nep-knm New Economics Papers
on Knowledge Management and Knowledge Economy
Issue of 2006‒10‒21
seven papers chosen by
Emanuele Canegrati
London School of Economics and Political Science

  1. On heuristic and linear models of judgment: Mapping the demand for knowledge By Robin Hogarth; Natalia Karelaia
  2. When Knowledge is an Asset: Explaining the Organizational Structure of Large Law Firms By James B. Rebitzer; Lowell J. Taylor
  3. Perceiving strategic environments: An experimental study of learning under minimal information By Andreas Nicklisch
  4. An Uncertainty-Based Explanation of Symmetric By Cozzi, Guido; Giordani, Paolo; Zamparelli, Luca
  5. The Impact of Institutions on the Decision How to Decide By Christoph Engel; Elke U. Weber
  6. From the ivory tower to the market place? The changing role of knowledge organisations in spurring the development of biotechnology clusters in Austria By Michaela Trippl; Franz Tödtling
  7. Creating Creativity: The organizational manipulation of aesthetics in a web-design department By Warren, Sam

  1. By: Robin Hogarth; Natalia Karelaia
    Abstract: Research on judgment and decision making presents a confusing picture of human abilities. For example, much research has emphasized the dysfunctional aspects of judgmental heuristics, and yet, other findings suggest that these can be highly effective. A further line of research has modeled judgment as resulting from “as if” linear models. This paper illuminates the distinctions in these approaches by providing a common analytical framework based on the central theoretical premise that understanding human performance requires specifying how characteristics of the decision rules people use interact with the demands of the tasks they face. Our work synthesizes the analytical tools of “lens model” research with novel methodology developed to specify the effectiveness of heuristics in different environments and allows direct comparisons between the different approaches. We illustrate with both theoretical analyses and simulations. We further link our results to the empirical literature by a meta-analysis of lens model studies and estimate both human and heuristic performance in the same tasks. Our results highlight the trade-off between linear models and heuristics. Whereas the former are cognitively demanding, the latter are simple to use. However, they require knowledge – and thus “maps” – of when and which heuristic to employ.
    Keywords: Decision making; heuristics; linear models; lens model; judgmental biases
    JEL: D81 M10
    Date: 2006–06
    URL: http://d.repec.org/n?u=RePEc:upf:upfgen:974&r=knm
  2. By: James B. Rebitzer; Lowell J. Taylor
    Abstract: We study the economics of employment relationships through theoretical and empirical analysis of an unusual set of firms, large law firms. Our point of departure is the "property rights" approach that emphasizes the centrality of ownership's legal rights to control important, non-human assets of the enterprise. From this perspective, large law firms are an interesting and potentially important object of study because the most valuable assets of these firms take the form of knowledge - particularly knowledge of the needs and interests of clients. We argue that the two most distinctive organizational features of large law firms, the use of "up or out" promotion contests and the practice of having winners become residual claimants in the firm, emerge naturally in this setting. In addition to explaining otherwise anomalous features of the up-or-out partnership system, this paper suggests a general framework for analyzing organizations where assets reside in the brains of employees.
    JEL: J4 L2 M5
    Date: 2006–10
    URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:12583&r=knm
  3. By: Andreas Nicklisch (Max Planck Institute for Research on Collective Goods)
    Abstract: We present the results of an experiment on learning with minimal information. Particularly, subjects are only provided with feedback about their own payoff from the last period of the game being played, but not with information about the structure of the game. We compare the empirical structure of the decision algorithm for this setting with the empirical structure of algorithms for subjects who receive sufficient information to learn the game. The laboratory data show that, depending on the information setting, players adjust their strategy choice differently. The structure of the decision algorithm for subjects operating with minimal information indicates myopic responses to success, while the structure for sufficiently informed players is more complex. As a consequence, sufficiently informed players outperform players who have minimal information in a simple coordination game. Yet, if the structure of the game changes, readjustment is more successful for the players operating with minimal information.
    Keywords: Experimental economics, learning, minimal social situation, myopia
    JEL: D83 D84
    Date: 2006–06
    URL: http://d.repec.org/n?u=RePEc:mpg:wpaper:2006_17&r=knm
  4. By: Cozzi, Guido (University of Macerata); Giordani, Paolo (European University Institute); Zamparelli, Luca (New School University)
    Abstract: We provide a re-foundation of the symmetric growth equilibrium characterizing the research sector of all vertical R&D-driven growth models. This result does not rely on the usual assumption of a symmetric expectation on the future per-sector R&D expenditure. Indeed, with this structure of expectations, returns in R&D are equalized, and agents turn out to be indifferent as to where targeting research: hence, the problem of the allocation of R&D investments across sectors is indeterminate. In line with the ’true’ Schumpeterian perspective, we solve this indeterminacy by allowing for decision makers strictly uncertain about the future per-sector distribution of R&D efforts. By using the Gilboa-Schmeidler’s MEU decision rule, we prove that the symmetric structure of R&D investment is the unique rational expectations (RE) equilibrium compatible with uncertainty-averse agents adopting a maximin strategy.
    Date: 2006–08–21
    URL: http://d.repec.org/n?u=RePEc:xrs:sfbmaa:06-08&r=knm
  5. By: Christoph Engel (Max Planck Institute for Research on Collective Goods, Bonn); Elke U. Weber (Columbia University, Professor of Psychology and Management)
    Abstract: The human mind is not a general problem solving machine. Instead of deliberately, consciously and serially processing the available information, men can rely on routines, rules, roles or affect for the purpose. They can bring in technology, experts or groups. For all of these reasons, men have a plurality of problem solving modes at their disposition. Often, the meta-choice of problem solving mode matters for behavioural output. Some performance standards are only to be met if a certain problem solving mode is used, like a well-established skill. Other requirements are easier to fulfil with some problem solving modes. This explains why institutions frequently impact on the choice of problem solving mode. To show how institutions are able to do that, a model of problem solving modes is developed. It allows to systematise the access points for institutional intervention.
    Keywords: Decision Making, Problem Solving, Institutions
    JEL: D10 D21 D83 K20 K40 L51 Z13
    Date: 2006–08
    URL: http://d.repec.org/n?u=RePEc:mpg:wpaper:2006_19&r=knm
  6. By: Michaela Trippl; Franz Tödtling
    Date: 2006
    URL: http://d.repec.org/n?u=RePEc:wiw:wiwsre:sre-disc-2006_07&r=knm
  7. By: Warren, Sam
    Date: 2005–01–01
    URL: http://d.repec.org/n?u=RePEc:hhb:pinkwp:9&r=knm

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