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Universities across the USA are facing challenging decision-making problems amid the COVID-19 pandemic. The purpose of this study is to facilitate universities in planning disease mitigation interventions as they respond to the pandemic.

An agent-based model is developed to mimic the virus transmission dynamics on campus. Scenario-based experiments are conducted to evaluate the effectiveness of various interventions including course modality shift (from face-to-face to online), social distancing, mask use and vaccination. A case study is performed for a typical US university.

With 10%, 30%, 50%, 70% and 90% course modality shift, the number of total cases can be reduced to 3.9%, 20.9%, 35.6%, 60.9% and 96.8%, respectively, comparing against the baseline scenario (no interventions). More than 99.9% of the total infections can be prevented when combined social distancing and mask use are implemented even without course modality shift. If vaccination is implemented without other interventions, the reductions are 57.1%, 90.6% and 99.6% with 80%, 85% and 90% vaccine efficacies, respectively. In contrast, more than 99% reductions are found with all three vaccine efficacies if mask use is combined.

This study provides useful implications for supporting universities in mitigating transmissions on campus and planning operations for the upcoming semesters.

An agent-based model is developed to investigate COVID-19 transmissions on campus and evaluate the effectiveness of various mitigation interventions.

Numerous exploratory, conceptual and empirical enquiries on financial behaviour and literacy have been conducted in the areas of economics, finance, business and management. However, no attempt was made to present a comprehensive science mapping of the area so far. Hence, the study intends to elicit the trend in the research field through synthesis of knowledge structures.

Bibliometric analysis in the field of financial literacy and financial behaviour was performed on a sample of 1,138 documents based on a scientific search strategy run on the Web of Science database for the period 1985–2020. Biblioshiny, which is a web-based application included in Bibliometrix package developed in R-language (Ariaa and Cuccurullo, 2017), was used for the study. With the help of automated workflow in the software, prominent journals, authors, countries, articles, themes were identified; and citation, co-citation and social network analysis were conducted.

Results show that the themes of financial literacy and financial behaviour have evolved over a period of time as an interdisciplinary field. In the initial stages, researchers focused on demographic and socio-economic determinants, but gradually the field embraced topics like behavioural and psychological constructs influencing financial behaviour. Along with conceptual structure, this research reveals the intellectual and social structure of the domain. This study provides important insights on areas that need further investigation.

The current research is a bibliometric analysis and hence limitations related to such studies are applicable. For future researchers to derive a strong conceptual framework, a systematic review of literature would be helpful. Science mapping for this study is limited to the Web of Science database owing to its wider coverage of good quality journals, structured formats which are compatible with the Bibliometrix software.

The current study provides important insights on financial literacy and financial behaviour and their inter-linkages. It highlights the most addressed issues in the area and leads towards the prospective areas for research. It informs the future researchers about the emergent themes, contexts and possibilities of collaborations in this area by revealing social and intellectual structure of the domain.

The paper can provide important insights for policy formulation in the areas of financial education and literacy.

There has been lot of conceptual and empirical work done in the past, across countries, spanning the disciplines such as economics, finance, psychology and consumer behaviour. A major contribution of this study is that it consolidates fragmented literature in the area, highlights significant sources, authors and documents, while exploring the relation between financial literacy and financial behaviour.

This paper seeks to examine the relationship between chief executive officer (CEO) turnover and firm performance and the moderating effects of ownership structure and board structure with respect to listed non‐financial companies in Thailand.

Logit model is employed to analyze the relationship between CEO turnover and firm performance.

The paper finds that both ownership and board structure have effects on the relationship between CEO turnover and firm performance. The probability of CEO turnover is lower when the firm is controlled by family, the CEO is part of the controlling family, and board size is larger. Contrary to previous studies, sensitivity of CEO turnover to firm performance is higher with the presence of CEO duality and lower degree of board independence. When a CEO continues to work beyond retirement age, the probability of turnover is not associated with firm performance.

This study provides evidence that CEO duality and low independent board is not necessarily bad corporate governance practice for Thai companies and would be of interest to regulatory bodies, practitioners, and academic researchers.

The purpose of this study is to construct a new index to assess the impact of an energy price shock on macroeconomic indicators of India. This paper also shows a comparative analysis of the constructed index along with pre-existing World Bank and International Monetary Fund indices on energy.

