With the evolution of the Web and development of web-based search engines, online searching has become a common method for obtaining information. Given this popularity, the question arises as to how much time people save by using search engines for their information needs compared to offline sources, as well as how online searching affects both search experiences and search outcomes. Using a random sample of queries from a major search engine and a sample of reference questions from the Internet Public Library (IPL), we conduct a real-effort experiment to compare online and offline search experiences and outcomes. We find that participants are significantly more likely to find an answer on the Web (100 %), compared to offline searching (between 87 % and 90 %). Restricting our analysis to the set of questions in which participants find answers in both treatments, a Web search takes on average 7 (9) minutes, whereas the corresponding offline search takes 22 (19) minutes for a search-engine (IPL) question. Furthermore, while raters judge library sources to be significantly more trustworthy and authoritative than the corresponding Web sources, they judge Web sources as significantly more relevant. Balancing all factors, we find that the overall source quality is not significantly different between the two treatments for the set of search-engine questions. However, for IPL questions, we find that non-Web sources are judged to have significantly higher overall quality than the corresponding Web sources. In comparison, for factual questions, Web search results are significantly more likely to be correct (66 % vs. 43 %). Lastly, post-search questionnaires reveal that participants find online searching more enjoyable than offline searching.

In many search environments, searchers are learning about the distribution of offers in the market. I conduct an experiment exploring a broad class of search problems with learning about the distribution of payoffs. My results support the prediction that learning results in declining reservation values, providing evidence that learning may be an explanation for recall. Theory predicts a “one step” reservation value strategy, but many subjects instead choose to set a high reservation value in order to learn about the distribution before adjusting based on their observations. Under-searching in search experiments may stem from a reinforcement heuristic and lack of negative feedback after using sub-optimal strategies.

We investigate how people make choices when they are unsure about the value of the options they face and have to decide whether to choose now or wait and acquire more information first. In an experiment, we find that participants deviate from optimal information acquisition in a systematic manner. They acquire too much information (when they should only collect little) or not enough (when they should collect a lot). We show that this pattern can be explained as naturally emerging from Fechner cognitive errors. Over time participants tend to learn to approximate the optimal strategy when information is relatively costly.

In theory, search conditions are a key determinant of Pandora’s rule (i.e. of the optimal search pattern), and of the eventual payoffs (Weitzman, 1979; Doval, 2018). We compare different search conditions in the laboratory and find strong evidence that they affect subjects’ order of inspection and payoffs greatly. Subjects are more conservative at the beginning of the search, and earn less if they are constrained to choose only among the inspected alternatives, than if they are not. These findings reinforce the empirical pertinence of the formal search literature, and generate novel insights regarding relevant settings of applied interest (e.g. the impact of market digitization on consumer behavior).

We seek to isolate in the laboratory factors that encourage and discourage the sunk cost fallacy. Subjects play a computer game in which they decide whether to keep digging for treasure on an island or to sink a cost (which will turn out to be either high or low) to move to another island. The research hypothesis is that subjects will stay longer on islands that were more costly to find. Eleven treatment variables are considered, e.g. alternative visual displays, whether the treasure value of an island is shown on arrival or discovered by trial and error, and alternative parameters for sunk costs. The data reveal a surprisingly small sunk cost effect that is generally insensitive to the proposed psychological drivers.

By reference to nominated attributes, a genus, being a population of objects of one specified kind, may be partitioned into species, being subpopulations of different kinds. A prototype is an object representative of its species within the genus. Using this framework, the paper describes how objects can be relatively differentiated with respect to attributes, and how attributes can be relatively differentiating with respect to objects. Methods and rationale for such differential ordering of objects and attributes are presented by example, formal development, and application.

For a genus Ω comprising n species of object there is a subset P ofn distinct prototypes. With respect to m nominated attributes, each object in Ω has an m-element characterization. Together these determine an n × m objects × attributes matrix, the rows of which are the characterizations of the prototypical objects. Over then species in Ω, an associated relative frequency vector gives the distribution of objects (and of their characterizations). The matrix and vector associate the objects in Ω with points in a metric space (P, δ); and it is with respect to various sums of distances in this attribute space that one can differentially order objects and attributes.

The definition of the distance function δ is generalized across kinds of difference, types of characterization, scale-types of measurement, Minkowski index ≧ 1, and any form of distribution of objects over species. Explanatory and taxonomic applications in psychology and other fields are discussed, with focus on classification, identification, recognition, and search. The Braille code and the identification of its characters provide illustration.

