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After a thorough briefing, classroom discussions and de-briefing, the students should be able to appreciate issues of leadership; understand challenges related to managing an organisation; and understand the aspects of organisational politics and power.

This real-life case study is based on a leading management institution of central India. The institute was quite successful in establishing its brand central India during 2011-2017 and is still going strong. The case here captures a change of leadership and the challenges/opportunities it posed to faculty and staff members. The case also intends to address the power struggle that ensued in later years of its functioning. The case is also about how the present leader would finally deal with it all. Students would be able to generate insights in leadership style, power and politics, employee retention, organisational decision-making and concerns in recruiting culturally fit employees.

Graduate level.

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CSS 1: Accounting and Finance

This paper is a first attempt to empirically calibrate the default and asset correlation for large companies in India and elaborate its implications for credit risk capital estimation for a bank.

The authors estimate default probabilities and default correlations of long‐term bonds of 542 Indian corporates using rating transitions and pair‐wise migrations over ten year cohorts of firms. Further, the implicit asset correlation from the estimated default correlations and default thresholds are derived using the asymptotic single risk factor approach.

The authors find evidence that default correlations are time variant and vary across rating grades and industries. The highest correlations are observed between companies within the same rating grades (systematic risk impact) and within the same industry (industry specific impact). More interestingly, significantly smooth monotonic relationship between the probability of default (PD) and asset correlation as prescribed by the Basel II IRB document (2006) are not found. Moreover, it is found that the asset correlation range for Indian corporates do not match with what is prescribed for corporate exposures by BCBS.

The authors address the dilemma implied by the negative relationship between PD and asset correlation as suggested by BCBS IRB formula and other research for developed economies with estimates of asset correlation for and emerging market like India and demonstrate its implications on the estimation of credit risk capital.

The primary objective of the paper is to demonstrate the importance of borrower‐specific characteristics as well as local situation factors in determining the demand prospect as well as the risk of credit loss on residential housing loan repayment behavior in India.

Using 13,487 housing loan accounts (sanctioned from 1993‐2007) data from Banks and Housing Finance Cos (HFCs) in India, this paper attempts to find out the crucial factors that drive demand for housing and its correlation with borrower characteristics using a panel regression method. Next, using logistic regression, housing loan defaults and the major causative factors of the same are examined.

In analyzing the housing demand pattern, some special characteristics of the Indian residential housing market (demographic and social features) and the housing loan facility structure (loan process, loan margin, loan rate, collateral structure etc.), that have contributed to the safety and soundness of the Indian housing market have been deciphered. The empirical results suggest that borrower defaults on housing loan payments is mainly driven by change in the market value of the property vis‐à‐vis the loan amount and EMI to income ratio. A 10 percent decrease in the market value of the property vis‐à‐vis the loan amount raises the odds of default by 1.55 percent. Similarly, a 10 percent increase in EMI to income ratio raises the delinquency chance by 4.50 percent. However, one cannot ignore borrower characteristics like marital status, employment situation, regional locations, city locations, age profile and house preference which otherwise may inhibit the lender to properly assess credit risk in home loan business, as the results show that these parameters also act as default triggers.

This study contributes on the micro side of the housing market in India, since it uses unique and robust loan information data from banks and HFCs. The empirical results obtained in this paper are useful to regulators, policy makers, market players as well as the researchers to understand housing market demand and risk characteristics in an emerging market economy such as India.

This study aims to determine the factors influencing consumers’ organic food purchase intention during Covid-19 and how Covid-19 impacted these factors. Understanding these factors will assist marketers in making strategic decisions on how to market their products during a crisis.

This study used a quantitative approach. Data were collected online from 278 organic food consumers based in India. The partial least squares-path modelling method was used for data analysis.

The results revealed that Covid-19 has substantially impacted consumers' health consciousness, environmental concern, availability, price and intention to buy organic food. This study also revealed that health consciousness, environmental concerns and availability of organic food affect consumers’ purchase intention even during the Covid-19. However, it has been found that price consciousness does not influence consumers’ purchase intention during Covid-19.

Marketers should come up with innovative promotional strategies. Providing information related to quality checks on packages, expanding online sales channels, boosting promotional activities and emphasising the long-term benefits of organic food items should be the go-to marketing strategy of organic food.

The study adds value to the extant literature by examining consumers' purchase intention towards organic food using more customised and thorough constructs that appear to be more practical during the challenging times of Covid-19 and whose findings are not restricted by some pre-established theoretical assumptions.

The purpose of this paper is to develop and test theory-driven hypothesis on trade costs’ effect of logistics performance (LP) and bureaucratic efficiency, primarily from SAARC (South Asian Association for Regional Cooperation) perspective.

