Julia Fonseca,* Victor Duarte, Weitong (Peter) Han | Department of Finance | $101,394.69

This proposal enhances an innovative data resource to enable research on consumer and small business credit markets and economic inequality by Gies faculty and students. It adds to an ongoing collaboration between the investigators and the Data Science Research Service called the Gies Consumer and small business Credit Panel (GCCP). The GCCP is a best-in-class dataset combining individual-level data on small business loans, personal credit, and alternative credit. The initial version of the GCCP is being actively used by 14 students and faculty for 11 research projects and doctoral theses, including a PI’s publication in the Journal of Finance (Fonseca, 2022). In addition to supporting the ongoing projects funded previously (Gies Grant 2021), this proposal describes three new projects that will take the GCCP to the next level and address several important topics: racial disparities in the bankruptcy system, unequal access to finance by women and minority entrepreneurs, and the role of tradeline data and machine learning in mitigating racial disparities in credit access. We seek funding for research assistance, data analytics, and expansions of the GCCP that will enhance the ability of all Gies researchers to answer critical questions related to gender, racial, and other disparities in financial markets.

Yilang Feng,* Hyewon Ma | Department of Business Administration | $69,254.25

The current process of de-globalization and rising political risks have created unprecedented challenges for multinational corporations. How do firms adapt to this structural change in the global business environment? We study this topic by focusing on how US firms adapt to geopolitical crises in two important but increasingly risky foreign markets: China since the US-China Trade War in 2018 (Paper 1) and Russia since the Russian invasion of Ukraine in 2022 (Paper 2). In addition, we will also compare and synthesize the findings from the two cases to develop general theoretical frameworks regarding how multinational firms navigate such significant political volatility and de-globalization shocks (Paper 3).

Yunchuan Liu* | Department of Business Administration | $46,169.50

In this project, we study the machine learning algorithm for a platform such as match.com serving to match different consumers to each other. The algorithm is designed to predict consumer types and facilitate the matching process. However, there has been increasing concerns about potential bias against certain demographic group in algorithm outputs, and therefore the platform may be subject to fairness constraints and "de-bias" the matching algorithm. We show that the "biased" matching algorithm by the platform may actually benefit consumers from both sides as well as the platform. If the platform is forced to de-bias its matching algorithm, it may hurt consumers and the platform. Our model highlights two important elements in the discussion of algorithmic bias issues. First, (statistical) bias exists not only in algorithm outputs, but also in rational people's beliefs. We specifically examine how the algorithm affect human beliefs. Second, there are externalities in algorithm outputs in the matching setting – the algorithm performance in one demographic group inevitably affects the matching outcomes in other groups. We demonstrate how such externalities could make de-biasing algorithm backfire.

Vishal Sachdev,* Wencui Han, Qingquan (Tony) Zhang, Steve Raquel | Department of Business Administration | $39,521.09

This grant seeks investment in building capabilities in analysis of data from blockchains in multiple domains. Specifically, we propose to:

1. Create pipeline of research leveraging blockchain data
2. Enhance classroom teaching
3. Build skills in research and the domain of Blockchain analytics among faculty and students
4. Create a pipeline of students to Ph.D. Programs
5. Build Institutional capability in handling and analyzing blockchain data
6. Encourage other faculty to build on the infrastructure and capabilities we develop to seek other grants
7. Encourage diverse representation in blockchain research by hiring students from underrepresented populations

Mahyar Kargar,* Belinda Chen | Department of Finance | $39,291.17

Unlike US stocks, which primarily trade on transparent exchanges, US corporate bonds largely trade over the phone in opaque over-the-counter markets. Because of this market structure, it is often difficult for investors to determine the best price currently available for a given bond. The goal of our research project is to determine if better price disclosures for corporate bonds would provide valuable information to investors and improve market efficiency, or if the existing market structure already performs its price discovery function appropriately, despite the apparent lack of transparency. To tackle this question, we leverage a new proprietary dataset that uses machine learning to provide unbiased estimates of bond prices at high frequency. Using this data to price the holdings of exchange traded funds (ETFs) invested in corporate bonds, we obtain implied valuations of bond ETF shares. By comparing our implied values to the actual market price of ETF shares, we can identify funds that are mispriced. In preliminary results, we have shown that funds that trade below their implied valuation tend to exhibit abnormally high future returns. The opposite is true for funds that trade above their implied valuation. These preliminary findings suggest that a higher level of price transparency in the corporate bond market would likely improve the price efficiency. Our project is timely and policy relevant given the recent policy discussions held at the SEC on potential reforms of the US corporate bond market. The funding received will allow us to establish the robustness of our results.

Maria Rodas* | Department of Business Administration | $39,151.74

We, the Multicultural Insights Lab (MIL), are seeking funding to launch a global research project that will benefit the marketing area faculty and advance the mission of the Gies College of Business. We propose an international, cross-cultural research project that will investigate the effect of political polarization on people’s cultural orientation, perceptions of society, and the marketplace. This initiative addresses one of the most sought-after questions in the current politically tumultuous world. Due to the interdisciplinary nature of this research, it will provide comprehensive insights into the changes at the individual, business, and society levels. Specifically, the findings will provide an answer to urgent needs for navigating the unstable, unpredictable market. In this proposal, we provide an overview of the research project and explain why this project is an excellent opportunity for BADM and Gies to advance their mission.

Tatyana Deryugina,* Mackenzie Alston | Department of Finance | $34,966.93

Social media, especially Twitter, has become an important outlet for academic researchers. Scholars use Twitter to disseminate and promote one’s research findings, exchange information and opinions, network, find collaborators, and receive informal mentorship. Whether social media use benefits scholars’ careers, however, and whether the benefits outweigh the costs are contested questions on which there is little reliable evidence. To shed light on this question, we will employ a randomized field experiment to measure the causal impact of Twitter use on academic researchers’ career outcomes. We will recruit relevant participants and collect baseline data on the level of Twitter engagement, demographics, and career trajectories. Academics randomly assigned to the treatment group will be regularly encouraged to use Twitter and provided with suggestions for how to do so effectively, while the control group will not receive these nudges or resources. We will then track both Twitter use and career outcomes (via follow-up surveys and web scraping), comparing the treated academics to the control group to determine the causal effect of additional Twitter use on career progression (e.g., number of citations). Analyses that consider the academic’s gender, race, seniority, university rank, and other characteristics will reveal whether certain groups benefit disproportionately from social media and why.

