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The purpose of this study is to investigate the relationship between African–American undergraduate students, racial microaggressions (RMAs) and college retention rates.

Data were obtained from a survey given out to African–American undergraduate students, recruited from a large, midwestern, predominantly white public university (n = 53).

The results indicate that students did experience a wide range of microaggressions. Furthermore, the data revealed a statistically significant relationship between the participants’ perceptions that others viewed them as if they were foreigners and did not belong to the place and the participants’ thoughts about dropping out during the ongoing semester [r(51) = 0.338, p = 0.05]. The results suggest that African–Americans frequently experience RMAs while on campus but these experiences are not significantly tied to their intentions to complete the ongoing semester or return for the subsequent semester.

This study shows that African–American students felt disconnected from the campus that they attend. This information may allow for faculty and staff members to assist in making students feel more welcomed and included in the classroom and on campus.

This is one of the few studies to provide evidence of the relationships between African–American undergraduate students, RMAs and college retention rates. In addition, most studies looking at the relationship between RMAs and retention are qualitative in nature. The use of a quantitative approach helps us eliminating possible observer bias and increasing sample size.

The purpose of this paper is to analyze the impact of firm-level corporate governance practices on the riskiness of a firm's stock returns.

The authors constructed an index of governance quality incorporating best practices stipulated by regulators. The authors employed regression analysis.

The empirical evidence, using an index of corporate governance, shows that well-governed New Zealand firms experience lower levels of risk, ceteris paribus. In particular, the results indicate that corporate governance aspects such as board composition, shareholder rights, and disclosure practices are associated with lower levels of risk.

A limitation of the study is that the corporate governance index constructed is somewhat arbitrary and due to limitation of data availability the authors may have excluded some factors such as share trading policy of directors and policies regarding provision of non-auditing services by auditors. The research supports the view that institutional context could have an impact on governance outcomes. The work has three implications for managers, investors, and policy makers. First, the results imply that well-governed firms have lower idiosyncratic risk and that this reduction is most likely due to the reduction in agency costs and information risk. Second, in the absence of features like an active corporate control market and stock option based managerial compensation, managers have little incentives to take on risky projects that increase firm value. Third, the results suggest that the managers of well-governed firms are not more risk averse with respect to investment decisions compared to poorly governed firms.

The work has practical implications for managers, investors, and policy makers. Well-governed firms face lower variability in stock returns compared to poorly governed firms. Firms that have independent boards that protect its shareholders’ rights and disclose its governance-related policies experience lower firm-level risk, other things being equal.

This study is the first one to examine the impact of a composite measure of corporate governance quality on stock return variability in a non-US setting. The results suggest that firms can use specific corporate governance provisions to mitigate firm-level risk. The findings of the paper are therefore relevant and useful to corporate managers, investors, and policy makers.

Partner firms to the same joint venture experience sharply different stock price reactions. These differences cannot be explained by mechanical factors related to differences in firm size and ownership share in the project, nor are they attributable to different partner roles in the project or differences in investor anticipation of the announcement. We conclude that the stock price reactions reflect a revaluation of non-project assets that is different for each partner. Additionally, we find evidence indicating that investors infer information about agency problems (in the sense of Jensen, 1986) from the joint venture announcements and subsequently, revalue the whole firm – not just the marginal project being announced. Finally, we find that free cash flow is value-enhancing for one type of partner firm after we control for the extent of agency problems.

The purpose of this paper is to develop a framework for utilizing Six Sigma (SS) principles and Big Data analytics at a US public university for the improvement of student success. This research utilizes findings from the Gallup index to identify performance factors of higher education. The goal is to offer a reimagined SS DMAIC methodology that incorporates Big Data principles.

The authors utilize a conceptual research design methodology based upon theory building consisting of discovery, description, explanation of the disciplines of SS and Big Data.