This paper uses three vector autoregressions and compute the long-term impact of the indices on the considered macroeconomic variables through impulse response functions.

This paper finds that an energy price shock has a detrimental impact on the macroeconomic indicators of India in the long run. This study also finds that the constructed index acts as a relatively more sensitive index in comparison to the International Monetary Fund and World Bank indices, which is bespoke to a developing economy case. This sensitivity is ascribed to dynamic weighting for a different basket of energy components, which are more pertinent to an Indian context.

The novelty of this research lies in the construction of a new index and its comparison to the existing ones. This study justifies why a developing economy would require a different measure of energy as opposed to the existing indices.

Tremendous measure of data lakes with the exponential mounting rate is produced by the present healthcare sector. The information from differing sources like electronic wellbeing record, clinical information, streaming information from sensors, biomedical image data, biomedical signal information, lab data, and so on brand it substantial as well as mind-boggling as far as changing information positions, which have stressed the abilities of prevailing regular database frameworks in terms of scalability, storage of unstructured data, concurrency, and cost. Big data solutions step in the picture by harnessing these colossal, assorted, and multipart data indexes to accomplish progressively important and learned patterns. The reconciliation of multimodal information seeking after removing the relationship among the unstructured information types is a hotly debated issue these days. Big data energizes in triumphing the bits of knowledge from these immense expanses of information. Big data is a term which is required to take care of the issues of volume, velocity, and variety generally seated in the medicinal services data. This work plans to exhibit a survey of the writing of big data arrangements in the medicinal services part, the potential changes, challenges, and accessible stages and philosophies to execute enormous information investigation in the healthcare sector. The work categories the big healthcare data (BHD) applications in five broad categories, followed by a prolific review of each sphere, and also offers some practical available real-life applications of BHD solutions.

The case is aimed at providing students with an opportunity to understand various aspects of corporate governance and the consequences of poor corporate governance. The case addresses the following objectives: The students need to assess the role of the board in implementing corporate governance. The students should be able to explain the conflicts experienced by various stakeholders in an organization. The students need to evaluate the balancing act of growth and governance in a startup. The students should be able to determine the current state of business sustainability of the high-growth startups in India.

The case presents the challenges faced by the CEO of BharatPe, Suhail Sameer. Beginning in 2022, Bharatpe was in deep trouble as there were allegations of financial mismanagement, toxic work culture and widening losses. Co-founder Ashneer Grover and his wife Madhuri had to leave the company following charges against them. As Grover was the face of the company, Sameer would have to quickly act on filling the void and reassuring investors. Because of the uncertainty, scores of employees had already quit or were looking for other jobs. Questions were also raised about the board’s inaction and lack of proactive measures. After a meteoric rise for three years, BharatPe was struggling to survive the whole episode and put its focus back on business.

The case is intended for MBA students in corporate governance, organizational behaviour, business ethics and strategic management areas. As the case reveals the impact of poor corporate governance, it can also be used for executive training purposes on corporate sustainability, governance and leadership with a special focus on Indian startups.

Teaching notes are available for educators only.

CSS 11: Strategy.

This paper aims to empirically investigate the evidence of the transmission of monetary policy impulses to firm profitability via manufacturing firms’ short-term and long-term corporate financing decisions.

This study decomposes the receptiveness of firm profitability to monetary policy shock under circumstances of financial flexibility. Additionally, the study extends its scope to undertake a sector-wise analysis of manufacturing firms from 2008 to 2020. Generalized methods of moments (GMM) and quantile regression models are employed.

The profitability of firms in the chemical, food and machinery sector are positively impacted by short-term financing, whereas the metal sector is positively impacted. But during the tight monetary policy, short-term financing does not appear to be a significant parameter while explaining the firms’ profitability. Secondly, the profitability of firms in the consumer goods and metal sector is positively impacted by long-term financing. Therefore, debt financing of assets could be more appropriate to maximize profitability in these sectors.

Analyzing the transmission of monetary policy impulses to firm profitability by clustering firms with financial flexibility across six key manufacturing sectors makes the study unique.

