Praveen M. Kulkarni

Purpose: This study aims to understand the role of university incubation centers (UICs) in fostering startup growth within an academic ecosystem, focusing on enhancing their effectiveness. Design/methodology/approach: Data was collected from startups and incubation centers in Karnataka, India. Warp partial least squares 6.0 was used for path analysis to examine the relationships between institutional pressures, startup performance and resource acquisition. Findings: UICs in India effectively support startup growth. Mimetic isomorphism positively influences resource munificence, while normative isomorphism enhances monitoring and assistance. Coercive pressures negatively impact startup performance. Research limitations/implications: The research is limited to India. Future studies in other developing countries would help validate and extend these findings, offering a more comprehensive understanding of incubation center dynamics globally. Practical implications: This study offers insights on optimizing UIC operations to better support startups. By integrating institutional theory, it highlights the significance of legitimacy, professional standards and strategic location in enhancing incubation center effectiveness. Social implications: UICs play a crucial role in bolstering the startup ecosystem, essential for employment generation and economic development in India. Effective incubation centers drive innovation and entrepreneurship, contributing to broader societal benefits. Originality/value: This study fills a gap by focusing on South Asia, providing insights into the unique challenges and opportunities faced by UICs in developing countries and enhancing understanding of incubation practices in these regions.

With technology advancing rapidly, organizations must continuously develop to remain competitive. They invest in technologies such as blockchain, artificial intelligence, machine learning, and cloud computing. This study focuses on the challenges of implementing blockchain technology in the manufacturing sector. Data was collected through structured interviews with production and design managers, as well as employees of organizations using new technologies. The snowball sampling method was employed, and analysis was conducted using the large group decision method. The findings will have significant implications for leveraging blockchain in manufacturing. The study focuses on exploring factors related to opportunities and challenges within the technology organisation's environment, addressing existing research gaps. The findings are constrained by the scope of the data series, presenting longitudinal facts. To tackle the prospects and complications highlighted in the study, organizations should make use of this technology to enhance their manufacturing processes.

This study investigates the impact of variables such as “IoT training,” “IoT deployment,” “performance metrics,” and “data quality” on supply chain agility in the foundry industry of North Karnataka, India. The study unravels the complex interplay between these elements through a multifaceted approach, incorporating these critical variables and utilizing various tools and techniques, including surveys, data analysis, and statistical modeling. The findings underscore the strategic importance of investing in IoT training and skill development, revealing their significant influence in augmenting supply chain agility. These collective insights offer a valuable roadmap for decision-makers in the foundry industry, guiding them towards more agile, data-driven, and efficient supply chains, well-prepared to thrive in the dynamic landscape of Industry 4.0 Request access from your librarian to read this chapter's full text.

In the past, the perspective of training programs has been used to understand employee motivation. However, there is a lack of normative and perceptive support that can guide the development of online training programs. Therefore, there is a need to understand employee motivation from the perspective of online training. This study aims to understand employee motivation and its relationship with online training in an organizational setting. The study adopted empirical research to investigate the relationship between training goals and trainee intentions to undergo online training, the role of self-efficacy in this relationship, and the expectancy of the learners from online training programs. The study tests the factors identified from the literature review for model validation. A total of 15 items were used in a survey of 812 randomly selected respondents from the organization in Belagavi, Karnataka, India. The structural equation modeling techniques were applied to explore and validate the model. The results show that factors such as learning goals, social interaction, time management and personalization have a great role to play in building training intention in the online environment, and the successful realization of the training goals.

This study focuses on the barriers to implementing supply chain management (SCM) 4.0 in the foundry industry and provides insights into its practical implementation in foundry units. Our study identifies barriers such as data privacy, legal issues, SCM complexity, and barriers related to implementing Industry 4.0 (I4.0)-enabled SCM in the foundry industry. It also provides insights into the role of digital infrastructure in building effective I4.0-enabled SCM. This study provides insights into how SCM 4.0 can be implemented in the foundry industry. The findings will be helpful to policymakers and foundry consultants in designing appropriate strategies for foundry units.