Makenzie Alston* | Department of Finance | $29,502.31

The increasing attention to diversity in hiring and promotion creates opportunities to build diverse teams, but it might result in perceptions that are detrimental to the long-term success of these minority employees. If underrepresented minorities believe that they were hired because of their identity versus skill, this could affect their self-confidence and performance. To better understand how employees respond to "diversity hiring," we will conduct an online field experiment in which we hire White and non-White participants to grade math problem sets. As part of the application process, applicants will complete a math quiz, and we will hire those who perform well. We will randomly sort these workers into two groups. One group will be told that we wanted to hire skilled individuals, and the other will be told that the hiring was based on their skills and diversity considerations. After receiving this feedback, workers will choose whether they want to grade easy or hard problem sets and rate their confidence in their grading. By analyzing the accuracy of their grading and their confidence in their work, we will determine how minority workers’ performance and self-confidence are affected when they believe their race was a factor in the hiring decision-making.

Oktay Urcan,* Wei Zhu | Department of Accountancy | $28,163.40

The “big data” revolution is reshaping business and academia. Big data allow researchers to test theories, evaluate corporate disclosures, and measure economic activities in ways that would otherwise be infeasible using "small data." In this proposal, we request funding for the purchase of three sets of big data: granular GPS (i.e., mobile device) data; environmental, social, and governance (ESG) data at the event level; and trade and quote (TAQ) data time-stamped to the millisecond. With these data we will examine a wide range of questions regarding the interplay between accounting, finance, and social factors (e.g., relations between consumers, retail investors, and sustainability). Funding this proposal would be consistent with the College’s strategic goal of fostering excellence in research and teaching, the College’s strategic prioritization of innovation, and the University’s land-grant mission.

Sarah Lim* | Department of Business Administration | $28,071.06

With technological advancements, an algorithm has become prevalent in business operations. Prior research has shown that people are often reluctant to rely on algorithmic (vs. human) decisions. In this proposal, we propose two projects that examine novel contexts in which people may prefer algorithmic (vs. human) decisions. The first project examines how social inferences people make about utilizing algorithmic versus human decisions affect their willingness to delegate decisions to algorithms (vs. humans). The second project examines how people perceive the accuracy of algorithmic recommendations differently for the self versus others. The proposed research will contribute to the emerging literature on algorithmic decision-making by elucidating the social and interpersonal aspects of utilizing algorithmic (vs. human) decisions. More broadly, this research promises to offer insights into how new technology (e.g., algorithms) transforms organizations and consumer decision making in the marketplace.

Mehmet Ahsen,* Wencui Han | Department of Business Administration | $27,701.70

The rapid explosion in AI has introduced many data-driven innovations that can improve the quality and equitable access to healthcare. However, there are many challenges associated with AI models that need to be addressed for the broad adoption of AI by the healthcare industry. Two such challenges that we aim to address in this proposal are (1) the black box nature of AI models and (2) the biases in algorithmic decisions due to biases in human-generated data used to generate them. In the first project, in collaboration with Dr. George Liu from Carle Foundation Hospital, we would like to study whether Explainable AI (XAI) will have an impact on clinicians’ decisions. Given that there are many types of AI explanations, we would like to study further what type of explanations has a better impact. In the second project, we would like to first mathematically model the source of algorithmic biases and come up with algorithms/mechanisms that can debias algorithmic recommendations. Moreover, we would like to study the impact of XAI in debiasing AI recommendations when a human decision-maker is involved.

Gautam Pant,* Abhijeet Ghoshal | Department of Business Administration | $27,701.70

As private organizations and public institutions increasingly rely upon machine learning-based systems for decision-making, it has become critical to audit and correct biases in such systems that may lead to discriminatory outcomes for certain groups of stakeholders. Recommender systems that present relevant job postings to users have the potential to alter the career trajectories of the workforce. Hence any bias in such systems can have a broad societal impact, such as worsening the underrepresentation of certain groups. In this project, we aim to develop a framework for debiasing recommender systems in the context of job postings. Our framework draws from recent analytical arguments in the literature that have highlighted the simplicity-equity tradeoff in machine learning models. In particular, we seek to minimize model complexity while maximizing equity for disadvantaged groups. We expect the project to lead to multiple high-quality publications of importance to practice as well as support at least one doctoral dissertation.

Stefan Zeume* | Department of Finance | $27,701.70

We seek to understand how the users of offshore tax haven vehicles respond to offshore data leaks such as the 2016 Panama Papers and the 2017 Paradise Papers. The use of offshore secrets creates benefits (tax savings, reduction in expected cost of expropriation) at an expected cost (probability of detection x cost if detected). The revelation of offshore secrets through unexpected data leaks may reduce benefits or increase costs of using offshore vehicles, e.g., through increased tax enforcement or increased probability of similar leaks. In response to data leaks, individuals and firms may (i) shift their offshore activities elsewhere to continue reaping the benefits (whack-a-mole) or (ii) stop using offshore secrets, thereby increasing transparency and creating a level playing field in the economy (deterrence). Offshore users may shift their activities to/away from other offshore havens or certain US locations known for their lax transparency requirements. We will use the funding to cover most of the costs of purchasing NETS data, which tracks 78 million establishments in the US. Understanding the drivers of the use of offshore tax havens is of first-order importance to investors, regulators, and taxpayers alike.

Yufeng Wu* | Department of Finance | $25,772.74

How does access to financing influence firms’ labor market power and wage of skilled workers? How does the labor market power channel, in return, shape firms’ leverage choice and the distribution of firm size in the economy? We investigate these questions using administrative data from the U.S. census. We start by building a model based on Jermann and Quadrini (2012), which describes the interaction of financial conditions and investments, and further incorporating labor market dynamics into the framework. In our model, firms compete for skilled workers and offer different levels of wages and job safety. Higher debt capacity leads to higher job security, helping firms to recruit and retain skilled workers ex ante. Firms make optimal leverage choices in anticipation of this effect, and the leverage choices, in return, can influence firms’ ex post bargain power and the split of surplus between firms and skilled workers. Our model suggests that differential access to financing across firms amplifies labor market concentration and yields nuanced implications for leverage. We provide evidence from reduced-form regressions to validify our model predictions. We also quantify the importance of the labor market power channel on the growth and size distribution of firms in the economy using a structural approach.

Qiping Xu* | Department of Finance | $23,084.75

Gender and racial disparities have persisted stubbornly in the United States. According to the 2020 U.S. Census Bureau survey, the median household income was $60,128 for Blacks, approximately 50% lower than the median of $90,500 for White Americans, and women earned 83 cents to every dollar earned by men. Although an extensive research body exists studying gender and racial inequality through factors such as discrimination and education (see Altonji and Blank 1999, Fryer 2011 for a review), the role of firms and financial markets remains less understood. This proposal describes two projects aiming to fill the gap. Our findings can have important policy implications in light of the persistence of the gender and racial wage gap and increasing awareness of diversity issues in the United States. Our proposal contains two projects aiming to fill the gap. In the first project, we investigate to what extent firm-level political ideology influences employee inequality. We ask whether firm political ideology, measured using the executives' political affiliation obtained from voter registration records, trickles down the corporate echelons and shapes inequality among rank-and-file employees. In the second project, we examine whether better access to the debt market can help attenuate employee inequality. We exploit the staggered introduction of anti-recharacterization laws in U.S. states, which facilitated debt financing by strengthening lenders' ability to repossess collateral in bankruptcy and study its impact on employee inequality.

