"Plateau"-related summary statistics are uninformative for comparing working memory models.

Performance on visual working memory tasks decreases as more items need to be remembered. Over the past decade, a debate has unfolded between proponents of slot models and slotless models of this phenomenon (Ma, Husain, Bays (Nature Neuroscience 17, 347-356, 2014). Zhang and Luck (Nature 453, (7192), 233-235, 2008) and Anderson, Vogel, and Awh (Attention, Perception, Psychophys 74, (5), 891-910, 2011) noticed that as more items need to be remembered, "memory noise" seems to first increase and then reach a "stable plateau." They argued that three summary statistics characterizing this plateau are consistent with slot models, but not with slotless models. Here, we assess the validity of their methods. We generated synthetic data both from a leading slot model and from a recent slotless model and quantified model evidence using log Bayes factors. We found that the summary statistics provided at most 0.15 % of the expected model evidence in the raw data. In a model recovery analysis, a total of more than a million trials were required to achieve 99 % correct recovery when models were compared on the basis of summary statistics, whereas fewer than 1,000 trials were sufficient when raw data were used. Therefore, at realistic numbers of trials, plateau-related summary statistics are highly unreliable for model comparison. Applying the same analyses to subject data from Anderson et al. (Attention, Perception, Psychophys 74, (5), 891-910, 2011), we found that the evidence in the summary statistics was at most 0.12 % of the evidence in the raw data and far too weak to warrant any conclusions. The evidence in the raw data, in fact, strongly favored the slotless model. These findings call into question claims about working memory that are based on summary statistics.

Building global products and competing in innovation: The role of chinese university spin-outs and required innovation capabilities

Usually, firms that produce innovative global products are discussed within the context of developed countries. New ventures in developing countries are typically viewed as low-cost product providers that generate technologically similar products to those produced by developed economies. However, this paper argues that some Chinese university spin-outs (USOs), although rare, have adopted a novel 'catch-up' strategy to build global products on the basis of indigenous platform technologies. This paper attempts to develop a conceptual framework to address the question: how do these specific Chinese USOs develop their innovation capabilities to build global products? In order to explore the idiosyncrasies of the specific USOs, this paper uses the multiple case studies method. The primary data sources are accessed through semi-structured interviews. In addition, archival data and other materials are used as secondary sources. The study analyses the configuration of capabilities that are needed for idiosyncratic growth, and maps them to the globalisation processes. This paper provides a strategic 'roadmap' as an explanatory guide to entrepreneurs, policy makers and investors to better understand the phenomena. © 2014 Inderscience Enterprises Ltd.