Artificial Intelligence (AI) is playing an increasingly important role in the global economy and has transformed many business practices. As AI has advanced beyond the conventionally narrow domains, it is starting to exhibit characteristics of “general purpose technologies (GPT)” that are expected to change the nature of more business innovations and reduce their associated financial costs and time.…Read More
Emerging technologies are an important driver of economic growth. However, the process of their emergence may not only be characterized by technological progress but also by setbacks. We offer a perspective on technology emergence that explicitly incorporates setbacks into the technology’s evolution and explains how industry participants may react to setbacks in emerging technologies.…Read More
This paper focuses on promoting the sustainability of renewable energy ecosystems to ensure socio-economic development. This is critical for emerging economies where rising demand for energy is likely to deplete resources rapidly.…Read More
In this paper, we explore how an industry’s watershed moments – vivid, publically salient, emotionally resonant events – can drive the emergence of a new market. Our empirical context is the New Space market, a growing number of new, private companies developing and using spaceflight-access technologies. …Read More
Market thickness is a key parameter that can make or break a platform’s business model. Thicker markets can offer more opportunities for participants to meet and higher chances that a potential match would exist. …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
This paper explores how multimarket overlap in knowledge activities influences firm decisions to internationalize their homecountry generated innovations.…Read More
Understanding how firms learn to make better strategic decisions and achieve superior performance is a question of significant concern to managers and scholars, especially in the context of mergers and acquisitions (M&A).…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
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
This project consists of a field experiment to assess a two-stage intervention intended to enrich healthcare professionals’ learning from patient experiences, as recounted in patients’ own words.…Read More
Why and how do private equity (PE) firms engage in technology acquisitions, and how do they create and capture value in these transactions? Observational data shows initial evidence that not only are PE firms engaging in an increasing number of technology buyouts, they are also seemingly behaving in distinct ways from both corporate acquirers, as well as PE firms in industries other than high-tech.…Read More
Does pivoting matter? How does it affect investment in innovation and firm performance? My goal is to analyze the relevance of pivoting for the development of a small firm into a mature one and to provide a better understanding of what constitutes a small firm.…Read More
The research objective is to determine how quickly product innovation translates into higher stock market valuations. The novelty in the research approach is using online consumer reviews on websites including Amazon, eBay; combined with stock market data.…Read More
One of the most important trends in business in recent years has been the growth of Big Data and predictive analytics. The trend started with traditional analytics and the emergence of decision support systems. With advances in machine learning (ML), systems can now take in large amounts of data, learn how human decision-makers have made decisions in the past, and make decisions autonomously (achieving human-level or superhuman performance in many activities). …Read More
Climate change remains a grand challenge of our time. Numerous actors relevant to business—both public and private—have worked to reduce or otherwise mitigate greenhouse gas emissions, and to focus management attention on the issue of climate change.…Read More
In this project, we seek to update the statistical paradigm for conducting A/B tests in the 21st century. In particular, we plan to develop a statistical framework that takes the guesswork out of deciding when to stop an experiment and to calibrate a firm’s decision thresholds based on their own historical data.…Read More
Standard economic theory recognizes a trade-off inherent in intellectual property protection between increased incentives for firms to innovate due to potential monopoly rights and the deadweight loss from those rights.…Read More
Over the last two decades many categories of services have shifted from the traditional to the digital format, including music, news, job postings, and dating, among many others. Meanwhile, the sale of products has shifted significantly from physical to online channels, including clothing, toys, cosmetics, and even food.…Read More
The project analyzes the regulatory and governance implications of cryptocurrencies, blockchain-based systems, and distributed ledger technologies. …Read More