Jordan Samet* | Department of Accountancy | $20,887.08

Teams and team-based work are fundamental to organizations – aiding in innovation and collaborative solutions. In addition, by working in teams, individuals develop relationships and social bonds that further benefit these individuals (e.g., growth through peer learning) and the organization (e.g., increased productivity). Yet there are often impediments to the development of team cohesion, such as a lack of shared life experiences among diverse teams. Given the moral imperative to improve diversity, equity, and inclusion in organizations and the empirical evidence noting the benefits of diversity, we look to examine how the framing of team incentives can help overcome the barriers to team cohesion and collaboration among diverse teams. Using multiple experiments, we plan to test the hypothesis that peers working under a loss-framed incentive, relative to a gain-framed incentive, will perceive the incentive as a shared hardship. This shared hardship increases feelings of closeness among peers resulting in greater team cohesion and cooperative behavior. Importantly, we expect the shared hardship to act as a substitute for shared life experiences, leading to the benefits of loss-framed incentives on team cohesion to be greater for highly diverse teams.

Ish Minefee* | Department of Business Administration | $18,652.48

The objective of this project is to advance a research agenda on multinational corporations' (MNCs') engagement in sociopolitical activism (SPA). This an increase in this phenomenon, research focusing on MNCs is lacking. Yet, MNCs allow for an opportunity to validate and extend theory on the antecedents and consequences of corporate SPA. Additionally, there is room to generate theoretical insight on the decision-making processes surrounding MNCs' SPA. I seek to create the first database on MNCs' SPA focusing on the time period of 2007-2022. In alignment with the values of Gies, advancement of this research agenda will add to academic insight on the shift in corporate purpose towards MNCs' involvement in addressing social challenges as well as how MNCs' create initiatives that enhance diversity, equity, and inclusion not only in the US but globally.

Denise Lewin Loyd,* David Reinhard | Department of Business Administration | $18,615.54

Our proposed work capitalizes on the new BioLab and corresponding iMotions physiological instruments, recently acquired by the Gies Business Research Lab (GBRL), to follow up empirical findings from our work on interactions between and within minority and majority group members in diverse groups. A major component of this research is exploring how concerns about appearing biased (bias concerns) influences the way majority group members treat those in the minority. However, our prior findings show that asking about bias concerns via self-report (e.g., "Are you concerned with looking biased toward the woman?") changes the way participants subsequently respond and behave. Examining these bias concerns at the physiological level will allow us to determine whether bias concerns influence intergroup interactions in ways that are implicit and not under the conscious control of participants. We propose to use all three of the iMotion instruments, including the: Eye Tracking system, Galvanic Skin Response, and Facial Action Coding System. Our proposal furthers Gies’ strategic priorities related to diversity, equity, and inclusion by exploring physiological reactions to changes in diversity (i.e., moving from having one numeric minority to two numeric minorities) and the social inclusion (vs. exclusion) behavior of majority group members.

Ying Bao* | Department of Business Administration | $14,404.88

With recent developments of digital technologies, the mobile phone has been playing an increasingly important role in consumers daily life. Meanwhile, more individuals are subject to digital addiction problems (WHO, 2017). We propose a field experiment in collaboration with a company that has designed a mobile phone application to help users track and reduce their phone usage. Our model results predict that tighter goals can be more helpful to users with high motivations; while users with lower motivations may benefit from a looser goal. We hope to experiment with assigning individuals tighter and looser goals, measure their motivations, and compare the short-term and long-term effectiveness of different levels of goals in helping reduce mobile phone usage. The results of our paper will contribute to goal-setting and self-control literature and will be broadly useful to phone users, firms, policymakers, and healthcare providers along with those struggling with regulating their mobile phone usage. Moreover, the insights could be generalized to other domains that involve goals and efforts, such as smoking cessation, weight loss, energy conservation, online education, and so on.

Jaewon Choi,* Taek Pae, | Department of Finance | $13,850.85

ESG investing has become one of the most critical issues in asset management. In this research program, we aim to study challenges facing asset managers in implementing ESG targets and the implications of such investing policies. Potential research questions include (but not limited to) the following. First, how is carbon transition risk priced in the financial markets, across asset classes and countries? The literature is still in its infancy, and we plan to provide a comprehensive examination of carbon risk on asset prices and the underlying economic mechanisms of carbon risk. Second, how do asset managers achieve net-zero emissions in their portfolio firms? Would they implement different net-zero strategies in developed markets versus emerging markets? We will examine the extent to which investors chase short-term performance in emerging markets while sacrificing environment-friendly investments. Third, do asset managers that care social values, compared with those that are indifferent to those values, provide better performance? Recently introduced ETFs, for example, MAGA, DRILL, VICE, and ACVF, focus on conservative values and are somewhat anti-ESG when selecting investment targets. We want to perform a full-scope analysis of these ESG-indifferent funds and compare their performance to popular ESG funds to provide insights to investors.

Don Fullerton* | Department of Finance | $13,850.85

Current households don't even know what items can or cannot be recycled. Their containers include food waste and other non-recyclable contamination. Here, I propose a pilot study of 150 households divided into a control group, a treatment group receiving special information, and a second treatment group receiving that information plus incentives for quality recycling. We will weigh weekly garbage and recycling cans, and estimate impacts of these treatments on garbage, recycling quantity, and recycling quality. This pilot study is not large enough for high statistical significance, nor to estimate heterogeneous treatment effects by income, age, or ethnicity. The full study might need 1,500 households. But the pilot is important to test and to practice our procedures for the full study, and for power tests to calculate the needed number of households for the full study to be proposed to the NSF and other foundations.

Min Jung Kim* | Department of Business Administration | $13,573.83

In this project, I examine how entrepreneurs – in particular, novice or minority entrepreneurs – can benefit from the positive externalities owing to shrinking industry clusters (i.e., regions where the geographic concentration of industry activity is high). I specifically look at the effects of cluster decline on entrepreneurs’ venture creation and the effects on existing venture firms’ establishment of alliances or collaborations with other organizations. I expect that shrinking clusters can be beneficial for entrepreneurs – in particular, novice or minority (e.g., female or ethnic minorities) entrepreneurs – and their venture firms. This is because a period of decline in the geographic concentration indicates that firms in the focal region and industry are increasingly leaving the focal clusters and likely to free up some resources. Given that, local entrepreneurs and their firms can access more easily these freed-up resources, such as talented inventors or opportunities to collaborate with other firms or university labs, which otherwise may not be accessible to them.

