Jayati Singh, Rupesh Kumar, Vinod Kumar and Sheshadri Chatterjee
The main aim of this study is to identify and prioritize the factors that influence the adoption of big data analytics (BDA) within the supply chain (SC) of the food industry in…
Abstract
Purpose
The main aim of this study is to identify and prioritize the factors that influence the adoption of big data analytics (BDA) within the supply chain (SC) of the food industry in India.
Design/methodology/approach
The study is carried out in two distinct phases. In the first phase, barriers hindering BDA adoption in the Indian food industry are identified. Subsequently, the second phase rates/prioritizes these barriers using multicriteria methodologies such as the “analytical hierarchical process” (AHP) and the “fuzzy analytical hierarchical process” (FAHP). Fifteen barriers have been identified, collectively influencing the BDA adoption in the SC of the Indian food industry.
Findings
The findings suggest that the lack of data security, availability of skilled IT professionals, and uncertainty about return on investments (ROI) are the top three apprehensions of the consultants and managers regarding the BDA adoption in the Indian food industry SC.
Research limitations/implications
This research has identified several reasons for the adoption of bigdata analytics in the supply chain management of foods in India. This study has also highlighted that big data analytics applications need specific skillsets, and there is a shortage of critical skills in this industry. Therefore, the technical skills of the employees need to be enhanced by their organizations. Also, utilizing similar services offered by other external agencies could help organizations potentially save time and resources for their in-house teams with a faster turnaround.
Originality/value
The present study will provide vital information to companies regarding roadblocks in BDA adoption in the Indian food industry SC and motivate academicians to explore this area further.
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Rupesh Rajak, Binod Rajak, Vimal Kumar and Swati Mathur
This study aims to provide a causal framework for teacher burnout (BO) and work engagement (WE) by examining the factors that contribute to it and evaluating how progressive…
Abstract
Purpose
This study aims to provide a causal framework for teacher burnout (BO) and work engagement (WE) by examining the factors that contribute to it and evaluating how progressive education (PE) affects teachers' performance in Higher education institutions (HEIs).
Design/methodology/approach
This study uses a multi-stage sampling technique with the help of computer random generation data from a selected list of teachers. The survey has two sections; the first consisted of a questionnaire of PE, BO, WE and organizational outcomes and the second contained four items to measure the demographic variables. The researcher contacted 745 teachers and asked them to fill up the questionnaire but the authors received only 498 useable responses.
Findings
The results of the study confirmed that moderating role PE reduces the BO of the teachers of HEIs and increases WE. The job demand-resource (JD-R) model was also validated in the Indian context and the model was found suitable for the Indian sample.
Research limitations/implications
The study has been conducted to manage BO and teachers' engagement in HEIs and the result suggests that the Management of HEIs should value PE characteristics as a crucial component of the educational process. PE encourages academic engagement among professors and students in HEIs.
Originality/value
The study tests the moderating role of PE with the JD-R and the JD-R model in the higher education system in India, which is rarely tested. The study's integrated approach to BO and WE, which provide insight into both viewpoints and aids in employees' poor health.
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Rupesh Chourasiya and Shrikant Pandey
This comprehensive review study aims to analyze the current state of technology adoption (TA) within the textile industry, with a particular focus on the economic, environmental…
Abstract
Purpose
This comprehensive review study aims to analyze the current state of technology adoption (TA) within the textile industry, with a particular focus on the economic, environmental, and social dimensions.
Design/methodology/approach
Twenty-four articles from the Scopus database, spanning from January 2015 to March 2024, were meticulously selected for analysis. The review uses a qualitative approach, synthesizing diverse perspectives to provide a holistic understanding of TA in the textile sector.
Findings
The review highlights a noticeable lag in the adoption of new technologies, particularly in developing nations like India, within the textile industry. Despite significant technological advancements, there remains a gap between innovation and implementation. Sustainable approaches to mitigate environmental impacts emerge as a key focus, underscoring the need for operational enhancements and policy interventions.
Research limitations/implications
The study’s reliance on articles from the SCOPUS database presents a limitation, potentially overlooking relevant research from other sources.
Practical implications
Practitioners in the textile industry can benefit from the review’s insights by understanding the importance of integrating technological advancements sustainably. By leveraging innovative solutions and collaborating with policymakers, firms can enhance operational efficiency while minimizing environmental impacts, thus ensuring long-term competitiveness.
Social implications
Efforts to advance TA in the textile industry have significant social implications, including job creation, improved working conditions and reduced environmental harm.
Originality/value
Study addressed the insights for policymakers, industry practitioners and researchers seeking to drive technological innovation while addressing socio-economic and environmental challenges.