EXPRESS: The Bulletproof Glass Effect: Unintended Consequences of Privacy Notices

Drawing from a content analysis of publicly-traded companies’ privacy notices, a survey of managers, a field study, and five online experiments, this research investigates how consumers respond to privacy notices. A privacy notice, by placing legally-enforceable limits on a firm’s data practices, communicating safeguards, and signaling transparency, might be expected to promote confidence that personal data will not be misused. Indeed, most managers expected a privacy notice to make customers feel more secure (Study 1). Yet, consistent with the analogy that bulletproof glass can increase feelings of vulnerability despite the protection offered, formal privacy notices undermined consumer trust and decreased purchase interest even when they emphasized objective protection (Studies 2, 3, and 5) or omitted any mention of potentially concerning data practices (Study 6). These unintended consequences did not occur, however, when consumers had an a priori reason to be distrustful (Study 4) or when benevolence cues were added to privacy notices (Studies 5-6). Finally, Study 7 showed that both the presence and conspicuous absence of privacy information are sufficient to trigger decreased purchase intent. Together, these results provide actionable guidance to managers on how to effectively convey privacy information (without hurting purchase interest).

Relationship Between Free Cash Flows and Corporate Governance Levels in the Light of Agency Theory

This research analyzes the relationship between free cash flows (FCFs) and the different levels of Corporate Governance present in the Brazilian stock market. To this end, the sample was composed of 212 Brazilian publicly traded companies listed on Brasil, Bolsa, Balcão [B]³, in the period from 2010 to 2018. The methodology consisted of estimating a regression for panel data, using the random effects model, estimating by generalized least square (GLS) and assuming adjustments for autocorrelation and robust standard errors for heteroscedasticity. The results found, for the sample studied, suggest that Corporate Governance levels are positively related to the FCFs. In synergy, when compared to the Traditional level of [B]³, companies listed on the Novo Mercado and Level 2 levels tend to present higher FCF values. In addition, the larger the size of the companies and the higher their return on equity, the higher their FCFs tend to be, just as companies in stages of maturity tend to present lower FCF values. The relevance of this research is based on analyzing, in a stock market subject to imperfections, factors that may affect decisions about the level of cash maintenance of companies, more specifically by evaluating how Corporate Governance mechanisms relate to the theory of FCFs, in a context of potential conflict of interest.

How Do Investors Perceive the Materiality of Data Security Incidents

Data security incidents are continually increasing; hackers, governments, and other actors increasingly attempt to gain unauthorized access to confidential data. Information Systems (IS) users are becoming more vulnerable to the risks of data breaches. Many stakeholders perceive cybersecurity incidents as indicators of firms' operational and technological internal deficiencies. Previous research has revealed that investors react negatively to data breaches, yet little is known about investors' reactions to material data security incidents. Using a sample of 232 data security incidents for 132 publicly traded companies in the United States, we applied an event study methodology to discern investors' reactions to material versus immaterial incidents. We also use multivariate regression and time-to-event analysis to examine what determines the degree of investors' reactions, considering several intervals around the event day. Our results show that investors perceive material data security incidents as a deficiency of breached companies in comparison to immaterial incidents.

How Do Investors Perceive the Materiality of Data Security Incidents

Data security incidents are continually increasing; hackers, governments, and other actors increasingly attempt to gain unauthorized access to confidential data. Information Systems (IS) users are becoming more vulnerable to the risks of data breaches. Many stakeholders perceive cybersecurity incidents as indicators of firms' operational and technological internal deficiencies. Previous research has revealed that investors react negatively to data breaches, yet little is known about investors' reactions to material data security incidents. Using a sample of 232 data security incidents for 132 publicly traded companies in the United States, we applied an event study methodology to discern investors' reactions to material versus immaterial incidents. We also use multivariate regression and time-to-event analysis to examine what determines the degree of investors' reactions, considering several intervals around the event day. Our results show that investors perceive material data security incidents as a deficiency of breached companies in comparison to immaterial incidents.

Research on Intelligent Prediction Method of Financial Crisis of Listed Enterprises Based on Random Forest Algorithm

Traditional financial crisis prediction approaches have a tough time extracting the properties of financial data, resulting in financial crisis prediction with insufficient accuracy. As a result, based on the random forest algorithm, an intelligent financial crisis prediction approach for listed enterprises is proposed. The random forest method is used to mine the characteristics of financial data based on financial index data from publicly traded companies. This research develops a financial crisis prediction index system based on the findings of data feature mining. The CCR model is used to assess the efficiency of listed firms’ decision-making units with more input and output, and the efficiency index of each decision-making unit is calculated. The efficiency evaluation index of publicly traded companies is used to divide the severity of the financial crisis. The experimental results reveal that, when compared to standard prediction methods, this method’s forecast accuracy is commensurate with the actual state of businesses, and it can reduce the time it takes to predict financial crises.

Law Firms as Tax Planning Service Providers

We provide large sample evidence of law firms facilitating U.S. publicly traded companies' tax planning, investigate when evidence of law firm involvement is strongest, and examine some tax planning mechanisms law firms facilitate. Because companies' tax planning relationships with law firms are not publicly observable, we use litigation filings and SEC comment letters to identify companies' observable law firm relationships. We find a positive association between companies' tax planning and the average tax planning of other companies that have a relationship with the same law firm. This association is stronger for companies that are smaller, younger, R&D intensive, financially constrained, and facing less capital market pressure but does not vary with auditor-provided tax services. We also find evidence consistent with law firms facilitating the use of tax havens, Double Irish structures, and special purpose entities. Our findings deepen our understanding of companies' tax planning ecosystems.

