Collaborative practices in new product development projects involving suppliers

Abstract

Collaboration with suppliers in New Product Development (NPD) is essential for business competitiveness. However, the management of such collaborative project needs to focus on interactions between team members from different companies since they performed inter-organizational activities. While the impact of collaboration with suppliers on NPD project performance has been widely studied, the investigation of practices to support daily collaborative activities between both teams has received limited attention. This paper aims at developing a framework of operational practices for successful inter-organizational collaboration in NPD. The practices enacted by both project teams in six case studies were examined according to the stages of the collaboration and a knowing perspective. The results revealed some peculiarities linked to the inter-organizational context. Practices interact with each other across stages with a specific dynamic. More particularly, early in the project, practices to justify the collaboration with the suppliers are determinant for practices related to the creation of social interactions between project members and project commitment. The results also show that boundary objects are useful formal socialization mechanisms for supporting the undertaking of collaborative work.     

Propensity score applied to survival data analysis through proportional hazards models: a Monte Carlo study

Propensity score methods are increasingly used in medical literature to estimate treatment effect using data from observational studies. Despite many papers on propensity score analysis, few have focused on the analysis of survival data. Even within the framework of the popular proportional hazard model, the choice among marginal, stratified or adjusted models remains unclear. A Monte Carlo simulation study was used to compare the performance of several survival models to estimate both marginal and conditional treatment effects. The impact of accounting or not for pairing when analysing propensity‐score‐matched survival data was assessed. In addition, the influence of unmeasured confounders was investigated. After matching on the propensity score, both marginal and conditional treatment effects could be reliably estimated. Ignoring the paired structure of the data led to an increased test size due to an overestimated variance of the treatment effect. Among the various survival models considered, stratified models systematically showed poorer performance. Omitting a covariate in the propensity score model led to a biased estimation of treatment effect, but replacement of the unmeasured confounder by a correlated one allowed a marked decrease in this bias. Our study showed that propensity scores applied to survival data can lead to unbiased estimation of both marginal and conditional treatment effect, when marginal and adjusted Cox models are used. In all cases, it is necessary to account for pairing when analysing propensity‐score‐matched data, using a robust estimator of the variance. Copyright © 2012 John Wiley & Sons, Ltd.     

Improving prediction performance of stellar parameters using functional models

This paper investigates the problem of prediction of stellar parameters, based on the star's electromagnetic spectrum. The knowledge of these parameters permits to infer on the evolutionary state of the star. From a statistical point of view, the spectra of different stars can be represented as functional data. Therefore, a two-step procedure decomposing the spectra in a functional basis combined with a regression method of prediction is proposed. We also use a bootstrap methodology to build prediction intervals for the stellar parameters. A practical application is also provided to illustrate the numerical performance of our approach.     

Konsensuale Effizenzbewertung und -verbesserung mittels DEA

This contribution is a new DEA approach in as much as it permits the decision making units (DMUs) to improve their respective efficiencies from the view of a peer rather than form their own self-appraisal attitudes. These authors study the output oriented model under constant scale efficiencies and first develop how a DMU can improve its performance by radial output increase or even by free output variation??in the light of the weight system of an arbitrary peer. The results are an improved cross-efficiency matrix and a maximum cross-efficiency matrix. Either of these matrices may serve as an appropriate instrument for a consensual choice of a peer??consensual among all DMUs. Input oriented models as well as simultaneous input/output considerations amend the so far developed results. A suitable example demonstrates all aspects of the new approach.     

On the role of data,statistics and decisions in a pandemic

AStA Advances in Statistical Analysis - A pandemic poses particular challenges to decision-making because of the need to continuously adapt decisions to rapidly changing evidence and available...     

How Dynamic Capabilities Affect the Effectiveness and Efficiency of Operating Routines under High and Low Levels of Environmental Dynamism

In analysing data on the purchasing routines of 200 small and medium‐sized enterprises (SMEs), this study underscores the overall importance of dynamic capabilities as a way to understand differences in operating‐routine performance. The results suggest that dynamic capabilities have different performance effects in high‐dynamic and low‐dynamic environments. Dynamic capabilities enhance the effectiveness of operating routines under both high and low levels of environmental dynamism. Yet, when analysing the efficiency of operating routines, taking into account the costs of increased effectiveness, dynamic capabilities appear to pay off only under high levels of environmental dynamism.     

The Syndrome of Group-Focused Enmity: The Interrelation of Prejudices Tested with Multiple Cross-Sectional and Panel Data

Different types of prejudice are usually treated as separate constructs. We propose that they constitute a syndrome of group-focused enmity (GFE), that is, they are related to each other and share a common core that is strongly predicted by a generalized ideology of inequality. Furthermore, GFE components are supposed to have similar predictors and outcomes. An empirical test is presented using structural equation modeling on the syndrome, its causes, consequences, and structural stability over time. The study relies on three German cross-sectional probability samples (each N = 2,700) and a related panel study (2002, 2003, and 2004). The idea of a GFE syndrome is strongly supported. Future research is discussed, as well as alternative approaches of a common prejudice factor .     

Explaining High‐Profile Coverage of State Supreme Court Decisions*

Objective. In this article, we investigate the decision of media in the U.S. states to give high‐profile coverage to state supreme court decisions. While research on the U.S. Supreme Court has forged an association between media coverage and the political salience of court decisions, scholars have been unable to examine such coverage in the increasingly important state courts of last resort. Methods. Utilizing new data of high‐profile coverage over time in these courts, we examine the extent to which case characteristics, judicial behavior, and institutional variation influence media attention. Our empirical model covers 28,045 state supreme court cases over all 50 states, between the years 1995–1998. Results. Our findings indicate that the likelihood of high‐profile coverage increases when certain case characteristics, particularly declarations of unconstitutionality, are present, in addition to dissent within a court. Despite the importance of institutional differences among state supreme courts, front‐page coverage is not affected by this variation. Conclusions. In our conclusions, we evaluate those scenarios in which high‐profile media coverage is more likely for state supreme court cases, and the possible implications this may have for judicial politics.     

Medical laboratory diagnostics and statistics

We review the statistical contributions to the development and production of laboratory diagnostic assays. The tasks and facets of the role of a statistician in diagnostic industry are discussed.