Robert S. Gazzale

Pricing information bundles in a dynamic environment

We explore a scenario in which a monopolist producer of information goods seeks to maximize its profits in a market where consumer demand shifts frequently and unpredictably. The producer may set an arbitrarily complex price schedule---a function that maps the set of purchased items to a price. However, lacking direct knowledge of consumer demand, it cannotcompute the optimal schedule. Instead, it attempts to optimize profits via trial and error. By means of a simple model of consumer demand and a modified version of a simple nonlinear optimization routine, we study a variety of parametrizations of the price schedule and quantify some of the relationships among learnability, complexity, and profitability. In particular, we show that fixed pricing or simple two-parameter dynamic pricing schedules are preferred when demand shifts frequently, but that dynamic pricing based on more complex schedules tends to be most profitable when demand shifts very infrequently.

Model Selection in an Information Economy: Choosing What to Learn

As online markets for the exchange of goods and services become more common, the study of markets composed, at least in part, of autonomous agents has taken on increasing importance. In contrast to traditional complete–information economic scenarios, agents that are operating in an electronic marketplace often do so under considerable uncertainty. In order to reduce their uncertainty, these agents must learn about the world around them. When an agent producer is engaged in a learning task in which data collection is costly, such as learning the preferences of a consumer population, it is faced with a classic decision problem: when to explore and when to exploit. If the agent has a limited number of chances to experiment, it must explicitly consider the cost of learning (in terms of foregone profit) against the value of the information acquired. Information goods add an additional dimension to this problem; due to their flexibility, they can be bundled and priced according to a number of different price schedules. An optimizing producer should consider the profit each price schedule can extract, as well as the difficulty of learning of this schedule.

Behavioral Biases in Annuity Choice: An Experiment

We conduct a neutral-context laboratory experiment to systematically investigate the role of the hit-by-bus concern in explaining the annuitization puzzle: the low rate of retirement-asset annuitization relative to the predictions of standard models. We vary endowed asset (annuity vs. stock of wealth vs. no explicit endowment), and find a strong endowment effect. Furthermore, we find that the ordering of survival risks matters. Compared to a frame in which a single draw from a known distribution determines survival outcome, annuity choice is lower when subjects must sequentially survive early periods to reach periods in which the annuity dominates. We conclude with policy implications.

Remain Silent and Ye Shall Suffer: Seller Exploitation of Reticent Buyers in an Experimental Reputation System

By providing incentives for sellers to act in a trustworthy manner, reputation mechanisms in many online environments can mitigate moral-hazard problems when particular buyers and sellers interact infrequently. However, these mechanisms rely on buyers sharing their private information about sellers with the community, and thus may suffer from too little feedback when its provision is costly. In this experimental study, we compare a standard feedback mechanism to one in which sellers can inspect a buyers feedback-provision history, thus providing the buyer with incentives to share private information even when costly. We find fairly high trust and trustworthiness levels in all markets, with buyers showing a willingness to provide costly feedback, especially negative feedback, sufficient to induce seller trustworthiness. While we find, ceteris paribus, evidence that the availability of feedback-provision histories increases buyer trust by reducing missing feedback, it did not improve overall trustworthiness as this information enabled sellers to discriminate and act in a trustworthy manner less frequently with those who share information less frequently.

Ambiguous Solicitation: Ambiguous Prescription

We conduct a two-phase laboratory experiment, separated by several weeks. In the first phase, we conduct urn games intended to measure ambiguity aversion on a representative population of undergraduate students. In the second phase, we invite the students back with four different solicitation treatments, varying in the ambiguity of information regarding the task and the payout of the laboratory experiment. We find that those who return do not differ from the overall pool with respect to their ambiguity version. However, no solicitation treatment generates a representative sample. The ambiguous task treatment drives away the ambiguity averse disproportionally, and the detailed task treatment draws in the ambiguity averse disproportionally.

Improving Learning Performance by Applying Economic Knowledge

Digital information economies require information goods producers to learn how to position themselves within a potentially vast product space. Further, the topography of this space is often nonstationary, due to the interactive dynamics of multiple producers changing their positions as they try to learn the distribution of consumer preferences and other features of the problem’s economic structure. This presents a producer or its agent with a difficult learning problem: how to locate profitable niches in a very large space.

Improving learning performance by applying economic knowledge

Digital information economies require information goods producers to learn how to position themselves within a potentially vast product space. Further, the topography of this space is often nonstationary, due to the interactive dynamics of multiple producers changing their position as they try to learn the distribution of consumer preferences and other features of the problems economic structure. This presents a producer or its agent with a difficult learning problem: how to locate profitable niches in a very large space. In this paper, we present a model of an information goods duopoly and show that, under complete information, producers would prefer not to compete, instead acting as local monopolists and targeting separate niches in the consumer population. However, when producers have no information about the problem they are solving, it can be quite difficult for them to converge on this solution. We show how a modest amount of economic knowledge about the problem can make it much easier, either by reducing the search space, starting in a useful area of the space, or introducing a gradient. These experiments support the hypothesis that a producer using some knowledge of a problems (economic) structure can outperform a producer that is performing a naive, knowledge-free form of learning.

System Design, User Cost and Electronic Usage of Journals

Dramatic increases in the capabilities and decreases in the costs of computers and communication networks have fomented revolutionary thoughts in the scholarly publishing community. In one dimension, traditional pricing schemes and product packages are being modified or replaced. We designed and undertook a large-scale field experiment in pricing and bundling for electronic access to scholarly journals: PEAK. We provided Internet-based delivery of content from 1200 Elsevier Science journals to users at multiple campuses and commercial facilities. Our primary research objective was to generate rich empirical evidence on user behavior when faced with various bundling schemes and price structures. In this article we explain the different types and levels of cost that users faced when accessing individual articles, and report on the effect of these costs on usage. We found that both monetary and non-monetary user costs have a significant impact on the demand for electronic access. We also estimate how taking user costs into account would change the optimal (least cost) bundle of access options that an institution should purchase.