Matias Carrasco Kind,* Julia Fonseca | Gies College of Business | $119,686

This proposal enhances the Gies Consumer and Small Business Credit Panel (GCCP), a distinctive dataset featuring comprehensive credit histories from 2004-2022, including a combination of consumer, subprime, and small business credit records. The initiative is critical for sustaining the dataset’s availability as a research tool for Gies faculty and students. This proposal advances data management and governance, including authorized user access, integrating GCCP into a sophisticated database, and providing analytical and visualization resources. To effectively handle these operations, this proposal supports the hiring of additional research assistants and expanding the extant computing infrastructure. Our budget also allocates funds for data provider updates and cloud computing improvements. Overall, this proposal pursues the strategic priorities of Gies Business: fostering innovation, excellence, and inclusivity in research. It will enable high-quality research addressing vital questions on financial health and inclusion, particularly concerning underrepresented groups.

Rosanna Smith,* Dan Zhou,* Jen Themanson | Gies College of Business | $105,000

The Gies Behavioral Research Lab (GBRL) enhancement proposal will improve three key resources. First, in technology and infrastructure, it will invest in web-based eye trackers/biosensors, a dedicated Sona platform for the Gies Online pool, and replacement of outdated laptops to support data collection and research needs. Second, the "Gies Excellence in Research Student Initiative" aims to support PhD students through seed funding for their dissertations and summer papers, fostering preparedness for the competitive job market, and expanding the undergraduate research assistant program to engage students in critical research projects. Third, it focuses on the growth and support of participant pools by establishing partnerships with external entities like Verasight and LinkedIn to recruit targeted participants, addressing specific demographic needs of Gies researchers. Additionally, funding is requested to provide incentives for participants involved in paid studies. The proposal emphasizes continual evaluation, ensuring accountability, and assessing both researcher and participant experiences. Overall, this proposal will expand GBRL’s technological resources, support of graduate student research, and enhance participant pool access to elevate the quality and impact of Gies behavioral research.

Arkadiy Sakhartov* | Business Administration | $85,000

The main resource in oil drilling are rigs whose use is the key to extracting over 4 billion barrels of unrecovered oil in Illinois. Such rigs embed various real options. A rig can be idled if its use gets unprofitable and reactivated if the profitability recovers; it can be redeployed to another oil field that provides higher profit; it can be divested; it can be upgraded to work more efficiently. Such flexibility increases the value of rigs to their owner and provides better employment opportunities. To what extent do drilling firms in Illinois use flexibility of their rigs? Are there ways to improve the use of rigs in the state? The proposed project will develop a formal/computational model characterizing the most efficient use of real options in oil-drilling and collect exhaustive data on deployment of drilling rigs in Illinois over three decades. The study will then empirically evaluate these data in terms of the use of various types of flexibility and the consistency of such use with the prescriptions of the formal model. This comparison will lead to recommendations on how to improve the use of drilling rigs in Illinois and to the publication of multiple research articles.

Julia Fonseca* | Finance | $66,350

This proposal outlines a study of the labor market consequences of mortgage lock-in and reduced mobility using novel data linking resumes and credit records. We propose to merge the Gies Consumer and small business Credit Panel (GCCP) – a state-of-the-art credit panel with linked consumer, subprime, and small business credit records – with individual employment records from online public profiles, résumés, and job postings. While labor-intensive, this merge will produce a dataset with very few analogs, if any, which we will make available to any Gies researcher who obtains a license to use these data. This work will create countless opportunities for cutting-edge work at the intersection of household finance and labor for the entire Gies community.

William Ocasio,* Pranav Gupta, E. Geoffrey Love | Business Administration | $65, 635

Organizational intelligence, defined as an organization’s ability to utilize knowledge and information to cope with and adapt to its environment, is becoming an important concept among organizational scholars. Yet, there is much potential to advance the concept. The Illinois Strategic Organizations Initiative (ISOI) proposes to establish Organizational Intelligence as an important programmatic focus, building upon its established leadership in corporate purpose. The strategic intent is to fundamentally advance and promulgate the concept of organizational intelligence to enable strategic adaptation under conditions of volatility, uncertainty, complexity, and ambiguity (VUCA) within organizations and their environments, focusing on complex adaptive systems of human and artificial agents and communication channels for knowledge development and decision-making. The proposal envisions two complementary activities. The first is theoretical and empirical research projects by the co-investigators and potentially other scholars that incorporate concepts from organization attention scholarship (e.g., shared and distributed organizational attention, planned and emergent communication channels) as well as recent work in collective intelligence, which has to date primarily focused at the group level. The second is building a transdisciplinary research community through a speaker series, workshops, and an international conference in Summer 2025, fostering cross-disciplinary connections and establishing Gies as a thought leader in organizational intelligence. 

