INSIDE THIS ISSUE
Drawbacks of Exposing Materiality Thresholds to Investors During Audits
The Power of Turning Weight Loss Into a Game
Not All AI Is Created Equal
Marketing for Good: Reducing the Weight of Sacrifice and Enhancing the Appeal of Organ Donation
Smart investors crave as much information as possible about publicly traded companies, but what if too much disclosure has a negative impact on the market? Can certain disclosures actually do more harm than good in the long term?
In 2013 the UK passed a law that requires auditors to publish more extensive disclosures to provide investors with added visibility into the financial statements of larger publicly traded companies— specifically their materiality threshold percentages. Materiality thresholds are preset levels auditors use to determine whether an error in financial statements is considered significant. Did this decision lead to unintended consequences for UK investors, and what might happen if the U.S. followed suit?
In response to growing concerns that a similar U.S. regulation might be detrimental for investors, Professors Patricia Wellmeyer and Mort Pincus of the UCI Paul Merage School of Business, and coauthor Lijie Yao, the School of Economics and Management, Beijing Jiaotong University, investigated the consequences of the UK regulation and published their findings in Accounting Horizons. “Do Client Managers Strategically Manage Earnings in Response to Auditors’ Quantitative Materiality Threshold Disclosures?” reveals several areas of concern and suggests passing such a law here in the United States may have negative repercussions.
“Those expanded audit reports in the UK now come with a lot more information than the old pass/fail model, which was typically just one paragraph that disclosed whether the financial statements were good or not,” says Wellmeyer. “These expanded UK audit reports provide the most extensive type of disclosures.” They also are required to include many other items, including critical audit matters, she says.
Critical audit matters (CAMs) are mandatory disclosures in the United States, but U.S. auditors are not required to disclose materiality threshold percentages. “The reason why that percentage is important,” says Wellmeyer, “is because it determines where the auditor will test. If they find misstatements, it will be the benchmark for whether they will require a company change or fix that misstatement in order for the auditor to say the financial statements are materially correct. If a company doesn’t change their financial statements to fix the error and the auditor considers that error material because it’s over this quantitative threshold, the auditor can’t issue a clean opinion on the financial statements.”
The biggest concern with publicly disclosing details about an auditor’s quantitative materiality threshold is fairly simple, Wellmeyer explains. “Auditors always try to keep that percentage as proprietary from clients because, if our clients know the threshold, the risk exists that they will book misstatements below that threshold in order to affect a desired outcome on the financial statements.”
In other words, if companies know in advance what an auditor’s threshold percentage is, they’re more likely to manage earnings successfully. “When you provide that quantitative materiality threshold, you’re providing clients with a road map,” informing the company of the extent of misstatements they can get away with, Wellmeyer says.
This concern is what led Wellmeyer and her colleagues to determine if disclosing this information created such an unintended consequence in the UK markets or not.
“When we saw that the UK was coming out with this requirement, one of the first things we wanted to know was how this would affect client behavior.
To examine the outcomes of the UK disclosure and the association between earnings management by companies and their auditors’ quantitative materiality threshold disclosure, Wellmeyer, Pincus, and Yao used several measures of earnings management to determine the answers. First, they gathered materiality threshold numbers from audit opinions in the UK for companies that were listed on the London Stock Exchange. “Specifically, we looked at premium classification companies because initially only premium companies actually had to apply the rule requiring their auditor had to give these additional disclosures,” says Wellmeyer. After hand-collecting the quantitative materiality threshold disclosure from these audit opinions for these companies, they compiled the financial data, including earnings management proxies, and ran the models to see if they had significant associations. “We looked at discretionary accruals, essentially judgmental liabilities companies have on their financial statements,” plus analyst forecasts, says Wellmeyer. “That’s a known-use proxy for earnings management.”
They found a significant relationship between the auditor’s materiality threshold disclosure and the extent to which companies manage earnings. “They are definitely related. What we anticipated is, in fact, happening,” Wellmeyer says, “except in situations where a client firm is at the point where auditors suspect managers will want to adjust earnings to beat analyst expectations to go from a loss to positive income. In those cases—what we call materially qualitative settings—the auditor is aware of the
heightened earnings management potential, and they tend to provide more scrutiny.”
