Improved Transferability of Data‐Driven Damage Models Through Sample Selection Bias Correction

Damage models for natural hazards are used for decision making on reducing and transferring risk. The damage estimates from these models depend on many variables and their complex sometimes nonlinear relationships with the damage. In recent years, data‐driven modeling techniques have been used to capture those relationships. The available data to build such models are often limited. Therefore, in practice it is usually necessary to transfer models to a different context. In this article, we show that this implies the samples used to build the model are often not fully representative for the situation where they need to be applied on, which leads to a “sample selection bias.” In this article, we enhance data‐driven damage models by applying methods, not previously applied to damage modeling, to correct for this bias before the machine learning (ML) models are trained. We demonstrate this with case studies on flooding in Europe, and typhoon wind damage in the Philippines. Two sample selection bias correction methods from the ML literature are applied and one of these methods is also adjusted to our problem. These three methods are combined with stochastic generation of synthetic damage data. We demonstrate that for both case studies, the sample selection bias correction techniques reduce model errors, especially for the mean bias error this reduction can be larger than 30%. The novel combination with stochastic data generation seems to enhance these techniques. This shows that sample selection bias correction methods are beneficial for damage model transfer.     

Taking Stock of Temporary Organizational Forms: A Systematic Review and Research Agenda

This paper brings together the research on temporary organizational forms. Despite a recent surge in publications on this topic, there have been few attempts to integrate knowledge on what we know of such temporary forms of organization. In order to correct this, an integrative framework is proposed around four central themes: time, team, task and context. Within each of these themes, the paper offers an overview of the literature, the gaps in what we know, and what future directions might be taken by scholars hoping to contribute to this important and rapidly growing field.     

Profit efficiency analysis under limited information with an application to German farm types

Lack of information about technology and prices often hampers the empirical assessment of the profit maximization hypothesis (viz. by measuring the degree of profit efficiency). The non-parametric Data Envelopment Analysis (DEA) methodology can deal with such incomplete information. We exploit the implicit but largely neglected profit interpretation of the DEA model that builds on assumptions of monotone and convex production possibility sets. We show how its embedded assessment of necessary conditions for profit maximization can be strengthened given partial information in the form of monetary sub-cost/-revenue data (that are often easier obtained than the pure quantity data). Finally, we argue that a ‘mix’ efficiency analysis is naturally complementary to such a profit efficiency analysis. An application to German farm types complements our methodological discussion. By using non-parametric statistical tests, we further demonstrate the potential of the non-parametric approach in deriving strong and robust statistical evidence while imposing minimal structure on the setting under study. In particular, we look for significant efficiency variation over regions.     

Discourse Analysis in Career Counseling and Development

Discourse analysis can be used to understand and interpret culturally and socially produced meanings regarding work and to outline how specific rules and conventions can configure meaning production of work in context. The implications of some core concepts in discourse analysis pertinent to career counseling are explored, including discourse, deconstruction, power/knowledge, psy‐complex, ideology, and identity. Such an exploration has the potential to initiate a process of critical self‐reflection in career counseling and development so as to enhance ethical, fair, and inclusive practices in the field.     

Sharing inventory risk in supply chain: The implication of financial constraint

A supply chain may operate under either preorder mode, consignment mode or the combination of these two modes. Under preorder, the retailer procures before the sale and takes full inventory risk during the sale, while under consignment, the retailer sells the product for the supplier with the supplier taking the inventory risk. The combination mode shares the risk in the supply chain. The existing research has examined the supply chain modes from various operational aspects. However, the impact of financial constraint is neglected. This paper examines the impact of financial constraint and investigates the supply chain efficiency under each mode. Based on a Stackelberg game with the supplier being the leader, we show that without financial constraint the supplier always prefers the consignment mode, taking full inventory risk. Whereas, in the presence of financial constraint, the supplier will sell part of the inventory to the retailer through preorder, which shares the inventory risk in the supply chain. We show that with financial constraint, the combination mode is the most efficient mode even if the retailer earns zero internal capital.     

Betting the farm on high food prices: A consumer based approach to agriculture protection

Our question is quite simple: If agriculture protectionism is a product of economic development, why is agriculture protected at such varying degrees by otherwise similarly developed countries? Previous attempts to fit agriculture into general models of trade policy formation have relied exclusively on producer demand for protection and merely assume the associated demand for lower prices that might come from consumers. Not surprisingly, these previous studies add only minimally to this strange phenomenon. Our method turns this approach on its head by modeling the political strategy of agriculture protection on the costs incurred by the consumer. Taking both producers and consumers into account more accurately reflects the intent of extant theoretical models of protectionism. Our results show that using the consumer as the dependent variable provides more robust results on common independent variables. Recent global events show that consumer disapproval of agriculture policies should not be underestimated by political scientists or politicians.     

An Introduction to ‘Benefit of the Doubt’ Composite Indicators

Despite their increasing use, composite indicators remain controversial. The undesirable dependence of countries’ rankings on the preliminary normalization stage, and the disagreement among experts/stakeholders on the specific weighting scheme used to aggregate sub-indicators, are often invoked to undermine the credibility of composite indicators. Data envelopment analysis may be instrumental in overcoming these limitations. One part of its appeal in the composite indicator context stems from its invariance to measurement units, which entails that a normalization stage can be skipped. Secondly, it fills the informational gap in the ‘right’ set of weights by generating flexible ‘benefit of the doubt’-weights for each evaluated country. The ease of interpretation is a third advantage of the specific model that is the main focus of this paper. In sum, the method may help to neutralize some recurring sources of criticism on composite indicators, allowing one to shift the focus to other, and perhaps more essential stages of their construction. An abridged version of this paper was presented at the Workshop on European Indicators and Scoreboards, organised by DG Education and the Joint Research Centre within the auspices of CRELL, in Brussels, October 24–25, 2005.     

The ��Semiotic Self��: From Peirce and Mead to Wiley and Singer

Norbert Wiley (1994) provides a synthesis of Peirce??s and Mead??s views on the self. The Peirce-Mead ideal type model of the self involves the I and the me as well as the I and the you. Hence, at each moment we are a combined ??me-I-you?? in past, present and future. Milton Singer (1989) discovers the semiotic self through his anthropological research, but does not apply the concept as rigorously as one might hope. Peirce??s triadic epistemology and Pragmatism is explored to frame his contribution to the semiotic self. His categories of Firstness, Secondnes and Thirdness are briefly considered. Some anecdotal information about the self in Indic Civilization is discussed. It is argued that the INSOR model can be useful. The key is to move beyond Cartesian notions and to see the semotic self as a ??semiotic object,?? always subject to interpretation by the person engaged in symbolic interaction and exchange.