“Tokenization of Digital Assets for Ethical and Equitable Model Training in an AI-based Proctoring Application” with Boscovic, D., Khullar, K., Oguri, P. B., Pandey, P., Olsen, M., & Dordevic, M.

Link: https://shorturl.at/flHUV

The COVID-19 pandemic catalyzed a significant shift in education towards online learning and remote examination processes. AI-based proctoring tools emerged to maintain exam integrity but raised ethical, bias, and privacy concerns. This paper proposes a blockchain-driven architecture to address these issues. Our approach incentivizes genuine data collection through blockchain-powered crowdsourcing, rewarding contributors with crypto tokens. It ensures decentralization by using a voting system to validate labels given by annotators for user images, with winners also receiving tokens. Emphasizing user privacy, our model enables users to retract image access, triggering server image removal and model retraining. To enhance accessibility, our trained models are available as a service through layered APIs accessed via crypto tokens. This proposed architecture aims to reconcile the challenges of online proctoring while prioritizing ethics, fairness, data reliability, and inclusivity.

“Are Immigrant Entrepreneurs Magnets for Foreign Investors?” with Wallskog, M., & Yi, L.

Link: https://shorturl.at/kltyA

Immigrant entrepreneurs play a vital role in the US startup landscape, yet how they affect the financing of US-based startups is not well understood. Using rich data on equity financing deals in the United States, we identify three key findings. First, immigrant entrepreneurs are disproportionately financed in their early stages by investors based outside the United States. This pattern is largely driven by immigrant entrepreneurs receiving equity financing from investors located in their home countries, consistent with homophily, and this homophily is not justified by better performance. Second, using capital supply shocks from different countries, we show that these homophilic investment patterns are not solely driven by startup demand for capital. Finally, we show that, through this homophily, immigrant-founded startups can attract international capital to the US startup ecosystem at large. We find evidence of financing spillovers, with native-founded startups receiving more international capital when they are located near immigrant-founded startups receiving international capital. Taken together, these findings suggest that immigrant entrepreneurs additionally contribute to the US startup ecosystem by serving as magnets for foreign investors.

“Equity-Investment Accelerators Are Cherry Pickers” (Solo Author)

Link: https://shorturl.at/hruF4

The dilemma of going big or staying small challenges entrepreneurs to wisely decide whether to trade equity in exchange for capital investment and have a more valuable equity share or retain a majority equity stake and look for noteworthy opportunities in later stages. I discuss a major heterogeneity among accelerators in terms of equity investment and early-stage seed funding. Using matched sample analysis, I provide evidence that although participating in an equity-investment accelerator has beneficial effects on the post-accelerator performance of portfolio companies to reach the next round of fundraising faster, they raise less capital in 12-month, 18-month, and 24-month time horizons after graduation in comparison to graduates of equity-free accelerators. In fact, in contrast to Yu (2020) who argues that equity-investment accelerators host lower-quality ventures, I find that founders with more years of corporate experience and higher-quality business ideas tend to shorten the path to success by participating in equity-investment accelerators. On the other hand, consistent with Hallen et al. (2020) who believe that a learning mechanism is the primary cause of accelerator effects on venture development, I find that, while ventures are heterogeneous and they learn at different rates and different depths, some entrepreneurs have already learned what to do, and it is accelerator equity design and seed investment that negatively impact acceleration and slow down venture growth.

“What Do Initial Coin Offering (ICO) Whitepapers Disclose?” with Rahmani Moghaddam, M.

Link: https://shorturl.at/cdltu

We study information exchanged between ICOs and investors via disclosed information in 2149 ICO white papers. We employ natural language processing (NLP) to quantify the structure of white papers and demonstrate their contribution to the success of ICOs. Following the content analysis by Toubia et al. (2021), we elicit information from ICO textual sources by calculating three measures namely, speed, volume, and circuitousness. Our findings show that ICO projects with a well-written white paper that disclose risk and routinely return to previously discussed topics (i.e., circuitousness) are likely to raise more funds. Consistent with this, white papers that cover more ground (i.e., volume) contribute positively to the successful outcomes of ICO fundraising campaigns. In contrast, white papers that transit quickly between topics (i.e., speed) are less likely to have a positive impact.

