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The purpose of this paper is to inform scholars and practitioners about the current body of knowledge on the role of social capital in scaling social impact since these concepts are still poorly understood and literature is fragmented despite their importance.

A systematic literature review of 27 highly relevant studies in leading journals is conducted, and the results are synthesized into an integrative theoretical framework.

The framework identifies possible dependent, independent, mediating and moderating variables which conceptualize the role of social capital in scaling social impact.

To the best of the authors’ knowledge, this is the first study to systematically map social capital’s role in scaling social impact literature with the help of an integrative theoretical framework. For researchers, this framework would help by providing a shared frame of reference to conceptualize the role of social capital in scaling social impact and identify future research directions. Practitioners can use the findings of this review as a guide while designing and implementing scaling social impact programs.

The purpose of this paper is to explore and advance on existing knowledge regarding supply chain integration (SCI) and absorptive capacity (AC). On the one hand, new elements, such as high-performance human resource practices (HPHRP) and internal integration (II) are proposed to foster AC within the supply chain. On the other hand, the study proposes a model and hypotheses to analyze the moderating effect of AC on the relationship between external SCI and supply chain performance.

Four hypotheses are formulated based on relevant literature. Data were collected from the horticultural marketing sector, using two different sources, a survey and archival data. A total of 99 responses were analyzed. Hierarchical multiple regressions were carried out to test the proposed hypotheses.

The results confirm that HPHRP are a crucial element when trying to increase the level of AC. In addition, the results show that AC has a moderating effect on the relationship between SCI and supply chain performance (both economic and financial). AC moderates the relationship between customer integration and economic performance.

This study examines the potential causes for the differences that exist in a firm’s ability to develop AC. Thus, on the one hand, HPHRP and II are proposed as triggers of AC, and on the other, AC is proposed as a moderator in the relationship between SCI and performance.

Researchers in economics and other disciplines are often interested in the causal effect of a binary treatment on outcomes. Econometric methods used to estimate such effects are divided into one of two strands depending on whether they require unconfoundedness (i.e., independence of potential outcomes and treatment assignment conditional on a set of observable covariates). When this assumption holds, researchers now have a wide array of estimation techniques from which to choose. However, very little is known about their performance – both in absolute and relative terms – when measurement error is present. In this study, the performance of several estimators that require unconfoundedness, as well as some that do not, are evaluated in a Monte Carlo study. In all cases, the data-generating process is such that unconfoundedness holds with the ‘real’ data. However, measurement error is then introduced. Specifically, three types of measurement error are considered: (i) errors in treatment assignment, (ii) errors in the outcome, and (iii) errors in the vector of covariates. Recommendations for researchers are provided.

This is a survey paper of the recent literature on the application of semiparametric–econometric advances to testing for functional form of the environmental Kuznets curve (EKC). The EKC postulates that there is an inverted U-shaped relationship between economic growth (typically measured by income) and pollution; that is, as economic growth expands, pollution increases up to a maximum and then starts declining after a threshold level of income. This hypothesized relationship is simple to visualize but has eluded many empirical investigations. A typical application of the EKC uses panel data models, which allows for heterogeneity, serial correlation, heteroskedasticity, data pooling, and smooth coefficients. This vast literature is reviewed in the context of semiparametric model specification tests. Additionally, recent developments in semiparametric econometrics, such as Bayesian methods, generalized time-varying coefficient models, and nonstationary panels are discussed as fruitful areas of future research. The cited literature is fairly complete and should prove useful to applied researchers at large.

Energy efficiency is critical for global sustainability (International Energy Agency, 2019). The purpose of this paper is to examine how agency conflicts arising from pyramidal ownership structures impact the energy intensity (EI) of group-affiliated Indian firms. Group-affiliated firms face unique governance challenges. For instance, parent owners (promoters) may transfer profits from one group-affiliated firm to another firm in which they have greater ownership. The authors hypothesize that such governance issues will lead to underinvestment in energy-saving projects among group firms in which promoters have a low ownership stake, resulting in their greater EI.

The authors measure EI as the ratio of total energy expense to total sales revenue (EI) and as the industry-adjusted version of this ratio. Group-affiliated Indian firms are divided into high- and low-stake firms based on the sample’s median promoter ownership.

Results support the authors’ prediction: group firms in which promoters have low ownership are more energy intensive, consistent with these firms being exposed to greater governance challenges and agency conflicts that result in operating inefficiencies and/or underinvestment in energy-saving projects.

