98 research outputs found

    Bringing 'place' back in: regional clusters, project governance, and new product outcomes

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    We examine new product outcomes in the context of regional clusters. Based on past research on marketing relationships, clusters, and social networks, we propose that the overall configuration of a cluster helps promote particular governance practices among its members. These practices have distinct value-creating properties, and when they are brought to bear on a specific new product development project within a cluster, they promote performance outcomes like product novelty and speed to market. Ultimately, these performance effects are reinforced by the configuration of the cluster itself. In general, we propose that new product outcomes follow from complex interactions between a cluster's macro-level configuration and its micro-level governance processes. More broadly, our framework points to the importance of geographical variables and to the role of “place” in marketing decision-making

    On the brain structure heterogeneity of autism:Parsing out acquisition site effects with significance-weighted principal component analysis

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    Neuroimaging studies have reported structural and physiological differences that could help understand the causes and development of Autism Spectrum Disorder (ASD). Many of them rely on multisite designs, with the recruitment of larger samples increasing statistical power. However, recent large-scale studies have put some findings into question, considering the results to be strongly dependent on the database used, and demonstrating the substantial heterogeneity within this clinically defined category. One major source of variance may be the acquisition of the data in multiple centres. In this work we analysed the differences found in the multisite, multi-modal neuroimaging database from the UK Medical Research Council Autism Imaging Multicentre Study (MRC AIMS) in terms of both diagnosis and acquisition sites. Since the dissimilarities between sites were higher than between diagnostic groups, we developed a technique called Significance Weighted Principal Component Analysis (SWPCA) to reduce the undesired intensity variance due to acquisition site and to increase the statistical power in detecting group differences. After eliminating site-related variance, statistically significant group differences were found, including Broca's area and the temporo-parietal junction. However, discriminative power was not sufficient to classify diagnostic groups, yielding accuracies results close to random. Our work supports recent claims that ASD is a highly heterogeneous condition that is difficult to globally characterize by neuroimaging, and therefore different (and more homogenous) subgroups should be defined to obtain a deeper understanding of ASD. Hum Brain Mapp 38:1208–1223, 2017.</p

    Forecasting Methods For Management - 5/E

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    The Supply Chain and New Products

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