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This article describes an experiment in a Kydland/Prescott type of environment with cheap talk. Individual evolutionary learning (IEL) acts as a policy maker that makes inflation announcements and decides on actual inflation rates. IEL evolves a set of strategies based on the evaluation of their counterfactual payoffs measured in terms of disutility of inflation and unemployment. Two types of private agents make inflation forecasts. Type 1 agents are automated and they set their forecast equal to the announced inflation rate. Type 2 agents are human subjects who submit their inflation forecast and are rewarded based on their forecast error. The fraction of each type evolves over time based on their performance. Experimental economies result in outcomes that are better than the Nash equilibrium. This article is the first to use an automated policy maker that changes and adapts its rules over time in response to the environment in which human subjects make choices.

Expectations play a crucial role in finance, macroeconomics, monetary economics, and fiscal policy. In the last decade a rapidly increasing number of laboratory experiments have been performed to study individual expectation formation, the interactions of individual forecasting rules, and the aggregate macro behavior they co-create. The aim of this article is to provide a comprehensive literature survey on laboratory experiments on expectations in macroeconomics and finance. In particular, we discuss the extent to which expectations are rational or may be described by simple forecasting heuristics, at the individual as well as the aggregate level.

The purpose of this paper is to consider queuing systems where captive repeat customers select a service facility each period. Are people in such a distributed system, with limited information diffusion, able to approach optimal system performance? How are queues formed? How do people decide which queue to join based on past experience? The authors explore these questions, investigating the effect of information availability, as well as the effect of heterogeneous facility sizes, at the macro (system) and micro (individual performance) levels.

Experimental economics, using a queuing experiment.

The authors find little behavioural difference at the aggregate level, but observe significant variations at the individual level. This leads the authors to the conclusion that it is not sufficient to evaluate system performance by observing average customer allocation and sojourn times at the different facilities; one also needs to consider the individuals’ performance to understand how well the chosen design works. The authors also observe that better information diffusion does not necessarily improve system performance.

Evaluating system performance based on aggregate behaviour can be misleading; however, this is how many systems are evaluated in practice, when only aggregate performance measures are available. This can lead to suboptimal system designs.

There has been little theoretical or empirical work on queuing systems with captive repeat customers. This study contributes to the understanding of decision making in such systems, using laboratory experiments based on the cellular automata approach, but with all agents replaced by humans.

Reports on a project to create a new infrastructure for experimental economics and sociology by connecting cutting edge research to Web‐based software development. The project will build and maintain an active Web site of highly flexible modular architecture for theoretically‐driven experimentation. The Web site, itself a laboratory, fundamentally advances experimental study, automatically records and archives data, and maintains electronic journals. To increase the integrity and effectiveness of social science knowledge acquisition, the Web site will support replications while creating large and systematic databases. The Web‐lab’s goal is to change social science investigation by allowing experiments to be run using subjects from large and diverse populations. The Web‐lab will democratize experimental research; a local laboratory will need no more than a few computers with access to the Web. Using designs at the Web‐lab, extensive laboratory components will be developed for mainstream graduate and undergraduate social science courses.

Communication between supply chain partners is critical for replenishment decision making. Decision support systems still require significant human decision making with regard to replenishment when promotions are involved. The purpose of this paper is to study the impact of the sharing of information about the magnitude and timing of retail promotions on cost efficiency in the supply chain. The authors compare performance against theoretical benchmarks and draw conclusions significant to managers.

The subjects in Study 1, 30 undergraduate students at a large, US university, completed the experiment in a single session lasting approximately 60 minutes. The experiment involved a simple, multi‐period replenishment task, played as individuals, that was somewhat like the newsvendor game. Subjects in the experiment employed in Study 2 were senior‐level members of multiple departments from a large consumer products manufacturer in the USA. Participating departments included sales, operations, and supply chain. Self‐reported questionnaires revealed that the average subject had 15 years of experience with supply chain issues and seven years of experience with replenishment. The study was conducted in a single session, lasting approximately two hours, at the corporate headquarters of the participating company. In this experiment, 76 unique subjects participated.