Wellmeyer also found an exception in cases of financial distress. “In those situations, we find no association between earnings management and the quantitative materialities threshold, but the fact that we didn’t find an association in these materially qualitative settings means auditors are actually doing what they’re supposed to,” she says. “In these special cases, they’re considering that managers have extraordinary pressures to manage earnings, and the auditors need to do more work above just that quantitative number. That was a bit surprising, but it was a good surprise.”
The implications for their findings should have a huge influence on how U.S. audit regulations develop in the future. “Our research will be important for regulators when they consider whether or not to require this disclosure,” Wellmeyer says. “Inevitably, some U.S. investor or advocacy group will want this materiality threshold percentage information. Chances are regulators will look at this disclosure again, so our research provides information on the unintended consequence of doing such a thing.”
The danger is, once auditors disclose their quantitative
materiality threshold, clients will know how to beat the system. “We need to ask auditors to think about the benefit of having the element of surprise,” she says. “Auditors need to maintain a certain level of uncertainty so clients are not be to get away with earnings management strategies based on their auditor’s quantitative materiality threshold.”
Wellmeyer sees an opportunity to emphasize the importance of proprietary information in their auditing process. “Qualitative circumstances, as we see from our research, are very important too,” she says. “Making sure students understand what qualitative materiality means as opposed to just the calculations around the quantitative piece will allow them to think about materiality, not just quantitatively but also qualitatively.”
Auditors commonly use five percent of income as a quantitative materiality threshold measure, but because of several recent accounting debacles, auditors have been tasked to come up with thresholds that are more company-specific. “Even if auditors use this five percent benchmark threshold, they also need to introduce riskbased tests,” says Wellmeyer. “Conceivably every client engagement should have its own quantitative threshold based on the risk profile of the client, the stakeholders, and again, what the auditor feels is the reputation of management and how aggressive they are in their accounting.”
Patricia Wellmeyer’s experience spans both the professional and academic arenas. In her over 10 years as an academic, Patricia has developed and taught courses across undergraduate and graduate programs in financial accounting, managerial accounting, auditing, data analytics, and emerging topics in accounting. She also helped co-found and is the current academic director of the Merage School’s first Specialty Master Program, the Master of Professional Accountancy (MPAc). Among the many electives she developed for the program is the School’s first ever accounting data analytics and ESG curriculum tracks.
Mort Pincus, Professor Emeritus in Accounting, focuses his research on an eclectic (and sometimes overlapping) set of topics, including: (a) the interaction of financial reporting and income taxes; (b) accounting information and stock market variables, including regulatory event studies and capital market efficiency; (c) US and international financial accounting policies; (d) the impact of complex information systems; and (e) auditing. He has published articles in top tier and other leading journals.
Weight management has become a massive global industry. The proliferation of diet trends, support groups, coaching methods, and targeted workout routines speaks to the need for diverse strategies. Recent research suggests that, even though weight loss is not a game, treating it like one might improve outcomes.
In their article “Gamified Challenges in Online Weight-Loss Communities,” published in Information Systems Research in 2022, Professor Behnaz Bojd of the UCI Paul Merage School of Business and her fellow researchers, Professor Xiaolong Song of Dongbei University of Finance and Economics, Professor Yong Tan of the Michael G. Foster School of Business, University of Washington, and Professor Xiangbin Yan of the University of Science and Technology Beijing, explore the potential for gamification to positively influence people who are working toward personal health goals.
“The adoption of game elements related to fitness was something we were interested in studying,” Bojd says. “Specifically, we wanted to know if it actually helped incentivize people to engage more and become more consistent with their weight loss or other health-related goals.”
To collect data, Bojd and her team used an online platform called FatSecret. “Their website had many different features like social, forums, and following other users—much like Facebook,” Bojd says. “People could comment on each other’s progress, take pictures of their food, and encourage each other on their diets.”
The researchers tracked individuals over several months, providing time-based or panel-level data. Bojd says they were lucky because they already had four months of prior data on participants when the website introduced gamification features. They followed the same people for the next four months to compare the before-and-after results.
