Key Areas of Research
Seductive Language for Narcissists in Job Postings
Management Science
Prior research indicates that narcissistic executives engage in earnings management and other negative organizational behaviors, and many studies ponder why firms hire such individuals, especially into corporate accounting positions. Utilizing a selection of terms from real-world job postings that we characterize as either describing a “Rule-Bender” or “Rule-Follower" candidate, we first conduct several validation studies which reveal that these terms vary predictably across types of job postings, that people generally agree with our categorization of these terms, and that Rule-Benders are viewed as possessing worse managerial skills but a higher proclivity for unethical behavior. We then demonstrate that narcissistic job seekers are more attracted to job postings that describe the ideal candidate using Rule-Bender terms for both general positions (Experiment 1) and senior accounting positions (Experiment 2). Finally, we examine firm characteristics that might lead professional recruiters to incorporate Rule-Bender language into Chief Accounting Officer job postings and find that Rule-Bender terms are preferred for higher-growth, higher-innovation firms (Experiment 3), and when more aggressive reporting would benefit the firm (Experiment 4). Our results suggest that recruiters’ language choices can attract Rule-Bending narcissists to firms, perhaps even in unintended circumstances.
Jonathan Gay (University of Mississippi), Scott Jackson (University of South Carolina), Nick Seybert (University of Maryland)
Bayesian Ensembles of Exponentially Smoothed Life-Cycle Forecasts
Manufacturing and Servoce Operations Management
We study the problem of forecasting an entire demand distribution for a new product before and after its launch. Firms need accurate distributional forecasts of demand to make operational decisions about capacity, inventory and marketing expenditures. We introduce a unified, robust, and interpretable approach to producing these pre- and post-launch distributional forecasts. Our approach is inspired by Bayesian model averaging. Each candidate model in our ensemble is a life-cycle model fitted to the completed life cycle of a comparable product. A pre-launch forecast is an ensemble with equal weights on the candidate models’ forecasts, while a post-launch forecast is an ensemble with weights that evolve according to Bayesian updating. Our approach is part frequentist and part Bayesian, resulting in a novel form of regularization tailored to the demand forecasting challenge. We also introduce a new type of life-cycle or product diffusion model with states that can be updated using exponential smoothing. The trend in this model follows the density of an exponentially tilted Gompertz random variable. For post-launch forecasting, this model is attractive because it can adapt itself to the most recent changes in a product’s life cycle. We provide closed-form distributional forecasts from our model. In two empirical studies, we show that when the ensemble’s candidate models are all in our new type of exponential smoothing model, this version of the ensemble outperforms several leading approaches in both point and quantile forecasting. In a data-driven operations environment, our model can produce accurate fore- casts frequently and at scale. When quantile forecasts are needed, our model has the potential to provide meaningful economic benefits. In addition, our model’s interpretability should be attractive to managers who already use exponential smoothing and ensemble methods for other forecasting purposes.
Xiaojia Guo (Assistant professor, Robert H. Smith School of Business, UMD), Casey Lichtendahl (Google), Yael Grushka-Cockayne (Professor, Darden school of business, University of Virginia)
Marketplace Expansion Through Marquee Seller Adoption: Externalities and Reputation Implications
Management Science
In the race to establish themselves, many early-stage online marketplaces choose to accelerate their growth by adding marquee (established brand name) sellers. We study the implications of marquee seller entry on smaller, unbranded sellers in a marketplace when both unbranded sellers and marquee sellers can vary vertically across reputation (referred to as sellers’ quality). While recent literature has shown that higher-quality unbranded sellers fare better than their lower-quality peers, we posit that this may not hold for entrants of any quality. To this end, we collaborate with an online business-to-business platform and exploit the entry of two marquee sellers of vastly differing quality. Using a difference-in-difference-in-differences framework, we causally identify the effect. We find that while higher-quality unbranded seller revenues increase relative to low-quality unbranded sellers when the entrant is of superior quality (consistent with the literature), the effect is reversed when the entrant is of inferior quality. Further, unbranded sellers change their supply quantities such that the platform’s average supply quality shifts in the direction of entrant quality. Using a stylized theoretical model, we identify two mechanisms that drive our findings – (i) new buyers brought in by the entrant disproportionately favor unbranded sellers who are quality neighbors to the entrant, and (ii) the unbranded seller’s ability to adjust their supply quantities. Most notably, the choice of marquee sellers, examined through the lens of their externality on unbranded sellers, can foster or undermine the platform’s long-term growth objectives.
