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Deregulation shifts the responsibility for mitigation of agency problems from the regulatory parties to the firms' shareholders. We investigate whether and how governance structure changes in response to the dynamics of the new business environment after the Regulatory Reform Act of 1994 for the US trucking industry. We show that deregulation increases market competition in the trucking industry. The deregulated trucking firms not only adjust internal governance structure but also alter antitakeover provisions to adapt themselves to the competitive status of business environment after deregulation.

The purpose of this paper is two‐fold. First, a case study is presented that examines a model of agricultural development created by Healing Hands International (HHI) as one answer to the United Nations' Food and Agriculture Organization call to reduce world hunger in half by 2015. Second, the study of HHI's agricultural model is used to identify some of the variables that might predict success in achieving sustainable agricultural systems in developing communities around the world. Specifically, training and establishing trust through social networks are explored as potential indicators in which HHI and other non‐governmental organizations (NGOs) can better determine whether they are meeting the goal of making trade work for the poor.

A case study of HHI's agricultural program is conducted as a means to identify success criteria for similar programs designed to establish economic viability in developing countries.

HHI has received global attention for its success in establishing long‐term economic viability in impoverished communities. Through the examination of their four‐step approach to agricultural development, two variables were identified as potential indicators of success that may generalize to similar programs: training and establishing trust through social networks.

There are currently over 40,000 NGOs operating to develop sustained economic viability for developing countries; however, a state of crisis continues to exist. As such, identifying predictors of success is essential for ensuring the successful implementation of similar programs and providing evidence that can result in greater financial support.

The paper examines the impact of market power on wages within the context of a developing country, focusing on Brazil.

With access to matched employer–employee data from Brazil, we first characterized the evolution of the local labor market concentration (Municipality Herfindahl–Hirschman Index [HHI]). Then, we built a fixed-effect model with instrumental variables to verify the association between the local labor market concentration and wages. Finally, a difference-in-difference (DiD) was implemented to verify whether a merger transaction impacted the workers’ earnings in the Brazilian banking sector.

The paper’s findings suggest that there may be a negative relationship between market power and workers’ earnings.

This research conducted an in-depth investigation of the labor market power in a developing country. As far as we know, our work is the first to evaluate the extension of local concentration in Brazilian formal labor markets and to illustrate its evolution over the last decades. Additionally, when going through the effects of market concentration on wages, we use a new identification strategy that explores changes in the HHI that are caused by national trends in an industry as a source of exogenous variation. Finally, the last part of the paper assesses the effects of antitrust policy on the labor market, a kind of investigation that is still scarce.

This study examines whether dividend payout, an internal corporate governance mechanism, is a substitute for or an outcome of product market competition, an external corporate governance mechanism. The sample includes firms in six of the world’s most prominent economies. We find that firms in more competitive industries pay less in the way of dividends to their shareholders, which is consistent with the notion that dividends and competition are substitutes. We also determine that the above negative relationship is weaker in countries with stronger regulation protecting minority shareholders against corporate self-dealing. Furthermore, the relationship has attenuated following the passage of the Sarbanes-Oxley Act that increased regulation and enhanced governance standards. Collectively, our findings provide consistent evidence across countries that the two corporate governance mechanisms examined in the study are substitutes, and greater regulation weakens the substitution effect. Our empirical findings are robust to alternative measures of dividend payout, industry definition, and shareholder protection.

Academic research has intensively analyzed the relationship between market concentration or market power and banking stability but provides ambiguous results, which are summarized under the concentration-stability/fragility view. We provide empirical evidence that the mixed results are due to the difficulty of identifying reliable variables to measure concentration and market power.

Using data from 3,943 banks operating in the European Union (EU)-15 between 2013 and 2020, we employ linear regression models on panel data. Banking market concentration is measured by the Herfindahl–Hirschman Index (HHI), and market power is estimated by the product-specific Lerner Indices for the loan and deposit market, respectively.

Our analysis reveals a significantly stability-decreasing impact of market concentration (HHI) and a significantly stability-increasing effect of market power (Lerner Indices). In addition, we provide evidence for a weak (or even absent) empirical relationship between the (non)structural measures, challenging the validity of the structure-conduct-performance (SCP) paradigm. Our baseline findings remain robust, especially when controlling for a likely reverse causality.

Our results suggest that the HHI may reflect other factors beyond market power that influence banking stability. Thus, banking supervisors and competition authorities should investigate market concentration and market power simultaneously while considering their joint impact on banking stability.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to examine whether media richness (MR), human-system interaction (HSI) and human-human interaction (HHI) as technological feature antecedents to medical professionals’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs).

Sample data for this study were collected from medical professionals at six university-/medical university-affiliated hospitals in Taiwan. A total of 600 questionnaires were distributed, and 309 (51.5%) usable questionnaires were analyzed using structural equation modeling in this study.