Yusaku Takeda* | Department of Business Administration | $12,004.07

In recent years, many new businesses have used political ideology to forge a corporate identity to attract investors, customers, and regulators who share political values. We conceptualize this phenomenon as the political coupling of venture identity and develop a theory that illustrates how this approach is a double-edged sword. Political coupling allows entrepreneurial firms to mobilize resources by persuading enthusiasts who share political values, but it also exposes businesses to external political polarization-depolarization dynamics. We take a mixed-methods approach: We combine a quantitative study of archival data to capture the overall dynamics and qualitative interviews to illuminate key mechanisms. Our contributions are three-fold. First, we extend the growing literature on political ideology and organizations to entrepreneurship research. Second, we bring a longitudinal perspective to the literature on entrepreneurial resource mobilization to illustrate that an initial resource-mobilization strategy may have an enduring consequence on the firm’s abilities to scale beyond core enthusiasts. Extant research on venture identity and resource mobilization attends exclusively to the initial identity formulation with little insight into its enduring consequences. Third, this research will shed light on how the effects of ideology on firm behavior and performance must be understood in conjunction with the broader political climates.

Tiffany White,* Nicole Davis | Department of Business Administration | $12,004.07

This research investigates the impact of disruptively positioned brands (DPB) on consumers’ trust of remaining brands in the category. A DPB is a brand that adopts a strategy in which it attempts to convince consumers that it is meaningfully distinct - not just from other brands in the category, but from the category itself (Morgan, 2004). We propose that DPBs influence perceptions of existing brands by increasing the salience of risks associated with the category as a whole – which they then separate themselves from. In so doing, DPBs undermine trust for existing brands in the category it disrupts, and does so disproportionately for bigger, more iconic brands, while simultaneously increasing trust in disruptive brands. This research informs marketing strategists and policymakers by elucidating the underlying process that signals and drives consumer (dis)trust in (established) disruptive brands.

Hongyan Liang* | Department of Business Administration | $11,080.68

The platform economy is on the rise globally, together with the speculation as to how it will affect the future of work. Emerged in 2009, China’s online food delivery market has expanded vastly towards an oligopolistic structure. In 2019, two dominating platforms have a combined 7 million registered couriers. This number almost doubled to 13 million after COVID-19, accounting for nearly 1% of the country’s population. As opposed to food-delivery platforms in the US, which classify couriers as independent contractors, platforms in China’s platforms introduced the three delivery models, including the franchise model, the on-demand crowdsourcing delivery model and the hybrid model. Hired by franchising stations, station couriers work in team as employees, but cannot refuse orders assigned by the platform. Crowdsourced riders are the real gig workers who can choose orders and work individually in flexible hours. Riders under the hybrid model surrender some autonomy for stable orders and income. The proposed research will use multi-source data including surveys, interviews, and social media data to analyze how couriers make choices from different work arrangements, and their mobility patterns within the platform.

Joseph Mahoney,* Fiona Yao, Xin Wang | Department of Business Administration | $11,080.68

The goal of our research project is to deepen the understanding of the impact of deglobalization backlash on multinational firms’ strategic decisions and performance. During the last decade, the world has been stepping into an era of deglobalization where the open market and economic integration have lost their attraction. A surge of pro-market policies retraction, accompanying a growing atmosphere of populism, shaped a more than ever complex environment for firms to adapt. What will multinational firms do under the deglobalization pushback? Will they fight or flee? Where will they fight, and where will they flee? If they fight, is there a smart way of doing so? Those questions are vital not only to multinational firms themselves but to a wide range of stakeholders across countries. In this research project, we view multinational firms as investment portfolios across time, sectors, communities, and countries and introduce portfolio-based factors to appreciate the pervasive interdependences involved in MNEs’ cross-border activities. Meanwhile, addressing the socio-political nature of deglobalization, we aim to identify different forms of deglobalization and explore how deglobalization presented matter. We maintain that the narratives of the political leader and the country’s history will determine where multinational firms posit in the confrontation within and between countries. With forms of deglobalization classified and the portfolio-level logic adopted, the current project will enable us to better explain and predict multinational firms’ decisions on divestment, expansion, and non-market strategy adoption.

Aravinda Garimella,* Tiffany White | Department of Business Administration | $9,510.92

Given the increasing use of algorithms by companies, there is growing consensus that consumers have a right to know when an algorithm is making decisions that affect them. However, companies are often not transparent about the use of algorithms, and even when they are, consumers are usually in the dark about what they are using algorithms for and how they are using them. In this study, we first examine the effect of algorithmic transparency on brand attitude and whether this effect differs for historically excluded social groups. We explore mechanisms through which such transparency could affect brand attitude. We then explore the effectiveness of two types of strategies, verbal and action-oriented, that can help companies maintain or improve brand attitude in the presence of algorithmic transparency. Our research is a call to brands to center algorithmic transparency in their consumer engagement strategy. We aim to offer insights that will shed light on how companies can include and genuinely empower consumers in the algorithmic age.

Nolan Miller,* Jiameng Zheng | Department of Finance | $8,310.51

Despite more than 30 years of efforts to limit lead exposure and about $2.0 trillion (measured in 2017 dollars) invested to provide safe drinking water since 1974 (Keiser and Shapiro, 2019), nearly 10 million people annually in the United States still drink water from utilities that violated the Lead and Copper Rule. This main regulation governs lead concentration in drinking water (Fedinick, 2018). Early childhood exposure to lead has irreversible health and behavioral consequences, as fetuses and young children absorb lead to a greater degree than adults (Hanna-Attisha et al., 2016). Despite the wealth of evidence of the harms of exposure to lead through sources like gasoline and paint, there is little evidence of the first evidence of lead impact from drinking water. Since ingested lead (from drinking water or paint chips) and inhaled lead (from gasoline or paint dust) is absorbed differently by the human body (Atsdr, 2020), there is an important gap in the literature in terms of the potential public health and economic ramifications. This project will use individual level blood lead levels data from the CDC and drinking water lead information from US EPA to identify the impact of drinking water lead on children’s blood lead levels.

