Auctions are widely used in practice. While also extensively studied in the literature, most of the developments rely on the significant common prior assumption. We study the design of optimal prior-independent selling mechanisms: buyers do not have any information about their competitors and the seller does not know the distribution of values, but only a general class it belongs to.
This article presents new conceptual and managerial insights about consumer experiences of positive emotions in the marketplace and how to engineer these emotional experiences for business purposes. Specifically, we provide an in-depth conceptual analysis of three positive emotions that are of high relevance for marketers: (1) consumer pride, (2) consumer excitement, and (3) consumer relaxation.
Words are part of almost every marketplace interaction. Online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data. But how can marketers best use such data? This article provides an overview of automated textual analysis and details how it can be used to generate marketing insights. The authors discuss how text reflects qualities of the text producer (and the context in which the text was produced) and impacts the audience or text recipient.
This article starts with the premise that while Design Thinking has value, there are yawning gaps in the research components of the process. More disciplined research will enable design thinkers to create better, more human-centered designs.
In a multi-armed bandit (MAB) problem a gambler needs to choose at each round of play one of K arms, each characterized by an unknown reward distribution. Reward realizations are only observed when an arm is selected, and the gambler's objective is to maximize cumulative expected earnings over some planning horizon of length T. To do this, the gambler needs to acquire information about arms (exploration) while simultaneously optimizing immediate rewards (exploitation). The gambler's policy is measured relative to a (static) oracle that knows the identity of the best arm a priori.
We examine economic consequences of US bank regulators' phased removal of the prudential filter for accumulated other comprehensive income for advanced approaches banks beginning on January 1, 2014. The primary effect of the AOCI filter is to exclude unrealized gains and losses on available-for-sale securities from banks' regulatory capital.
We estimate the benefit of life-extending medical treatments to life insurance companies. Our main insight is that life insurance companies have a direct benefit from such treatments as they lower the insurer's liabilities by pushing the death benefit further into the future and raise future premium income. We apply this insight to immunotherapy, treatments associated with durable gains in survival rates for a growing number of cancer patients. We estimate that the life insurance sector's aggregate benefit from FDA approved immunotherapies is $9.8 billion a year.
We consider a fundamental pricing model in which a fixed number of units of a reusable resource are used to serve customers. Customers arrive to the system according to a stochastic process and upon arrival decide whether or not to purchase the service, depending on their willingness-to-pay and the current price. The service time during which the resource is used by the customer is stochastic and the firm may incur a service cost. This model represents various markets for reusable resources such as cloud computing, shared vehicles, rotable parts, and hotel rooms.
We study the dynamic mechanism design problem of a seller that repeatedly auctions independent items over a discrete time horizon to buyers that face a cumulative budget constraint. A driving motivation behind our model is the emergence of real-time bidding markets for online display advertising in which such budgets are prevalent. We assume the seller has a strong form of limited commitment: she commits to the rules of the current auction but cannot commit to those of future auctions.