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The study aims to empirically analyze whether financial literacy can improve the financial behavior of individuals in the context of emerging markets like India.

The authors use the nationally representative Financial Inclusion Insights survey conducted in India during 2018 for the analysis. The authors consider the financial literacy score based on the standard financial literacy quiz that includes understanding basic numeracy, interest rates, inflation and diversification concepts to study its effect on payment attitude, savings attitude and risk management behavior proxied by insurance uptake. Using an instrumental variable approach, the authors account for the possible endogeneity associated with the financial literacy variable.

The authors find that less than 9% of individuals have correctly answered questions capturing all four aspects of financial literacy. The analysis suggests that improvements in financial literacy scores indeed increases the likelihood of exhibiting superior financial behavior. The results are robust to alternative definitions of financial literacy, outcome variables and inclusion of additional controls. The authors find that financial literacy increases financial planning, and this, in turn, possibly improves financial behavior. The effects are prominent for those residing in the urban area and having confidence in their financial skills.

This is among the few studies that provide insights regarding how improvements in financial literacy can improve financial behavior in an emerging economy context. Moreover, this study highlights financial planning as a possible channel through which financial literacy affects financial behavior. Further, the heterogeneous effects based on the area of residence and own ability underscore the need for complementary policies.

The study analyzes the relationship between homeownership and financial investment of households in the context of emerging markets like India. It also examines how homeownership affects the portfolio decisions of Indian households.

Using the nationally representative All-India Debt and Investment Survey of 2019 and employing an instrumental variable approach, the authors analyze the relationship between homeownership and the share of financial assets held by Indian households. The study also employs several sensitivity checks, including alternate estimation techniques and alternative definitions of the housing variables, and accounts for additional factors to ensure that the authors are able to capture the effect of homeownership on the outcome variable.

The analysis suggests homeownership crowds out financial investment in India due to high repair and maintenance costs. The negative effect is mainly observed in urban households. Further, the findings imply that homeownership leads households to reallocate their asset portfolio. Homeowners have a lower share in liquid short term deposits, indicating the high liquidity risk of their portfolios. On the other hand, homeownership increases the share of long term retirement funds along with no effect on risky asset share. The authors observe that the crowding out effect is more striking for younger households and poorer households with low income, and the effect is lower for indebted households.

The findings underscore the need for financial awareness programs so that housing does not crowd out liquid investments of households. Additionally, the results highlight that policies should first focus on young and poor households as the negative effect is more prominent for these groups. Finally, there is scope for policies to support repair and maintenance costs incurred by vulnerable households to reduce the negative effect of housing on liquid financial investments.

This paper is among the few studies that provide insights into how homeownership relates to financial investment and portfolio decisions in the context of an emerging economy. Furthermore, the heterogeneous effects based on poor economic status and age underscore the need for complementary policies.

This study examines whether female directorship on board is related to firm's risk-taking behavior in India.

The study considers the top 500 listed companies in India during the period 2013 to 2018 for the analysis. The paper employs fixed effects as well as a dynamic panel data model to address the bias in the fixed effects model when the lagged risk outcome is included as an explanatory variable.

The study finds that the presence of female directors on board is unrelated to the firm's risk-outcomes and the risk-adjusted return earned by the shareholders. The results are in line with the tokenism theory of board diversity. Having a higher share of female independent directors is also unrelated to the risk-taking behavior of firms. The findings are in contrast to the critical mass theory and the agency theory of gender diversity. The study does not rule out the possibility of female directors' risk-preferences being similar to those of male directors.

The findings suggest that regulations related to having independent female directors may not add value for the shareholders in the short run. The business case for such stringent regulations in India on the gender diversity of boards remains unclear.

This is the first study to analyze the relationship between gender diversity of boards and firm-level risk in India. Most of the studies have focused on gender diversity and firm performance in India. However, modern portfolio theory suggests that both risk and return are important as shareholders care about risk-adjusted returns.

After completion of the case study, the students would be able to comprehend the crisis at hand for Milkbasket, why did it resist Reliance’s takeover in the first place, then to evaluate the pros-cons and future prospects for the organization post-acquisition; to evaluate from an ethical standpoint the process of mergers and acquisitions using ethical frameworks to understand how, when, to whom and through what processes do mergers and acquisitions qualify the test of being ethical; and to analyse different hostile takeovers, especially through tender offers, proxy contests and toehold bidding strategy in this case.

