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Title: A microeconomic study of exporting and innovation activities and their impact on firms : a resource-based perspective
Author: Li, Qian Cher
Awarding Body: University of Glasgow
Current Institution: University of Glasgow
Date of Award: 2009
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Various models explaining micro knowledge-generating behaviour (in particular exporting and innovating) in the economics literature are underpinned by the overlapping assumption that these activities are largely determined by the resources/capabilities possessed by firms. Despite their perceived importance, there is a dearth of evidence on how these heterogeneous resources and firm-specific capabilities can be incorporated into economics models to quantify their roles in determining microeconomic behaviour. Therefore this thesis attempts to bridge this gap in the literature by integrating the resource-based view (RBV) as a new IO theory into the microeconomics literature and empirically utilising micro level data to investigate the significance of such resources/capacities in determining exporting and innovation activities, moderating their inter-relationships as well as conditioning their impacts on the firm’s performance. These heterogeneous resources have been proxied using firm size, productivity, capital intensity, intangible assets, various dimensions to absorptive capacity, the deployment of R&D sourcing strategies and so on. Using establishment-level data covering all UK market-based sectors in 2000, the findings show that all these factors have a large impact upon the propensity and/or intensity of establishments’ exporting and/or R&D activities, with an especially noticeable role in breaking down entry barriers to undertaking such activities. Given the significant impact of exports on knowledge-creating R&D activity, the thesis subsequently investigates and confirms additional learning effect of exporting as embodied in the firm-level exports-productivity relationship using a nationally representative panel dataset covering both manufacturing and services sectors in the UK, for the 1996-2004 period. Lastly, this thesis also attempts to provide an initial inspection of the contribution of innovation (proxied by R&D stock) to productivity using plant-level panel data for Northern Ireland. Based on the estimation of a ‘knowledge production function’ separately for various manufacturing industries, the overall long-run results show that R&D stock does have a positive impact upon productivity.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: H Social Sciences (General) ; HA Statistics ; HB Economic Theory