Michael Roach* | Department of Business Administration | $7,431.44

Universities play an essential role in the creation of fundamental research discoveries that spur innovation, entrepreneurship, and economic growth. And yet, we have a limited understanding of which university discoveries are commercialized, whether this is through university startups or established firms, and the respective roles of faculty and graduate students in university startups. This is largely due to the difficulty of obtaining detailed longitudinal data at the invention and inventor level across different universities. To investigate these questions, I have constructed a dataset that combines university administrative data on invention disclosures, licensing agreements, and startups from four leading research universities with data on inventor career histories, patents, and venture capital investments. This small grant proposal seeks funding to include UIUC Office of Technology Management data into this project. The funding will be used to hire undergraduate RAs to match university administrative data to external data from LinkedIn, Pitchbook, SBIR, and US patents for all university inventors, startups, and startup founding team members. This project aims to provide new empirical insights on the broader societal and economic impact of university research discoveries with implications for academic scholarship and science & innovation policy.

Kim I Mendoza,* Yuepin (Daniel) Zhou | Department of Accountancy | $6,463.73

Fraud detection, despite its importance, remains a challenging task for many auditors. We aim to experimentally examine how interoception affects auditors’ deception detection capabilities. Interoception is an individual’s ability to sense their body’s physiological state. Individuals with higher interoception are more likely to incorporate their body’s physiological reactions into decisions, even when their brains do not consciously pick up on these stimuli. We predict that auditors with higher interoception will better detect deception since they are more likely to pick up subtle physiological stimuli than their counterparts with lower interoception. We also predict that the positive effects of interoception on deception detection is larger when the medium of communication is via audio than via text because the former medium contains more stimuli than the latter. Across two proposed experiments, we will examine the effects of both trait levels of interoception (Experiment 1 with undergraduates) and the effects of an interoception training intervention (Experiment 2 with auditors) on deception detection when the communication medium is either text or audio. We expect our findings to inform the practitioners and the literature on the factors that affect deception detection and tools that will improve auditor deception detection capability.

Andrea Rozario* | Department of Accountancy | $5,501.56

We investigate whether investors’ judgments are affected by misinformation obtained from social media and whether there is a continuing effect after the misinformation is subsequently corrected. Misinformation reflects people’s perceptions about matters that are not supported by facts and expert opinion. Social media facilitates the rapid dissemination of misinformation thereby increasing the likelihood that it influences investors’ judgments and decisions. This raises concern about the unintended consequences of social media as a useful channel of communication that investors rely upon. We expect to find that investors will be influenced by misinformation on social media. Further, we propose that the continued effect of the misinformation will be influenced by the type of communication strategies the firm chooses to address the misinformation. Specifically, we expect to find that when the firm uses an explanatory communication strategy, the effect of misinformation on investors’ judgments is reduced. Our study aims to provide insights into the role of misinformation on social media on capital markets and communication strategies to mitigate the effect of misinformation.

Vidya Haran,* Sheny Lin | Department of Business Administration | $5,540.34

The research proposal aims to develop a toolkit of 3-4 cases to teach, conduct workshops, and practice design thinking in the classroom and across campus. These cases will be based on the design work conducted by Gies faculty in collaboration with Siebel Center for Design and Illinois Design Consulting. The cases will showcase the design solutions based on the unique needs and motivations of the UIUC community, solutions developed for and by community partners. This will also help promote learning through "I See Me" lens where students learn through cases where see they themselves and can relate to and identify with. This standardized toolkit of cases will also be used to highlight that UIUC actively engages in developing a design thinking mindset in classrooms, and also practice it in its everyday solutions.

Heather Swenddal* | Department of Business Administration | $5,170.98

Business schools are increasingly incorporating client-based projects into their curricula, providing students with hands-on experience in addressing real-world business challenges. Client-based projects offer valuable authenticity for student learning, yet they also introduce pedagogical complexity, moving learning beyond the structured purview of instructors. The working professionals who serve as clients in experiential projects impact learning through their interactions with students. However, they do so in different ways. Experiential-learning literature and practice has revealed variations in how project clients interact with students, raising questions about how clients envision their roles in these projects. The topic of client role identities is unexplored in current literature; we see an opportunity to address this gap. Gies College of Business is a leader in experiential pedagogy, running the largest client-based course in the United States with the support of the Magelli Office of Experiential Learning. We plan to leverage the Magelli Office’s extensive network to explore the role identities that inform project clients’ interactions with students. Through semi-structured interviews with 20-30 clients, we will identify patterns in client perspectives and develop a grounded-theory typology of client role identities and their associated behaviors. Expected outputs include publications in business-education journals as well as practice-focused papers and presentations.

Spencer B. Anderson,* Kimberly Mendoza, Cassie Mongold | Department of Accountancy | $4,616.95

We propose a study examining how financial statement users process the information found in parenthetical disclosures relative to other types of disclosure (e.g., in the footnotes). Using eye-tracking capabilities, we expect to find that parenthetical disclosure helps investors process the parenthetical information, but also elicits a distraction effect on other information. As an alternative, we expect to find that hover-over parenthetical disclosure will mitigate the negative distraction effects of parenthetical disclosure while still being conducive to information acquisition for investors. Our results have important implications for financial accounting standard setters and regulators aiming to provide effective disclosure to investors.

Julia Fonseca* and Jialan Wang  |  Gies College of Business  |  $118,000

This proposal combines leading-edge research projects by Gies faculty and students with data infrastructure that supports future research at Gies. It adds to an ongoing collaboration between the PIs and the Data Science Research Service (DSRS) to build the Gies Consumer and Small Business Credit Panel (GCCP). The GCCP is a rich dataset combining individual-level data on small business loans, personal credit, and alternative credit that has never before been used in academic research. The initial version of the GCCP is currently being rolled out and has received broad interest from Gies faculty for wide-ranging research projects.

This proposal describes four projects that will use the GCCP to study several important topics: the reliance of entrepreneurs on personal credit, unequal access to finance by women and minority entrepreneurs during COVID-19, the effects of market power and monetary policy on credit markets, and innovations in credit bureau data. We seek funding for research assistance, data analytics, and an expansion of the GCCP. This funding is critical because the data provider purges information on an ongoing basis, and a timely update is necessary to preserve the ability to conduct research and to study the effects of the COVID-19 economic crisis.

Tatyana Deryugina, David Molitor, and Nolan Miller*  |  Gies College of Business  |  $100,000

We propose to acquire a new panel data asset consisting of 15 years of Medicare administrative data for a 100% sample of the U.S. elderly and disabled populations. With an average of 50 million individuals per year during the sample period, this dataset will contain annual information on demographics, summary health information, and detailed information on hospital visits. Because it is a 100% sample, the data are nationally representative for the elderly and disabled populations demographically, geographically, and in terms of health status. After initial purchase, the data will be accessible by researchers at Gies and throughout the campus by applying to the Centers for Medicare & Medicaid Services and securing a project-specific data use agreement for a nominal per-project fee of $2,000. Beyond providing a data source that is comprehensive enough to study rare health events and impacts on particular subpopulations, the data can also be used early in the research process to apply for external funding from sources such as the NIH or NSF. The Interdisciplinary Health Science Institute, Carle-Illinois College of Medicine, NCSA, Gies DSRS, and campus Data Justice Initiative have expressed interest in these data, potentially creating new opportunities for collaboration across the units.