Founded in 2015, Milkbasket was a micro-delivery start-up based in Gurugram (near New Delhi), India. Milkbasket would let its subscribers order till midnight and deliver groceries, milk and other everyday essentials to its subscribers before 7 a.m. next day. It had burnt a lot of cash and was facing difficulty in getting investors; as such they were engaged in discussions with many companies. Two of them – Reliance Retail Venture Limited and BigBasket – were not accepting the proposed valuation, but Milkbasket got term sheets from other two companies.

This case study can be used for graduate courses on strategic management, business ethics and corporate governance. This case study can also be used in corporate finance course to highlight the importance of making ethical/responsible judgements to protect stakeholder interests.

Teaching notes are available for educators only.

CSS 3: Entrepreneurship.

This study compared different types of full-time caregiver (e.g., children, older adults, COVID-19 patients) and subgroups (e.g., disability, race/ethnicity, sexual orientation) in the United States during the COVID-19 pandemic for potentially meaningful distinctions.

Data from the 9,854 full-time caregivers identified in Phase 3.2 (July 21–October 11, 2021) of the US Census Household Pulse Survey (HPS) were analyzed in this study using multinomial logistic regression to examine relationships between caregiver types, marginalized subgroups, generation, and vaccination status.

The prevalence of caregiving was low, but the type of full-time caregiving performed varied by demographic group (i.e., disability, race/ethnicity, sexual orientation, gender, generation, and vaccination status). The relative risk of being a COVID-19 caregiver remained significant for being a member of each of the marginalized groups examined after all adjustments.

To date, the HPS has not been analyzed to predict the type of full-time informal caregiving performed during the COVID-19 pandemic or their characteristics. Research limitations of this analysis include the cross-sectional, experimental dataset employed, as well as some variable measurement issues.

Prior informal caregiver research has often focused on the experiences of those caring for older adults or children with special healthcare needs. It may be instructive to learn whether and how informal caregivers excluded from paid employment during infectious disease outbreaks vary in meaningful ways from those engaged in other full-time caregiving. Because COVID-19 magnified equity concerns, examining demographic differences may also facilitate customization of pathways to post-caregiving workforce integration.

The study aims to facilitate the medical tourists visiting emerging countries for various kinds of ailments by ranking the possible destinations to avail medical treatments.

A Fuzzy Analytical Hierarchical Process (FAHP) with a mixed-method approach is applied to analyze data collected from patients and substantiate it with medical tour operators in India to gain managerial insights on the choice-making patterns of the patients.

India is a preferred emerging market location due to the low cost and high medical staff quality. India offers value for money, whereas Singapore and Thailand are preferred destinations for quality and technology.

The study will facilitate the emerging markets' governments, hospitals and medical tourists to understand the importance of various determinants responsible for availing medical treatment outside their country.

The study recommends that cost and quality care are the patients' prime focus; government policies must provide clear guidelines on what the hospitals and country environment can offer and accordingly align the marketing strategies.

This study is the first attempt to rank various factors affecting medical tourism using the FAHP approach.

To advance Java programming educations, the authors have developed a Web-based Java programming learning assistant system (JPLAS). It offers the element fill-in-blank problem (EFP) for novice students to study Java grammar and basic programming skills by filling in the missing elements in a source code. An EFP instance can be generated by selecting an appropriate code, and applying the blank element selection algorithm. As it is expected to cover broad grammar topics, a number of EFP instances have been generated. This paper aims to propose a recommendation function to guide a student solving the proper EFP instances among them.

This function considers the difficulty level of the EFP instance and the grammar topics that have been correctly answered by the student, and is implemented at the offline answering function of JPLAS using JavaScript so that students can use it even without the Internet connections.

To evaluate the effectiveness of the proposal, 85 EFP instances are prepared to cover various grammar topics, and are assigned to a total of 92 students in two universities in Myanmar and Indonesia to solve them using the recommendation function. Their solution results confirmed the effectiveness of the proposal.

The concept of the difficulty level for an EFP instance is newly defined for the proper recommendation, and the accuracy in terms of the average numbers of answer submission times among the students is verified.