STRATEGIC KNOWLEDGE ARBITRAGE AND SERENDIPITY (SKARSE™) in Action

By Elias G. Carayannis
Professor of Science, Technology, Innovation and Entrepreneurship in  the Department of Information Systems and Technology Management, Director of Research, Science, Technology, Innovation and Entrepreneurship in the European Union Research Center (EURC) and co-founder and Co-Director of the Global and Entrepreneurial Finance Research Institute (GEFRI), School of Business, George Washington University

In today’s globalizing and hypercompetitive marketplace, knowledge and learning are the only capabilities that can provide sustained competitive advantage. ‘Knowledge’ is the content of learning, and a firm gains competitive superiority either by knowing something that its competitors do not know or by having a certain type of knowledge that cannot easily be replicated. ‘Learning’ is the process of gaining new knowledge, so that the firm is constantly accumulating and assimilating knowledge and this becomes the basis for creating and improving organizational routines. Learning is also the basis of what strategists are calling firms’ ‘dynamic capabilities,’ which enable them to build new competences in an evolutionary cycle to maintain an edge in an ever-changing industrial environment.

This article briefly explores the nature and dynamics of strategic knowledge arbitrage and serendipity (SKARSE™). The author reviews and assesses how, why and when SKARSE™ serve as high value adding decision and action triggers and implications for private and public policies and practices.

Strategic knowledge serendipity refers to the unintended benefits of enabling knowledge to ‘spill over’ between employees, groups and functional domains (‘happy accidents’ in learning). More specifically, it describes the capacity to identify, recognize, access and integrate knowledge assets more effectively and efficiently to derive, develop and capture non-appropriable, defensible, sustainable and scalable pecuniary benefits (see related publications by author).

Strategic knowledge arbitrage refers to the ability to distribute and use specific knowledge for applications other than the intended topic area. More specifically, it refers to the capacity to create, identify, reallocate and recombine knowledge assets more effectively and efficiently to derive, develop and capture non-appropriable, defensible, sustainable and scalable pecuniary benefits (see related publications by author).

 

Empirical Results and Work-in-Progress:

In our research, we have attempted to assess conceptually and integrate empirically three fundamental aspects of the process of creative destruction:

  • strategic knowledge serendipity and arbitrage as means of unlocking and capturing the value added by creative destruction;
  • real options as a methodology to assess and maximize the value added by creative destruction; and
  • multi-layered, multi-modal and multi-nodal technological learning as a mechanism that internalizes and leverages the value added by creative destruction and, especially, by lessons from the previous stages of a technological lifecycle and from evolving, successive or overlapping technological lifecycles.

To empirically validate SKARSE™, we have started formulating and simulating the lifecycle of knowledge-driven, including technology-driven, ventures that can be viewed as the exercise of real options under regimes of risk and uncertainty that is modeled in the form of “happy accidents” namely, strategic knowledge serendipity, arbitrage and acquisition events that punctuate the process of the venture’s lifecycle (see Figures 1 and 2) (see related publications by author).

Figure 1

Figure1

Adapted from Carayannis et al, Knowledge Serendipity, ieee tem, 2011

In practical terms, we find that the timing, selection and sequencing of key decisions pertaining to new venture formation and evolution are contingent in a non-linear manner to the breadth and depth as well as the quality and density of the network structure of the business and technology ecosystem within which a venture is situated.

We find that up to a certain point of cultivating and nurturing the new firm’s “socio-economic” network, the costs outweigh the benefits but with an abrupt about-face once a critical mass in the scale, scope and quality of this “socio-economic” network or business and technology ecosystem is attained. At which point, the benefits start outweighing and exponentially exceeding the costs.

The implications are clear for current and aspiring technology entrepreneurs and regional economic development managers and policy-makers alike: figure out what are the nature and dynamics of your regional business and technology ecosystem (including global and local connections and extensions to it) and aim to enter the market (as an entrepreneur) when the ecosystem appears to be close to its critical mass of maximum likelihood knowledge serendipity and arbitrage (“happy accidents”) events. In addition, aim to help the ecosystem reach its maximum “happy accident” likelihood state (as a regional economic development manager and policy maker) as sustainably and fast as possible. In this context, strategic public-private partnerships and networks as well as risk capital may serve as key pillars of sustainable and accelerated economic development.

Figure 2

Figure2

Adapted from Carayannis et al, Knowledge Serendipity, ieee tem, 2011

Our research suggests the following lessons:

1. Public Policy

Governments have not surrendered their power to capitalism, even if the world’s biggest companies are more powerful than many of the world’s governments. Democracy is not a sham. People rule, not profits. Admittedly though, companies would run the world for profit if they could. What stops them is not governments, but markets.

2. Public Practice

Technology-enabled free trade is an economic equalizer. Governments have power, but they do not always exercise it wisely. They are unreliable servants of the public interest. Distributed tactical planning works best under the control of the entrepreneurs, organizations, and actors operating in a free-market system. Government and NGOs function best when serving as facilitators and resources, not as managers and operators.

3. Private Policy

Research and innovation must be managed today to secure sustainability for tomorrow. Open innovation is a policy of collaboration. Companies must manage intellectual property to manage research: they need to access external IP and profit from internal IP. Researchers must be knowledge brokers as well as knowledge generators. Science-driven academic research is vital to returns. Scientists decide the basic research; industrialists decide the applied R&D.

4. Private Practice

The priorities of new venture formation in the knowledge economy are: ICT and Internet access; linkages to investors and lenders; formation of lean management and advisory boards comprised of experienced individuals, competent in their fields of discipline and having as few members as needed to get the job done; and planning and securing facilities. nvtc

 

REFERENCES

Carayannis, E. (1998). The speed and acceleration of technological innovation in the small satellite manufacturing industry: a co-opetitive dynamics perspective. IEMC ‘98 Proceedings. International Conference on Engineering and Technology Management: Pioneering New Technologies: Management Issues and Challenges in the Third Millennium. 221 -230.

Carayannis, E. & Alexander, J. (2002). Is technological learning a firm core competence, when, how and why? A longitudinal, multi-industry study of firm technological learning and market performance. Technovation, 22 (1), 625-643.

Carayannis, E. (2008) Knowledge-Driven Creative Destruction, or Leveraging Knowledge for Competitive Advantage: Strategic Knowledge Arbitrage and Serendipity as Real Options Drivers Triggered by Co-Opetition, Co-Evolution and Co-Specialization. Industry and Higher Education, 22 (6), 343-353

Carayannis, E. & Provance, M. (2008). Measuring firm innovativeness: towards a composite innovation index built on firm innovative posture, propensity and performance attributes. Int. J. Innovation and Regional Development 1(1), 90-107.

Carayannis, E. (2011). Knowledge Arbitrage, Serendipity, and Acquisition Formality: Their Effects on Sustainable Entrepreneurial Activity in Regions. IEEE Transactions on Engineering Management, 58 (3), 564 – 577.