Unveiling the temporally contingent role of codification in alliance success

While prior research highlights the importance of codifying alliance experience to achieve alliance success, it is unclear whether codification is equally useful in the different phases of an alliance. Based on a sample of 192 technology firms that report on over 3,400 strategic alliances, we find that in the partner selection and termination phases, reliance on codified knowledge is useful. However, in the partner management phase, reliance on codified knowledge is less beneficial and can be even negatively related to performance. Our findings have implications for the tension between flexibility and efficiency and the relationship between structure and performance. Copyright © 2013 John Wiley & Sons, Ltd.     

Collaborative cost-cutting: productive efficiency as an interdependency between public organizations

Collaboration between public sector organizations is typically understood as a response to complexity. Agencies collaborate in order to address complex, cross-cutting policy needs that cannot be met individually. However, when organizational size is a constraining factor in public service efficiency, collaboration can also reduce costs by capturing scale economies unavailable to organizations of sub-optimal size. Using organization theory, the article conceptualizes these two different triggers for public sector collaboration, and builds a framework for tracing their wider impact upon the formation, operation, and outcome of inter-agency partnerships. The framework is illustrated, and its implications for future research are explored.     

The Costs of Coexistence Measures for Genetically Modified Maize in Germany

We estimate the perceived costs of legal requirements (‘coexistence measures’) for growing genetically modified (GM) Bt maize in Germany using a choice experiment. The costs of the evaluated ex‐ante and ex‐post coexistence measures range from zero to more than €300 per measure and most are greater than the extra revenue the farmers in our survey expect from growing Bt maize or than estimates in the literature. The cost estimates for temporal separation, the highest in our evaluation, imply that the exclusion of this measure in Germany is justified. The costliest measures of the ones that are currently applied in Germany are joint and strict liability for all damages. Our results further show that neighbours do not cause a problem and opportunities for reducing costs through agreements with them exist. Finally, we find that farmers’ attitudes towards GM crops affect the probability of adoption of Bt maize. Our results imply that strict liability will deter the cultivation of Bt maize in Germany unless liability issues can be addressed through other means, for example, through neighbours agreements.     

Evaluating,Comparing, Monitoring,and Improving Representativeness of Survey Response Through R‐Indicators and Partial R‐Indicators

Non‐response is a common source of error in many surveys. Because surveys often are costly instruments, quality‐cost trade‐offs play a continuing role in the design and analysis of surveys. The advances of telephone, computers, and Internet all had and still have considerable impact on the design of surveys. Recently, a strong focus on methods for survey data collection monitoring and tailoring has emerged as a new paradigm to efficiently reduce non‐response error. Paradata and adaptive survey designs are key words in these new developments. Prerequisites to evaluating, comparing, monitoring, and improving quality of survey response are a conceptual framework for representative survey response, indicators to measure deviations thereof, and indicators to identify subpopulations that need increased effort. In this paper, we present an overview of representativeness indicators or R‐indicators that are fit for these purposes. We give several examples and provide guidelines for their use in practice.     

Technological innovation and complexity theory

Complexity theory has become influential in recent models in social science. In the context of innovations and new technologies, most applications have focused on technology adoption and technology diffusion, whereas the topic of the innovation process has received less attention. This paper discusses three families of complexity models of technological innovation: fitness landscape models, network models and percolation models. The models are capable of analysing complex interaction structures (between components of technologies, between agents engaged in collective invention) while avoiding ‘over-parameterisation’. The paper ends with discussing the methodological challenges and critiques regarding the application of complexity theory that remain.     

Argumentation-Based Qualitative Preference Modelling with Incomplete and Uncertain Information

This paper presents an argumentation-based framework for the modelling of, and automated reasoning about multi-attribute preferences of a qualitative nature. The framework presents preferences according to the lexicographic ordering that is well-understood by humans. Preferences are derived in part from knowledge. Knowledge, however, may be incomplete or uncertain. The main contribution of the paper is that it shows how to reason about preferences when only incomplete or uncertain information is available. We propose a strategy that allows reasoning with incomplete information and discuss a number of strategies to handle uncertain information. It is shown how to extend the basic framework for modelling preferences to incorporate these strategies.     

Capitalization of Flood Insurance and Risk Perceptions in Housing Prices: An Empirical Agent‐Based Model Approach

Federally regulated or insured lenders in the United States are mandated to require flood insurance on properties that are located in areas at high risk of flooding. Despite the existence of this mandatory flood insurance requirement, take‐up rates for flood insurance have been low, and the federal government's exposure to uninsured property losses from flooding remains substantial. Meanwhile, the value of capital at risk varies significantly with flood events and changing risk perceptions, which necessitates mechanisms that stabilize these dynamics. In this article we discuss how a scenario of complete insurance uptake, under various risk attitudes, affects the value of properties in the 100‐year and 500‐year flood zones. Our results indicate that an increase in flood insurance uptake may provide such a mechanism by lowering the value of capital at risk in the flood zone consistently, independent of homeowners' risk attitudes. We apply an empirical adaptive agent‐based model to examine the capitalization of insurance costs, risk premiums, and their interaction in housing prices. Our approach combines widely‐used empirical hedonic analysis with the computational economic framework. We highlight the usefulness of our method in capturing the marginal implicit price of homeowners' preferences that may change over time and separately assess the effect of various factors and policies on property values, illustrating the agent‐based modeling as a valuable complement to traditional hedonic analysis.     

Test validation from a conceptual and legal perspective: Issues and trends

A little-explored issue in the psychological and legal literature involves test validation. This article discusses issues of test validation from both psychological and legal perspectives. Areas of inconsistency are noted and probable future directions are high-lighted.