In the researchers’ study, the control group didn’t sign up for the competition, while the treatment group did. This allowed the team to measure the causal effects of the competition. “Would people be more engaged if their weight loss goals were gamified?” Bojd asks. “In the specific platform we studied, leaderboards were used to track results for people engaged in the competition. This is not necessarily a new thing. In sports, they always use leaderboards to track who’s winning and who’s losing.” While collecting data, the researchers wondered if gamification alone would induce a sense of competition, or if an added financial incentive would be necessary to encourage participants to work toward a top-five ranking.
to the leaders in the competition. You can see how much they walked or how much they exercised, but if you have a target in mind, then the element of social comparison becomes weaker.”
If people achieve their personal goals, they don’t care if they are in third or last place on the leaderboard because they already achieved their goals, says Bojd. To fire up the competition, an individual person’s goal may not be a great way to incentivize people. “We can’t prove this, but based on our research, it seems like a specific target weakens the effect of social competition.”
The research team also found that, in smaller group sizes, people benefit more from competition. “We think this is probably because of the social comparison factor,” Bojd says. “Elements of social comparison create more meaningful competition in smaller groups. In larger groups, the top 10% of people might feel very proud of themselves, but for the other 90%—the people who need more of a push or an incentive—their ranking doesn’t motivate them to keep going. That means weight loss programs that use gamification incentives should keep their groups smaller if they want to increase engagement and improve results.”
Unfortunately, Bojd and her team were unable to interview participants to determine for sure if their theory is correct. The overall pattern, however, is gamification works for exercise instructions, but it doesn’t work for dieting.
In each of the exercise groups, specific instructions included 100 push-ups a day or walking 1,000 steps, among others. Some of the participants had a specific additional target. “For example, some participants wanted to lose this much weight in this amount of time,” says Bojd. “Surprisingly, we found that the absence of a target was more helpful, which is a bit counterintuitive.”
It is difficult to explain this result, but Bojd’s team has a theory: “We believe people were comparing themselves
“We found that, on average, the people in the gamification group were losing one kilogram per month compared to the control group, so it seems like leaderboards work—at least when it comes to weight loss.”
Bojd’s motivation to engage in this type of research is simple: “I have a personal interest in fitness, well-being and health-related outcomes,” she says. “Nowadays it’s
even easier to get access to data about how people set goals and engage in pursuing their goals. The availability of the data was a big factor.”
Another aspect of Bojd’s research focuses on how best to design platforms that engage people more. The marketing world is mostly measured by driving sales, she says. In this context, however, it is more about how we can engage people to achieve their personal weight loss goals.
“It’s not only about designing a platform where you can increase consumer engagement, but it’s also about helping people get what they want. It’s a real win-win situation. The platform is engaging more people, and the people are achieving their goals. Gamification helps people experience the excitement of competition and helps the platform keep people engaged with their product.”
Prior to the study, Bojd believed competition is mainly about external achievement. For instance, on The Biggest Loser television show, there is a financial prize and a reputation factor, she says. Based on their research, though, gamification works despite a free website, no prizes, and competition among strangers.
“The simplicity of the leaderboard was really all that was necessary to produce the results. That was very surprising to me. Competition with imaginary strangers can make you more committed to your goals. It’s funny and, at the same time, a little sad how we as human beings are so wired to compete, but at least in this case, it’s being leveraged for something meaningful.”
What are the implications of this research for the
fitness industry? “What we found about the differences between diet and exercise and how people need different incentives to commit to their goals is very interesting,” Bojd says. “We know we need both diet and exercise to become healthier. We can’t expect to exercise to remain healthy without changing our diets, nor can we diet without doing some exercise. They go hand in hand.”
However, Bojd and her fellow researchers found that we need specific incentives for each type if we want people to become more committed to certain methods of weight loss. “Diet and exercise are different animals. If someone is a life coach, or health coach, and they have clients who need to address their diet first, it’s not effective to put them in a competition mindset, but for clients who need to train, or who want to be more active, the competition incentive is most likely to produce the best results.”
