after free services. Even after providing extensive warranties and other free service benefits, customers don’t use authorised workshops although their vehicles are still under warranty. By not arranging regular maintenance services, customers lose warranty benefits, with product performance and safety related awareness undermined; companies lose huge business potential. Therefore, this study aims to measure and improve customer retention at authorized automobile workshops after free services. To achieve this, a four-phased study has been conducted. In phase one, a combination of a literature review and expert opinions is used to identify customers’ retention factors. The second and third phases describe how data is collected from industry experts and customers. Analytical Hierarchy Process (AHP) and Decision Making Trial & Evaluation Laboratory (DEMATEL) are used to prioritise and examine inter-relationships among factors. In the last phase, the study recommends three business strategies to help a company to improve customer retention and make their Annual Maintenance Contract (AMC) product more customer friendly.
    • Predicting changing pattern: building model for consumer decision making in digital market

      Kumar, Anil; Mangla, Sachin Kumar; Luthra, Sunil; Rana, Nripendra P.; Dwivedi, Yogesh K.; BML Munjal University; Graphic Era University, Dehradun, India; State Institute of Engineering and Technology, Nilokheri, India; Swansea University; BML Munjal University, Gurgaon, India; et al. (Emerald Insight, 2018-09-10)
      Purpose Consumers have the multiple options to choose their products and services, which have a significant impact on the pattern of consumer decision making in digital market and further increases the challenges for the service providers to predict their buying pattern. In this sense, the purpose of this paper is to propose a structural hierarchy model for analyzing the changing pattern of consumer decision making in digital market by taking an Indian context. Design/methodology/approach To accomplish the objectives, the research is conducted in two phases. An extensive literature review is performed in the first phase to list the factors related to the changing pattern of consumer decision making in digital market and then fuzzy Delphi method is applied to finalize the factors. In the second phase, fuzzy analytic hierarchy process (AHP) is employed to find the priority weights of finalized factors. The fuzzy set theory allows capturing the vagueness in the data. Findings The findings obtained in this study shows that consumers are much conscious about innovative and trendy products as well as brand and quality; therefore, the service providers must think about these two most important factors so that they can able to retain their consumer in their online portal. Practical implications The analysis shows that “innovative and trendy” is the first priority factor for the consumers followed by “brand and quality” and “fulfilment and time energy.” The proposed model can help the marketers and service providers in predicting customers’ preferences and their changing pattern efficiently under vague surroundings. The outcomes of this research work not only help the service provider to update their products and services according to consumers’ needs but can also help them to increase profit and minimize their risk. Originality/value This work contributes to consumer research literature focusing on problem evaluation in the context of changing pattern of consumer decision making in digital era.
    • A step to clean energy - Sustainability in energy system management in an emerging economy context

      Mangla, Sachin; Luthra, Sunil; Jakhar, Suresh; Gandhi, Sumeet; Muduli, Kamalakanta; Kumar, Anil; Plymouth Business School (PBS), University of Plymouth, Plymouth, PL4 8AA, United Kingdom; Department of Mechanical Engineering, State Institute of Engineering & Technology (Also Known As Government Engineering College), Nilokheri, 132117, Haryana, India; Operations Management Group, Indian Institute of Management, Lucknow, India; Kirloskar Pneumatic Company Ltd, Pune, Maharashtra, 411013, India; et al. (Elsevier, 2019-09-23)
      Due to high consumption of energy, its associated concerns such as energy security and demand, wastage of resources, and material-energy recovery are leading to the importance of sustainable energy system development. This is a high time to assess the sustainability in energy systems for meeting the requirements of energy with an enhanced economic, ecological, and social performance from a nation context. The energy system plays a significant role in deciding the economic progress of emerging economies such as India, China, Brazil, and Africa. In this paper, an original attempt has been made to list and evaluate important indicators for sustainability assessment of energy systems development and management in an emerging economy especially India. Firstly, based on the analysis of the extant literature and then followed by expert opinion, potential key sustainability assessment indicators for energy systems development and management were identified. Further, grey based Decision-Making Trial and Evaluation Laboratory technique to understand the causal interactions amongst indicators and segregate them into cause and effect groups, is used. This work can provide useful aids to decision making bodies, sustainability practitioners and business organisations in selective implementation, monitoring and control of sustainable strategies in energy systems development and management and meeting sustainable development goals of clean energy in a nation context.