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This study aims to examine whether the pay gap between the chief executive officer (CEO) and non-executive employees affects the firm’s research and development (R&D) efficiency.

The dependent variable is the firm’s R&D efficiency, defined as a percentage increase in revenue from a 1-per cent increase in R&D spending. The main independent variable is the CEO-employee pay gap, defined as the ratio of annual total compensation for the CEO to the average of non-executive employees of the firm. The authors estimate fixed-effects models to examine the association between R&D efficiency and the pay gap between CEO and non-executive employees.

Results indicate a negative and significant association between R&D efficiency and CEO-employee pay gap, which suggests that a wider pay gap reduces employee motivation and effort, consistent with pay equity theory. We also find that the CEO-employee pay gap negatively moderates the relationship between employee pay growth and R&D efficiency

Recently enacted pay gap disclosure requirements mandated by the Dodd-Frank Act will make the disparity between CEO and non-executive compensation more salient. This study provides evidence of a firm outcome associated with that disparity.

This study is among the first to investigate the impact of the pay gap on R&D efficiency, a firm outcome not previously explored in the literature. This study also investigates CEO-employee pay gap’s role as a factor that moderates the effects of employee pay growth and institutional ownership on R&D efficiency

This study aims to examine a firm’s disclosure properties subsequent to receiving a going-concern opinion.

A difference-in-difference research design was used to control for endogeneity issues. Annual report readability is used as a proxy for firm disclosure.

The results indicate a negative and significant association between issuance of a going-concern report to a firm and the firm’s readability index in the subsequent year. In other words, after receiving a going-concern opinion, a firm’s annual report exhibits increased readability. The results, when broken into subsamples of surviving and failing firms, are concentrated in the surviving firms.

Prior research has shown that firms change their disclosure properties due to endogenous choices motivated by incentive or exogenous shocks. The results of this study, however, suggest that firms that receive going-concern opinions are incentivized to be more forthcoming in disclosing their financial information.

To the authors’ knowledge, this study is the first to investigate how firms’ general disclosures change subsequent to receiving a going-concern opinion.

This study addresses the issue of decreasing accounting student interest in the specialized taxation discipline. Using survey responses from accounting students around the United States, the authors find that one of the most important influences on the choice of a taxation specialization over other accounting fields is the fascination and interest created as part of the initial taxation course in the student’s undergraduate education. This finding echoes prior research on how to motivate pre-business students toward accounting as a major area of study. The authors find that the challenging nature of the initial tax course and potential differences in future career options do not deter students from taxation. Other driving forces for pursing taxation include perceptions of entry-level and long-term compensation, long-term career opportunities, and having an interesting and challenging career. This study can be of interest to academic institutions, public accounting recruiters, and the accounting profession in general as it highlights the meaningful role each can play in encouraging accounting students to pursue taxation as a profession.

A reliability analysis of a solid oxide fuel cell (SOFC) system is presented for applications with strict constant power supply requirements, such as data centers. The purpose is to demonstrate the effect when moving from a module-level to a system-level in terms of reliability, also considering effects during start-up and degradation.

In-house experimental data on a system-level are used to capture the behavior during start-up and normal operation, including drifts of the operation point due to degradation. The system is assumed to allow replacement of stacks during operation, but a minimum number of stacks in operation is needed to avoid complete shutdown. Experimental data are used in conjunction with a physics-based performance model to construct the failure probability function. A dynamic program then solves the optimization problem in terms of time and replacement requirements to minimize the total negative deviation from a given target reliability.

Results show that multi-stack SOFC systems face challenges which are only revealed on a system- and not on a module-level. The main finding is that the reliability of multi-stack SOFC systems is not sufficient to serve as sole power source for critical applications such as data center.

The principal methodology may be applicable to other modular systems which include multiple critical components (of the same kind). These systems comprise other electrochemical systems such as further fuel cell types.

The novelty of this work is the combination of mathematical modeling to solve a real-world problem, rather than assuming idealized input which lead to more benign system conditions. Furthermore, the necessity to use a mathematical model, which captures sufficient physics of the SOFC system as well as stochasticity elements of its environment, is of critical importance. Some simplifications are, however, necessary because the use of a detailed model directly in the dynamic program would have led to a combinatorial explosion of the numerical solution space.