Are Consumers Fooled by Discounts? An Experimental Test in a Consumer Search Environment

In this paper we investigate experimentally if people search optimally and how price promotions influence search behavior. We implement a sequential search task with exogenous price dispersion in a baseline treatment and introduce discounts in two experimental treatments. We find that search behavior is roughly consistent with optimal search but also observe some discount biases. If subjects don't know in advance where discounts are offered the purchase probability is increased by 19 percentage points in shops with discounts, even after controlling for the benefit of the discount and for risk preferences. If consumers know in advance where discounts are given then the bias is only weakly significant and much smaller (7 percentage points).Consumer Search Theory, Search Cost, Price Promotion

Bandit Problems with Side Observations

An extension of the traditional two-armed bandit problem is considered, in which the decision maker has access to some side information before deciding which arm to pull. At each time t, before making a selection, the decision maker is able to observe a random variable X_t that provides some information on the rewards to be obtained. The focus is on finding uniformly good rules (that minimize the growth rate of the inferior sampling time) and on quantifying how much the additional information helps. Various settings are considered and for each setting, lower bounds on the achievable inferior sampling time are developed and asymptotically optimal adaptive schemes achieving these lower bounds are constructed.Comment: 16 pages, 3 figures. To be published in the IEEE Transactions on Automatic Contro

Search and Active Learning with Correlated Information: Empirical Evidence from Mid-Atlantic Clam Fishermen

This paper examines search with active learning and correlated information. We first develop a simple model to show how correlation affects the decision to acquire information. A unique data set on fishing site choice by mid-Atlantic clam fishermen is used to test the model predictions. Results find that clam fishermen search new sites when the catch at familiar sites declines, i.e., when the opportunity cost of gathering information is low, but also when catch at familiar sites is on the rise. Search following a catch decline occurs at spatially distant sites whereas search following a catch increase occurs at nearby sites. Correlated learning is crucial for explaining the site choice patterns in our data. These results provide new insights that may extend to a variety of economic search problems where correlated learning is important.

PREDICTING CONSUMER INFORMATION SEARCH BENEFITS FOR PERSONALIZED ONLINE PRODUCT RANKING: A CONFIDENCE-BASED APPROACH

Product ranking mechanism is an important service for e-commerce that facilitates consumers’ decision-making process. This paper studies online product ranking under uncertainty. Different from previous studies that generally rank products merely based on predicted ratings, a new personalized product ranking method is proposed based on estimating consumer information search benefits and taking prediction uncertainty and confidence into consideration. Experiments using real data of movie ratings illustrate that the proposed method is advantageous over traditional point estimation methods, thus may help enhance customers’ satisfaction with the decision-making process and choices through saving their time and efforts

Providing a Service for Interactive Online Decision Aids through Estimating Consumers\u27 Incremental Search Benefits

Consumer information search has been a focus of research nowadays, especially in the context of online business environments. One of the research questions is to determine how much information to search (i.e., when to stop searching), since extensive literature on behavior science has revealed that consumers often search either “too little” or “too much”, even with the help of existing interactive online decision aids (IODAs). In order to address this issue, this paper introduces a new approach to IODAs with effective estimation of the incremental search benefits. In doing so, the approach incorporates two important aspects into consideration, namely point estimation and distribution estimation, so as to make use of the relevant information by combining both current and historical facts in reflecting the behavioral patterns of the consumers in search. Moreover, experiments based on data provided by Netflix illustrate that the proposed approach is effective and advantageous over existing ones

Search and active learning with correlated information: Empirical evidence from mid-Atlantic clam fishermen

This paper examines search with active learning and correlated information. We first develop a simple model to show how correlation affects the decision to acquire information. A unique data set on fishing site choice by mid-Atlantic clam fishermen is used to test the model predictions. Results find that clam fishermen search new sites when the catch at familiar sites declines, i.e., when the opportunity cost of gathering information is low, and also when catch at familiar sites is on the rise. Search following a catch decline occurs at spatially distant sites whereas search following a catch increase occurs at nearby sites. Correlated learning is crucial for explaining the site choice patterns in our data. These results provide new insights that may extend to a variety of economic search problems where correlated learning is important

Learning about one\u27s own type: a search model with two-sided uncertainty

経済学 / EconomicsThis paper examines the movement of an individual\u27s reservation level over time in a two-sided search model with two-sided imperfect self-knowledge, where agents are vertically heterogeneous and do not know their own types. Agents who do not know their own types update their beliefs about their own types through the offers or rejections they receive from others. The results in this paper show that an agent with imperfect self-knowledge revises his or her reservation level downward when the agent receives a rejection that has some information about his or her own type. In contrast, an agent with imperfect self-knowledge revises his or her reservation level upward when the agent receives an o¤er from an agent of the opposite sex who is of lower type than the reservation level. This upward revision of an agent\u27s reservation level is due to the environment of two-sided imperfect self-knowledge.JEL Classification Codes: D82, D83, J1

Optimal Search and Discovery

This paper studies a search problem where a consumer is initially aware of only a few products. At every point in time, the consumer then decides between searching among alternatives he is already aware of and discovering more products. I show that the optimal policy for this search and discovery problem is fully characterized by tractable reservation values. Moreover, I prove that a predetermined index fully specifies the purchase decision of a consumer following the optimal search policy. Finally, a comparison highlights differences to classical random and directed search.Comment: 48 pages, 2 figures, 3 table

One-sided learning about one’s own type in a two-sided search model: The case of n types of agents

This study analyzes a two-sided search model in which agents are vertically heterogeneous and agents on one side do not know their own type. Agents with imperfect self-knowledge update their beliefs based on the offers or rejections they receive from others. The results are as follows. An agent with imperfect self-knowledge lowers his or her reservation level if the agent receives a rejection that leads him or her to revise belief downward. However, an agent with imperfect self-knowledge does not raise his or her reservation level even if the agent receives an offer that leads him or her to revise his or her belief upward. As a result, an agent with imperfect self-knowledge has the highest reservation level when he or she has just entered the market; after that, a series of meetings gradually lowers his or her reservation level over the duration of the search.JEL Classification Codes: D82, D83, J12http://doi.org/10.24545/0000134