Chain-store pricing and the structure of retail markets

This paper examines competition between chain-stores and independent retailers in the UK retail opticians' market. We demonstrate that the pricing policy adopted by chain-stores can determine the impact their entry has on independent retailers. Crucially, in this market the chain-store retailers set an identical national price across all local markets. Our results suggest that this pricing strategy lessens the detrimental effect competition from chain-stores has on independent retailers

Cluster Performance reconsidered: Structure, Linkages and Paths in the German Biotechnology Industry, 1996-2003

This paper addresses the evolution of biotechnology clusters in Germany between 1996 and 2003, paying particular attention to their respective composition in terms of venture capital, basic science institutions and biotechnology firms. Drawing upon the significance of co-location of "money and ideas", the literature stressing the importance of a cluster's openness and external linkages, and the path dependency debate, the paper aims to analyse how certain cluster characteristics correspond with its overall performance. After identifying different cluster types, we investigate their internal and external interconnectivity in comparative manner and draw on changes in cluster composition. Our results indicate that the structure, i.e. to which group the cluster belongs, and the openness towards external knowledge flows deliver merely unsystematic indications with regard to a cluster's overall success. Its ability to change composition towards a more balanced ratio of science and capital over time, on the other hand, turns out as a key explanatory factor. Hence, the dynamic perspective proves effective illuminating cluster growth and performance, where our explorative findings provide a promising avenue for further evolutionary research

Industry dynamics, technological regimes and the role of demand

In this paper, we propose an industrial dynamics model to analyze the interactions between the price-performance sensitivity of demand, the sources of innovation in a sector, and certain features of the corresponding pattern of industrial transformation. More precisely, we study market concentration in different technological regimes and demand conditions. The computational analysis of our model shows that market demand plays a key role in industrial dynamics. Thus, although for intermediate values of the price-performance sensitivity, our results show the well-known relationships in the literature between technological regimes and industry transformation, we find surprising outcomes when demand is strongly biased either towards price or performance. Hence, for different technological regimes, a high performance sensitivity of demand tends to concentrate the market. On the other hand, under conditions of high price sensitivity, the industry generally tends to atomize. That is to say, for extreme values of the price-performance sensitivity of demand, we find concentrated or atomized market structures no matter the technological regime we are in. These results highlight the importance of considering the role of demand in the analysis of industrial dynamics

An integrative framework of preemption strategies

Pre-print; author's draftThis paper performs a review of the various pre-emption strategies prescribed in the economics literature. These are cost superiority, consumers' switching cost, channel exclusivity, environmental barriers of entry and credible commitment to react aggressively. Through our analysis, we develop an integrative framework of the pre-emption strategies that will result in long-term payoffs to the firm. The framework proposes that there are two key dimensions—strategic advantage and strategic focus—and identify five generic types of pre-emption strategies for market incumbents. These are the switching cost, blockade, credible commitment, tie-up, and cost leadership strategies. The pre-emption strategies and the framework presented can assist managerial decision-making for the successful pre-emption of potential competition to complement their existing efforts

Topological Data Analysis for Discovery in Preclinical Spinal Cord Injury and Traumatic Brain Injury

Data-driven discovery in complex neurological disorders has potential to extract meaningful syndromic knowledge from large, heterogeneous data sets to enhance potential for precision medicine. Here we describe the application of topological data analysis (TDA) for data-driven discovery in preclinical traumatic brain injury (TBI) and spinal cord injury (SCI) data sets mined from the Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI) repository. Through direct visualization of inter-related histopathological, functional and health outcomes, TDA detected novel patterns across the syndromic network, uncovering interactions between SCI and co-occurring TBI, as well as detrimental drug effects in unpublished multicentre preclinical drug trial data in SCI. TDA also revealed that perioperative hypertension predicted long-term recovery better than any tested drug after thoracic SCI in rats. TDA-based data-driven discovery has great potential application for decision-support for basic research and clinical problems such as outcome assessment, neurocritical care, treatment planning and rapid, precision-diagnosis