10178 research outputs found
Sort by
Gender and Engagement Partner Quality
No full textPurpose
The purpose of this study is to examine whether the gender of an audit engagement partner (EP) is associated with the quality of the EP’s audit output. Design/methodology/approach
This paper defines a low-quality EP as an EP who leads the audit of at least one client firm that subsequently restates its financial statements, while a high-quality EP is an EP that is not associated with any restatement. Using a sample of 6,082 observations from 2016 to 2020, the study estimates a logistic regression of EP quality on EP gender and control variables. Findings
The results show that female EPs are more likely to be high-quality EPs. With an odds ratio of 1.25, the results imply that female EPs are 1.25 times more likely to be associated with higher-quality audits compared to male EPs. Research limitations/implications
The results of this study imply that female EPs are more likely to perform high-quality audits, and it supports the assertion that EP gender plays a significant role in determining EP quality. Further studies may apply gender theory to investigate the behavior of female EPs. Practical implications
The results show that female EPs are more likely to be high-quality EPs. With an odds ratio of 1.25, the results imply that female EPs are 1.25 times more likely to be associated with higher-quality audits compared to male EPs. Originality/value
The results of this study should be of interest to stakeholders such as audit committees, regulators, investors and creditors, as they provide an indicator for assessing the quality of audits. Moreover, considering the EP’s important role in an audit, the current study extends the existing literature by providing evidence of a relationship between EP gender and EP quality
AI Chatbots in Education: A Comparative Analysis at Bryant University
No full textArtificial Intelligence (AI) has been making significant strides in various sectors, and education is no exception. AI chatbots, in particular, have been gaining popularity for their potential to enhance teaching, learning, research, and administrative tasks. A recent survey conducted at Bryant University reveals an interesting trend: while students and faculty are increasingly adopting AI chatbots, staff members seem to lag behind. This guest blog post delves into the possible reasons behind this disparity using the 77 faculty, 111 staff, and 224 student responses collected between November 2023 and February 2024. A full survey report will be published on the Bryant University website at a later date. Bryant University is participating in Ithaka S+R’s cohort project, Making AI Generative for Higher Education
Kwon, H. (2024) Language Brokers: Children of Immigrants Translating Inequality and Belonging for Their Families. Stanford University Press.
Get PDF