Today, as more people have wearable devices or use smartphones to track their steps, this creates a wonderful opportunity for companies to develop apps that use this data to help people achieve their diet and exercise goals, and if they can leverage the gamification side for those wanting to become more active, they should see better results.
“The fitness industry should definitely use the gamification features to induce competition and leverage social comparison in a way that they can engage more users,” Bojd says. “They’ll have more successful users, which will bring in more clients via word of mouth.”
Based on this research, people who set resolutions in the new year to lose weight, exercise more and become healthier may do well to join small group weight loss competitions to achieve quick and better results.
Behnaz Bojd is Assistant Professor of Information Systems at the Paul Merage School of Business. She is fascinated by how advances in information technologies have enabled us to understand and draw causal inferences about human behaviors and design business solutions and policies. Her Research Interests include, Digital Health, Gamification, Matching Markets, and Causal Inference.
For the last 40 years, software developers, marketers and researchers have been creating and running various machine-learning models and methods for analyzing how customers make choices about brands, quantities and timing.
One of those fortunate enough to be among the first to assist in creating those models is Professor Imran Currim of the UCI Paul Merage School of Business. His work in this area uniquely qualifies him to inquire about the quantitative and qualitative differences between the various models currently used today.
That’s why his recent coauthored article was unsurprisingly of great interest to others in the field. “An Empirical Comparison of Machine Learning Methods for Text-Based Sentiment Analysis of Consumer Reviews,” coauthored with fellow researchers Huwail J. Alantari, PhD, the UCI Paul Merage School of Business, Yiting Deng, PhD, UCL School of Management, and Sameer Singh,PhD, UCI Donald Bren School of Information and Computer Sciences, was published in the International Journal of Research in Marketing (IJRM).
“In the past 40 years, I have been fortunate enough to be among the first few professors worldwide to build models of how customers make choices about brands, quantities and timing,” says Currim. “I was among the first handful of people to develop models of customer choices based on point-of-sale data when I was doing my PhD dissertation in Palo Alto at Stanford School of Business. This was before point-of-sale data became electronic.”
The development of the UPC scanner in 1974 allowed for the estimation of econometric models on how customer choices are based on the features of the product, the service, the price, advertising, temporary sales promotions, coupons redeemed and much more. “The last 40 years were all about numerical data,” says Currim. “We used econometric models with mathematical equations, which was the marketing version of Newton’s law. Fast forward to today. What we find is that verbal and text data also influence customer choice. For example, suppose you have dinner at a restaurant, then want to convey your experience to others. You may go to Yelp and give the restaurant somewhere between a one- and five-star rating. Then you may write a series of words to explain why you gave it a two or a five. Maybe you do this because you used Yelp to choose the restaurant, and now you want to give back. You made a choice, and now you want to help others make a choice.”
With the advent of review sites like Yelp, Expedia, Amazon and others, an explosion of text and numerical data needs to be unpacked. “Today we build mathematical models of the relationship between the rating on the left-hand side of the equation and the words people write on the other side,” says Currim. “In the same way Newton’s law was force is equal to mass times
acceleration, we create an equation explaining these ratings and rankings. This is novel relative to the last 40 years because we once built all our models based on numerical data, and now we have text data. This is market-based data. They’re not laboratory-based data. They’re not experimental data. These are realworld data. We use the data to build mathematical models or equations. We do that for two reasons: to predict the next product someone might buy or the next restaurant someone might go to. Prediction is one goal. Diagnostics is the second role. It’s all about predictive and diagnostic ability.”
Currim was born and raised in Bombay, India, where his parents owned one of the largest umbrella manufacturing companies. “In my childhood, I used to watch customers,” he says. “I had a very powerful speech impediment, so I hid in the mezzanine of our largest store and watched customers. I became very interested in how customers behave—how they choose.”
Currim has had extensive experience looking at numerical data in his career, but his vision was to create a model that combined numerical data with text and image data. “Six or seven years ago, I stood in a grocery store parking lot talking to one of my PhD students who had a bachelor’s degree in computer science,” he says. “I was telling him about this vision, and he said, ‘Okay, let’s do this analysis together.’”