Qiping Xu* | Finance | $47,500

Human capital has been one of the most important assets for firm value creation (Becker (2009), Crook et al. (2011)). However, there exists very limited evidence regarding how employees' political ideology and managerial networks affect talent allocation across large US public firms and geographic locations, and how such effects vary across corporate hierarchies.  This proposal describes two projects aiming to further our understanding in this area. Our findings can have important policy implications for human capital allocation and firm value creation in the United States. Meanwhile, the data effort proposed in this project will produce the most comprehensive database of worker employment history with individual political ideology in the US. It can be useful for any faculty interested in studying various drivers and consequences of workforce dynamics and political ideology- topics that are of broad interest to all areas both inside and outside of the Gies College of Business. 

Stefan Zeume* | Finance | $46,400

This is a funding request to purchase an annual subscription to RepRisk data. RepRisk contains environmental, social, and governance (ESG) scores for 220,000 public and private firms over the 2007 to 2022 period along with hundreds of thousands of ESG incidents such as environmental pollution or violations of regulations. ESG incident data identifies firms that caused the incident, incident location, and type of incident. Access to RepRisk data would (i) allow the principal investigator (PI) to substantially improve and extend an existing research project but also (ii) satisfy massive interest for access to RepRisk among the Gies research community: The PI plans to use the data to study the stock market response to domestic and foreign ESG incidents, distinguishing by type (environmental, social, governance, legal), location (foreign or domestic), and other event characteristics. Preliminary results on a much earlier iteration of RepRisk data (covering 2007-2015) indicate that shareholders punish incidents but less so when incidents occur abroad. Extension of the time series to 2022 will allow the PI to double the sample period, to include the COVID period (interesting because investors may be distracted from ESG incidents during that period), and to respond to reviewer feedback related to the obsolete data (ending in 2015) used in the current draft.  There is broader faculty and doctoral student interest in using among faculty in accountancy and finance to use RepRisk ESG data.

Ujjal Mukherjee,* Sridhar Seshadri | Business Administration | $42,000

The Healthcare Research and Analytics (HEART) group at Gies is a group of faculty members and postdoctoral researchers who are focused on conducting healthcare research and engagement with the practice of healthcare delivery. Following are our planned projects for which we seek funding. In partnership with a large multispecialty hospital from Mumbai, India, we will conduct a project on automating dementia detection using magnetic resonance imaging (MRI) and other related health measures. We have involved students from the Carle Illinois College of Medicine to conduct this project. The group received two-year funding from JUMP Arches for developing and implementing rural health kiosks. We have collaborated with a technology partner to develop the kiosk, and currently, we are gathering data from OSF and other sources to select the target regions. Additionally, our group has completed writing a case study on chronic care management using telehealth platforms, specifically, the CareSignal system. Our case study is currently being reviewed and edited for submission to Harvard Research Publishing. A primary activity that enables collaboration activities with healthcare organizations is the annual healthcare conference. We are publishing a book on learnings from COVID-19 as a follow-up to the healthcare conference in 2023. Finally, we are conducting research on the optimal funding of underserved communities. For this research, we seek to purchase data from the Hospital Cost and Utilization Project (HCUP). To conduct the research and collaboration activities, we are seeking support for a dedicated post-doctoral researcher who is skillful in data analytics and advanced computing techniques. 

Hyun Euh,* Maria Rodas, Carlos Torelli | Business Administration | $37,200

We propose longitudinal research that tracks cultural shifts over time in the digital era. Building on our previous project, which investigated the impact of political polarization on cultural orientation and market perceptions, this study aims to provide a more comprehensive, time-extended understanding of the phenomena. Specifically, we focus on a newly emerging phenomenon, “dispersion of culture.” We link how common modern-day features of social media and online platforms, such as algorithmic personalization and similarity-based recommendation systems, may create eco-chambers and ultimately widen the chasms between social groups within society. To capture the dynamic nature of global digital influences, we will conduct two biannual surveys to conduct a longitudinal analysis of three waves (including our first project in 2023) across the span of 6 years. Furthermore, we will identify the nation-level correlates that worsen or improve the dispersion to gain insights into the solutions. Lastly, we will identify the consequences of cultural dispersion in the domains of subjective well-being, social connections, and marketplace behavior. Our findings will contribute to academic discourse and provide actionable insights to public organizations for navigating the challenges and opportunities presented by this new cultural landscape.

