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.
Faced with demand uncertainty in a nascent industry, entrants often consider which customer segments to serve by tailoring the usage breadth and coherence of their product portfolios. Portfolios have high or low usage breadth, which is the extent to which they target customers in many segments, and high or low coherence, which measures how much the portfolios’ products overlap in targeted customer segments.
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”.
Professor of Marketing Sridhar Balasubramanian and his coauthors studied the optimal management of tasks in technology-intensive projects. Engineers working on software maintenance projects strive to maintain customer satisfaction by resolving reported problems promptly. These engineers are typically faced with a continuous inflow of software problems that need fixing. However, there is substantial task uncertainty – it is unclear how much time and effort will be required to resolve each problem. Engineers must therefore make calls about how much effort and time they should allocate across problems. Their surprising finding was that managers must “ditch” unresolved problems after expending a specific amount of resolution effort – this effort level depended on the nature and source of the problems.
The autonomous car began as an opportunity that required breaking all kinds of limits: engineering, navigation, adjusting to traffic conditions, distinguishing objects, predicting what those objects might do, reacting in time, calculating quickly and juggling a vast number of ever-changing variables. The developers used more and more computer power to address these needs. But the initial bounding limit turned out to be very fundamental; rule-based computers don’t have pattern power.
Our briefing paper offers a perspective that centers on what we can reliably learn from the general direction of AI impacts on business change, rather than just speculate about. Only then can executives assess what AI points to for their firm’s development in its current and potential competitive ecosystem, leveraging its organization, technology and financial capabilities.
AI has become close to bewildering in its promises, met and unmet, its terms and tools, acronyms, “use” case examples of wild successes countered by duds and disappointments. There’s an overall lack of clear pointers for business leaders to shape the direction, priorities and pace of their organization’s AI activities. Over the past two years, we have explored the widening AI space; what stood out in our reviews is that there is today a lack of management perspective on AI.
Marketing academics are keenly aware of the seismic shifts in today's marketing environment caused by digital (dis)intermediation. In this article, we discuss four types of digital (dis)intermediation, and how they affect branding activities of incumbents and new firms.