Search results
1 – 10 of over 21000Monika Causholli and W. Robert Knechel
The purpose of this paper is to examine the circumstances under which high quality audits reduce a firm's cost of debt. The paper extends previous research by Pittman and Fortin…
Abstract
Purpose
The purpose of this paper is to examine the circumstances under which high quality audits reduce a firm's cost of debt. The paper extends previous research by Pittman and Fortin by considering how auditor quality relates to the capital cycle and industry of the firm.
Design/methodology/approach
The paper uses a sample of US initial public offerings (IPOs) from 1986 to 1998 to analyze a firm's debt costs for the five years following the IPO. The paper uses a firm's private age as a proxy for its capital cycle and existing banking relationships to capture the likely extent of debt dependence prior to IPO. The authors separately analyze technology firms from other firms.
Findings
Consistent with prior literature, it is found that firms that are young at the time of an IPO pay higher interest rates and auditor quality plays a significant role in lowering the cost of debt financing. Consistent with the hypotheses made, the authors also observe that the effect of auditor quality is larger for firms in the high tech industry sector. Further, the relationship between auditor quality and age depends on industry, with the benefits of hiring a high quality auditor primarily accruing to younger tech firms and older non‐tech firms.
Originality/value
While the issue of auditor quality and cost of debt has been examined by previous researchers, the additional insight that the effect of auditor quality depends on both capital cycle (age) and industry of a firm, increases understanding of the circumstances under which the audit of financial statements is socially desirable and economically valuable to investors and other stakeholders.
Details
Keywords
The purpose of this study was to examine consumer data acquired by branded prescription drug websites and the ethics of privacy related to the interconnected web of personal…
Abstract
Purpose
The purpose of this study was to examine consumer data acquired by branded prescription drug websites and the ethics of privacy related to the interconnected web of personal information accessed, packaged and resold by tracker technologies.
Design/methodology/approach
The research used the DMI Tracker Tool to collect data on the top 17 branded prescription drug websites, with a specific interest in the tracker technologies embedded in those websites. That data was analyzed using Gephi, an open-source data visualization tool, to map the network of trackers embedded in those branded prescription drug websites.
Findings
Findings visualize the interconnections between tracker technologies and prescription drug websites that undergird a system of personal data acquisition and programmatic advertising vehicles that serve the interests of prescription drug marketers and Big Tech. Based on the theory of platform ethics, the study demonstrated the presence of a technostructural ecosystem dominated by Big Tech, a system that goes unseen by consumers and serves the interests of advertisers and resellers of consumer data.
Research limitations/implications
The 17 websites used in this study were limited to the top-selling prescription drugs or those with the highest ad expenditures. As such this study is not based on a random sampling of branded prescription drug websites. The popularity of these prescription drugs or the expanse of advertising associated with the drugs makes them appropriate to study the presence of tracking devices that collect data from consumers and serve advertising to them. It is also noted that websites are dynamic spaces, and some trackers within their infrastructures are apt to change over time.
Practical implications
Branded prescription drug information has over the past three decades become part of consumers’ routine search for information regarding what ails them. As drug promotion moved from print to TV and the Web, searching for drug information has become a part of everyday life. The implications of embedded trackers on branded prescription drug websites are the subject of this research.
Social implications
This study has significant social implications as consumers who are searching for information regarding prescription medications may not want drug companies tracking them in a way that many perceive to be an invasion of privacy. Yet, as the Web is dominated by Big Tech, web developers have little choice but to remain a part of this technostructural ecosystem.
Originality/value
This study sheds light on branded prescription drug websites, exploring the imbalance between the websites under study, Big Tech and consumers who lack awareness of the system that operates backstage.
Details
Keywords
This case is designed to enable students to understand the role of women in artificial intelligence (AI); understand the importance of ethics and diversity in the AI field;…
Abstract
Learning outcomes
This case is designed to enable students to understand the role of women in artificial intelligence (AI); understand the importance of ethics and diversity in the AI field; discuss the ethical issues of AI; study the implications of unethical AI; examine the dark side of corporate-backed AI research and the difficult relationship between corporate interests and AI ethics research; understand the role played by Gebru in promoting diversity and ethics in AI; and explore how Gebru can attract more women researchers in AI and lead the movement toward inclusive and equitable technology.
Case overview/synopsis
The case discusses how Timnit Gebru (She), a prominent AI researcher and former co-lead of the Ethical AI research team at Google, is leading the way in promoting diversity, inclusion and ethics in AI. Gebru, one of the most high-profile black women researchers, is an influential voice in the emerging field of ethical AI, which identifies issues based on bias, fairness, and responsibility. Gebru was fired from Google in December 2020 after the company asked her to retract a research paper she had co-authored about the pitfalls of large language models and embedded racial and gender bias in AI. While Google maintained that Gebru had resigned, she said she had been fired from her job after she had raised issues of discrimination in the workplace and drawn attention to bias in AI. In early December 2021, a year after being ousted from Google, Gebru launched an independent community-driven AI research organization called Distributed Artificial Intelligence Research (DAIR) to develop ethical AI, counter the influence of Big Tech in research and development of AI and increase the presence and inclusion of black researchers in the field of AI. The case discusses Gebru’s journey in creating DAIR, the goals of the organization and some of the challenges she could face along the way. As Gebru seeks to increase diversity in the field of AI and reduce the negative impacts of bias in the training data used in AI models, the challenges before her would be to develop a sustainable revenue model for DAIR, influence AI policies and practices inside Big Tech companies from the outside, inspire and encourage more women to enter the AI field and build a decentralized base of AI expertise.
Complexity academic level
This case is meant for MBA students.
Social implications
Teaching Notes are available for educators only.
Subject code
CCS 11: Strategy
Details