Nerissa Brown,* Isaac Yamoah | Accountancy | $35,918

In this study, we test for racial discrimination in Investor Relation Officers' (IROs) communication with retail investors and whether such bias can be mitigated by asking IROs to take the perspective of investors. Specifically, we conduct a between-firms field experiment using STOXX Europe 600 listed companies. Firstly, we contact IROs with a survey email that contains our perspective-taking manipulation. Two weeks later, we contact the same IROs again using a fictitious investor name to request information about their sustainability initiatives. We use names that signal investor ethnicity and examine whether investors with a non-native name (e.g., Habtamu Yerga) receive fewer responses than investors with a native name (i.e., James Robinson). We also test whether perspective-taking mitigates discriminatory actions. As such, we propose a perspective-taking intervention that firms may consider in tandem with their ongoing DEI investments to attain representational and non-discriminatory outcomes. 

Gopesh Anand,* Abhijeet Ghoshal, Shreya Gokhale | Business Administration | $35,000

In recent years, cyberattacks have increased not only in frequency but also in severity resulting in increased losses for firms. Firms deploy a variety of methods to fight this menace. One such method is to increase the awareness among their own employees about the cybersecurity threats they may inadvertently facilitate. This is because employees, in several instances, turn out to be the weak part of the overall process to fight cyber-threats. Employees either knowingly violate security protocols, or unknowingly perform actions that allow hackers to breach the systems. In this research, we aim to study how the prior security awareness of incoming employees in the information technology areas and the knowledge and experience of current employees in different areas, affect the security preparedness and financial performance of firms. While we will assess security preparedness through occurrences and magnitude of instances, we will use balance sheet figures to assess financial performance. For data on knowledge and experience of incoming and current employees, we intend to purchase a data set, including job postings and employee profiles that we have identified and for which we have obtained details and pricing information. 

Yuchen Chen* | Finance | $30,000

In this project, we would like to study how the scalability of intangible capital affects firms’ productivity, value and stock return using individual resume data provided by Revelio Labs. We track the job transitions for managers (talents) and document the corresponding expenditure of talent reallocation (and therefore intangible capital accumulation). Our project provides a new measure of intangible capital, and we show that this measure contains better information of firm policy and asset prices, compared to the previous studies. 

Can Huang* | Finance | $29,000

This research delves into the impact of technology literacy on venture capital (VC) investments, with a specific focus on deep tech startups, key players in significant scientific and technological advancements. Traditional VCs, often with a finance-centric background, encounter challenges in accurately evaluating these complex startups. This can lead to underfunding vital technologies and, at times, overfunding less promising ones. The study unfolds in two directions: firstly, it examines the effect of VCs possessing advanced technological education, like PhDs in computer science, on their investment patterns in deep tech startups, assessing whether such tech-literacy equips them to better support these ventures. Secondly, it explores if VCs compensate for their knowledge gap by leveraging networks with technology experts or partnering with specialized VC firms. Leveraging comprehensive data from Pitchbook and Revelio Labs, which provide insights into startup finance and individual professional trajectories, this research seeks to offer a detailed understanding of how VC technology literacy influences investment decisions. The findings are anticipated to impact VC investment strategies in deep tech, potentially influencing academic curricula at technologically renowned universities like UIUC and broadening career prospects for tech-focused student entrepreneurs.

Laura Li,* Ciao-Wei Chen, Yifei Lu | Accountancy |  $27,500

We analyze the content and quality of firm disclosure in job postings. Job postings serve as a critical interface between employers and potential employees, facilitating the matching of job roles with suitable candidates. Using large language model GPT-4, we analyze a near-universe of job postings from public and private companies and examine two key elements of job postings. The first element is firms’ self-branding in the job postings, including disclosures of financial standing, performance, and growth potential. We investigate the credibility of these disclosures and their implications for workers’ future wages and job security. The second element is job descriptions, which discuss the roles and responsibilities of the position. We explore reasons behind the variations in the level of details in job descriptions and study its impact on the efficiency and quality of matches between employers and workers. Our multi-project examination intends to push the frontier of accounting research from information for capital resources allocation to information for human resources allocation. Our findings should aid workers in interpreting firm disclosure in job postings and shed lights on the quality of information exchange during the early phase of the job-matching process.

