Search results
1 – 4 of 4Renu L. Rajani, Githa S. Heggde, Rupesh Kumar and Deepak Bangwal
The purpose of this paper is to empirically examine the impact of supply chain risks (SCRs) and demand management strategies (DMSs) on the company performance in order to study…
Abstract
Purpose
The purpose of this paper is to empirically examine the impact of supply chain risks (SCRs) and demand management strategies (DMSs) on the company performance in order to study the use of DMSs in delivering improved results even in the presence of SCRs. The SCRs considered under the study are as follows: demand variability, constrained capacity and quality of services delivery, and competitive performance, customer satisfaction and financial performance are the measures considered for company performance.
Design/methodology/approach
This study is based on a survey of 439 businesses in India representing 10 groups of services industries (information technology/IT enabled services, business process outsourcing, IT infrastructure, logistics/transportation, healthcare, hospitality, personal services, consulting, education and training, consumer products and retail), using structural equation modeling (SEM) methods.
Findings
The findings reveal that presence of demand variability risk has significant influence upon the use of demand planning and forecasting, controlling customer arrival during peaks and shifting demand to future. Mismatch of capacity against demand (unused capacity) leads to the use of techniques to influence business during lean periods, thereby resulting in enhanced supply chain (SC) and financial performance. Controlling customer arrival during peaks to shift the demand to lean periods leads to enhanced financial performance. Presence of delivery quality risk does not significantly influence the use of DMS. Also, short-term use of customer and business handling techniques does not exert significant influence on company performance.
Research limitations/implications
The study has limitations as follows: (1) respondents are primarily from India while representing global organizations, (2) process/service redesign to relieve capacity as a DMS is not considered and (3) discussion on capacity management strategies (CMSs) is also excluded.
Practical implications
SC managers can be resourceful in shifting the peak demand to future with the application of techniques to control customer arrival during peaks. The managers can also help enhance business by influencing business through offers, incentives and promotions during lean periods to use available capacity and improve company performance.
Originality/value
This study is one of the first empirical works to explore how presence of SCRs influences the use of DMS and impacts the three types of company performance. The study expands current research on demand management options (DMOs) by linking three dimensions of company performance based on the data collected from ten different groups of service industry.
Details
Keywords
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.
Details
Keywords
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.
Details
Keywords
Ganesh Narkhede, Satish Chinchanikar, Rupesh Narkhede and Tansen Chaudhari
With ever-increasing global concerns over environmental degradation and resource scarcity, the need for sustainable manufacturing (SM) practices has become paramount. Industry 5.0…
Abstract
Purpose
With ever-increasing global concerns over environmental degradation and resource scarcity, the need for sustainable manufacturing (SM) practices has become paramount. Industry 5.0 (I5.0), the latest paradigm in the industrial revolution, emphasizes the integration of advanced technologies with human capabilities to achieve sustainable and socially responsible production systems. This paper aims to provide a comprehensive analysis of the role of I5.0 in enabling SM. Furthermore, the review discusses the integration of sustainable practices into the core of I5.0.
Design/methodology/approach
The systematic literature review (SLR) method is adopted to: explore the understanding of I5.0 and SM; understand the role of I5.0 in addressing sustainability challenges, including resource optimization, waste reduction, energy efficiency and ethical considerations and propose a framework for effective implementation of the I5.0 concept in manufacturing enterprises.
Findings
The concept of I5.0 represents a progressive step forward from previous industrial revolutions, emphasizing the integration of advanced technologies with a focus on sustainability. I5.0 offers opportunities to optimize resource usage and minimize environmental impact. Through the integration of automation, artificial intelligence (AI) and big data analytics (BDA), manufacturers can enhance process efficiency, reduce waste and implement proactive sustainability measures. By embracing I5.0 and incorporating SM practices, industries can move towards a more resource-efficient, environmentally friendly and socially responsible manufacturing paradigm.
Research limitations/implications
The findings presented in this article have several implications including the changing role of the workforce, skills requirements and the need for ethical considerations for SM, highlighting the need for interdisciplinary collaborations, policy support and stakeholder engagement to realize its full potential.
Originality/value
This article aims to stand on an unbiased assessment to ascertain the landscape occupied by the role of I5.0 in driving sustainability in the manufacturing sector. In addition, the proposed framework will serve as a basis for the effective implementation of I5.0 for SM.
Details