Vishal Sachdev, Ramanath Subramanyam, and Sridhar Seshadri*  |  Gies College of Business  |  $100,000

We propose to form a Business Analytics Collaboratory as a systematic way to create and enhance corporate interactions such that area faculty can identify new research opportunities, and students from undergraduate and graduate programs benefit from the latest application of analytics. The investment in the Collaboratory will supplement our current investments in undergraduate and graduate programs, particularly, the new MS in Business Analytics program. We request support to identify firms, scope out research projects, publicize our efforts, make connections and develop new ideas. In the Collaboratory: (a) Faculty will work with firms in boundary-spanning research problems at the interface of business processes, healthcare operations, public policy, and analytics. (b) Firms will share problems and learn best practices from faculty and each other, thus enriching our research /teaching endeavors. (c) Build upon such interactions for pedagogical innovations such as, innovative data cases, sponsored data competitions, and more. (d) Create opportunities for faculty engagement with alumni‚ where alumni can be both participants or sponsors. (e) Develop deeper relationships with firms to become corporate affiliates. And (f) Facilitate student engagement with industry mentors and analytics practice.

Jessen Hobson, Sharon Shavitt, and Jennifer Themanson*  |  Gies College of Business  |  $99,480

Over the first year, Gies Business Research Lab (GBRL) has prioritized expanding current participant pools to include alumni, online master's programs, and community members in order to provide researchers with expanded and unique opportunities to recruit a diversity of participants. Our priority at GBRL is to collaboratively facilitate as many behavioral projects as possible, fostering an environment that supports innovation in study design and methods. GBRL is focused on responding to the emerging needs of Gies researchers and providing tangible support and structure that leads to demonstrable excellence in data collection, analysis, and publication. With this mission in mind, the three main goals of this funding proposal are to serve the emerging needs of behavioral researchers across the college by growing, cultivating, and maintaining participant pools, support efficient and rich data collection through best practices related to recruitment, management, and incentivizing studies, and provide support for innovative and pioneering research methods employing new technologies and designs that expand the business relevance of Gies research and promote Gies Innovation and Excellence in Research.

Nerissa Brown, Martin Persson,* and Kecia Williams  |  Department of Accountancy  |  $68,796

The accounting profession has long recognized the need to increase workplace diversity, as highlighted by the Pathway Commission report in 2012 and several recent initiatives to support underrepresented minority students, professionals, and scholars. Nonetheless, the most recent report from the American Council on Education (2019) finds that underrepresented minority scholars continue to occupy only a tiny fraction of university appointments and that they face higher barriers to promotion and tenure compared to their peers, despite no discernable difference in job performance. Our research project explores the historical presence and contribution of underrepresented minority scholars to the development of accounting thought before the passage of the Civil Rights Act of 1964, which prohibited discrimination and segregation in higher education. We are not aware of any prior studies exploring this topic, although historical evidence suggests that underrepresented minority scholars’ contribution has and continues to shape our discipline. The funding proposal seeks to defray the cost of creating a unique dataset of all English language accounting articles published by underrepresented minority scholars from 1881 through 1964. The main product of our research project is aimed at a proposed special issue of The Accounting Review focused on diversity and social justice, with auxiliary articles targeted at other top-tier journals.

Jack Goncalo, Maria Rodas, Sharon Shavitt, and Carlos Torelli*  |  Department of Business Administration  |  $67,803        

We are seeking large financial support to launch the Multicultural Insights Lab (MIL) to benefit multiple faculty in BA. This initiative would leverage our unique expertise in cross-cultural behavior in BA, and address timely research questions prompted by major demographic and societal changes impacting U.S. cultural values and norms. Specifically, MIL will focus on investigating how the contrast between individualistic and collectivistic cultural ideals confounds efforts to address major societal and business challenges (e.g., debates pitting individualistic views about the right to refuse to wear a mask against the collective need to battle COVID-19), and help marketers and managers understand and respond to these cultural contrasts. The MIL initiative will support cutting-edge multicultural academic research, as well as disseminate findings from this research to practitioners and others through courses (e.g., MOOCs, executive education modules), consulting, and conferences. These objectives align with Gies’ strategic priorities of fostering excellence in research and expanding access to our world-class education. This initiative will also help Gies to claim a unique leadership position in this pivotal area.

Benjamin Osswald and Anh Vuong Persson*  |  Department of Accountancy  |  $49,728

The landscape of corporate tax transparency has changed dramatically within the last decade. Since 2013, several governments have adopted or are currently considering adopting country-by-country reporting, a new framework that requires multinationals to disclose tax payments and economic activities in every jurisdiction in which they operate to the relevant tax authorities. Although these reports remain confidential, many multinationals voluntarily disclose this information to the public. Given the tremendous demand from both regulators and investors for access to these reports and the reputational and proprietary costs of disclosure, our project set out to understand the determinants and consequences of this voluntary disclosure practice. The findings from our study will help regulators and investors to understand the factors that drive firms' decisions to be more tax transparent and inform managers on the economic consequences of their disclosure choice. To answer these research questions, we aim to create a unique granular dataset on voluntary country-by-country report disclosures of the largest multinationals headquartered in more than 70 countries. This dataset will allow us to examine our main research questions set out above and other important questions related to tax disclosure, transparency, and corporate social responsibility.

Denise Loyd*  |  Department of Business Administration  |  $49,500

Organizations are focused on increasing their diversity. However, even with proportional representation, some social categories will remain in the distinct minority in groups. Thus, understanding experiences in these groups is critical. I focus on the experience of solos and minority duos (one of exactly two members of a minority subgroup). I examine how group composition affects the behavior of members of the majority towards members of the minority, specifically the extent to which the majority members include duos in the groups’ activities relative to solos. If individuals in groups with duos are less concerned about how their actions toward members of the duo appear to others, they may be less attentive to making sure they include them in the group. In this case, increased diversity may actually result in decreased inclusion. Further, I explore how group composition affects how solos and duos relate to others in the group. The presence or absence of a similar other in a group can lead to cooperation with, competition against, or simply indifference toward other group members. This work will enhance scholarly understanding of dynamics in diverse groups and help leaders better manage diversity.

