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Organizations are increasingly required to take up extended responsibilities for social and environmental outcomes, including in global value chains. To address these challenges, the organization must call upon stakeholders to engage, contribute, and innovate, and in turn, this requires the organization to have a stronger social basis for its relationships. An integrative model of global value chain management based on social cooperation shifts the focus from corporate reputation to value chain reputation, from a firm-centric view of corporate reputation to a multistakeholder conception of value chain reputation. This approach conceptualizes reputation as a dynamic and potentially vulnerable organizational feature which cannot always be managed by public relations but requires a more stable notion grounded in something more permanent in the organization’s character, history, and the quality of its relationships with stakeholders. We consider the prospects for attending to organizational integrity as a stabilizing force for its public reputation. Integrity may be adopted as a hypernorm for motivating stakeholders who share a concern for the organization’s reputation. Co-creating reputation depends upon a social bond of cooperation developed by stakeholders caring about the organization and in turn, the organization caring about its stakeholders. This socialized understanding of reputation-building is grounded in an ethic of care and manifested through joint purposes, boundary-crossing processes, collaboration practices, and a division of labor into which value chain members are integrated and brought into relation with one another. We propose a model of global value chain management that discusses organizational capabilities required for such an approach.

A number of multidimensional poverty measures that respect the ordinal nature of dimensions have recently been proposed within the counting approach framework. Besides ensuring a reduction in poverty, however, it is important to monitor distributional changes to ensure that poverty reduction has been inclusive in reaching the poorest. Distributional issues are typically captured by adjusting a poverty measure to be sensitive to inequality among the poor. This approach, however, has certain practical and conceptual limitations. It conflicts, for example, with some policy-relevant measurement features, such as the ability to decompose a measure into dimensions post-identification and does not create an appropriate framework for assessing disparity in poverty across population subgroups. In this chapter, we propose and justify the use of a separate decomposable inequality measure – a positive multiple of “variance” – to capture the distribution of deprivations among the poor and to assess disparity in poverty across population subgroups. We demonstrate the applicability of our approach through two contrasting inter-temporal illustrations using Demographic Health Survey data sets for Haiti and India.

This chapter investigates whether and to what extent tax benefits affect the likelihood of firms undertaking leveraged buyout (LBO) transactions.

With an identified sample of LBO firms and similar non-LBO counterparts, this chapter utilizes staggered changes in state corporate income tax rates as exogenous shocks and adopts a Logistic regression to analyze how these tax changes affect firms' probability of engaging in LBOs.

Firms are more likely to engage in LBOs after increases in corporate income tax rates. Specifically, the increase in the likelihood of firms undertaking LBOs following tax increases is between 6.9% and 12.9%. We also find that this positive relation is more pronounced for firms with higher levels of return on assets (ROA) and marginal tax rates (MTR). Finally, we report that the mean value of tax benefits accounts for between 28.5% and 170% of the premium paid to pre-buyout shareholders.

This chapter provides strong evidence that tax benefits constitute an important source of value creation in LBOs and adds to the debate regarding the role of tax benefits in LBOs.

Behavioral finance literature has long claimed that internet stock message boards can move markets. In this chapter, the authors study more than 2,000 internet board messages posted across finance message boards in India (Chittorgarh, etc.) for 110 companies that went for initial public offering (IPO) in the last one year. This study has multi-fold objectives. First, the authors try to identify the factors which lead to a discussion on an IPO stock in the message board. Second, the authors identify the factors which differentiate a widely discussed stock from the less discussed one. Next, the authors apply advanced machine learning technique to identify the topics which are discussed in the message board through automatic topic modeling. The methodology used includes a logistic regression model for identifying firm characteristics which leads to a probability of getting stakeholders’ attention and hence more discussion. The authors also use advanced topic modeling techniques to identify topics of discussion on the message boards through machine learning. The authors find that larger sized firms, younger firms, firms with low leverage, and non-manufacturing firms get discussed more and the topics of discussion relate to their financial statements, trading strategies, stock behavior, and performance.