The paper develops hypothesis based on the review of the literature and theory linking LP, trade costs and institutions. The authors test the hypothesis using secondary data sources: World Bank-UNESCAP trade costs database, World Bank Logistics Performance Index (LPI) and Political Risk Service's Political Risk Rating. Fixed-effect approach is used to test the hypothesis.

The influential role of bureaucratic quality on relationship between LPI and South Asian trade costs (inter-SAARC and intra-SAARC) is evident. The results also point out that bureaucratic quality also conditions the effect of different dimensions of LPI on South Asian trade costs. Further, it is found that bureaucratic inefficiency mitigates the effects of LPI on South Asia's trade costs with its proximate trading partners APEC (Asia–Pacific Economic Cooperation) and ASEAN (Association of Southeast Asia Nations).

The analysis is conducted using short span of data. With the availability of long span of data, the understanding of the relationship studies in this paper will improve.

The results suggests policymakers to improve bureaucratic efficiency for utilizing the full potential effect of LPI in deceasing trade costs. The study inspires businesses to act and advocate in favor of reforms in governance system.

This paper is among the first, which investigates the possibility that the relationship between LPI and trade costs depends on the bureaucratic efficiency. It provides a more detailed description of the LPI-trade costs relationship.

This study aims to assess housing affordability and estimate demand using a hedonic regression model in the context of Lucknow city, India. This study assesses housing affordability by considering various housing and household-related variables. This study focuses on the impoverished urban population, as they experience the most severe housing scarcity. This study’s primary objective is to understand the demand dynamics within the market comprehensively. An understanding of housing demand can be achieved through an examination of its characteristics and components. Individuals consider the implicit values associated with various components when deciding to purchase or rent a home. The components and characteristics have been obtained from variables relating to housing and households.

A socioeconomic survey was conducted for 450 households from slums in Lucknow city. Two-stage regression models were developed for this research paper. A hedonic price index was prepared for the first model to understand the relationship between housing expenditure and various housing characteristics. The housing characteristics considered for the hedonic model are dwelling unit size, typology, condition, amenities and infrastructure. In the second stage, a regression model is created between household characteristics. The household characteristics considered for the demand estimation model are household size, age, education, social category, income, nonhousing expenditure, migration and overcrowding.

Based on the findings of regression model results, it is evident that the hedonic model is an effective tool for the estimation of housing affordability and housing demand for urban poor. Various housing and household-related variables affect housing expenditure positively or negatively. The two-stage hedonic regression model can define willingness to pay for a particular set of housing with various attributes of a particular household. The results show the significance of dwelling unit size, quality and amenities (R² > 0.9, p < 0.05) for rent/imputed rent. The demand function shows that income has a direct effect, whereas other variables have mixed effects.

This study is case-specific and uses a data set generated from a primary survey. Although household surveys for a large sample size are resource-intensive exercises, they provide an opportunity to exploit microdata for a better understanding of the complex housing situation in slums.

All the stakeholders can use the findings to create an effective housing policy. The variables that are statistically significant and have a positive relationship with housing costs should be deliberated upon to provide the basic standard of living for the urban poor. The formulation of policies should duly include the housing preferences of the economically disadvantaged population residing in slum areas.

This paper uses primary survey data (collected by the authors) to assess housing affordability for the urban poor of Lucknow city. It makes the results of the study credible and useful for further applications.

Estimation of default and asset correlation is crucial for banks to manage and measure portfolio credit risk. The purpose of this paper is to find empirical relationship between the default and asset correlation with default probability, to understand the effect of systematic risk.

The authors have estimated single default and implicit asset correlations for banks and corporates in India and compare it with global scenario. This paper deduces a simple methodology to estimate the default correlations from the variance of temporal default rates. Next, the asset correlations have been estimated analytically by decomposition of variance equation in Merton's one factor risk model following approaches of Gordy and of Bluhm and Overbeck.

The authors empirically find a negative relationship between asset correlation and the probability of default using Moody's global corporate data that support Basel II internal ratings‐based (IRB) correlation prescription. However, they do not find any smooth relationship between the probability of default (PD) and asset correlation for Indian corporate. The magnitude of correlation estimates based on a large bank's internal rating‐wise default rates are much lower than what is prescribed by the Basel committee. Thus, the standardized correlation figures as assumed by the Basel Committee on Banking Supervision need to be properly calibrated by the local regulators before prescribing their banks to calculate IRB risk weighted assets.

These correlation estimates will help the regulators, insurance firms and banks to understand the linkage between counterparty default risks with the systematic factors. The findings of this paper could be used further in estimating portfolio economic capital for large corporate exposures of banks and insurance companies.