Yang Gao* | Business Administration | $25,500

As misinformation proliferates on social media, traditional fact-checking struggles to keep up, prompting social media platforms to adopt community-based approaches to leverage the wisdom of crowds. This project delves into the effectiveness of X’s Community Note, where registered contributors add notes to potentially misleading tweets and those considered helpful by a ranking algorithm will be displayed under the original tweet. Leveraging the regression discontinuity design and survival analysis, we aim to examine the effect of receiving a public note on the focal authors’ retraction decisions, including whether to retract the original tweet and when to retract. Additionally, with a difference-in-differences design, we plan to investigate how receiving a public note would affect the focal authors’ future posting behavior, including posting frequency, post type, and textual characteristics (e.g., quality/credibility). Overall, the findings provide valuable insights into the role of community-based fact-checking in combatting misinformation on social media.

Mackenzie Alston* | Finance | $23,460

The objective of most PhD candidates on the job market is to secure a job; however, not all job offers are created equal. In particular, some candidates may be given “exploding offers,” offers where the applicant has a limited time to decide whether to accept them. If these exploding offers come early in the market, candidates who accept them may miss the opportunity to accept a better offer that would have arrived later. In a survey, we will explore what factors might explain when and why an exploding offer is accepted. Then, we will conduct an experiment in which we explore how job candidates respond when given an exploding offer and whether such offers increase or decrease their welfare. Furthermore, in both the survey and experiment, we will investigate whether there are differences in the response to exploding offers based on certain characteristics of the candidates (e.g., citizenship status, gender).

Rosanna Smith,* Hyun Euh, Ari Garimella | Business Administration | $19,500

This project examines theory and practice-driven questions at the intersection of AI, beauty, and culture. Major social media platforms such as Instagram and TikTok have face/body filters designed to enhance appearances. It is speculated that these filters, enabled by artificial intelligence algorithms, encourage the adoption of Eurocentric beauty standards; however, to date, little research has examined how AI is influencing beauty standards both at a local and global level and the consequences of this influence. This project will empirically examine this underexplored area via the following aims: Aim 1: Test whether and how AI reinforces Eurocentric beauty standards; Aim 2: Examine similarities vs. differences across cultures in the use of filters and other AI-related body modification techniques and their consequences for consumer behavior and mental health; Aim 3: Identify managerially relevant interventions on the presentation of beauty-related AI that can have a positive impact on consumers. We plan to employ a multimethod approach to test these aims including archival analysis of filter use in popular apps and experiments on local and global populations. This approach involves the creation of a beauty app, which will afford us the ability to test with precision how consumers across cultures interact with technology that allows for face/body modification.

Robert Brunner,* Jamshed Kaikaus | Gies College of Business | $19,452

In this proposed work, we aim to develop a novel multimodal dataset of quarterly earnings conference call transcripts and audio recordings, annotated with emotion, sentiment, and cognitive dissonance labels. We will investigate the feasibility of annotations generated using large language models (LLMs), such as ChatGPT, and compare against those obtained from crowd-workers with suitable domain expertise. Numerous considerations will be taken into account regarding this research, including studying the effect of prompt engineering choices, domain-specific LLMs, and multimodal LLMs on the annotation quality and reliability. The project has already resulted in two publications in a major IEEE conference and will facilitate future research of finance-specific applications, including market movement prediction and financial fraud detection, as well as artificial intelligence tasks, such as natural language processing and automatic speech recognition. It is our goal to make the final annotations and data available to the Gies College of Business in order to promote academic research. As such, the project requests a small funding of 19,425 dollars, primarily for obtaining LLM-generated annotations. 

Neil Pearson,* Liheng Lei | Finance | $19,069

Security-based swaps (SBS) are derivative financial instruments that enable counterparties to exchange securities’ cash flows. They are used by financial institutions and other entities to either acquire or hedge exposure to specific markets or securities, without the necessity of direct ownership. The most important types of SBS are total return swaps (TRS), which can be based on equities or equity indexes, bonds or bond indexes, and corporate loans. Despite their importance, TRS swaps have received limited attention in the academic literature, because they are traded over the counter, and data have only recently become available through the SEC’s regulation SBSR. The raw data, which consist of various trade messages, are essentially not documented and difficult to download and use. We propose to create a clean dataset that will enable researchers are Illinois and elsewhere to study this important market. In addition, we plan to use the data to write a series of papers studying several aspects of this market.

