Welcome to Merlin

Commercial home automation systems are becoming increasingly common, affording the opportunity to study technology-augmented homes in real world contexts. In order to understand how these technologies are being integrated into homes and their effects on inhabitants, we conducted a qualitative study involving smart home professionals who provide such technology, people currently in the process of planning or building smart homes, and people currently living in smart homes. We identified motivations for bringing smart technology into homes, and the phases involved in making a home smart. We also explored the varied roles of the smart home inhabitants that emerged during these phases, and several of the challenges and benefits that arise while living in a smart home. Based on these findings we propose open areas and new directions for smart home research.

Recent work on searching the Semantic Web has yielded a wide range of approaches with respect to the style of input, the under- lying search mechanisms and the manner in which results are presented. Each approach has an impact upon the quality of the information re- trieved and the user’s experience of the search process. This highlights the need for formalised and consistent evaluation to benchmark the cov- erage, applicability and usability of existing tools and provide indications of future directions for advancement of the state-of-the-art. In this paper, we describe a comprehensive evaluation methodology which addresses both the underlying performance and the subjective usability of a tool. We present the key outcomes of a recently completed international evalu- ation campaign which adopted this approach and thus identify a number of new requirements for semantic search tools from both the perspective of the underlying technology as well as the user experience.

Traders' values and information typically consist of both private and common-value elements. In such environments, full allocative efficiency is impossible when the private rate of information substitution differs from the social rate (Jehiel and Moldovanu, 2001). We link this impossibility result to a failure of the efficient market hypothesis, which states that prices adequately reflect all available information (Fama, 1970, 1991). The intuition is that if prices were able to reveal all information then the common value would simply shift traders' private values by a known constant and full allocative efficiency would result. In a series of laboratory experiments we study price formation in markets with private and common values. Rational expectations, which form the basis for the efficient market hypothesis, predict that the introduction of common values has no adverse consequences for allocative and informational efficiency. In contrast, a "private" expectations model in which traders' optimal behavior depends on both their private and common-value information predicts that neither full allocative nor full informational efficiency is possible. We test these competing hypotheses and find that the introduction of common values lowers allocative efficiency by 28% on average, as predicted by the private expectations model, and that market prices differ significantly and substantially from their rational expectation levels. Finally, a comparison of observed and predicted payoffs suggests that observed behavior is close to the equilibrium predicted by the private expectations model.

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This paper reports results from a series of laboratory experiments designed to evaluate the impact of exposure risk on market performance. Exposure risk arises when there are complementarities between trades, e.g. when the purchase of a new house requires selling the old one. The continuous double auction (CDA), which has proven to be remarkably effective in a wide variety of settings, performs poorly in a treatment with high exposure risk: overall market efficiency is only 20% and there are many instances of no trade. In a parallel treatment with lower exposure risk, efficiency under the CDA is higher (55%) but is dominated, for instance, by a top-trading-cycles procedure that uses no money. The CDA's poor performance does not depend on whether house values are private information or common knowledge, indicating that exposure risk is due to strategic uncertainty not objective uncertainty about others' preferences. We introduce a simple package market and show that it effectively resolves exposure risk: efficiency levels are 82% and 89% respectively for the low and high exposure treatments. The proposed package market is a simple extension of the CDA and could potentially be applied in a variety contexts.

This paper examines whether and how cheap talk communication can facilitate within-group coordination when two unequal sized groups compete for a prize that is shared equally among members of the winning group, regardless of their (costly) contributions to the group’s success. We find that allowing group members to communicate before making contribution decisions improves coordination. To measure how much miscoordination remains, we employ a control treatment where miscoordination is eliminated by asking group members to reach a unanimous contribution decision. Average group contributions are not significantly different in this control treatment. Cheap talk communication thus completely solves miscoordination within groups and makes group members act as a single agent. Furthermore, it is the larger group that benefits from communication at the expense of the smaller group. Finally, content analysis of group communication reveals that after the reduction of within-group strategic uncertainty, groups reach self-enforcing agreements on how much to contribute, designate specific contributors according to a rotation scheme, and quickly discover the logic of the mixed-strategy equilibrium.

This paper determines the value of asset tradeability in an option pricing framework. In our model, tradeability is valuable since it allows investors to exploit temporary mis- pricings of stocks. The model delivers several novel insights on the value of tradeability: The value of tradeability is the larger, the higher the pricing e±ciency of the market is. Uncertainty increases the value of tradeablity, no matter whether the uncertainty results from noise trading or from new information about the fundamental value of the stock. The value of tradeability is the larger, the longer the illiquid stock cannot be traded and the more trading dates the liquid stock offers.

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Today, the purpose of a model is often kept implicit. The lack of explicit statements about a model's purpose hinders both its creation and its (re)use. In this paper, we adapt two goal modeling techniques, the Goal-Question-Metric paradigm and KAOS, an intentional modeling language, so that the purpose of a model can be explicitly stated and operationalized. Using some examples, we present how these approaches can document a model's purpose so that this model can be validated, improved and used correctly.