Wenchang Zhang (Kelly School of Business, Indiana University), Wedad Elmaghraby and Ashish Kabra (University of Maryland)
The Financial Consequences of Pretrial Detention
Review of Financial Studies
In the United States, a significant number of criminal defendants are held in pretrial detention and face substantial financial burdens. Matching individual-level criminal case records to household-level financial data, we exploit the quasi-random assignment of court commissioners to study how pretrial detention affects household solvency. We find that pretrial detention results in higher rates of household insolvency, driven by higher rates of Chapter 7 bankruptcies and judgment liens, and higher foreclosure rates during periods of decreasing house prices. We document that the effects spill over to family members and show that home equity can cushion households from insolvency.
Pablo Slutzky (UMD), Sheng-Jun Xu (University of Alberta)
Liability of Foreignness in Immersive Technologies: Evidence from Extended Reality Innovations
Journal of International Business Studies
This study investigates the persistence of the Liability of Foreignness (LOF) in the realm of immersive technologies like Extended Reality (XR), which includes Augmented Reality (AR) and Virtual Reality (VR). Challenging the assumption that digitalization eliminates traditional barriers for foreign firms, we argue that LOF in XR stems from foreign companies' difficulties in providing a "mentally fluent" experience to consumers in foreign markets. Cultural mismatches can disrupt smooth information processing and diminish the effectiveness of XR innovations. Our research identifies specific XR technological features—realism, interactivity, and vividness—and brand-related factors like brand newness and platform orientation that can either exacerbate or mitigate LOF. Confirming the existence of LOF in XR innovations, we find that foreign brands in the South Korean beauty market are at a disadvantage in generating positive brand engagement through XR compared to local brands. XR innovations that are less realistic, more interactive, and highly vivid tend to amplify LOF due to the need for deeper cultural understanding. Conversely, higher realism in XR experiences helps reduce LOF by offering universally relatable content. Newer foreign brands and those using communication-centered platforms experience less LOF, as consumers may overlook cultural mismatches to resolve information uncertainty and develop attitudinal loyalty.
Hyoryung Nam, Assistant Professor, Martin J. Whitman School of Management at Syracuse University (Ph.d. from Smith – Marketing Department), Yiling Li, Doctoral Student, Yonsei Business School, Yonsei University, Seoul, Korea, P.K. Kannan, Dean’s Chair in Marketing Science, Robert H. Smith School of Business, University of Maryland, Jeonghye Choi, Professor of Marketing, Yonsei Business School, Yonsei University, Seoul, Korea
Distributed Ledgers and Secure Multi-Party Computation for Financial Reporting and Auditing
August 2024
To understand the disruption and implications of distributed ledger technologies for financial reporting and auditing, we analyze firm misreporting, auditor monitoring and competition, and regulatory policy in a unified model. A federated blockchain for financial reporting and auditing can improve verification efficiency not only for transactions in private databases but also for cross-chain verifications through privacy-preserving computation protocols. Despite the potential benefit of blockchains, private incentives for firms and first-mover advantages for auditors can create inefficient under-adoption or partial adoption that favors larger auditors. Although a regulator can help coordinate the adoption of technology, endogenous choice of transaction partners by firms can still lead to adoption failure. Our model also provides an initial framework for further studies of the costs and implications of the use of distributed ledgers and secure multiparty computation in financial reporting, including the positive spillover to discretionary auditing and who should bear the cost of adoption.
