Do the tech industry’s four most powerful players – Amazon, Apple, Facebook, and Google – have too much power?
For medications available in multiple formulations, are there significant price differences between formulations, and what are the opportunity for savings if prescribers ordering the more expensive formulation switched to the less expensive formulation?
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
Information technologies — and information — have deeply transformed firms, markets, and industries, a script that has repeated over and over again in industries such as retail, travel, and banking. Technology transforms how goods are made and exchanged, how they are priced, what goods are made and where they are sold, who the winners and losers are, and the industry structure itself.
Industry leaders from Google and Autodesk share about the demand for talent in business analytics, how the future of business is transforming, and how the UC Davis Master of Science in Business Analytics program will partner with Silicon Valley and Bay Area corporations on real-world, hands-on student projects to prepare leaders for the digital economy. The inaugural UC Davis MSBA class will begin in San Francisco fall 2017.
The Future of Work Series at UC Davis presents “Artificial Intelligence or Sophisticated Mimicry: The Business and Ethics of Automated Systems”
Featuring speaker Mark Nitzberg, AI scientist, entrepreneur, and consultant to industry and government. Currently the Executive Director of the Center for Human Compatible Artificial Intelligence at UC Berkeley, head of strategic outreach for the Berkeley AI Research Lab, and a principal at the Cambrian.ai think tank network. Also featuring Hemant Bhargava, who currently serves as MSBA Program Chair at the UC Davis Graduate School of Management and is the Jerome and Elsie Suran Chair in Technology Management.
Uniphore, an early Conversational Service Automation category leader, continues to execute its global strategy and has opened a new headquarters in Palo Alto CA. which will help further its expansion into new markets and serve its growing customer base.
Platform Powered Ecosystems | Prof. Hemant Bhargava | Apigee Ecosystems Summit, 2017
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
Physician productivity is an important driver of key healthcare outcomes, such as quality of care, treatment costs and patient satisfaction, because physicians influence a vast majority of treatment decisions, and are central to the care delivery process. Thus, it is critical for researchers to understand how transformation technologies, such as electronic medical records (EMRs) impact physician productivity.
This article discusses emerging trends in mobilehealth apps,
covering potential and opportunities, challenges, and a framework
for overcoming them.
What Action is Needed: Bold Decisions to Stop COVID-19
We urge decision-makers to take bold, decisive, and preventive action
As COVID-19 cases continue to skyrocket globally, Professor Hemant Bhargava and UC Davis colleagues recommend decisive action and support systems to put into place.
Professor Hemant Bhargava advises policymakers that reopening the economy should be viewed as a collection of simultaneous, rapid, data-driven science experiments.