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Computational \& Mathematical Organization Theory provides an international forum for interdisciplinary research that combines computation, organizations and society. The goal is to advance the state of science in formal reasoning, analysis, and system building drawing on and encouraging advances in areas at the confluence of social networks, artificial intelligence, complexity, machine learning, sociology, business, political science, economics, and operations research. The papers in this journal will lead to the development of newtheories that explain and predict the behaviour of complex adaptive systems, new computational models and technologies that are responsible to society, business, policy, and law, new methods for integrating data, computational models, analysis and visualization techniques. Various types of papers and underlying research are welcome. Papers presenting, validating, or applying models and/or computational techniques, new algorithms, dynamic metrics for networks and complex systems and papers comparing, contrasting and docking computational models are strongly encouraged. Both applied and theoretical work is strongly encouraged. The editors encourage theoretical research on fundamental principles of social behaviour such as coordination, cooperation, evolution, and destabilization. The editors encourage applied research representing actual organizational or policy problems that can be addressed using computational tools. Work related to fundamental concepts, corporate, military or intelligence issues are welcome. The journal publishes a number of special issues on focused topics, including organizations of intelligent agents, counter-terrorism, computational statistics for networks, and organizations in crises. In addition, tutorial papers, such as how to check the robustness of a simulation, or system details - such as algorithm descriptions are also welcome. The audience is international in scope. It includes researchers, students, academic, corporate and military personnel in all of the social and organizational disciplines, operations research and graph theory, mathematics, computer science, and management.

Book review in The Economist: JOHN CASSIDY'S new book is a sequel of sorts. In his previous work, “Dot.Con”, which came out in 2002, he chronicled the follies of the stockmarket bubble of the late 1990s. In “How Markets Fail”, Mr Cassidy, a British writer for the New Yorker, recounts the story of America's housing boom and its devastating bust. It is more than just an account of the failures of regulators and the self-deception of bankers and homebuyers, although these are well covered. For Mr Cassidy, the deeper roots of the crisis lie in the enduring appeal of an idea: that society is always best served when individuals are left to pursue their self-interest in free markets. He calls this “Utopian economics”. This approach turns much of the book into a very good history of economic thought. Mr Cassidy starts in 1776 with Adam Smith and his butchers, brewers and bakers, who supplied their wares as if guided by an unseen hand. Smith's analysis was made richer in the 1940s by Friedrich von Hayek, the Austrian who saw market prices as signals of which goods were scarce and which were abundant. Hayek's idea of the free market as a machine for processing and transmitting information “was one of the great insights of the 20th century,” writes Mr Cassidy. The book gives a detailed account of how the formal “proof” of the efficiency of free markets evolved. The breakthrough was made in the early 1950s by Kenneth Arrow, an American economist, and Gérard Debreu, a French mathematician who died in 2004. Mr Cassidy admires the maths, but points out that their findings rely on some unrealistic assumptions, something the two theorists were quite open about. Arrow and Debreu's “general equilibrium theory” seemed to give the stamp of scientific approval to unfettered markets. And it may have made it harder to challenge the purist free-market views of Alan Greenspan, the Federal Reserve chairman until 2006 whom Mr Cassidy partly blames for the dotcom and housing bubbles. Having set out the tenets of Utopian economics, the author then pokes holes in them. Individual self interest does not always benefit society, he argues, and draws on a deep pool of research what he calls “reality-based economics” to support his case. Markets fail if prices send the wrong signals. For instance, an increase in house prices ought to discourage new homebuyers. In practice, however, higher prices are a spur to buyers who hope to benefit from further rises. For would-be homeowners, the signal is that it is time to buy; for banks, that it is time to lend. Those who suspect a bubble face the same dilemma as textbook prisoners: it makes sense to act sensibly only if others do so too. Since that cannot be relied upon, it is safer to go with the herd. The result of such individually rational behaviour is a housing and credit boom, followed inevitably by a nasty bust. Markets also founder when there is hidden information—if sellers know more than buyers, for example—and when the prices paid by individuals do not fully reflect social costs, such as pollution. Such failures were evident in the build-up to the current crisis: dud mortgages were packaged as supposedly safe bonds to investors; banks did not factor in the wider costs of bad debt when making risky loans. Policymakers should have intervened to curb the excesses but were hamstrung by free-market ideology. “How Markets Fail” is an ambitious book, and one that mostly succeeds. Despite its title, it makes rather a good case for market economics; what it rails against is “free market idolatry”. Its call for a better balance between individual autonomy and state oversight might have seemed off-centre just a few years ago. Now its prescription is firmly in the mainstream.