This paper assesses the development of emerging computing applications that fall under the family of digital applications and technologies. These applications and technologies — Internet 2 based technologies for short — enable new ways of connectivity for networking, interfacing and producing content. They have the capacity and the force to disrupt existing social and economic relations and thus have major impacts on society. Hence, the term ‘e-ruptions’: emerging e-trends with potential disruptive power. This paper investigates the socio-economic impact of emerging e-ruptions, in an attempt to try and contextualise their implications and relevance for policy formulation.
Evidence on trend development is presented from both formal and less formal sources such as weblogs, journals, independent commercial sources and industry-produced data. Although this evidence is largely anecdotal, at least for Europe [1], it is consistent and growing, and is reflected in social and economic impacts. Some of the social computing applications are only at the promotion stage (e.g. Ajax, social networks and wikis [2]), but others (such as VoIP) have already been widely adopted.
The social relevance of these trends appears clear. They affect the way people find information, learn, share, communicate and consume and the way businesses do business. Throughout, an emphasis can be detected on interpersonal communication and on the role of the user as a supplier or co-producer of the service (content, taste, contacts, reputation, relevance, physical goods, but also software, connectivity and storage). In economic terms, these trends are already having a visible impact: new players and markets provide significant threats and opportunities for the ICT and media industries, and the new applications are increasingly used for professional purposes.
The rise of the user — as a person, group or firm — as a producer is recognisable as the common thread of most of the emerging trends. Users produce utility-bearing information that minimises the transaction costs on various markets for goods and services in a potentially Pareto-optimal setting. In interacting, they use platforms that enable social networking and facilitate the further development and spread of the new e-ruptive trends. This process also changes the structural composition of (primarily) ICT and media industries, influencing directly their competitiveness. The nature of the competition for platforms that support current e-ruptive trends has been identified as one of the key factors in the continuing development of these trends.
Although spectacular success stories of trend-setting companies promoting some of these applications can be observed, one has to be more cautious (bearing the Internet bubble in mind) when assessing their sustainability. In other words, a second bubble is not impossible. However, the success of innovation is measured by how established it is on the market and not by of any individual company. During the Internet bubble, the ‘holy grail’ of company success was "first-mover advantage"; now the focus has shifted back to more traditional business concepts, such as income, providing a more stable economic base. Internet 2 computing companies tend to have a smaller cost base, since they rely on users for a large part of their output, viable business models, and real market and they are much more closely integrated with the old economy, providing increasingly predictable income streams. This was not so much the case when the Internet bubble burst a few years ago.
The paper starts by analyzing the available evidence on the usage growth of these trends (point 2). It then spells out the drivers of this growth (point 3), the different types of social and economic impacts (points 4 and 5 respectively). Building on this analysis, it puts forward interpretations on the sustainability of these trends (point 6), and on the main implications for innovation and competitiveness (point 7). The conclusions point to further research needs, and European policy options (point 8). In the annex (point 9), the main empirical data and a rough impact assessment are given.
Detecting Discrimination