Dylan Boynton, Deepak Somaya,* and Jingya You  |  Department of Business Administration  |  $41,267

A research program on business models and business model innovation is proposed, with its primary focus being the creation of a novel transformative dataset on business models. Taking advantage of a major change in disclosure requirements in the United Kingdom, this longitudinal dataset (2014-2021) would include the business models of all firms listed on the London Stock Exchange and would be complemented by financial and stock market data. Two main research projects are proposed that will use this dataset. The first project will examine the digital transformation of companies following the COVID-19 pandemic and assess the drivers of firms' adoption of various digital business model innovations and their impacts on performance. This research promises to provide valuable insights into how firms respond to significant external shocks and how business model innovations affect firm performance. The second project will use text analysis of companies' self-described business models in order to address important definitional questions in the field about what constitutes a business model and how it differs from strategy. It is anticipated that the research database of business models will also serve as a valuable research platform for PhD dissertations and other large-scale projects at Gies.

Elizabeth Luckman,* Gretchen Winter, and Patricia Werhane  |  Gies College of Business  |  $39,750

A multidisciplinary team of diverse tenure-stream and specialized faculty will create relevant and innovative classroom educational materials that explore emerging issues of professional responsibility pertinent to today's complex, global business environment. The educational materials will focus on true-to-life ethical dilemmas in business and thereby help meet expressed demand by surveyed Gies faculty so they can enrich their students’ thinking about ethics and professional responsibility issues. We also will lever qualitative and quantitative research methods to glean and organize insights from 50 business ethics pioneering scholars, who have expressed their views on pressing research questions about business ethics. The collective insights and different themes expressed by these scholars will inform the agenda for future research on business ethics and professional responsibility across numerous disciplines including accounting, AI and business analytics, finance, diversity and inclusion, and entrepreneurship.

Sarah Ward*  |  Department of Business Administration  |  $39,097

Stress experienced at work is a key threat to worker and organizational well-being, leading to poor motivation, performance, and health as well as increased turnover (American Institute of Stress, 2017). Over 80% of employees experience stress at work and report it as a key source of psychological and physical illnesses (American Institute of Stress, 2017). Despite these problems, few reliable solutions exist for reducing workers’ stress. Identifying how to mitigate workers' stress is a crucial goal with substantial theoretical and practical importance. Studies in the proposed research will investigate whether meaning in life and meaningful work can facilitate lower occupational stress and improved work motivation. These studies will also examine mechanisms that account for the stress-reduction benefits of meaning and examine if these stress-reduction benefits also promote improved work motivation. Importantly, this project will involve developing and testing stress-reduction interventions aimed at enhancing meaningful work and meaning in life among workers in high-stress occupations. Together, these studies will clarify how meaningful work and meaning in life can reduce stress and promote improved motivation.

Anton Ivanov,* Ashen Mehmet, Ujjal Mukherjee, and Sebastian Souyris  |  Department of Business Administration  |  $34,000

COVID-19 has globally disrupted supply chains in healthcare, automotive, natural resources, energy, and other sectors. However, disruption of different sectors and tiers of supply chains has been different. We intend to understand sources of disruption of supply chains, strategies that help supply chains recover from disruption, and evaluate the effectiveness of different risk mitigation strategies that can help supply chains in preparing for future potential disruption. Our research aims are threefold: (i) collect and organize global supply chain data to estimate the impact of COVID-19 related disruption, (ii) model the time to recover from the supply chain disruption, and (iii) model potential future risk mitigation strategies. The intended outcomes include academic research papers that address two important aspects of supply chain: understanding vulnerabilities and preparedness for disruption. This work is a continuation of the ongoing efforts towards mitigation of COVID-19 from the team that is currently engaged in understanding COVID-19 testing and vaccination strategies, and prediction of diffusion of the disease. We seek funds towards supporting data collection and research support. This funding will enable us to extend current work in practically significant and theoretically interesting directions, and addresses the intersection of supply chains and disruptive events such as COVID-19.

Fernando Luco and Unnati Narang*  |  Department of Business Administration  |  $32,376

U.S. drivers record 3.22 trillion miles on the roads each year. Granular information about their movement is constantly tracked by apps on their smartphones. This information can be useful for retailers to interact with consumers real-time. However, collecting these granular data also leads to privacy concerns among consumers who may feel invaded by the extent of real-time tracking, and regulators who are concerned about how firms treat consumer data. Thus, such tracking introduces a trade-off between the value of these data and privacy concerns for firms. Furthermore, modeling spatio-temporal driving data is challenging because they are computationally intensive and high dimensional. To solve these challenges, we propose a deep learning algorithm that combines convolutional neural network (CNN) and a long short-term memory model (LSTM) using individual driving trajectories in order to learn from driving data, predict retail visits and quantify value-privacy trade-offs. Our efficient modeling approach will be tremendously useful for studying important spatio-temporally heterogeneous global phenomena, including movement patterns during a pandemic, and the implications of data-tracking by firms in retail, freight, and shipping. Thus, such an approach can benefit researchers across different domains including marketing, information systems, supply chain, and public policy at Gies, on campus and beyond.

Bethany Brumley, Keith Czerney, Anne Thompson,* Devin Williams, and Wei Zhu  |  Department of Accountancy  |  $25,000

Funds data acquisition to conduct studies examining the role of auditing in the $3.8 trillion municipal bond market and governmental/not-for-profit sectors (these purchases provide financial statement data and an audit report mapping file). The first study examines the impact of COVID-19 on audit planning and audit adjustments using a unique set of audit work papers for state and local governments. Second, we will test the presumption in professional standards that unpredictability in audit programs is important for detecting and deterring fraud by exploiting a shock to auditors’ scoping decisions imposed by the Office of Management and Budget. Third, we will augment an existing study with promising results by examining whether municipal bondholders perceive differences in audit quality when the auditor is voluntarily registered with the PCAOB. Finally, we will test whether the online launch of the Federal Audit Clearinghouse impacted the municipal bond market. These purchases will benefit at least four researchers in the College, are aligned with the College's strategic priorities for excellence and innovation, further the university’s land-grant mission, and position researchers in the College to respond to future RFPs.

Robert Brunner, Justin Leiby,* and Anh Persson  |  Department of Accountancy  |  $25,000

This project will explore mechanisms to increase underrepresented groups' employment, firm ownership, and wealth accumulation when high barriers to entry are present. We focus on the role of social networks that develop among high status actors, a common barrier to success for underrepresented groups. The project will explore these networks and examine how public policies intended to increase diversity affect the evolution and negative effects of these networks. To collect data, we will collaborate with the State of Illinois to reengineer its processes to collect, manage, and process data on the diversity of participants in the state’s cannabis industry. This will involve redesigning the state's existing survey that all market participants must complete and building a web-based tool to host and administer the redesigned survey. We believe this proposed research project advances multiple strategic priorities of the Gies College of Business, most importantly by directly influencing the regulation of diversity, equity, and inclusion practices in Illinois. It will also open potential avenues for research, curricular, and co-curricular collaborations between Gies and the State of Illinois.

