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.     

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.     

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.     

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.     

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.     

Alliance Capability as a Mediator Between Experience and Alliance Performance: An Empirical Investigation into the Alliance Capability Development Process*

abstract This study centres around the way in which firms can enhance alliance performance through the development of alliance capabilities. Whereas most research has focused on inter-firm antecedents of alliance performance, research on intra-firm antecedents pointing to prior experience and internal mechanisms to foster knowledge transfer has only recently emerged. As little is known about how firms develop alliance capabilities, this study aims to uncover how differences in sources of alliance capabilities explain performance heterogeneity. The data are derived from a detailed survey held among alliance managers and Vice-Presidents of 151 firms. The survey covers over 2600 alliances for the period 1997–2001. This study not only finds that alliance capabilities partially mediate between alliance experience and alliance performance, but also yields novel insights into the micro-level building blocks underlying the process of alliance capability development.     

The Size of Terroir: A Theoretical Note on Economics and Politics of Geographical Indications

Geographical indications (GI) certify the geographical origins of a product and delineate the specific area in which the certified product must be produced. Despite a large literature on the economics of GIs, few papers have explored the question of the optimal size of GI regions. This note presents a flexible conceptual framework to explore the economics and politics of the delimitation of a GI. The general framework describes the efficiency and distributional effects of the size of a GI and shows how this affects interest groups’ incentives to influence government decision‐making.     

A multivariate Poisson mixture model for marketing applications

This paper describes a multivariate Poisson mixture model for clustering supermarket shoppers based on their purchase frequency in a set of product categories. The multivariate nature of the model accounts for cross-selling effects between the purchases made in different product categories. However, for computational reasons, most multivariate approaches limit the covariance structure by including just one common interaction term, or by not including any covariance at all. Although this reduces the number of parameters significantly, it is often too simplistic as typically multiple interactions exist on different levels. This paper proposes a theoretically more complete variance/covariance structure of the multivariate Poisson model, based on domain knowledge or preliminary statistical analysis of significant purchase interaction effects in the data. Consequently, the model does not contain more parameters than necessary, whilst still accounting for the existing covariance in the data. Practically, retail category managers can use the model to devise customized merchandising strategies.