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Web Manifestations of Knowledge-Based Innovation Systems in the U.K

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Web Manifestations of Knowledge-Based Innovation Systems in the U.K Web Manifestations of Knowledge-based Innovation Systems in the U.K. David Patrick Stuart B.A.(hons) A thesis submitted in partial fulfilment of the requirements of the University of Wolverhampton for the degree of Doctor of Philosophy January 2008 This work or any part thereof has not previously been presented in any form to the University or to any other body whether for the purposes of assessment, publication or for any other purpose (unless otherwise indicated). Save for any express acknowledgments, references and/or bibliographies cited in the work, I confirm that the intellectual content of the work is the result of my own efforts and of no other person. The right of David Stuart to be identified as author of this work is asserted in accordance with ss.77 and 78 of the Copyright, Designs and Patents Act 1988. At this date copyright is owned by the author. Signature……………………………………….. Date…………………………………………….. Publication List Journal Papers: Stuart, D., & Thelwall, M. (2006). Investigating triple helix relationships using URL citations: a case study of the UK West Midlands automobile industry. Research Evaluation, 15(2), 97-106. Stuart, D., Thelwall, M., & Harries, G. (2007). UK academic web links and collaboration – an exploratory study. Journal of Information Science, 33(2), 231-246. Thelwall, M., & Stuart, D. (2006). Web crawling ethics revisited: Cost, privacy, and denial of service. Journal of the American Society for Information Science and Technology, 57(13), 1771-1779. Conference Papers: Stuart, D., & Thelwall, M. (2005). What can university-to-government web links reveal about university-government collaborations? In P. Ingwersen, & B. Larsen (eds.), Proceedings of the 10th International Conference of the International Society for Scientometrics and Informetrics: Vol. 1. (pp.188-192). Stockholm: Karolinska University Press. Stuart, D., & Thelwall, M. (2007). University-industry-government relationships manifested through MSN reciprocal links. In D. Torres-Salinas, & H. F. Moed (eds.), Proceedings of the 11th International Conference of the International Society for Scientometrics and Informetrics: Vol. 2. (pp.731-735). Madrid: CINDOC. i Abstract Innovation is widely recognised as essential to the modern economy. The term knowledge- based innovation system has been used to refer to innovation systems which recognise the importance of an economy’s knowledge base and the efficient interactions between important actors from the different sectors of society. Such interactions are thought to enable greater innovation by the system as a whole. Whilst it may not be possible to fully understand all the complex relationships involved within knowledge-based innovation systems, within the field of informetrics bibliometric methodologies have emerged that allows us to analyse some of the relationships that contribute to the innovation process. However, due to the limitations in traditional bibliometric sources it is important to investigate new potential sources of information. The web is one such source. This thesis documents an investigation into the potential of the web to provide information about knowledge-based innovation systems in the United Kingdom. Within this thesis the link analysis methodologies that have previously been successfully applied to investigations of the academic community (Thelwall, 2004a) are applied to organisations from different sections of society to determine whether link analysis of the web can provide a new source of information about knowledge-based innovation systems in the UK. This study makes the case that data may be collected ethically to provide information about the interconnections between web sites of various different sizes and from within different sectors of society, that there are significant differences in the linking practices of web sites within different sectors, and that reciprocal links provide a better indication of collaboration than uni-directional web links. Most importantly the study shows that the web provides new information about the relationships between organisations, rather than just a repetition of the same information from an alternative source. Whilst the study has shown that there is a lot of potential for the web as a source of information on knowledge-based innovation systems, the same richness that makes it such a potentially useful source makes applications of large scale studies very labour intensive. ii Table of Contents Publication List ............................................................................................................................ i Journal Papers: ......................................................................................................................... i Conference Papers: .................................................................................................................. i Abstract .......................................................................................................................................ii Table of Contents .......................................................................................................................iii 1 General Introduction........................................................................................................... 1 1.1 Introduction................................................................................................................. 1 1.2 Knowledge-based innovation systems ........................................................................ 2 1.3 Traditional bibliometric indicators of knowledge-based innovation systems ............ 4 1.4 The web as a source of information on knowledge-based innovation systems .......... 6 1.5 Link analysis............................................................................................................... 7 1.6 A link analysis of the United Kingdom ...................................................................... 9 1.7 Aims and objectives .................................................................................................... 9 1.7.1 Developing an appropriate data collection methodology.................................. 10 1.7.2 Determine what can be inferred from web links............................................... 10 1.7.3 Explore the extent that web link derived information is new ........................... 10 1.8 Research contributions.............................................................................................. 10 1.9 Dissertation structure................................................................................................ 10 1.9.1 The literature review ......................................................................................... 11 1.9.2 The preliminary studies..................................................................................... 11 1.9.3 The main research: methodology, results and discussion ................................. 12 1.9.4 Conclusions of the investigation into web manifestations of knowledge-based innovation systems............................................................................................................ 12 2 Review of the literature..................................................................................................... 13 2.1 Introduction............................................................................................................... 13 2.2 Key link terminology ................................................................................................ 13 2.3 Macro studies of knowledge-based innovation systems ........................................... 15 2.4 Other web manifestations of organisational interlinkages........................................ 18 2.5 Link analysis............................................................................................................. 19 2.5.1 Identifying web pages relevant to the research question .................................. 19 2.5.2 Data collection.................................................................................................. 21 2.5.2.1 Manual data collection .................................................................................. 21 2.5.2.2 Personal web crawlers for data collection..................................................... 22 2.5.2.3 Search engines............................................................................................... 24 2.5.3 Data cleaning..................................................................................................... 29 2.5.4 Validation of link analysis ................................................................................ 30 2.5.4.1 Partially validating link count results through correlation tests.................... 31 2.5.4.2 Partially validating the interpretation of the results through a link classification exercise.................................................................................................... 36 2.6 Summary ................................................................................................................... 39 3 Preliminary investigations................................................................................................. 40 3.1 Introduction............................................................................................................... 40 3.2 Web crawling ethics revisited: Cost, privacy and denial of service ......................... 40 3.2.1 Introduction......................................................................................................
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