Currim had to find a way to analyze and categorize all 25 different models for forecasting ability and diagnostic ability. “I believe that in life you have many options,” he says, “and when you have many options, the key is we have to make trade-offs between the benefits and the costs. To find the answers, we needed automation. How can we as humans train machines that will learn to answer these questions regarding the predictive power and the diagnostic capability of each of the 24 models?”
Once Currim and his fellow researchers developed
their automated system, they began to run their study. “We found out these 25 methods fall into one of three buckets: vocabulary-based, classification and topic discovery,” he says. “Vocabulary-based models are used by researchers in psychology, sociology and by qualitative scholars who want to understand qualitative concepts like emotion. Here there’s a dictionary of words related to emotion, and you can study the role of emotion in customer decisionmaking or customer reviews, for example. The second category is classification. These are methods focused on prediction. The third bucket is diagnostic ability, which is about what factors influence the decisions.”
Right away Currim and his team realized the second bucket—prediction—was by far the largest of the three, but that wasn’t their most fascinating discovery. “We realized the methods that are the best in prediction are the worst in diagnostics, and the methods that are the best in diagnostics are the worst in prediction. They were trade-offs,” he says, “because, of course, everything in life is a trade-off. Do you walk into a BMW dealership, or do you walk into a Honda dealership? The trade-off is universal across products, services or even options in life.”
Even before they started their research, Currim was looking for evidence of trade-offs. “I did not know how much of an advantage one method had over another. The cutting edge of AI today is in the area of explainable AI. That means trying to explain the predictions to determine why certain types of people rate things a certain way.”
Currim says there’s especially much hype around predictive models that can provide good diagnostics. Many papers are written on this, and several companies are working on this diagnostic AI, he explains. He has trained the senior executives at some of those companies, but when he sets up a call, goes in with a scalpel searching for key insights even worldwide experts claim, he looks for the solution and tries to glean diagnostics from these predictive models. “When I got to the heart of the clogged artery, I found the solution is not ready for prime time. In fact, it’s very far from ready.”
While this may sound like a negative assessment of the AI landscape, Currim is exceptionally optimistic. “I think it’s very exciting because this gives us something to work for in the future.”
Currim’s research reveals that building mathematical equations that incorporate numerical and textual data is one thing, but out of the 25 different models currently in operation, all of them fall into three main categories: vocabulary, predictive and diagnostic. Of those, the best method depends on one’s objective. “Remember, like anything in life, choosing one method over the other involves a trade-off. Why are you building these models? What are you hoping to get out of it? If you seek to gain prediction, then go for the forecasting or classification model, as long as you don’t care about an explanation. If you want to understand why people do certain things, but you’re not interested in prediction, then go with the topic discovery method. But if you really want to gain a deeper understanding,” he quips, “then read the paper.”
Prior to his appointment as Faculty Director of the Beall Center in 2014, Imran Currim served The Paul Merage School of Business as Associate Dean for 8 years, overseeing Masters, Executive, Undergraduate, and Doctoral Programs. Since 2014, Professor Currim has focused on the development of curriculum and new programs on innovation and entrepreneurship; a new Masters of Innovation and Entrepreneurship (MIE) to begin in 2019, the first of its kind in the University of California system; an Undergraduate Minor; and Certificate Programs for Merage Graduate and Undergraduate Students.
In the United States, more than 103,000 people are in need of a lifesaving organ transplant, yet only 23,286 people, both deceased and living, donated an organ in 2023. The vast majority of candidates on the list need a kidney, but tragically, 12 of them die every day waiting for one.
“It’s really a market-controlled process,” says Tonya Williams Bradford, associate professor of marketing and inclusive excellence term chair professor at the UCI Paul Merage School of Business. “Despite there being eight possible transplants from every healthy individual who passes away, there remains more demand than supply.”
In a study published in the Journal of Marketing, Bradford and her coauthor Naja Williams Boyd set out to discover how this supply-demand problem might be addressed in part with the right marketing mix—product, price, promotion, place, process and people—that motivates individuals to consider supporting the missions of nonprofit organizations. Specifically, they explored how the experiences of sacrifice play out for individuals participating in living organ donation.