Exploration of District Level Household Survey 4 data show that among the selected states, Karnataka, West Bengal, Meghalaya, Tripura, Telengana, Arunachal Pradesh and Andhra Pradesh show higher rates of school dropout of girls compared to the all India level. Using multilevel probit technique, the study shows that the incidence of school dropout of girls decreases if the first born of the parents is male and mother is more educated than father while it increases with lower asset endowment, land-holding and high spousal age-gap between parents. Further it is high among the Muslim religion and schedule caste category.

In the era of financial capitalism, how to manage and hold global corporations accountable has become too multifarious a topic for a solitary focus of one theme, to sufficiently outline the whole gamut and implications of their activities. Capitalism is characterized by several well-organized antinomies and contrasts, with reflections of critical dualities that bear a resemblance to the primeval paradoxes of Hellenic philosophy. The challenge of governance of capitalism to be effectual entails breaking out of the entrenched precincts of habitual academic silos. Various standpoints while reasonably informative falls short to explain fully the complex interlinkages between the concept of global governance and the state’s capacity to put into effect its will on corporate power.

Spotlighting on assessing the praxis of political economy at global and national level and the corporate reality, this chapter aims to provide a renewed thrust for the focused recalibration of global regulatory regime. In this chapter, the inquiries take the regulation as the main explanandum for elucidation of the shifting governance framework.

Post reform India has generated high economic growth, yet progress in income poverty and many other key development outcomes has been modest. This chapter primarily examines how inclusive economic growth has been in India between 2005–2006 and 2015–2016 in reducing multidimensional poverty captured by the global multidimensional poverty index (MPI). The authors employ a constellation of elasticity and semi-elasticity measures to examine vertical, horizontal as well as dimensional inclusiveness of economic growth. Nationally, the authors estimate that a 1% annual economic growth in India during their study period is associated with an annual reduction in MPI of 1.34%. The association of the national growth to state poverty reduction (horizontal inclusiveness) is, however, not uniform. Some states have been successful in reducing poverty faster than the national average despite slower economic growth between 2005–2005 and 2015–2016; whereas, other states have been less successful to do so despite faster economic growth during the same period. The authors’ analyses and findings show how these tools may be used in practical applications to measure inclusive growth and inform policy.

We examine whether loan securitization has an impact on bank efficiency. Using a sample of large US commercial banks from 2002 to 2012, we find that bank loan securitization has a significant and positive impact on bank efficiency, and this relationship is stronger for banks with higher capital ratios, higher default risk, and lower level of liquidity and diversification. Our results are robust to Heckman self-selection correction and difference-in-difference (DID) analysis. In addition, these results are found mainly in non-mortgage loan securitizations but not in mortgage loan securitizations. Finally, we show that loan sales also have a positive impact on bank efficiency.

Nonperforming assets in any banking system have stressed the economic health of nations. Resultantly, literature has given considerable impetus to predict failures and bankruptcy. Past studies have focused on the outcome of failures, while, there is a dearth of studies focusing on ongoing firms in bad shape. We plug this gap and attempt to identify underlying communication patterns for firms witnessing prolonged underperformance. Using text mining, we extract and analyze semantic, linguistic, emotional, and sentiment-based features in non-numeric communication channels of these poor-performing firms and their peers. These uncovered patterns highlight the use of vocabulary and tone of communication, in correspondence to their financial well-being. Furthermore, using such patterns, we deploy various Machine Learning algorithms to identify loser firm(s) way ahead in time. We observe promising accuracy over a time window of five years. Such early warning signals can be of critical importance to various stakeholders of a firm. Exploration of writing style-related features for any firm would help its investors, lending agencies to assess the likelihood of future underperformance. Firm management can use them to take suitable precautionary measures and preempt the future possibility of distress. While investors and lenders can be benefitted from this incremental information to identify the likelihood of future failures.