This article reviews recent advances in the psychometric and econometric modeling of eye-movements during decision making. Eye movements offer a unique window on unobserved perceptual, cognitive, and evaluative processes of people who are engaged in decision making tasks. They provide new insights into these processes, which are not easily available otherwise, allow for explanations of fundamental search and choice phenomena, and enable predictions of future decisions. We propose a theoretical framework of the search and choice tasks that people commonly engage in and of the underlying cognitive processes involved in those tasks. We discuss how these processes drive specific eye-movement patterns. Our framework emphasizes the central role of task and strategy switching for complex goal attainment. We place the extant literature within that framework, highlight recent advances in modeling eye-movement behaviors during search and choice, discuss limitations, challenges, and open problems. An agenda for further psychometric modeling of eye movements during decision making concludes the review.

When faced with a decision, people collect information to help them decide. Though it may seem unnecessary, people often continue to search for information about alternatives after they have already chosen an option, even if this choice is irreversible (e.g., checking out other cars after just purchasing one). While previous post-decision search studies focused on “one-shot” decisions and highlighted its irrational aspects, here we explore the possible benefits of post-decision search in the long run. We use a simple search task in which participants repeatedly decide whether to select the current alternative or continue to search for a better alternative. In a preliminary study we find that participants indeed conduct post-decision search even in unique environments, where information about forgone options cannot be used in future choices. In the main studies exposure to post-decision information was manipulated directly in unique environments, and was found to lead to better performance. The source of the observed improvement was further investigated with an explicit strategy elicitation methodology. We find that following exposure to post-decision information, people collect more data before generating thresholds. Thus, although post-decision search in unique environments might appear redundant, our results suggest it can help decision makers to modify their strategy and improve their future choices.

As nudge interventions have become more popular, academic research is developing that assesses to what extent these interventions are effective. My paper contributes to this stream of research: collating and synthesising evidence on the effectiveness of nudge interventions that aim to increase consumer search and switching in retail financial markets. Following a systematic search strategy, I identify 35 relevant papers, including qualitative studies, laboratory experiments, field experiments and ex post analyses, covering a range of retail financial products and different types of nudges. The review results in two main contributions. First, it demonstrates that different study designs serve different purposes in evidence accumulation. Second, based on over 400 estimates extracted from these papers, it establishes that the currently available evidence shows that nudges increase consumer search and switching in retail financial markets by 2–3 percentage points on average. Structural nudges that change the choice architecture more profoundly have a higher impact on search and switching than nudges that provide, simplify or highlight information. While nudge interventions may be efficient on a cost–benefit basis and can lead to a large increase in relative terms (e.g. doubling switching rates from 1% to 2%), regulators cannot expect them to significantly alter consumer behaviour.

We use a labor search model with heterogenous households and firms to study the efficacy of a wage subsidy during a pandemic, relative to enhancing unemployment benefits. A large proportion of the economy is forced to shut down, and firms in that sector choose whether to lay off workers or keep them on payroll. A wage subsidy encourages firms to keep workers on payroll, which speeds up labor market recovery after the pandemic ends. However, a wage subsidy can be costlier than enhancing unemployment benefits. If the shutdown is long or profit margins are low, then a wage subsidy is preferable and vice versa. The optimal mixture of policies includes a wage subsidy that covers 90$\%$ of the first $200/week of earnings and expands unemployment benefits to cover all salary up to $275/week. Low-income workers, as well as those in less productive jobs, benefit the most from a wage subsidy.

This paper proposes and evaluates swarming mechanisms of patrolling unmanned aerial vehicles (UAVs) that can collectively search a region for intruding UAVs. The main contributions include the development of multi-objective searching strategies and investigation of the required sensor configurations for the patrolling UAVs. Numerical results reveal that it is sometimes better to search through a region with a single swarm rather than multiple swarms deployed over sub-regions. Moreover, a large communication range does not necessarily improve search performances, and the patrolling swarm must have a speed close to the speed of the intruding UAVs to maximize the search performances.

We introduce business-to-business (B2B) relationships into an otherwise standard model to revisit two aspects of price dynamics in a unified analysis. On one side, the pass-through of cost shocks to prices is empirically incomplete. On the other side, the literature contains conjectures that long-term relationships may reduce the allocative role of price changes. After a partial equilibrium analysis of these aspects, we consider the general equilibrium effects. The formation of B2B relationships implies that the trade of intermediate goods depends on search, bargaining, and the adjustment along the intensive margin as opposed to the extensive margin. We find that, when this adjustment is costly, retailers have a relatively high bargaining power, and mismatch shocks are possible, the model can account for the second moments of the US producer price index and other variables. In this case, although its allocative role is low, the intermediate goods price affects the allocation of goods through the search externalities and is sufficiently volatile. The analysis includes several sensitivity tests and comparisons.