“I am a living organ donor myself, so I am personally familiar with the many challenges both donors and recipients face,” says Bradford. “As a researcher, I believe there is a marketplace solution for many of these challenges.” In fact, the donation experience for Bradford goes beyond personal and professional into familial—she donated a kidney to her coauthor who is also her sister.
Through their own experiences, as well as the ethnographic data obtained from semi-directed phenomenological interviews of 20 living organ donors, the authors found that a carefully curated marketing mix may help mitigate experiences of sacrifice among donors, thereby overcoming consumer reluctance to donate. This is key because notions of sacrifice are not easy to capture or quantify.
“Most research focuses on the monetary sacrifices associated with charitable giving, but that’s not the only sacrifice, and for organ donation, it’s not even the most challenging,” Bradford explains. “Rather, it’s the mental, emotional and physical sacrifices of donation that have the biggest impact on the donor.”
According to the United Network for Organ Sharing, there were approximately 16,000 deceased donors in 2023 but only 6,900 living donors. As the process for consent for living donation is typically less emotionally charged than for deceased donation, it is worthwhile for organizations to find ways to increase the number of living donors. In particular, the loved ones of
potential deceased organ donors are faced with an unexpected and often traumatic death. Further, deceased donors need to be exceptionally healthy, which leaves organ procurement organizations with a limited number of donation candidates. And not only the deceased person’s wishes must be considered; the remaining family members have a say in whether donation will occur.
“One of the biggest challenges for deceased organ donation is that time is of the essence,” says Bradford. “It is necessary to respect the grieving family while also keeping the organ viable. Keep in mind that deceased donors have usually died suddenly and tragically— often at a young age. If the message from the organ procurement organization is simply, ‘This is a great opportunity to help another person stay alive,’ that will feel like a cold splash to the face of a family whose loved one is suddenly and unexpectedly no longer alive.”
That’s not to say living donation isn’t emotionally and relationally complicated. Family and friends of a living donor have opinions and preferences as well. For instance, one research participant in Bradford’s study ended a long-time relationship with a partner who questioned his desire to donate an organ. On top of that, living donors wrestle with concerns about how their own bodies will function after donation, whether the transplant will successfully improve quality of life and longevity for the recipient, and the possibility of surgical complications. Procurement organizations primarily rely on promotion to raise awareness about the donation opportunity generally—and organ procurement specialists when potential donors are deliberating over these concerns. Bradford’s research suggests these organizations have an opportunity to more fully address the donation, transplantation and recovery experience. Donors need to have both the information to fully consider the benefits and risks for themselves, the recipient and their families, and the support from the transplant center to navigate the experience.
Marketing efforts that focus only on the opportunity to donate miss an opportunity to include important messaging about the psychological and relational
weight of these sacrifices through careful planning for, facilitation of and communication about the full spectrum of experiences that occur before, during and after donation.
To do this, the study identifies steps organizations can take to make use of the marketing mix in addressing each of the three types of sacrifice involved in the donation process: psychic, pecuniary and physical. In particular, organizations must understand the full extent of what they ask of donors and how those donors may experience the three types of sacrifice. That understanding allows organizations to strategically employ the six marketing-mix components to foster an environment in which people feel their donations are valued and respected to an extent commensurate with their sacrifices.
“It continues to surprise me how little support there is for donors because organ procurement organizations haven’t fully untangled the complexities of sacrifice,” Bradford says. “Oftentimes the staff interacting with donors are nurses and doctors who are very good at keeping people alive and may be focused on the possibilities due to organ donation. Such conversations may not also take into account the various sacrifices involved to agree to be an organ donor. With our research, we want to change that. We want staff to be well equipped and confident when talking to donors and families about the full range of experiences within donation and its accompanying sacrifices.”
Bradford is a big believer in what has been described as marketing for good. She wants marketers and the organizations they serve to have an opportunity to improve what’s happening in society and in particular the well-being of individuals. In this case, that means elevating the stories of organ donors and recipients so they’re more visible and consequential.
“It breaks my heart that people die because an organ isn’t donated in time to save them, and I think having better ways to identify and recruit potential donors is a key part of the solution,” explains Bradford. “Most of the donors and recipients I’ve talked to really want their story told, even those who had less than ideal outcomes. They want people to understand the complete scope of the donation experience so future donors can make informed choices.”
