The study presents the results of the work undertaken to analyse constructs that make the companies adopt big data in the food industry towards the financial and market performance. Data was collected from 300 food industry employees who work in vital roles in the company. Primary data was collected through a survey method and a theoretical model was tested. Technological—Organizational—Enviornmental (TOE) framework was adopted, and the factors were analysed using Smart PLS software. It reveals that trialability, observability, complexity, and top management support are having a greater influence on big data analytics (BDA) adoption. Furthermore, external support, uncertainty and insecurity, and organizational readiness are also identified to affect BDA adoption. The findings ascertain the impact of BDA on the financial performance and marketing performance of the organisations. Understanding the variables that affect BDA acceptability enables managers to take the appropriate steps for a successful deployment. The research aids BDA service providers in luring and spreading BDA in the food sector.

The tourism industry is rapidly adopting artificial intelligence (AI) to enhance customer experiences and improve service delivery. However, the adoption of AI has raised concerns about concierge chatbots, digital assistance, proactiveness, anthropomorphism, and security, and its impact on overall customer satisfaction. Therefore, the aim of this research is to measure the service quality of AI in the tourism industry, with primary data collected in Pondicherry. This study is a quantitative research study that utilized a survey method to collect primary data. A total of 350 respondents were targeted, with 307 valid responses obtained. The data were analyzed using confirmatory factor analysis and structural equation modeling. The study highlights that AI technology has a significant positive impact on the service quality of the tourism industry. This study contributes to the literature by providing empirical evidence to service quality in the context of AI technology and the importance of AI technology to enhance service quality and customer satisfaction.

The purpose of this study is to examine the value chain analysis of, consumers' awareness level of, and buying motives toward mushroom products. The primary data were collected through face-to-face interviews and by using a questionnaire filled out by 70 consumers from various major mushroom production districts, selected by non-random sampling. Secondary data were collected from various sources. Based on the data analysis, it was found that around 73% of consumers preferred to buy their mushroom products in the supermarket, and 71% of consumers responded that factors other than the shape, color, and size of mushrooms motivated them to buy them. The research concludes that urban consumers were well aware of the nutrition value of mushrooms, but their consumption level was very low compared to non-vegetarians urban consumer in the studied area. Nearly 30% of respondents believed a myth about mushrooms having a mold and were prepared from compost, which causes a bad smell. It was found that that while producers put forth more effort and energy than other actors into the mushroom value chain they received less revenue and profit than wholesalers and retailers. Therefore, policy makers should develop new norms to remove barriers and others issues to safeguard mushroom producers for sustainable growth of the mushroom sector in India. In the future, there will be an increase in the consumption of processed foods. Hence, food companies have to concentrate on mushroom processing and fresh mushroom production.

The objective of this study is to investigate the level of understanding that internet users have regarding data privacy, security, and protection. The study aims to determine the extent to which individuals are conscious of the potential hazards of sharing personal information online and the steps they take to secure their data. The research also examines the role of technology companies and government agencies in educating internet users about data privacy and security. The study was conducted in Bhopal using stratified random sampling, and data were collected from employees and students of an educational institution in Bhopal. The findings of this study will give an understanding of the current awareness of internet users and aid in future efforts to enhance data privacy and security for all users.

Innovative approaches and regulatory laws for fake technology are clarified in this study. This chapter contributors explores the regulatory and legal implications of one specific real-world deepfake case study. The writers note that individuals are initially frightened of these deep fakes, similar to how they have been with numerous other innovations in the past. Although deepfakes are anticipated to be applied more often in the years to come, the writers focus on a number of societal and constitutional concerns that Humans and government will have to contend effectively. The probable role of legislatures and digital broadcasting networks in countering deepfakes is further addressed in the study. Furthermore, the researchers of this study offer suggestions and ideas on how to mitigate and reduce the growth of deepfakes from a standpoint of regulation and one from a point of view of technology.