AI-Generated Digital Twins: Shaping the Future of Business
During a Columbia AI Summit satellite workshop, faculty shared cutting-edge research on the opportunities and challenges of AI in business decision-making.
During a Columbia AI Summit satellite workshop, faculty shared cutting-edge research on the opportunities and challenges of AI in business decision-making.
Insights shared at Columbia University’s AI Summit show how the technology is redefining the creative process and influencing executive decision making.
Professors Boaz Abramson and Stijn Van Nieuwerburgh investigate whether insurance for missed rent payments could help individuals and the broader economy.
507 firms hold over $1 billion in goodwill with market-to-book ratios below one, suggesting hidden risks. Learn how investors can scrutinize these firms for potential write-downs and what this reveals about corporate governance with insights from Columbia Business School.
In this episode of Columbia Bizcast, join Columbia Business School Dean Costis Maglaras and faculty as they explore how the School is harnessing AI to transform classroom learning and equip students for the future of work.
Columbia Business School Professors Todd Jick and Stephan Meier discuss AI in the workplace and why companies must prioritize people.
As the U.S. election nears, the American public is witnessing the power of social media and elections: the partnership between political candidates and content creators, says Professor Mohamed Hussein.
Professor Laura Veldkamp outlines the key issues to consider when evaluating the candidates’ approach to Big Tech and monopolies during this election season.
Professor Netzer's expertise centers on one of the major business challenges of the data-rich environment: developing quantitative methods that leverage data to gain a deeper understanding of customer behavior and guide firms' decisions. He focuses primarily on building statistical and econometric models to measure consumer preferences and understand how customer choices change over time, and across contexts. Most notably, he has developed a framework for managing firms' customer bases through dynamic segmentation.
Olivier Toubia is the Glaubinger Professor of Business at Columbia Business School. His research focuses primarily on innovation, customer insights, and creative industries. Specifically, he combines methods from social sciences and data science in order to study human processes such as motivation, choice, and creativity. He previously served as the Editor-in-Chief at the journal Marketing Science. He teaches Foundations of Innovation, Generative AI for Business and the core marketing course. He received his MS in Operations Research and PhD in Marketing from MIT.
Professor Chan teaches the MBA core Operations Management course and the MBA electives, The US Healthcare System: Structures and Strategies; Healthcare Management, Design, and Strategy; and The Analytics Advantage. Her research is in the area of healthcare operations management. Her primary focus is in data-driven modeling of healthcare systems. Her research combines empirical and mathematical modeling to develop evidence-based approaches to improve patient flow.
Will Ma is the Roderick H. Cushman Associate Professor of Business at the Graduate School of Business, Columbia University. His research centers around online algorithms in e-commerce systems, both for supply-side problems like inventory and fulfillment, and revenue management problems like dynamic assortment optimization. He specializes in designing simple online algorithms with performance guarantees, that can be tuned to historical data. Will also has miscellaneous experience as a professional poker player, video-game startup founder, and karaoke bar pianist.
We aim to stimulate discussion on how innovation research within marketing can use a better world (BW) perspective to help innovation become a driver of positive change in the world. In this "Challenging the Boundaries" series paper, we hope to provide purposeful research opportunities for scholars seeking to bridge innovation research with the BW movement. We frame our discussion with four areas of innovation research in marketing that are particularly relevant to BW objectives.
One of the most crucial aspects and significant levers that gaming companies possess in designing digital games is setting the level of difficulty, which essentially regulates the user’s ability to progress within the game. This aspect is particularly significant in free-to-play (F2P) games, where the paid version often aims to enhance the player’s experience and to facilitate faster progression.
Language is a uniquely human trait at the core of human interactions. The language people use often reflects their personality, intentions and state of mind. With the integration of the Internet and social media into everyday life, much of human communication is documented as written text. These online forms of communication (for example, blogs, reviews, social media posts and emails) provide a window into human behaviour and therefore present abundant research opportunities for behavioural science.
Language is a uniquely human trait at the core of human interactions. The language people use often reflects their personality, intentions and state of mind. With the integration of the Internet and social media into everyday life, much of human communication is documented as written text. These online forms of communication (for example, blogs, reviews, social media posts and emails) provide a window into human behaviour and therefore present abundant research opportunities for behavioural science.
The cyclically adjusted price-to-earnings ratio is now elevated. But should that lead you to exit the stock market? Perhaps not. The predictive power of CAPE has waned meaningfully in recent years.
With unprecedented access to consumer information, firms are increasingly interested in designing highly effective data-driven targeting policies based on detailed consumer data. The current standard for implementing such policies involves the “test-then-learn” approach, where randomized experiments are used to estimate the differential impact of marketing interventions on various customers. However, this method fails to incorporate the firm’s ultimate business objectives, leading to inefficient experimentation and suboptimal targeting strategies.
One of the most significant levers available to gaming companies in designing digital games is setting the level of difficulty, which essentially regulates the user’s ability to progress within the game. This aspect is particularly significant in free-to-play (F2P) games, where the paid version often aims to enhance the player’s experience and to facilitate faster progression. In this paper, we leverage a large randomized control trial to assess the effect of dynamically adjusting game difficulty on players’ behavior and game monetization in the context of a popular F2P mobile game.
Routines shape many aspects of day-to-day consumption. While prior work has established the importance of habits in consumer behavior, little work has been done to understand the implications of routines — which we define as repeated behaviors with recurring, temporal structures — for customer management. One reason for this dearth is the difficulty of measuring routines from transaction data, particularly when routines vary substantially across customers. We propose a new approach for doing so, which we apply in the context of ridesharing.