
Many domains provide us with (largely untapped) detailed trace data on human decisions in complex, dynamic environments. These decisions are often made by experts with deep experience in the task at hand.…Read More
Many domains provide us with (largely untapped) detailed trace data on human decisions in complex, dynamic environments. These decisions are often made by experts with deep experience in the task at hand.…Read More
Product innovation can result from the novel design and combination of product components as well as from changing the underlying product architecture, that is, the way components interact with each other.…Read More
Prior research has argued and shown that firms with centralized R&D produce broader innovations relative to decentralized firms, but the organizational mechanisms underlying this relationship are underexplored. This gap limits our understanding of whether and how formal R&D structure can be used as a lever to influence research outcomes.…Read More
We study how a new development in entrepreneurship—crowdfunding—interacts with more traditional financing sources, such as venture capital (VC) and bank financing. …Read More
Using data on employer job search, this study demonstrates that employers are seeking algorithmic literacy from workers in a particularly broad class of occupations because familiarity with algorithms in downstream “using” occupations is important for integrating AI and data science into production. …Read More
This paper addresses the recent trend of offering unlimited vacation to employees. While potentially useful for acquiring human capital benefits, unlimited vacation is a risky perk for firms due to the possibility of abuse.…Read More
We will examine the cost of inventor mobility from a talent poaching perspective. It is either prohibitively costly or impossible to contract over all states of the world (Grossman and Hart, 1986; Tirole, 1999).…Read More
In today’s connected world, individuals are no longer mere consumers of goods, information and services, but public producers of often valuable data. In fact, personal data is becoming such a core input that The Economist called it “the world’s most valuable resource” ahead of oil.…Read More
The idea that source code for computer software be accessible to anyone has gained increasing popularity among software developers, fueling the rapid growth of the open source software (OSS) movement. Platforms for OSS development currently host incredibly valuable projects like the Linux kernel, TensorFlow and various blockchain software projects.…Read More
In this project, we attempt to provide a rigorous, empirical study of e-commerce A/B testing strategies. We perform a meta-analysis on 2,732 A/B tests conducted by 252 ecommerce companies across seven industries over the course of three years.…Read More
The impostor phenomenon is the individual proclivity to believe that one has fooled those around them into adopting an overly positive view of oneself. Studies have shown that at least two out of five successful people have this proclivity. …Read More
We examine how wealth windfalls affect self-employment decisions using data on cash payments from claims on Texas shale drilling to people throughout the United States. Individuals who receive large wealth shocks (greater than $50,000) have 51% higher self-employment rates.…Read More
We investigate whether the effect of network position on innovation is causal or spurious. Although empirical evidence demonstrates that certain structural positions in alliance networks (e.g. structural holes) affect firm innovation, it is hard to disentangle the factors allowing a firm to put itself in a certain position from the innovation outcomes that stem from being in that position.…Read More
Traditional online platforms (e.g., Amazon Marketplace) use Unilateral Rating System (URS), where customers rate sellers. However, sharing economy platforms (e.g., Uber, Airbnb) have adopted Bilateral Rating System (BRS) that also allows service providers to rate customers, and even selects customers based on their ratings.…Read More
I exploit unsupervised machine learning and natural language processing techniques to elicit the risk factors that firms themselves identify in their annual reports. I quantify the firms’ exposure to each identified risk, design an econometric test to classify them as either systematic or idiosyncratic, and construct factor mimicking portfolios that proxy for each undiversifiable source of risk.…Read More
Many large firms try to encourage entrepreneurial initiatives by their employees, but the question of which employees undertake such initiatives has not been explored. In this study, we argue that the formal division of labor within a firm affects employees’ likelihood of engaging in internal corporate venturing. …Read More
We study the association of spending per employee with startup firm survival. Our theory model posits that entrepreneur’s knowledge defines the complex decision process of combining human and non-human inputs to increase firm value. …Read More
When turbulence is the new normal, an organization’s survival depends on vigilant leadership that can anticipate threats, spot opportunities, and act quickly when the time is right. …Read More
Data-analytics technology can accelerate the innovation process by enabling existing knowledge to be identified, accessed, combined, and deployed to address new problem domains.…Read More
I aim to contribute to corporate strategy and technology and innovation management literatures by refining the way we think about how firms’ externally accessible resources and capabilities influence those firms’ heterogeneous boundary choices and their resulting outcomes. …Read More