Do the tech industry’s four most powerful players – Amazon, Apple, Facebook, and Google – have too much power?
This paper examines ecosystem management issues in multi-sided
platforms that provide infrastructure to coordinate the
activities and interactions of contributors, consumers, and
advertisers, and which motivate external contributors through
revenue-sharing of ad payments. It provides insights on how
various platform design parameters interplay with content
provision decisions of contributors and the revenue-sharing
arrangement between contributors and the platform.
Jonas Boehm, Hemant K. Bhargava, and Geoffrey Parker, “The Business of Electric Vehicles: A Platform Perspective”, Foundations and Trends in Technology, Information and Operations Management (forthcoming, last revised July 2020).
While platform business tactics are very visible and dominant in
industries and firms that have embraced platform thinking, many
businesses and firms are engaged in a platform game without
realizing it, often to negative consequences. This article
focuses on the electric vehicle (EV) segment.
A new business form that is increasingly prominent, especially in
platform business models, is an economic structure in which value
is co-created by multiple producers and aggregated into a common
bundle by a producer-consortium or independent firm. Examples
include in-home video entertainment, technology goods and
services, multi-sourced data platforms, and patent pools. This
paper develops an economic model to study demand, production
choices, revenue-sharing, and relative market power in such
markets. Beyond these specific questions, it provides an
architecture to rigorously answer additional questions in
platform competition, market power, and effects of industrial
It was a lot of fun attending Apigee’s “Adapt or Die” event on September 27 in the heart of San Francisco, and speaking on the panel “Who Ubers Who: How to Survive and Thrive in a Digital World of Mash-Ups, Matchmakers, and Marketplaces.” The best part was the 10-minute thriller movie “Adapt or Die” made by Mike Slade and starring Alexandra Grossi, whom I had a chance to meet, and featuring Apigee CEO Chet Kapoor as the muffin man! A hilarious and engaging way to get the point across about APIs, what Apigee is all about. Most of all it was joyful to observe the intensely positive “Can-do,” “Yes, or Here’s how” (rather than “No”) philosophy and exuberant attitude of Apigee employees.
Objective: To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical research.
Theory suggests two sources of price dispersion amongst homogenous goods: market frictions or product heterogeneity. We collected posted-price listings for Kindle Fire tablets from eBay to determine if listing heterogeneity can explain the high degree of dispersion we observe. Using a basic set of controls and empirical techniques in line with the previous literature, we can explain only 13% of variation in posted prices, which is also in keeping with previous research. However, we can explain 42% of the dispersion by applying machine learning to a richer set of variables, which we extract from raw downloaded HTML pages. We interpret this number as a bound on the role of market frictions in driving price dispersion. Variables describing the amount of information in the listings, the style of the listings, and the content of the listings’ text are effective price predictors independently of one another. Our analysis suggests that the content of the listings’ text plays a primal role in generating the predictions of the machine learning estimator. We repeat our analysis on a cross-section of products across a variety of categories on eBay, including household products, sporting goods, and other consumer electronics, and we find a comparable degree of price predictability across all of the products.
We provide a model of a decentralized, dynamic auction market platform (e.g., eBay) in which a continuum of buyers and sellers participate in simultaneous, single-unit auctions each period. Our model accounts for the endogenous entry of agents and the impact of intertemporal optimization on bids. We estimate the structural primitives of our model using Kindle sales on eBay. We find that just over one third of Kindle auctions on eBay result in an inefficient allocation with deadweight loss amounting to 14% of total possible market surplus. We also find that partial centralization–for example, running half as many 2-unit, uniform-price auctions each day–would eliminate a large fraction of the inefficiency, but yield slightly lower seller revenues. Our results also highlight the importance of understanding platform composition effects–selection of agents into the market–in assessing the implications of market redesign. We also prove that the equilibrium of our model with a continuum of buyers and sellers is an approximate equilibrium of the analogous model with a finite number of agents.
This paper provides an analysis and guidelines for developing
data strategy for different types of platforms, and it identifies
promising research opportunities into platform data strategy to
better inform future academic research, strategic
decision-making, and regulatory analysis.
A vital function of multi-sided platforms is to “match”
participants across the sides. Most platforms practice either
one-to-one matching (e.g., Uber) or one-to-many simultaneous
matches (e.g., lead- marketing platforms), for which the
mechanism design problem is understood. A few platforms mix
one-to-one and one-to-many matches opportunistically, but in a
very ad hoc manner. This paper proposes a theoretical
incentive-compatible (and approximately) revenue-maximizing
design for these mixed-format auctions.
Mutli-sided platforms typically thrive on the positive feedback
loop of indirect network effects. However, many platforms also
have to engage in active selling, through the use of sales agents
to mobilize network participants. This paper is the first to
examine sales force compensation design under network effects and
develops a series of insights regarding how network effects alter
Platform-enabled marketplaces, and other Internet-based goods and products with digital components and network effects are transforming the very idea of what a business is, how it creates value, and how it should be managed.