Earlier research on “Hole-in-the-Wall (HiWEL)” conclusively indicated groups of children pick up computer literacy on their own and are adept at performing basic functions such as cut, copy, paste, surf the internet to answer high-end questions. Research also indicates that children self-organize themselves to figure out things which they find difficult and thus learning is a continuous process for them. The studies have also indicated that HiWEL pedagogy is child centric and is at the discretion of the child. Children organize themselves and become self-regulated learners. However, so far no study has been undertaken to determine whether children accessing Hole-in-the-Wall learning stations (HiWEL LSs) can improve in mathematics and English. The intent of the present study is to examine whether groups of children are able to pick up mathematics and English on their own using the learning station. The paper aims to discuss these issues.

In order to study the impact of HiWEL LS on mathematics and English, the authors took two groups; experimental group and control group from six states. Experimental group – 31 children from each site (except for two sites, where experimental group consisted of 30 children) were randomly selected to be a part of the study. 16 children from class 6th and 15 children from class 7th were identified. For this study, the experimental group consisted of a total of 277 children from nine locations. Mathematics and English tests were administered at two time points, pre and post within a gap of six months of installing the learning station. Control group – children that formed the control group were selected from nearby villages with similar socioeconomic background as the experimental group. A total of 135 children (15 children per location) were selected for this study. This group did not have access to HiWEL LS or to any other computers. These children were also tested on the same two tests at two time points, pre and post within a gap of six months.

Children exposed and using HiWEL LSs pick up academic English and mathematics on their own for grade 6th and 7th. These are government school going children. Qualitatively, the teachers and parents feel that they too have seen the benefits in the academic achievement of these children.

The study was done for a six-month period across seven sites. This study should be replicated over across entire India and a bigger sample should be taken for results to be conclusive.

The actual quantity of schooling that underprivileged children experience and the quality of teaching they receive are extremely insufficient. This seems to be true of both the educationally more advanced states and the educationally backward states. These findings suggest a new pedagogy for enabling children to improve their academic performance which in turn leads to improvement in school performance. Thus, for the current educational system, it is important to have alternatives.

So far, no study has been undertaken to determine whether children accessing HiWEL LSs can improve in mathematics and English. The intent of the present study is to examine whether groups of children are able to pick up mathematics and English on their own using the learning station. And, the findings have been positive.

This study aims to assess the risk profile of millennial investors residing in the Delhi NCR region. In addition, the relationship between the risk profile and demographic traits of millennial investors was also analyzed.

Data was collected using a structured questionnaire segregated into two sections. In the first section, millennials were asked questions on socio-demographic factors, and the second section contained ten Likert-type statements to cover the multidimensionality of financial risk. Factor analysis and one-way ANOVA were used to analyze the primary data collected for this study.

The findings indicate that the risk profile of millennials is mainly affected by three factors: risk-taking capacity, risk attitude and risk propensity. Except for educational qualification and occupation, all other demographic features, such as age, gender, marital status, income and family size, seem to significantly influence the factors defining millennials' risk profile.

Uncertainty is inherent in any financial decision, and an investor’s willingness to deal with these variations determines their investment risk profile. To make sound financial decisions, it is mandatory to understand one’s risk profile. The awareness of millennials' distinctive risk profile will come in handy to financial stakeholders because they account for one-third of India’s population, and their financial decisions will shape the financial world for the decades to come.

The purpose of this study is to examine the fiscal sustainability issue by dividing the fiscal deficit into high and low regimes using the quarterly data from 1997: Q1 to 2013: Q3. Further, we obtain the optimum level of public debt at which fiscal sustainability can be achieved.

This study uses the Markov Switching-Vector Error Correction Model (MS-VECM) for examining fiscal sustainability and threshold regression model to obtain the optimum level of debt.

The results derived from MS-VECM reveal the evidence in favor of fiscal sustainability during low fiscal deficit periods. Similarly, using a threshold regression model, the optimum public debt as a percentage to GDP seems to be around 21 per cent on a quarterly basis, beyond this level, public debt hurts economic growth.

From the policy front, the government of India should cut down the fiscal deficit only if debt reaches beyond a threshold level.

Noting that the vast literature has focused on examining the fiscal sustainability in India, the novelty of this study is to examine the fiscal sustainability by considering high and low deficits regimes using a non-linear approach.