Democracy, the Market, and the Firm

This book is an attempt to resolve an enigma that has puzzled social scientists since Condorcet in the eighteenth century: Why are collective choices so stable and easy to make in practice, when in theory it should be totally otherwise? A striking illustration of this enigma is the almost unanimous support of shareholders in publicly traded companies for the motions tabled by directors. The first part of the book explores the interplay between the voting and trading mechanisms. Two main arguments are proposed: on the one hand, the better the market works, the easier it is for majority voting to achieve political stability; on the other hand, among all market equilibria, those that are politically stable are more likely to be economically efficient. The second part of the book explores the feedback from collective choices to individual preferences. It investigates the behavioral assumptions leading to an alignment of shareholders, even in a context of severe market failures, and provides an analysis of the philosophical and axiomatic underpinnings of these assumptions. In sum, and figuratively, the book argues that the invisible hand of the market and the active hand of democracy can work hand in hand to give rise to a better world. The analysis relies on formal models which are kept as simple as possible and make use only of elementary convex and vector analysis.

Public versus Private: New Insights into the Private Company Discount

We examine whether private companies are valued with a discount compared to publicly traded companies. The analysis is based on a comparison of private company transactions with those of public companies. Whereas prior studies build pairs based on industry membership, we match private companies with public counterparts that are comparable in value relevant firm characteristics, i.e. profitability, risk, and growth, to calculate the percentage difference in valuation multiples. We find that private companies are valued on average with a discount on the EBITDA-multiple of 13% compared to their public counterparts. Private companies sell at lower discounts, if the acquirer firm is publicly listed. As size is associated with lower risk, we show that larger private companies sell at lower discounts.

“PENSI BINTEY”: PENGARUH IMPLEMENTASI BIG DATA ANALYTICS TERHADAP TERJADINYA AUDIT DELAY

ABSTRACT Audit delay states the complexity of transactions that occur within a business entity. Many companies have tried to find ways to avoid audit delay conditions in their business processes, one of which is by implementing big data analytics in the company's operational activities. The purpose of this study was to determine the effect of implementing big data analytics on audit delay and several other factors such as company size, company age, company profit and loss, auditor opinion, and reputation of public accounting firms. This study will use empirical data based on publicly traded companies with the 2017-2019 period. The selection for the 2017-2019 period is based on the hypothesis that many companies are starting to apply big data analytics in carrying out their business processes. Big data analytics is projected based on disclosures made by companies. Based on the results of logistic regression analysis, big data analysis has no significant effect. This suggests that the accountant/auditor should consider implementing big data analytics because of its complexity.Keywords: audit delay, big data analytics ABSTRAK Audit delay mengindikasikan adanya kompleksitas transaksi yang terjadi dalam suatu entitas bisnis. Banyak perusahaan yang telah mencoba mencari cara agar terhindar dari kondisi audit delay dalam proses bisnisnya, salah satunya dengan mengimplementasikan big data analytics dalam kegiatan operasional perusahaan. Tujuan penelitian ini adalah untuk mengetahui pengaruh implementasi big dataanalytics terhadap audit delay serta beberapa faktor lainnya seperti ukuran perusahaan, umur perusahaan, laba rugi perusahaan, opini auditor, dan juga reputasi kantor akuntan publik. Penelitian ini akan menggunakan data empiris berdasarkan perusahaan go public dengan periode 2017-2019. Pemilihan periode 2017-2019 didasarkan pada mulai banyaknya perusahaan yang menerapkan big data analytics dalam menjalankan proses bisnisnya. Big data analytics diproyeksikan berdasarkan pengungkapan yang dilakukan perusahaan. Berdasarkan hasil analisis regresi logistik, big data analytics tidak berpengaruh signifikan. Hal ini menunjukkan bahwa akuntan/auditor harus mempertimbangkan pengimplementasian big data analytics karena terkait dengan kompleksitasnya.Kata kunci: audit delay, big data analytics

Does capital structure influence the performance of corporate social responsibility? An analysis in companies of the world's largest economies

Companies are under external and internal pressure to adopt Corporate Social Responsibility (CSR) practices. Positive and significant results of the relationship between CSR and financial performance are not always confirmed in empirical studies, demonstrating, thus, no consensus has been achieved in CSR literature yet. Thereby, we seek to understand the influence of capital structure on the performance of CSR practices, since there is a theoretical omission about intangible attributes. We formulated three hypotheses about the relationship between CSR and: the capital structure (H1); the debt financing (H1a); and the shareholder’s equity (H1b). We used a sample of 1,642 publicly traded companies on the 10 highest GDP countries. Using GMM 2SLS estimator, the results reveal positive and significant relationship between shareholders’ equity and CSR, while for the relationship between debt financing and CSR shown a negative and significative correlation. Our findings suggest that companies with higher scores of CSR tend to finance itself through equity. We found differences between countries related to the Capital Structure volume required to achieve a CSR positive index. Our findings provoke further debate concerning the reasons that conduct organizations to adopt such practices and foster new discussions about the aspects that involve social practices responsible adoption in companies.