Results from the single‐echelon study reveal the cost‐reducing effect of knowing the magnitude and timing of demand generated by a promotion. However, the poor performance, compared with the theoretical benchmarks, by respondents in the multi‐echelon study, even when the lead time per node is half that of the single‐echelon case and the subjects were experienced managers, highlights the complexity of the task that results from a lack of coordination.

Billions of dollars are spent on retail promotions each year. The management of the forecasting and replenishment of inventory for such promotions is difficult to automate and requires significant human decision making. The paper explores some key issues that are important in the replenishment decision‐making scenario when a promotion is involved.

Although the most obvious managerial recommendation for reducing the coordination and planning problems associated with promotions is simply to communicate more, the authors' research also suggests it may not be enough to alter performance. The results suggest that while communication is helpful, coordination may represent a more serious challenge.

This paper aims to advocate and facilitate undertaking research focused on the effects of human behaviour, judgment and decision making in logistics and supply chain management (SCM).

In addition to providing an overview of the potential benefits of behavioural research, this paper presents two modified frameworks for identifying and addressing behavioural issues in logistics and SCM.

Behavioural research can significantly advance both theory and practice in logistics and SCM. Little behavioural research appears in top logistics journals. As researchers begin to conduct more such projects, knowledge pertaining to issues of importance to logistics and SCM will be created.

This paper highlights an important research area and a methodology, (controlled behavioural experiments), that are currently underutilized in logistics and SCM. It further presents potential research questions and suggestions for ways in which interested researchers could begin to address such issues.

Certain elements of Hayek’s work are prominent precursors to the modern field of complex adaptive systems, including his ideas on spontaneous order, his focus on market processes, his contrast between designing and gardening, and his own framing of complex systems. Conceptually, he was well ahead of his time, prescient in his formulation of novel ways to think about economies and societies. Technically, the fact that he did not mathematically formalize most of the notions he developed makes his insights hard to incorporate unambiguously into models. However, because so much of his work is divorced from the simplistic models proffered by early mathematical economics, it stands as fertile ground for complex systems researchers today. I suggest that Austrian economists can create a progressive research program by building models of these Hayekian ideas, and thereby gain traction within the economics profession. Instead of mathematical models the suite of techniques and tools known as agent-based computing seems particularly well-suited to addressing traditional Austrian topics like money, business cycles, coordination, market processes, and so on, while staying faithful to the methodological individualism and bottom-up perspective that underpin the entire school of thought.

Argues that Humphrey’s tearoom trade study, misinforms readers as much as it informs, regarding moral and ethical foundations for research with human subjects. States that Humphrey’s tearoom study made significant positive contributions to the population he studied. Concludes that few studies in sociology have accomplished as much in a single work.

The purpose of this paper is to propose practical and usable interactions that will allow more informed, risk-aware comparisons for individuals during app selections. The authors include an explicit argument for the role of human decision-making during app selection and close with a discussion of the strengths of a Bayesian approach to evaluating privacy and security interventions.

The authors focused on the risk communication in mobile marketplace’s realm, examining how risk indicators can help people choose more secure and privacy-preserving apps. Combining canonical findings in risk perception with previous work in usable security, the authors designed indicators for each app to enable decisions that prioritize risk avoidance. Specifically, the authors performed a natural experiment with N = 60 participants, where they asked them to select applications on Android tablets with accurate real-time marketplace data.

In the aggregate, the authors found that app selections changed to be more risk-averse in the presence of a user-centered multi-level warning system using visual indicators that enabled a click-thru to the more detailed risk and permissions information.

Privacy research in the laboratory is often in conflict with privacy decision-making in the marketplace, resulting in a privacy paradox. To better understand this, the authors implemented a research design based on clinical experimental approaches, testing the interaction in a noisy, confounded field environment.