Economic impact of e20 F. Biagi Tech4i2
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Economic impact of e20 F. Biagi Tech4i2

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Presentation given at the "Enterprise 2.0 in Europe" workshop where the results of the interim report of the “Enterprise 2.0 study were presented and discussed with experts. Economic impact of e20 F ...

Presentation given at the "Enterprise 2.0 in Europe" workshop where the results of the interim report of the “Enterprise 2.0 study were presented and discussed with experts. Economic impact of e20 F Biagi Tech4i2
Brussels, 14th of September 2010

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Economic impact of e20 F. Biagi Tech4i2 Economic impact of e20 F. Biagi Tech4i2 Presentation Transcript

  • Economic impact of E2.0 September 14th 2010 Federico Biagi: Tech4i2, SDA Bocconi and University of Padova Enterprise 2.0 study
  • What can be done
    • Providing accurate numbers on the economic impact of E2.0 is, at this stage, an impossible task. This is so because there is no statistical evidence on direct and indirect effects of E2.0.
    • Only scant case-based evidence exist, it is very difficult to generalize starting from these cases because they are not representative of the potentially interested population and because from such cases is has proven to be almost impossible to extract accurate evidence on costs and benefits of E2.0 adoption
  • What can be done
    • However, the economic literature can provide some very useful insights on the most-likely future development and on the potential impact of E2.0.
    • In this part of the presentation we will use economic theory and empirical evidence relative to these aspects.
  • Firm innovation capacity C Input Causal links (cause at tails, effect ad heads of arrows) C Counteracting loop Main output Direct outcome Indirect effects Macro impacts Unintended effects Innovation More efficient knowledge sharing and creation reduced revenues for ICT industry Jobs loss and other exclusionary effects Productivity Growth E 2.0 tools running Intangibles Software Firm productivity capital/labour mix and selective increase in Human capital C (-) Cost of adoption / set-up Additional revenues for ICT industry
  • Direct effects
    • From the empirical analysis of the relationship between ICT and growth, conducted with aggregate data, we know that the direct impact of ICT appears to be quite small (in terms of per-capita GDP growth rate a gain of 0.3-0.8% points for the period 1990-2001) . However, aggregate data do not capture the full range of indirect effects that ICT adoption can have. This is particularly true for E2.0.
  • Direct effects
    • It is very difficult to measure the impact of ICT on productivity and growth, especially in the service sector, because data do not generally represent the output aspects that ICT are most likely to affect such as timeliness in production, quality of products and services, impact of innovative effort etc.
  • Indirect effects
    • Macro or sectorial studies are not able to capture the overall effects of ICT diffusion and adoption, since most of its effects are indirect (i.e. they do not come from either capital deepening or from increased productivity in the ICT producing sector). This is particularly true for E2.0
  • Indirect effects
    • A literature has emerged studying the role of ICT and complementarity assets in the determination of firms’ productivity (possibility of time lags).
    • Such literature has stressed the importance of organizational change and work practices: ICT is an enabler of complementary innovations and particularly organizational investments such as business processes and work practices (Examples and relevance for E2.0).
  • Indirect effects
    • Brynjolfsson and coauthors believe that the effects of organizational change are of an order of magnitude larger than those captured by growth accounting methodology (2-3 percentage points in productivity growth).
  • Indirect effects
    • Black and Lynch estimate that changes in organizational capital may have accounted for approximately 30 percent of output growth in the manufacturing sector. This is a very large number.
    • Gant, Ichiniowski and Shaw find robust evidence of positive impact of connective capital –defined as workers’ access to the knowledge and skills of other workers-on productivity (relevance for E2.0).
  • Indirect effects
    • Employees’ connectivity has a stronger impact on productivity than traditional human capital variables, such as education and experience. This means that individual human capital is not sufficient: from individual knowledge to organizational knowledge (implications for E2.0).
  • Indirect effects
    • Causes and consequences:
    • 1) decentralized and more flexible organizational structures allow faster and cheaper information transmission (reduction of coordination costs);
    • 2) the benefits from decentralization tend to rise with the firm’s skill intensity ( distributional and band-wagon effects ).
  • Open innovation
    • Open innovation is a paradigm that assumes that firms can and should use external ideas as well as internal ideas, and internal and external paths to markets.
    • Open innovation combines internal and external ideas into architectures and systems whose requirements are defined by a business model
    • Open innovation is the purposive inflow and outflows of knowledge to accelerate internal innovation and expand the markets for external use of innovation.
    • Open innovation is both a set of practices for profiting from innovation, and also a cognitive model for creating, interpreting and researching these practices.
  • Open innovation
    • 1) large companies are four times more likely to collaborate than small and medium size enterprises;
    • 2) the rate of collaboration is fairly similar across countries among SMEs, but it changes very much for large companies (data do not reveal the intensity of collaboration;
    • 3) ICT, pharmaceuticals and also chemical show high incidence of collaboration, which is recorded also in wholesale and retail, transport and communication
    • However: no evidence on the quantitative impact of open innovation (only anecdote and case-base evidence)
  • Direct effect of E2.0
    • Impact on ICT industry is likely to be small : 0,1% of software industry but growing 10 times faster($108 million in 2009 compared to $79.9 billion for the EU packaged software market )
    • Most producers from North America (Australia)
    • EU producers small but growing fast (e.g. Huddle) also incl. large vendors (Dassault, SAP)
    • E2.0 to become a feature of enterprise software?
    • Adoption rate in SME is likely to be a key issue
  • Indirect effects of E2.0
    • E2.0 is an enabler of
    • Open innovation
    • Innovative working practices
    • Impact to be determined by those two aspects rather than by E2.0 itself
  • Indirect effects of E2.0
    • Organizational structure and culture are key variables for E2.0 fruitful adoption.
    • Little capital/labour substitution effects .
    • No evidence of negative impact on employee productivity.
    • Increased relative productivity of knowledge workers, increased salary gap > knowledge sharing makes knowledge acquisition more valuable (critical mass?).
    • Very difficult to distinguish between first and second order effect (due to the very nature of the tool).
  • Indirect effects of E2.0
    • Large organizations have larger expected benefits by E2.0 adoption (while set-up costs do not rise proportionally to a firm’s size).
    • E2.0 to impact on sectors with higher technological change and higher competitive pressure (because in these sectors the gains from information diffusion are higher).
    • Accordingly, Manufacturing, Finance and Professional Services are main sectors. Telecoms and Media come after (analogous considerations hold for Distribution).
    • Overall the biggest impact is expected in large companies in Manufacturing and FP services.
  • Indirect effects of E2.0
    • Key questions
      • 1) how to protect innovations obtained through informal collaboration and
      • 2) how to provide workers the right incentives to produce the optimal effort when they work in collaborative unstructured networks.