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Managing Uncertainty (managing + uncertainty)
Selected AbstractsManaging Uncertainty in Creative Industries: Lessons from Jerry Springer the OperaCREATIVITY AND INNOVATION MANAGEMENT, Issue 3 2006Anna M. Dempster This article considers the impact of uncertainty on entrepreneurial performance in the UK theatre industry. The article identifies and evaluates the major determinants of demand uncertainty ,audience composition, critical acclaim and media coverage, whose management is key to entrepreneurial success. An in-depth historical case study of the controversial production, Jerry Springer the Opera, analyses the evolution of these three distinct sources of uncertainty and illustrates that they should not be treated in isolation since they interact in complex ways which change with time. The case study shows how the entrepreneurs involved used a multi-staged production process as a strategy to market test their product and to distribute their risks across agents and over time. The article therefore considers what contributed to both the successes and failures of these entrepreneurs as well as highlighting important strategic lessons for managing uncertainty in creative industries. [source] Hybrid Framework for Managing Uncertainty in Life Cycle InventoriesJOURNAL OF INDUSTRIAL ECOLOGY, Issue 6 2009Eric D. Williams Summary Life cycle assessment (LCA) is increasingly being used to inform decisions related to environmental technologies and polices, such as carbon footprinting and labeling, national emission inventories, and appliance standards. However, LCA studies of the same product or service often yield very different results, affecting the perception of LCA as a reliable decision tool. This does not imply that LCA is intrinsically unreliable; we argue instead that future development of LCA requires that much more attention be paid to assessing and managing uncertainties. In this article we review past efforts to manage uncertainty and propose a hybrid approach combining process and economic input,output (I-O) approaches to uncertainty analysis of life cycle inventories (LCI). Different categories of uncertainty are sometimes not tractable to analysis within a given model framework but can be estimated from another perspective. For instance, cutoff or truncation error induced by some processes not being included in a bottom-up process model can be estimated via a top-down approach such as the economic I-O model. A categorization of uncertainty types is presented (data, cutoff, aggregation, temporal, geographic) with a quantitative discussion of methods for evaluation, particularly for assessing temporal uncertainty. A long-term vision for LCI is proposed in which hybrid methods are employed to quantitatively estimate different uncertainty types, which are then reduced through an iterative refinement of the hybrid LCI method. [source] Fuzzy extensions for relationships in a generalized object modelINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 7 2001Valerie V. Cross Numerous approaches for introducing and managing uncertainty in object-oriented models have been proposed. This paper examines various semantics of uncertainty and the interaction with three kinds of relationships inherent to object models: for instance-of, a-kind-of, and a category. A generalized object model incorporating the perspective of semantic data modeling, artificial intelligence, and database systems is the basis for the recommendations for fuzzy extensions to these three kinds of relationships. © 2001 John Wiley & Sons, Inc. [source] Forecasting plant migration rates: managing uncertainty for risk assessmentJOURNAL OF ECOLOGY, Issue 3 2003S. I. Higgins Summary 1Anthropogenic changes in the global climate are shifting the potential ranges of many plant species. 2Changing climates will allow some species the opportunity to expand their range, others may experience a contraction in their potential range, while the current and future ranges of some species may not overlap. Our capacity to generalize about the threat these range shifts pose to plant diversity is limited by many sources of uncertainty. 3In this paper we summarize sources of uncertainty for migration forecasts and suggest a research protocol for making forecasts in the context of uncertainty. [source] Civil-Military Affairs and Security Institutions in the Southern Cone: The Sources of Argentine-Brazilian Nuclear CooperationLATIN AMERICAN POLITICS AND SOCIETY, Issue 4 2004Arturo C. Sotomayor Velázquez ABSTRACT This paper analyzes the conditions in which the governments of Argentina and Brazil founded security institutions in the early 1990s, while they were democratizing. It advances the hypothesis that international cooperation in the security field is often linked to the evolution of civil-military relations. Civilian leaders in both countries established institutions and sought international participation deliberately to achieve civilian control and gain leverage over the military establishment, which they sorely distrusted. The need to stabilize civil-military relations at home was therefore the prime motivating force behind the emergence of security institutions in the Southern Cone. Three mechanisms were at work: omnibalancing, policy handling, and managing uncertainty. These mechanisms are derived from three different schools of thought: realism, organizational-bureaucratic models, and theories of domestic political institutions. Besides explaining the sources of nuclear bilateral cooperation, this argument also serves as a critique of two prominent theories in international relations that attempt to explain cooperation and peaceful relations among democracies: neoliberal insti-tutionalism and democratic peace theory. [source] Joint venture evolution: extending the real options approachMANAGERIAL AND DECISION ECONOMICS, Issue 4 2008Jing Li Real options theory has emerged as a promising avenue to study joint venture (JV) evolution as a strategic response to managing uncertainty. We extend the real options approach by integrating it with game theory. Such a combined method enriches the valuation functions of each partnering firm and helps to identify the optimal decisions for exercising options in a JV. In our model, each firm's synergy from the joint operation and its knowledge acquisition capability (KAC) can significantly influence the competitive dynamics between partners, potentially affecting how each firm decides to acquire, divest, or dissolve. We employ a new solution technique in real options theory to capture the stochastic process of three factors, and use computer simulation to test the model under varying conditions. The results are stated in five testable propositions, providing a better understanding of the dynamics of a JV. We find that symmetries between partners in synergy or KAC contribute to stability or dissolution of the JV, whereas asymmetries in synergy or KAC make acquisition of the JV assets by one partner desirable. Copyright © 2008 John Wiley & Sons, Ltd. [source] | ||||||||||