This study certified that medical professionals’ perceived MR, HSI and HHI in MOOCs positively affected their emotional LE, cognitive LE and social LE elicited by MOOCs, which together explained their LP in MOOCs. The results support all proposed hypotheses and the research model accounts for 84.1% of the variance in medical professionals’ LP in MOOCs.

This study uses the S-O-R model as a theoretical base to construct medical professionals’ LP in MOOCs as a series of the psychological process, which is affected by MR and interaction (i.e. HSI and HHI). Noteworthily, three psychological constructs, emotional LE, cognitive LE and social LE, are adopted to represent medical professionals’ organisms of MOOCs adoption. To date, hedonic/utilitarian concepts are more commonly adopted as organisms in prior studies using the S-O-R model and psychological constructs have received lesser attention. Hence, this study enriches the S-O-R model into an invaluable context, and this study’s contribution on the application of capturing psychological constructs for completely explaining three types of technological features as external stimuli to medical professionals’ LP in MOOCs is well-documented.

We are interested in modeling the impact of spatial and interindustry dependence on firm-level innovation of Chinese firms The existence of network ties between cities imply that changes taking place in one city could influence innovation by firms in nearby cities (local spatial spillovers), or set in motion a series of spatial diffusion and feedback impacts across multiple cities (global spatial spillovers). We use the term local spatial spillovers to reflect a scenario where only immediately neighboring cities are impacted, whereas the term global spatial spillovers represent a situation where impacts fall on neighboring cities, as well as higher order neighbors (neighbors to the neighboring cities, neighbors to the neighbors of the neighbors, and so on). Global spatial spillovers also involve feedback impacts from neighboring cities, and imply the existence of a wider diffusion of impacts over space (higher order neighbors).

Similarly, the existence of national interindustry input-output ties implies that changes occurring in one industry could influence innovation by firms operating in directly related industries (local interindustry spillovers), or set in motion a series of in interindustry diffusion and feedback impacts across multiple industries (global interindustry spillovers).

Typical linear models of firm-level innovation based on knowledge production functions would rely on city- and industry-specific fixed effects to allow for differences in the level of innovation by firms located in different cities and operating in different industries. This approach however ignores the fact that, spatial dependence between cities and interindustry dependence arising from input-output relationships, may imply interaction, not simply heterogeneity across cities and industries.

We construct a Bayesian hierarchical model that allows for both city- and industry-level interaction (global spillovers) and subsumes other innovation scenarios such as: (1) heterogeneity that implies level differences (fixed effects) and (2) contextual effects that imply local spillovers as special cases.

This research addresses the question of whether market competition influences a firm's implicit tax burden. Implicit taxes are defined as the pretax rate of return disadvantage earned on an investment that is taxed preferentially. The Scholes and Wolfson (1992) model predicts that implicit taxes will fully offset any benefit from preferential tax treatment leading to no benefit from lower explicit taxes; however, their theory assumes perfect market competition. This chapter relaxes the assumption of perfect market competition and finds that firms in industries with lower competition bear lower implicit taxes and firms in industries with higher competition bear higher implicit taxes. These findings are consistent with monopoly and oligopoly behavior predictions where firms in less competitive industries have greater price setting power and can retain more of their tax savings while market forces in competitive industries force companies to pass along any savings to customers (Mason, 1939). Furthermore, these findings answer the call in the literature for more research on determinants of cross-sectional variation in implicit taxes (Shackelford & Shevlin, 2001).

Professional sports teams employ highly paid managers and coaches to train players and make tactical and strategic team decisions. A large literature analyzes the impact of manager decisions on team outcomes. Empirical analysis of manager decisions requires a quantifiable proxy variable for manager decisions. Previous research focused on manager dismissals, tenure on teams, the number of substitutions made in games or the number of healthy players on rosters held out of games for rest, generally finding small positive impacts of manager decisions on team success.

The authors quantify manager decisions by developing a novel measure of game-specific coaching decisions: the Herfindahl–Hirschman Index (HHI) of playing-time across players on a team roster over the course of a season.

Evidence from two-way fixed effects regression models explaining observed variation in National Basketball Association team winning percentage over the 1999–2000 to 2018–2019 seasons show a significant association between managers’ allocation of playing time and team success. A one standard deviation change in playing-time HHI that reflects a flattened distribution of player talent is associated with between one and two additional wins per season, holding the talent of players on the team roster constant. Heterogeneity exists in the impact across teams with different player talent.

This is one of the first papers to examine playing-time concentration in the NBA. The results are important for understanding how managerial decisions about resource allocation lead to sustained competitive advantage. Linking coaching decisions to wins can help teams to better promote this core product.