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Introduction: Artificial intelligence (AI) and digitisation offer substantial human potential and profit margins, making them promising retail solutions. Retail leaders have successfully integrated comprehensive uses into their daily operations, while competitors heavily invest in new projects. The Indian retail sector is undergoing a significant transformation, which can be attributed to factors such as growing income, demographic characteristics, and enhanced consumerism, as well as the rapid development of new technologies such as digitisation and AI, which is changing both consumers’ and retailers’ buying behaviour.

Purpose: This study aims to determine the influence of AI on elements that drive digitisation in the retailing sector, as well as the factors that lead to organised retailers adopting digitisation and its impact on their business.

Methodology: The study employs a standardised questionnaire distributed to organised stores via an online link, and the data are analysed with SmartPLS software 3.0.

Finding: The retail sector is driven by elements that promote digitalisation in food and groceries retailing, such as simplicity of operation, adoption of digital payment, quicker internet connection, retailer consumer interface, and the involvement of AI.

Research implication: AI has significant consequences for retailing, which serves as the interface between marketers and customers.

Theoretical implication: The study’s findings reflect the perspectives of retailers, store managers, and entrepreneurs on how digitalisation and AI are crucial for the creation and growth of long-term competitive advantages in retail.

The purpose of this chapter is to identify and analyze various critical success factors (CSFs) that can facilitate retailing business in Thailand. This chapter further aims to understand the mutual interactions among these CSFs through identification of the hierarchical relationships among them. A framework for Thai retailers has been developed, wherein the hierarchical interrelationships between identified CSFs have been presented and interpreted using total interpretive structural modeling (TISM). Cross-impact matrix multiplication applied to classification analysis has been further employed to identify the driving power as well as dependence power of these CSFs. In the present research, 15 CSFs have been identified through literature review and expert opinions. The methodology employed in this study provides a mechanism to conduct an exploratory study by identifying the factors and analyzing their interactions through the development of a hierarchical framework. The proposed framework developed through qualitative modeling is an effort to understand relevant factors that can apply to the Thai retailers. This study makes a significant contribution in the literature of retailing business, which captures the perspective of different customers.

The COVID-19 pandemic has recently had an impact on the stock market all over the globe. A thorough review of the literature that included the most cited articles and articles from well-known databases revealed that earlier research in the field had not specifically addressed how the BRIC stock markets responded to the COVID-19 pandemic. The data regarding COVID-19 were collected from the World Health Organization (WHO) website, and the stock market data were collected from Yahoo Finance and the respective country’s stock exchange. A random forest regression algorithm takes the closing price of respective stock indices as target variables and COVID-19 variables as input variables. Using this algorithm, a model is fit to the data and is visualised using line plots. This study’s findings highlight a relationship between the COVID-19 variables and stock market indices. In addition, the stock market of BRIC countries showed a high correlation, especially with the Shanghai Composite Stock Index with a correlation value of 0.7 and above. Brazil took the worst hit in the studied duration by declining approximately 45.99%, followed by India by 37.76%. Finally, the data set’s model fit, which employed the random forest machine learning method, produced R² values of 0.972, 0.005, 0.997, and 0.983 and mean percentage errors of 1.4, 0.8, 0.9, and 0.8 for Brazil, Russia, India, and China (BRIC), respectively. Even now, two years after the coronavirus pandemic started, the Brazilian stock index has not yet returned to its pre-pandemic level.

There is sufficient evidence to prove that the improved health status of a nation’s citizens results in economic growth and development via improved functionality and productivity of labor. It is also commonly accepted that healthcare expenditure significantly influences health status through, for instance, improving life expectancy at birth and reducing morbidity, death, and infant mortality rates. Within healthcare, medicines account for a considerable share of health-related expenditure in both developed and developing countries. Therefore, it seems reasonable to assume that improved access to medicines is likely to contribute not only to the well-being of families and individuals but also to the economic growth and development in all societies. It has been widely advocated that pharmaceutical multinational enterprises (MNEs) can play an important role to address this problem, as they develop and supply a significant proportion of the drugs imported by low- and middle-income countries. This chapter is dedicated to a systematic review of literature in order to identify the strategies implemented by pharmaceutical MNEs to improve access to medicines in the low- and middle-income countries. A total of 76 research articles have been identified, and we have found that the main strategies of pharmaceutical MNEs are related to improving health outcomes through R&D, establishing partnerships for product development, pricing strategies to improve access to medicines, technology transfer, licensing agreements, and nonmarket efforts to improve access to medicines, among other strategies to overcome barriers imposed by intellectual property rights. We have also found that pharmaceutical MNEs’ strategies take place within a complex system and often involve interactions with a wide range of actors, such as international organizations, governments, private not-for-profit sector, universities and research institutes, and generic manufacturers. However, there is still a need for major progress in the field of access to medicines, and pharmaceutical MNEs should be more active in this field in order to avoid potential negative consequences, such as loss of legitimacy and compulsory licensing of their patented medicines.

Aadhaar card is an innovative step taken by the Government of India to facilitate smooth functioning of government welfare programs among the needy citizens of this country. This chapter deals about the Aadhaar Project of the Central Government, its features, its impact on the welfare schemes of government, etc. Second, it also deals with the challenges and loopholes associated with the Aadhaar scheme which eventually led to the case of Justice K. S. Puttaswamy and Another v. Union of India [Writ Petition (Civil) No. 494 of 2012]. At last, the chapter deals with the potential challenges which the Aadhaar scheme may face even after it has been declared constitutional by the Apex Court in the case of Justice K. S. Puttaswamy and Another v. Union of India [Writ Petition (Civil) No. 494 of 2012].