Discerning industrial acitvity in N.E. England : networks and clusters through the lens of the Internet

Abstract

Research on industrial activity has taken many forms over last century as both practitioners and academics alike have sought to gain an understanding of the drivers of the economy in any particular sphere of interest. One facet of this research effort is that associated with the determination of industrial clusters or the particular groupings of economically linked firms and other networked organisations. The tools available to researchers in the field have improved with time but still rely heavily on sources of data gained from databases describing the firm’s activity and other fields of information. Many researchers in this field have noted the shortcomings of such data sources and in particular the indications of a firm’s activity gleaned from its SIC (Standard Industry Classification) code. SICs were originally introduced to enable authorities to understand the make up of basic manufacturing industry and then the supporting service sector but with the passage of time and the introduction of completely new forms of work it has been necessary to expand both the scope and resolution of SICs, a process that invariably lags behind the development of new industry. In the last 15 years the rise of the internet and its vast capacity as an information source has opened up the possibility of gaining new insights into the activity of firms and possibly the ways in which they interact. This research is concerned with an investigation into the usefulness or otherwise, of the internet and the world wide web as serious adjuncts to conventional information sources for the study of industry in general and networks and clustering phenomena in particular. The research looks first at the practicality of using a corpus of regional company URLs from which has been extracted all descriptive text from each firm’s website and which is then stored in a database. This database describing the firm’s activity, markets and connections can then be interrogated to gain an insight into industrial activity across the region. Such an insight is much richer in both detail and depth than that to be obtained from the rather coarse grained SIC approach and its accompanying brief text descriptors. The second part of the research, again following the definitions associated with industrial clusters, is to look at the connections between firms and possible untraded interdependencies. Again this is done using publicly available data sources on the internet by a combination of embedded links, visible connections to external references and web derived in-links, the latter being third parties who reference the firm on their own web site. It has thus been possible to both discern commonalities of firm activity and also to draw some of the visible connecting networks as a result of these investigations which leads to the interesting conclusion that, for the sectors studies in the North East of England at least, we are looking not so much at the clustering of artefacts per se but the clustering of ‘competencies’ in a wide range of sectors that share both common antecedents and current practice in forms of activity requiring strong engineering skills for the design and manufacture of complex structures operating in difficult or even hostile environments. The conclusion overall is that the internet does indeed offer additional insights over more conventional forms of determining industrial clusters but that such insights, at the present time, should be regarded as an adjunct rather than a complete method of analysis in their own right. It is further noted that the tools available for internet search are continually evolving as is the take up and use of corporate websites by all sectors of industry and sizes of the firm. A logical conclusion of this process would be that in the not too distant future the prospects for acquiring information from web based sources will be significantly enhanced.