Time: Friday, 27 January 2023, 10:30–12:00
Room: LW420
Design
Mar 18 – Hemant Bhargava to present “Platform Ecosystems: Co-Dependence, Scale, Design”
Platform Ecosystems: Co-Dependence, Scale, Design
by
Hemant K. Bhargava
Professor
Jerome and Elsie Suran Chair in Technology Management
Director, Center for Analytics and Technology in Society
Graduate School of Management
University of California Davis
Friday, Mar 18
11:00 am – 12:30 pm
In-person: 1810 Liacouras Walk, Room 420
Abstract:
I will discuss a couple of recent papers on platform economics, that aim to develop a highly general and extensible modeling architecture for analyzing the economics of platform ecosystems, specifically studying issues such as:
What factors govern the scale of the platform ecosystem? How are platform scale and power affected by: (i) Complementors’ production attributes? (ii) Platform’s economic + technical design, and strategic choices? (iii) Platform market structure? (iv) Nature of dependence between a platform and its complementors?
How does ecosystem structure influence distribution of power (and revenue) between platform and complementors?
How will ecosystem structure, and platform-complementor co-dependence, evolve?
The two papers provide the basic modeling infrastructure, applied to platforms that monetize through advertising and through user fees. I will then discuss how the models can be adapted to address questions related to platform power, revenue-sharing, and platform regulation.
Bio:
Professor Hemant K. Bhargava is an academic leader in economic modeling and analysis of technology-based business and markets. He holds the Jerome and Elsie Suran Chair Professorship in Technology Management at UC Davis, and is the Director of the Center for Analytics and Technology in Society. His research focuses on decision analytics and how the distinctive characteristics of technology goods influences specific elements of operations, marketing, and competitive strategy, and the implications it holds for competitive markets and technology-related policy. He has examined deeply these issues in specific industries including platform businesses, information and telecommunications industries, healthcare, media and entertainment, and electric vehicles. He has published extensively in the top journals Management Science, Operations Research, Marketing Science, Journal of Marketing Research, Information Systems Research, INFORMS Journal on Computing, and Production and Operations Management. He is a Distinguished Fellow of the INFORMS Information Systems Society. He serves as Department Editor (Information Systems) for INFORMS’ flagship journal Management Science, and is on the Editorial Board of Marketing Science and other major journals. He co-founded the annual Theory in Economics of Information Systems workshop. He co-founded and was the first Academic Director of the UC Davis Master of Science in Business Analytics program, and previously served as Associate Dean at the Graduate School of Management. He was listed among the Global 100 Top Academic Data Leaders by Chief Data Officer magazine in 2020. He has received several research awards, including most recently the INFORMS Journal on Computing “Test of Time” award for his 2007 paper on search engines, a Best Paper Award at INFORMS CIST 2021 for his work on revenue-sharing in platforms, and a Research Excellence Gift by Google in 2017-18.
April 10 – JaeHwuen Jung to present “The secret to Finding Love: A Field Experiment of Choice Structure in Online Dating Platform”
The secret to Finding Love: A Field Experiment of Choice Structure in Online Dating Platform
by
JaeHwuen Jung
Assistant Professor
Department of Management Information Systems
Fox School of Business
Temple University
Friday, April 10
10:30 – 12:00 pm | Zoom
Abstact:
Online matching platforms require new approaches to market design since firms can now control many aspects of search and interaction process through various IT-enabled features. While choice structure—the size of choice set and the number of choices a platform offers to its customers—is one of the key design features of online matching platforms, its impact on engagement and matching outcomes remains unclear. In this study, we examine the effect of different choice structures on the number of choices and matches on the platform by conducting a randomized field experiment in collaboration with an online dating platform. Specifically, we design four treatment groups with different choice structures where users can only interact with other users in the same group, select users who are in a similar age range and live in the same geographical location, and randomly assign them to each treatment group. We find that providing higher choice capacities to male and female users have a different effect on choice behaviors and matching outcomes. Moreover, while increasing the choice capacity of male users yields the highest number of choices, increasing the choice capacity of female users is the most effective way to increase matching outcomes. Structural analysis further reveals the underlying mechanisms of choice behavior and matching results, suggesting that users significantly decrease the number of choices after receiving a choice from other users and the effect of the choice capacity on matching outcomes differs by gender. We further provide a counterfactual analysis that explores optimal choice structure design depending on the gender ratio of the online dating platform.