ChatGPT and other generative AI programs can replicate much of the work performed across the knowledge worker class. This gives us a glimpse of what ever-more-powerful AI tools might be able to do, which is both exciting and, to say the least, unsettling.
A panel of industry and academic leaders discusses what ever-more-powerful generative artificial intelligence tools might be able to do.
Faced with demand uncertainty and heterogeneity in a nascent industry, entrants often consider how many customer segments to serve by tailoring the usage breadth of their product portfolios. Portfolio usage breadth is the extent to which products in a portfolio collectively span distinct customer segments. We suggest that when entrants have use experience in contexts that are potential users of the new product, their portfolios exhibit low usage breadth, due to demand-oriented cognition and knowledge.
The workshop explores research on the processes of emergence in order to advance our understanding of innovation and the dynamics of change.
Join us to hear from Seth Lloyd, Professor of Mechanical Engineering and Physics at MIT, as he shares his findings on quantum algorithms for analyzing financial data and predicting time series
A large body of social science evidence indicates that objective, reliable and valid risk assessment instruments are more accurate in evaluating risk than professional human judgements alone. In the world of pretrial detention, where more than 10 million people are jailed each year in the United States after arrest, pretrial risk assessment tools may provide a more efficient, transparent and fairer basis for making assessments than having a judge quickly scan documents detailing the defendant’s prior record and current charges and make a decision in mere minutes. However, these assessments will retain any bias present in the data used by criminal justice agencies.
We study the impact of widespread adoption of work-at-home technology using an equilibrium model where people choose where to live, how to allocate their time between working at home and at the office, and how much space to use in production. A key parameter is the elasticity of substitution between working at home and in the office that we estimate using cross-sectional time-use data.
The patent system grants inventors temporary monopoly rights in exchange for a public disclosure detailing their innovation. These disclosures are meant to allow others to recreate and build on the patented innovation. We examine how the quality of these disclosures affects follow-on innovation.
We examine the impact of logistics performance metrics such as delivery time, and customer’s requested delivery speed on logistics service ratings and third-party sellers’ sales on an e-commerce platform.
We estimate the causal effects of employee-friendly scheduling practices on store financial performance at the US retailer Gap, Inc. The randomized field experiment evaluated a multi-component intervention designed to improve dimensions of work schedules – inconsistency, unpredictability, inadequacy, and lack-of-employee control – shown to undermine employee well-being and productivity.
As live streaming of events (e.g., video games, political commentary, and makeup tutorials, among others) gains traction, pay-what-you-want (PWYW) pricing strategies are emerging as critical monetization tools. In this research, we assess the viability and efficacy of PWYW by examining the relationship between popularity (i.e., audience size) of a live streaming event and the revenue it generates under a PWYW scheme.
E-commerce platforms, such as Amazon, Alibaba and Flipkart, that match sellers and consumers at an unprecedented scale, operate their internal search engines to help buyers find relevant products from a large number of sellers, and also allow sellers to advertise to consumers for positions in the search listing. Determining an optimal ranking of products in response to a search query is a challenging problem for the platform because sellers have certain private information about their products that the platform does not have. Using a theoretical model, we show that sellers’ bids in ad auctions, through which sponsored slots are typically allocated, can reveal (some of) this private information to the platform (“information effect”), which it can optimally combine with information that it has about consumers to improve the placement of organic results, a practice we call “strategic listing”.