Jalal Sani* | Accountancy | $19,000

This research project includes two studies. The first study explores the effects of greenhouse gas (GHG) disclosure mandates on employee outcomes. The second study examines the effects of GHG disclosure mandates on firms’ GHG emissions. We utilize a regulatory program in Canada that mandates facilities with GHG emissions above a specific threshold to disclose their GHG emissions. We plan to use administrative employer-employee matched data from Statistics Canada that covers the universe of employers and employees in Canada to explore the impacts of this disclosure mandate on (i) worker-firm match quality, and (ii) the mechanisms through which facilities might decrease their GHG emissions in the post-regulation period. To conduct these studies, we plan to purchase access to the employee-employer matched dataset on wages and employment at the employee level; financial data at the firm level; and financial and GHG emissions data for manufacturing plants from the administrative records of Statistics Canada. 

Ramanath Subrahanyam,* Aravinda Garimella, Mukul Kaushik | Business Administration | $16,640

Digital philanthropic platforms like DonorsChoose.org and Watsi.org have been pivotal for fundraising across diverse causes, connecting institutional and individual needs with donor generosity. Our research at Gies has been at the forefront of this stream of work. For instance, our large-scale empirical analysis of such platforms, during COVID-19-necessitated school closures, found evidence of successful matching of school initiatives to funding sources, through the engagement of institutional donors. Despite such successes, matching processes of platforms have remained largely inefficient. For example, in a second study, we found strong evidence of a "rich get richer" phenomenon despite well-intentioned education policies.

In this multifaceted research effort, we propose a comprehensive approach using the capabilities of neural networks and large language models (LLMs) trained on platform-specific data and econometric innovations to examine and enhance matching performance. Capturing emotional, objective, and messaging components from unstructured textual data, and augmenting it with objective and structured measures on fund-seeker and donor sides and public data sources, we aim to refine the matching process. For example, stakeholder-paired LLM encodings, like Teacher<->Fundraising Request and School<->Teacher, hold strong potential for improved matches. Methodologically, we plan to augment this analysis with field experiments. Our holistic examination aims to advance knowledge in digital philanthropy research and practice, contributing to areas of policymaking, non-profit operations, information systems, and social welfare.

Fiona Kun Yao,* Joseph Mahoney, Taeksang Jang | Business Administration | $16,000

In an era marked by escalating geopolitical tensions, multinational enterprises (MNEs) face the significant challenge of navigating these complexities. Our study bridges the gap between political science, economics, and international business literature by exploring nonmarket strategies that MNEs can employ to manage geopolitical tensions. We introduce the concept of corporate diplomacy to analyze these strategies, moving beyond existing literature that often focuses solely on corporate political or social strategies. This approach acknowledges the inter-dependence of corporate strategies. We propose a two-by-two typology, delineating four types of corporate diplomacy: Minimalist, Immersive, Social, and Political. Utilizing this typology, we investigate the relationship between geopolitical tensions and an MNE’s selection among these diplomatic approaches. This study offers valuable theoretical and practical insights, enhancing understanding of how businesses can effectively address international geopolitical crises. Furthermore, our research sheds light on how MNEs can support or engage in diplomacy and peacekeeping initiatives through their strategic choices.

Michelle Hutchens,* Andrea Rozario, Brian Forsberg | Accountancy | $15,000

Companies spend a significant amount of time and money preparing voluntary and required disclosures related to their environmental impact. We use Google search data to measure stakeholder demand for a firm’s environmental disclosures. We observe an increase in search for environmental disclosures over our sample period and co-movement in search activity within industries. Our empirical evaluation of the determinants of demand for a firm’s environmental disclosures highlights the importance of brand visibility and sustainability-focused investors as drivers of the demand. We plan to increase the contribution of our study by examining firm specific ESG news as an additional driver of demand for environmental disclosures. Prior research suggests that consumers and investors respond to ESG news and ESG ratings. However, it is unclear whether stakeholders seek additional information from environmental disclosures prior to responding to ESG news and the extent to which information in firm-specific disclosures may amplify their response. We predict that stakeholders’ demand for environment-related disclosures, via Google search, amplifies consumer and investor reactions to positive and negative ESG news. Our study contributes to our understanding of the drivers of demand for a firm’s environmental disclosures and how stakeholder demand for environmental disclosures impacts their purchasing and investment decisions.