Carlos Inoue* and Leandro Pongeluppe  |  Department of Business Administration  |  $19,840

Entrepreneurship has the ability to create wealth and improve the standards of living. Yet, most entrepreneurs fail at growing their business due to capital constraints and lack of management experience. This project seeks to evaluate the impact of cash provision and financial advice on entrepreneurial growth in low-income communities in Brazil. In partnership with a non-governmental organization (Banco da Providencia), a leading provider of financial technology solutions (Stone), and municipal governments in Brazil, we will randomize cash grants and financial advice to micro-entrepreneurs in multiple low-income communities in the country. We will be able to track business decisions of entrepreneurs using Stone’s financial technology solutions and examine the impact on business growth and personal income. This project will enrich our understanding about entrepreneurs and entrepreneurial programs and provide lessons to governments and communities in low- and middle-income countries.

Vic Anand* and Theodore Sougiannis  |  Department of Accountancy  |  $19,100

We propose two machine learning-based fundamental analysis projects. In the first project we will attempt to improve the forecast accuracy of extant models with additional predictors that have been shown to have predictive ability, such as nonfinancial information (e.g., firm life cycle, order backlog), past market information (i.e., information the market has impounded into prices), and macroeconomic expectations. In addition to predicting earnings, we will explore the prediction of cash flows given that prior related papers have focused only on the prediction of earnings, and theoretical valuation models establish an equivalence between cash flows and earnings in fundamental analysis. Therefore, whichever can be predicted more accurately will be more useful in forming investment portfolios. In a second project, we will compare the investment performance of magnitudes and directions (i.e., up/down) predictions. While prediction of magnitudes is theoretically more desirable, it also comes with potential larger error than the prediction of directions. It is an empirical issue whether the prediction of magnitudes generates better investment performance than the prediction of directions. In case both perform equally well on average we will perform conditional analysis to discover the conditions under which one performs better than the other.

Kimberly Mendoza,* Roshan Sinha, & Michael Yip  |  Department of Accountancy  |  $17,876

The use of virtual reality (VR) is growing in a vast number of industries and settings. Individuals can currently find business-related VR experiences, such as viewing new technologies/products, attending investor meetings, and visually comparing financial data for investment funds. As the use of VR increases, it is likely this technology will be used in more investor experiences such as earnings calls. Prior research finds that greater immersion experienced through VR leads to stronger emotional responses than less immersive devices, such as videos. The purpose of our study is to investigate how more immersive technology such as VR will influence investor judgments and decisions. We plan to conduct two experiments to answer our research question. In both experiments, participants will assume the role of an investor watching an earnings call either via video or VR. We will also manipulate whether the earnings news is good or bad. We will measure investor judgments and decisions after the call. Our second experiment will explore the process and theory for why individuals respond differently in the VR modality. We are applying for this grant because creating a fake earnings call and a VR application are more involved and expensive than a typical experimental study.

Spencer Anderson,* Mike Durney, Shannon Garavaglia, and Kurt Gee  |  Department of Accountancy  |  $10,000

Our study proposes to examine how professional investors view the usefulness of different ways of measuring assets. To examine investors' perceptions, we plan to conduct a comprehensive survey with follow-up semi-structured interviews. This study will be the first to survey professional investors and gather large sample evidence of how and why professional investors use accounting information with different measurements. Our proposal is motivated by the relative lack of empirical data informing standard setting bodies such as the Financial Accounting Standards Board (FASB) surrounding measurement guidance. Existing standards prescribe a mixed-measurement model for companies in which different types of assets are measured in different ways. This mixed-measurement approach assumes that investors prefer different measurements for different assets, and that certain measurements are more useful for certain investing activities (e.g., ascertaining liquidity versus firm value). The FASB is currently developing a Conceptual Framework chapter on measurement to guide their standard setting decisions for measurement. By equipping standard setters with evidence on investor preferences for certain measures, this study can help the FASB develop a conceptual foundation for measurement that is grounded in investors' views, rather than assumptions about investors' views.

Abhijeet Ghoshal*  |  Department of Business Administration  |  $10,000

I will study the sampling process from a network to best represent the original network. These projects will have wide applications, and I believe they can be published in top journals. However, these projects are computationally intensive. In order to properly complete the studies, I need efficient, high-performance computers. The cluster computers provided by the Illinois Campus Cluster Program are suitable for this purpose. Given the long-term nature of the projects, participating in the cluster program by investing in it is the justified approach. For that, I need to invest in at least one node. Through this proposal, I am requesting the money to invest in the campus cluster. The cluster computer can also benefit other faculty in the area who needs high-performance computing.

Daniel (Yuepin) Zhou*  |  Department of Accountancy  |  $8,300

Auditors work in hierarchical teams in which effective upward communication is critical to audit quality. However, academic research and regulator findings suggest that auditors may at times struggle to speak up. In this study, we examine the joint effects of auditors' workplace identity (professional vs. political identity) and team distribution (distributed vs. non-distributed team) on auditors' willingness to speak up. We propose that auditors with a strong political identity (i.e., focused on advancing their careers) are less likely to raise potential audit issues in distributed teams than in non-distributed teams. We further predict that auditors’ reluctance to speak up in distributed teams can be mitigated when auditors have a strong professional identity (i.e., focused on serving the public interests). We expect our results to address regulators' concern on the impact of distributed teams, a common phenomenon in the current audit environment due to advances in technology and disruptions caused by the pandemic, on audit quality, and inform practitioners on how firms may mitigate the potential negative impact of distributed teams through firm culture and tone at the top.

Estha Gondowijoyo, Christie Hayne,* & Pamela R. Murphy  |  Department of Accountancy  |  $5,000

We analyze 38 stories of group fraud, half from the perspective of someone who committed group fraud and half from the perspective of someone who resisted joining a group fraud. Our goal is to better understand the controls that helped push people toward group fraud or against it. With data collection complete, our analysis examines the effects of social versus administrative controls. Social controls are based on the influence of others (e.g., culture, mentorship, management style) rather than rules or policies to which individuals must adhere (e.g., reward systems, internal controls). We find that social controls are significantly more influential than administrative controls in pushing respondents toward fraud, but that these controls also support respondents’ resistance. For example, management style and culture played significant roles in pushing some respondents toward and others against fraud. Our field study includes tentative control combinations that appear to have an even greater influence on decisions to join or resist fraud. Financial support would permit us to hire an expert in qualitative comparative analysis (QCA)‚ an advanced set theoretic technique that would allow us to identify “causal recipes” or combinations of controls in our data that commonly push individuals toward or against fraud.