Sean Cao, Associate Professor (with tenure), Robert H. Smith School of Business, University of Maryland, United States of America
Holding Horizon: A New Measure of Active Investment Management
June 2024
This article introduces a new holding horizon measure of active management and examines its relation to future risk-adjusted fund performance (alpha). Our measure reveals a wide cross-sectional dispersion in mutual fund investment horizons, and shows that long-horizon funds exhibit positive future long-term alphas by holding stocks with superior long-term fundamentals. Further, stocks largely held by long-horizon funds outperform stocks largely held by short-horizon funds by more than 3% annually, adjusted for risk, over the following 5-year period. We also find a clientele effect: to reduce liquidity costs, long-horizon funds attract more long-term investors through share classes that carry load fees.
Authors: Fabio Moneta, Associate Professor, University of Ottawa; Chunhua Lan, Assistant Professor of Finance, University of New Brunswick; Russ Wermers, University of Maryland
Applied AI for finance and accounting: Alternative data and opportunities
February 2024
Big data and artificial intelligence (AI) have transformed the finance industry by altering the way data and information are generated, processed, and incorporated into decision-making processes. Data and information have emerged as a new class of assets, facilitating efficient contracting and risk-sharing among corporate stakeholders. Researchers have also increasingly embraced machine learning and AI analytics tools, which enable them to exploit empirical evidence to an extent that far surpasses traditional methodologies. In this review article, prepared for a special issue on Artificial Intelligence (AI) and Finance in the Pacific-Basin Finance Journal, we aim to provide a summary of the evolving landscape of AI applications in finance and accounting research and project future avenues of exploration. Given the burgeoning mass of literature in this field, it would be unproductive to attempt an exhaustive catalogue of these studies. Instead, our goal is to offer a structured framework for categorizing current research and guiding future studies. We stress the importance of blending financial domain expertise with state-of-the-art data analytics skills. This fusion is essential for researchers and professionals to harness the opportunities offered by data and analytical tools to better comprehend and influence our financial system.
Sean Cao, Associate Professor (with tenure), Robert H. Smith School of Business, University of Maryland, United States of America
Site Visits and Corporate Investment Efficiency
April 2024
Site visits allow visitors to physically inspect productive resources and interact with on-site employees and executives face to face. We posit that, by allowing visitors to acquire investment-related information and monitor the management team, site visits offer disciplinary benefits for corporate investments. Using mandatory disclosures of site visits in China, we find that corporate investments become more responsive to growth opportunities as the intensity of site visits increases, consistent with the notion that site visits yield disciplinary benefits. We also find that the positive association between site visits and investment efficiency is more pronounced when visitors can glean more investment-related information and when they have stronger incentives and greater power to monitor managers. This positive association is also stronger among firms with more severe agency problems and higher asset tangibility. The overall evidence supports the notion that site visits serve as a unique venue for institutional investors and financial analysts to acquire valuable information and serve a monitoring function, which generates disciplinary benefits for corporate investments.
Sean Cao, Associate Professor (with tenure), Robert H. Smith School of Business, University of Maryland, United States of America
"Lying and Cheating the Company: The Positive and Negative Effects of Corporate Activism on Unethical Consumer Behavior,” published in Journal of Business Ethics
Companies engage in corporate activism, defined as taking a stance on a controversial socio-political issue, such as gun control and banning transgender athletes. We show that taking such a stance can make consumers cheat the company more or less, depending on their political ideology. When the company's stance is incongruent with the consumer's values (compared to no stance information), consumers are more likely to lie to or cheat the company. When the company's stance is congruent, however, cheating decreases. This is relevant to companies, given the increase in consumers' unethical behavior (e.g., writing fake reviews; lying to gain discounts; insurance fraud; shoplifting; and wardrobing).
In Hye Kang, California Polytech-Pomona (Smith School PhD); Amna Kirmani, Smith School