In subsequent research, Bradford wants to better understand how family members view the organ donation of a deceased loved one and how those perspectives can influence marketing efforts. She is currently working on a study centering experiences of families who donated the organs of their deceased loved ones to determine how marketing may elevate stories of healing and hope. Bradford realizes these stories will not bring their loved ones back. However, early findings show that deceased organ donation provides a source of hope through the transformation of a tragic death into one that leads to prolonged lives for others.
Tonya Williams Bradford is an associate professor of marketing and the inclusive excellence term chair professor at the UCI Paul Merage School of Business. Her research focuses on rituals and identity across phenomena, including gifting, relationships with money, communities, acculturation and consumer-brand relationships. She also serves as associate editor for the Journal of the Academy of Marketing Science, Journal of Public Policy & Marketing and the Journal of Retailing and as a member of the editorial review board for the Journal of Marketing, the Journal of Consumer Research and the Journal of Consumer Psychology
Professors Chuchu Liang and Ben Lourie
Title: “Does the Risk Aversion of Accountants Matter? Female Rank-and-File Accounting Employees and Internal Control Quality”
Co-author: Alex Nekrasov
Accepted at: Journal of Accounting and Public Policy
Using novel data on corporate accounting employees, we find that the risk aversion of rank-and-file accounting employees, proxied by the proportion of female accountants, is negatively associated with the likelihood of internal control weaknesses. The results are incremental to controlling for other accounting employee characteristics, such as experience and quality, which are also associated with fewer internal control weaknesses. In contrast, female non-accounting employees explain operating risk and not internal control risk. We mitigate endogeneity concerns by using an entropy balanced sample and an instrumental variable approach that exploits variation in the external supply of female accountants. Our study is among the first to provide largesample archival evidence that characteristics of accounting employees matter to financial reporting and how these effects differ from non-accounting employees.
Professors Chuchu Liang and Ben Lourie
Title: “Buy Now Pay (Pain?) Later”
Co-authors: Ed deHaan and Jungbae Kim
Accepted at: Management Science (Journal on Financial Times Top 50 list)
“Buy-Now-Pay-Later” (BNPL) is a largely unregulated FinTech innovation that provides consumers with easy access to credit for retail purchases. BNPL spending is projected to reach $1 trillion by 2025, but we know little about its effects. Using banking data for 10.6 million U.S. consumers, we investigate the effects of BNPL on leading indicators of users’ financial health. We find that new BNPL users experience rapid increases in bank overdraft charges and credit card interest and fees, as compared to non-users. An instrumental variable exploiting consumers’ pre-BNPL shopping habits increases the credibility of BNPL having a causal negative effect. Our results inform regulatory investigations into the effects of BNPL on users’ financial health, and expand the academic literature’s understanding of an important consumer credit innovation.
Professor Emeritus David Hirshleifer
Title: “Do Sell-Side Analysts Say `Buy’ While Whispering `Sell’?”
Co-authors: Yushui Shi (PhD alumnus) and Weili Wu
Accepted at: Review of Finance (Journal on Financial Times Top 50 list)
We study here say-buy/whisper-sell behavior wherein analysts issue optimistic recommendations to attract retail investors while providing more accurate information to fund managers in private, sometimes resulting in fund managers selling the recommended stocks. We test whether fund managers return the favor using their votes for analysts in a Chinese “star analyst” competition. Managers are more likely to vote for analysts who exhibit greater “say-buy/whisper-sell” behavior toward these managers. This suggests that analysts reduce the accuracy of their public recommendations, thereby maintaining the value of their private advice to funds. Our findings help explain several empirical puzzles about analyst public recommendations.