Given energy efficiency will be key in addressing climate change, this study could raise awareness among activists, motivate regulators to consider agency problems among group-affiliated firms in emerging markets and may underscore the importance of environmental-related corporate disclosures.

To the best of the authors’ knowledge, this study is the first to identify the significant impact that firm ownership structure and associated governance challenges have on corporate EI.

In light of the ever-growing complexity of real estate transactions, the need for vendors and buyers to better understand the role of vendor due diligence (VDD) is imperative. The purpose of this paper is twofold: firstly, it provides a detailed literature review regarding the role of VDD from both the vendor's and buyers' perspectives. Secondly, it analyses the value of VDD over and above the buyer's due diligence (BDD) in real estate transactions by proposing a theoretical model involving two-stage auctions.

Real-world examples from the industry are used as a motivation behind listing a set of practical questions. A theoretical construct is built to approximate the real estate environment under study. The construct is then studied from a game-theoretic perspective to obtain theoretical answers to the questions. These answers are then used to shape recommendations for the relevant industry and beyond.

The model suggested accommodates the feature that even though the VDD is broadly increasing informational efficiency in the market, its value is limited and sometimes harmful when the vendors have a sound prior understanding of their assets and the buyers' pre-transaction information about the asset is already high.

Though the real estate market is considered here, the theoretical model we propose is applicable to any other complex asset transaction decision that supports endogenous information disclosure considerations using VDD.

Biotech companies stand as key actors in pharmaceutical innovation. The high risk and long timelines inherent with their R&D investments might hinder their access to funding, potentially stifling innovation. This study aims to explore into the appeal of biotech companies to capital market investors, whose financial backing could bolster the growth of the biotechnology sector.

This paper uses a dataset of 774 US publicly listed biotech firms to investigate their risk and return characteristics by comparing them to pharmaceutical firms and a sample of matched non-biotech R&D-intensive firms over the sample period 1980–2021. Tests show that the conclusions remain consistent across diverse methodological approaches.

The paper shows that biotech companies are riskier than the average firm in the market index but outperform on a risk-adjusted basis both the market and a matched group of R&D-intensive firms. This is particularly true for large capitalization biotech, which is also shown to provide a diversification benefit by reducing the downside risk in past crisis periods.

This paper provides insight relevant to the current debate about the overall performance of the biotech industry in terms of policy changes and their impact on small, early-stage biotech firms. While small and early-stage biotech firms are playing an increasing role in scientific innovation, this study confirms their greater vulnerability to financial risks and the importance of access to capital markets in enabling those companies to survive and evolve into larger biotech.

The purpose of this paper is to obtain a comprehensive structure of past empirical studies on financial contagion which can provide the present growth and future scope of research work on the field of contagion analysis.

Present study identifies 151 empirical studies on financial contagion and summarises all the studies on the basis of tools and methodology used, year of the studies, origin of the studies, sample period and sample countries taken, studies undertaken on the basis of different crisis period and markets considered and finally sources of the studies.

The results of the analysis show that the empirical studies on contagion increased continuously over the past five years. Higher order test of contagion with more number of sample countries may provide more accurate picture on financial contagion.

This paper collects, classifies and summarises past empirical studies on financial contagion and provides valuable conclusion on present growth and future scope of studies on financial contagion. The information given in this paper can be helpful for future researchers and academicians on this particular field; the summary of the conclusion (from past reviews) may be helpful for the policy makers for asset allocation and risk management.

This study examines the effect of firm-level investor sentiment on a firm's level of financial distress.

The authors use Bloomberg's firm-level, daily investor sentiment scores derived from firm-level news and Twitter content in a beta-regression model to explain the variability in a firm's financial distress.

The results indicate that improvements (deterioration) in investor sentiment derived from both news articles and Twitter content lead to a decrease (increase) in the average firm's financial distress level. We also find that the effect of sentiment derived from Twitter on a firm's financial distress is significantly stronger than the sentiment derived from news articles.

Our proxy for financial distress is Bloomberg's financial distress measures, which may be an imperfect measure of financial distress. Our results have important implications for market participants in assessing the determinants of financial distress.

Our sample period covers four years (2015–2019), which is determined by Bloomberg sentiment data availability.

Market participants are increasingly using social media to express views on firms and seek information that might be used to determine a firm's level of financial distress. Our study links investor sentiment derived from social media (Twitter) and traditional news articles to financial distress.

By examining the relationship between a firm's sentiment and its financial distress, this paper advances our understanding of the factors that drive a firm's financial distress. To our knowledge, this is the first study to link US firms' investor sentiment derived from firm-level news and Twitter content to a firm's financial distress.