The authors have found that the interdisciplinary approach to SS and Big Data may be grounded in a framework that reimagines the define, measure, analyze, improve and control (DMAIC) methodology that incorporates Big Data principles. The authors offer propositions of SS DMAIC to be theory tested in subsequent study and offer the practitioner managing the performance of higher education institutions (HEIs) indicators and examples for managing the student success mission of the organization.

The study is limited to conceptual research design with regard to the SS and Big Data interdisciplinary research. For performance management, this study is limited to HEIs and non-FERPA student data. Implications of this study include a detailed framework for conducting SS Big Data projects.

Devising a more effective management approach for higher education needs to be based upon student success and performance indicators that accurately measure and support the higher education mission. A proactive approach should utilize the data rich environment being generated. The individual that is most successful in engaging and managing this effort will have the knowledge and skills that are found in both SS and Big Data.

HEIs have historically been significant contributors to the development of meritocracy in democratic societies. Due to a variety of factors, HEIs, especially publicly funded institutions, have been under stress due to a reduction of public funding, resulting in more limited access to the public in which they serve.

This paper examines Big Data and SS in interdisciplinary effort, an important contribution to SS but lacking a conceptual foundation in the literature. Higher education, as an industry, lacks penetration and adoption of continuous improvement efforts, despite being under tremendous cost pressures and ripe for disruption.

This study aims to identify critical online teaching effectiveness factors from instructors’ perspectives and experiences during COVID-19.

This study used a qualitative phenomenology approach. In addition, the research used a snowball sample to identify faculty in the engineering and engineering technology fields with experience in online teaching and learning. All interviews were conducted online by the researchers. The interview questions were based on findings in the current literature. Further, the questions were open-ended.

The analysis identified eight major themes that impact online teaching effectiveness: class recordings; course organization; collaboration; engagement; exam, assignment and quiz grades; games; valuable course content; and student timely feedback and response.

The study was not designed to be generalizable to the entire population of professors who teach online classes but to gain insights from faculty who taught online courses during the COVID-19 pandemic.

Faculty can use the factors identified for online teaching effectiveness to enhance their course design and delivery while teaching online or blended courses.

This research provides insights into factors that impact online teaching effectiveness during the COVID-19 pandemic.

Teaching effectiveness is essential to student learning, engagement and success. This study aims to identify the perceived teaching effectiveness attributes from the student’s perspective through a pilot study.

A comprehensive literature review identified 6 demographic and 25 teaching effectiveness characteristics. The Kano model was used to gather and analyze the student’s voices. The research validated the survey instrument using Cronbach’s alpha to ensure internal consistency and Chi-square goodness of fit to test the data distribution. Differences in response patterns were analyzed using Fisher’s exact test. Furthermore, the magnitude of the effect between the teaching effectiveness attributes was determined using Cramer’s V test.

This study determined that students perceived 19 attributes as one-dimensional, 3 as indifferent, 2 as attractive and 1 as one-dimensional and attractive. The analysis found differences in response patterns concerning readings and materials, grading rubrics to set assignment expectations and group/teamwork on projects.

As a pilot study, the sample size was small. Additional research should validate the survey using a larger sample. While the study results are specific to the college surveyed, other educators can use the methodology to identify the attributes important to their students.

Categorizing attributes based on the student’s voice enables instructors to focus on attributes that will improve the learning experience.

This research provides a comprehensive methodology for identifying critical teaching effectiveness attributes from the student’s perspective.

We identify a novel concept of discretionary idiosyncratic volatility proxied by the idiosyncratic volatility component not related to the non-systematic industry volatility as a source of agency problems that have implications for firms’ cash holdings and their investment decisions. We find that firms with low discretionary idiosyncratic volatility, which likely captures discretionary effort and risk-taking by managers, have smaller cash reserves. Moreover, while high discretionary idiosyncratic volatility firms spend cash internally (internal capital building), low discretionary idiosyncratic volatility firms use it for external acquisitions, consistent with the “quiet life” hypothesis. Our findings thus indicate a need for reinforcement of existing regulations and corporate laws to control for agency costs, which could in turn reduce firm risk and the probability of financial meltdown at the aggregate level.