Maria Rodas,* Andrea Rozario, Isaac Yamoah | Accountancy and Business Administration | $15,000

Remote work has become prevalent in the post-pandemic world. However, there is limited understanding of its psychological implications. This study will examine the relation between remote work and self-complexity of employees and the consequences of self-complexity on job satisfaction and well-being. We will study our research questions using a comprehensive online survey where we will capture work situation details, self-complexity using a novel measure, and well-being metrics. The data will be analyzed using statistical methods to understand the relationship between work environment, self-complexity, and well-being. We will then conduct an experiment to understand the effects of having a more complex self-identity. Experimental data will be analyzed using ANOVAs. Our study aims to add to the understanding of how remote work affects individuals’ perceptions and integrations of their various roles and identities. In doing so, we expect our study to be relevant for the development of organizational policies and inform the broader discussion on work-life balance and public policy. 

Jenny Ulla,* Mark Peecher, Andrea Rozario, Dan Zhou | Accountancy | $14,700

Effective coaching and on-the-job learning are crucial to audit quality. However, the COVID-19 pandemic has triggered a mass adoption of remote working by public accounting firms that has continued well past the pandemic. Prior research shows that remote working could harm group cohesion among team members, threating audit quality. This study will examine the effects of remote training on supervisor coaching quality and subordinate task performance and how increasing supervisor accessibility in a remote working environment could increase group cohesion and thus mitigate the potential negative effects of remote working. We will study our research questions using an experiment in which we will manipulate Training Mode (In-person vs. Virtual) and Supervisor Accessibility (Continuous or Revolving Door audit room). We expect our findings to inform academics and practitioners on the factors that affect audit quality in the remote working environments and practices that can mitigate the negative effects of remote working on audit quality.

Jenny Ulla,* Kim Mendoza, Jessica Thornton | Accountancy | $10,050

Generative AI tools are becoming widely utilized by companies around the world, accounting firms included. While historically the hierarchical structure of audit firms relied on knowledge transfer to occur from human mentor to human mentee, auditors will now or will soon have the ability to receive knowledge from an AI tool. Our proposal investigates the effect of this shift to utilizing generative AI tools on knowledge acquisition. Prior literature suggests that knowledge transfer could suffer when the source of knowledge is an AI tool compared to a human. Therefore, we document this issue in the audit setting and propose a solution to the problem. Identifying a solution is paramount as generative AI tools are here to stay. Ultimately, our study’s results will provide invaluable insight that is generalizable across disciplines and industries beyond accounting where knowledge transfer occurs (i.e., marketing, finance, management, etc.). For our proposal, we are requesting funding for (1) a computer programmer to create a generative AI chatbot for our experimental materials, and (2) payment for auditor participants.

Vanitha Virudachalam* | Business Administration | $8,960

The 2022 Supreme Court decision to overturn Roe v. Wade fundamentally altered women’s healthcare in the United States, with 24 states now banning abortion in some form. Patients, particularly those from vulnerable populations, must travel long distances to receive healthcare. At the same time, the already-strained supply of providers is under increased pressure in states in which abortion remains legal. We aim to empirically study the long-term implications of the abortion ban on the availability of skilled healthcare services for women. We plan to investigate two aspects of this issue. First, how has the geographic distribution of OB-GYN practitioners changed in response to abortion bans? Specifically, as providers relocate, do they move to bordering abortion-friendly states to remain available to their prior patient population, or do they relocate to entirely new areas? What drives their decision, and are there policies that can better match supply to demand? Additionally, the dearth of abortion providers means that providers are more likely to split their time between different centers, but researchers have shown that multi-siting can negatively impact productivity. Does this finding hold in the context of women’s health, and if so, how can physicians be optimally deployed to meet demand? 

Olga Khessina* | Business Administration | $5,840

We aim to investigate how local cultural sentiments shape what types of organizations are founded and succeed in a region. We argue that local culture shapes a localized opportunity structure that affects whether local entrepreneurs perceive the founding of specific types of organizations as worthy. Consequently, regions with different cultures may significantly differ in founding patterns of the same type of firms. In this project, we aim to test these ideas by studying how in U.S. counties, local cultures regarding the meanings and use of automobiles affected foundings of drive-in movie theaters – an organizational form that combined movie watching and car use – from 1933 (when the industry started) to 1970 (when the industry declined). Because a drive-in theater was an entertainment-based organizational form, we predict that counties with cultural sentiments linking cars to family and entertainment created a more favorable entrepreneurial opportunity structure and, as a result, experienced more drive-in theater foundings than regions with cultures linking cars to industrialization and work. Receiving a grant would allow us to collect archival data on drive-in theaters to test our theoretical ideas.

Julia Fonseca,* Victor Duarte, Weitong (Peter) Han, Jialan Wang | 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.