“Digital Health Transformation: A Case Study of Mayo Clinic’s Innovations and Impacts” 

This research project, in collaboration with the Mayo Clinic, examines the transformative effects of digitalization in healthcare. The Mayo Clinic, a leader in healthcare innovation, has been integrating new medical technologies through internal development and strategic acquisitions. This study focuses on how digital technology adoption impacts patient clinical outcomes and the financial performance of the Mayo Clinic. Key areas include the use of advanced technologies like surgical navigation robots and efficient emergency room care processing systems, aiming to improve patient experiences and operational efficiency. Additionally, the study explores the economic benefits of digital solutions like chatbots in streamlining communication and reducing operational costs. Another critical aspect is assessing the value of digital technologies in enhancing organizational investments, exemplified by the Mayo Clinic’s blockchain platform venture. This platform, designed for secure patient data collection, offers a new revenue stream and facilitates advanced personalized medicine research. The research aims to provide a holistic analysis of digital technology’s role in reshaping healthcare delivery and economics, offering valuable insights into the broader implications of digital transformation in the sector.

“Digital Transformation in PE-Restructured Firms: Impact on Value Creation and Performance” 

This research explores the critical role of organizational change in maximizing value from digital technologies, focusing on companies restructured by Private Equity (PE) firms. PE firms often acquire and strategically restructure companies, particularly in the manufacturing, distribution, and business services sectors, to enhance value. These firms, mainly first-time acquisitions with revenues between $50 and $150 million, typically lack advanced digital capabilities or fundamental business processes. The study investigates how PEs implement foundational operating processes, preparing these companies for scalable growth and innovation under new ownership. The hypothesis suggests that non-technology firms, restructured and sold by PEs, exhibit superior financial performance when engaging in digital activities compared to industry peers. This is attributed to the development of organizational capabilities during PE ownership, enabling more efficient digital transformation and scaling. The research uses metrics like profit margins, asset turnover, and sales growth to measure performance, aiming to demonstrate the benefits of digital activities in post-PE ownership.

“Network Effects in Unicorn Evolution: A Comparative Study of Investor Influence on Platform Giants” 

This research aims to explore the causal relationship between venture capital (VC) investments and the success of platform unicorns such as Uber and Airbnb. The primary objective is to study how VC networks and investment decisions influence the creation, launch, and growth of platform unicorns globally. Specifically, the project seeks to understand how VC networks and investment strategies contribute to the rapid growth and global adoption of these companies. By analyzing cases like Uber and its international counterparts, the research aims to shed light on the patterns of innovation spillover and the phenomenon of ‘innovation lag’ in different countries.

“The Dark Side of Venture Capital Investments, The Brain Drain” with Amrita Nain & Jue Wang
This paper provides the first large-sample comparison of all patent holders to investigate the move and relocation decisions of inventors to VC hubs in order to finance their innovative initiatives. In general, besides the positive impacts that VCs have on local economies, they also serve as a magnet to attract entrepreneurs to relocate nearby. Indeed, the growth in some regions (i.e., VC hubs) may occur at the expense of other regions. Moreover, in some states, the net pattern can be dominated by a single urban region, which can result in a misleading representation of rural areas. VC hubs have clearly hurt some regions, such as the Midwest, where there is less venture capital available to retain high-ability founders, who can generate high-paying jobs and contribute to economic growth. To fill the current gap in the literature, this paper conducts a rigorous statistical analysis to determine the effect of VC investments on economic inequality. The argument is that a cyclical process of investment by VCs in entrepreneurial activities causes talented inventors to aggregate in a few regions, and this drives economic inequality.

“Can CDFI Loans Secure Venture Capital Funds for Minority Entrepreneurs?” with Agustin Hurtado
In this project, we study the role of public funding for CDFI loans and venture capital funds in the financing of low-income and minority entrepreneurs. CDFIs are defined by the Treasury Department as specialized depository institutions that provide financial services for low-income communities and to people who lack access to financing, including minorities. CDFIs are eligible to apply for awards to finance a wide range of activities, including mortgage lending for first-time homebuyers, flexible underwriting for community facilities, and commercial loans for businesses in low-income areas. We plan to use Crunchbase data and a regression discontinuity analysis to study what entrepreneurial activities CDFI loans and venture capital funds finance after getting public funding from the Treasury Department.

“Killer Startup Pitch: A Machine Learning Approach”

Data and video collection – early video, image, and speech to word analysis

“Loser Founders or Winner Entrepreneurs; Unexpected Outcomes of a Successful Exit”

Data Analysis (USA IPOs and M&A after 1970)