Professor Emeritus David Hirshleifer
Title: “News Diffusion in Social Networks and Stock Market Reactions”
Co-authors: Lin Peng and Qiguang Wang (PhD alumnus)
Accepted at: Review of Financial Studies (Journal on Financial Times Top 50 list)
We study how the social transmission of public news influences investors’ beliefs and securities markets. Using data on social networks, we find that earnings announcements from firms in higher-centrality counties generate stronger immediate price, volatility, and trading volume reactions. Post-announcement, such firms experience weaker price drift and faster volatility decay but higher and more persistent volume. These findings indicate that greater social connectedness promotes timely incorporation of news into prices, but also opinion divergence and excessive trading. We propose the {\it social churning hypothesis}, which is confirmed using granular data from StockTwits messages and household trading records.
Professor Emeritus David Hirshleifer
Title: “Information Cascades and Social Learning”
Co-authors: Sushil Bikhchandani, Omer Tamuz, and Ivo Welch
Accepted at: Journal of Economic Literature
Social learning is the updating of beliefs based on the observation of others. It can lead to efficient aggregation of information, but also to inaccurate decisions, fragility of mass
behaviors, and, in the case of information cascades, to complete blockage of learning. We review the theory of information cascades and social learning, and discuss important themes, insights and applications of this literature as it has developed over the last thirty years. We also highlight open questions and promising directions for further theoretical and empirical exploration.
Professor Emeritus David Hirshleifer
Title: “Social Contagion and the Survival of Diverse Investment Styles”
Co-authors: Andrew Lo and Ruixun Zhang
Accepted at: Journal of Economic Dynamics and Control
We examine the contagion of investment ideas in a multiperiod setting in which investors are more likely to transmit their ideas to other investors after experiencing higher payoffs in one of two investment styles with different return distributions. We show that heterogeneous investment styles are able to coexist in the long run, implying a greater diversity than predicted by traditional theory. We characterize the survival and popularity of styles in relation to the distribution of security returns. In addition, we demonstrate that psychological effects such as conformist preference can lead to oscillations and bubbles in the choice of style. These results remain robust under a wide class of replication rules and endogenous returns. They offer empirically testable predictions, and provide new insights into the persistence of the wide range of investment strategies used by individual investors, hedge funds, and other professional portfolio managers.
Professor Frank MacCrory
Title: “Competition of Multiplatform Firms: Implications for the Internet of Things”
Co-author: Evangelos Katsamakas
Accepted at: PLOS ONE
Abstract: The Internet of Things (IoT) technology trend is transforming business and society. This creates a need to understand strategic behavior in the consumer IoT, where firms tend to offer multiple platform devices, and new generations of devices are introduced frequently. We propose a novel analytical model that formalizes the concept of a multiplatform firm that offers a system of platforms, such as a smartphone, and a new platform device, such as a smartwatch, and orchestrates a multiplatform ecosystem. The analysis shows how a platform design decision, like offering a new standalone device, affects consumer choices and market outcomes.
We identify two classes of new devices that matter, and show when a new platform device may disrupt the smartphone market. Moreover, we characterize conditions under which it is profitable for a vendor to make its new platform device look and feel more like its smartphone. Overall, we provide insights into how multiplatform firms differ from platform firms. We identify future research opportunities on the economics of consumer IoT and multiplatform ecosystems.
Professor Noah Askin
Title: “Feature-Based Structures of Opportunity: Innovation in the American Popular Music Industry, 1958-2016”
Co-author: Khwan Kim
Accepted at: American Sociological Review
We offer a new perspective on how cultural markets are structured and the conditions under which innovations are more likely to emerge. We argue that in addition to organization- and producer-level factors, product features—the locus of marketplace interaction between producers and consumers—also structure markets. The aggregated distribution of product features helps producers gauge where to differentiate or conform and when consumers may be more receptive to the kind of novelty that spawns new genres, our measure of innovation. We test our arguments with a unique dataset comprising the nearly 25,000 songs that appeared on the Billboard Hot 100 chart from 1958 to 2016, employing computational methods to capture and analyze the aesthetic (sonic) and semantic (lyrical) features of each song and, consequently, the market for popular music. Results reveal that new genres are more likely to appear following markets that can be characterized as diverse along one feature dimension while homogenous along the other. We then connect specific configurations of feature distributions to subsequent song novelty before linking the aesthetic and semantic novelty of individual songs to genre emergence. We replicate our findings using industry-wide data and conclude with implications for the study of markets and innovation.
