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Knowledge-based (Oil) Clusters

This article explores the role of science, technology, and innovation in the future of extractive industries in Latin America and the Caribbean. It discusses the potential for knowledge-based extraction, the importance of human capital, and the benefits of building clusters. The example of the Ekofisk oil field showcases the link between field building and innovation. The article also highlights the competitiveness factors for attracting knowledge-intensive industries and offers policy implications for economic development.

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Knowledge-based (Oil) Clusters

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  1. Knowledge-based (Oil) Clusters The Future of Extractive Industries in LAC and the role of STI 21 September 2016 Buenos Aires Amir Sasson, BI, Norwegian Business School

  2. Extraction Industries: Two stories • Raw material extraction • Relatively low human capital • Scale economies • Localities blossom and strive • Efficiency gains from • Learning by doing • Importing technology • Export material • Knowledge-based extraction • Relatively high human capital • Reputation • Localities blossom and adjust • Efficiency gains from: • The above and applying technology through exploring solutions • Export material and solutions

  3. A different story: Ekofisk as an example

  4. A simple exercise • Expected recovery at ca. 1971: 17% • Today (not final): >50% • In terms of oil barrels the difference is 1905m or for USD 50 price, USD 95.2 billions or USD 20,000 per inhabitant. • The story: “Norwegian participation was limited. [..] Engineering and procurement was mainly performed in London, and besides construction of the Ekofisk storage tank and some verification work by Det Norske Veritas, very little activity took place in Norway.” (Hagen 2001)

  5. Field building and innovation go hand in hand Sources: Adapted from Ministry of Petroleum and Energy (2010) and Fjose et al. (2010a)

  6. The two sides • Licenses and operatorships, 179 entries, increased competition and diversity in the last decade* • Ca. 22,000 employees • The largest exporter. • Supplier industry • Ca. 114,000 employees in 2500 firms. • Second largest exporter.

  7. ‘Forthcoming’ Business Knowledge based Change driven Global Environmentally robust

  8. Understanding Competitiveness How can we develop value creating economic activities in countries or regions where manufacturing is disappearing and cost level is very high?

  9. Beauty contest Nations and regions compete to be the most attractive locations for the establishment of knowledge intensive industries

  10. The Emerald Model Knowledge Dynamics Cluster Attractiveness Environmental Attractiveness Ownership Attractiveness Educational Attractiveness Talent Attractiveness R&D and Innovation Attractiveness

  11. The Emerald Model Knowledge Dynamics Cluster Attractiveness Environmental Attractiveness Ownership Attractiveness Educational Attractiveness Talent Attractiveness R&D and Innovation Attractiveness

  12. Cluster Attractiveness • How large is the cluster? • To what extent does it add value? • Is it complete? • Does it indicate specialization (Regionally, Nationally, Internationally) • How much does it export? • Is it productive (e.g., Value creation/Employee)?

  13. Educational Attractiveness(Supply of knowledge workers) • Do cluster specific educational programs exist? • Do they attract more students at vocational, undergraduate, and graduate levels? • Do they attract more foreign students?

  14. Talent Attractiveness • Do firms manage to attract high skilled employees (e.g., Engineers, Scientists and PhD)? • And Skilled foreign workers? • Does the media assist? Industry Sexiness.

  15. R&D and Innovation Attractiveness (Cluster knowledge production) • Cluster specific researchers • Cluster specific foreign researchers • R&D investments • R&D output (Publications, Patents) • Innovation output (Products, Services, Markets) • Innovation content (New products/Total sales)

  16. Ownership Attractiveness (Cluster competent capital) • Local competent owners. • Cluster serial entrepreneurship • Is foreign ownership so bad?

  17. Environmental Attractiveness • Emissions and pollutants • Total energy usage (CO2) • Proportion of renewable energy • Environmental investments • Environmental technology • Industry specific measures

  18. Knowledge Dynamics • Employee Mobility between firms • Knowledge Linkages between firms (in innovation and internationalization) • Knowledge Linkages with institutions • Cooperative Networks: Alliances

  19. Offshore Oil & Gas Knowledge Dynamics Cluster Attractiveness Environmental Attractiveness Ownership Attractiveness Educational Attractiveness Talent Attractiveness R&D and Innovation Attractiveness

  20. Global knowledge Hub Drilling Technology

  21. Tourism Knowledge Dynamics Cluster Attractiveness Environmental Attractiveness Ownership Attractiveness Educational Attractiveness Talent Attractiveness R&D and Innovation Attractiveness

  22. Policy Implications • Geographical areas host the occupants of hives. If the conditions are not attractive, they fly away or even worse, never visit. • Areas or firms will find it cumbersome to excel in isolation. • Distributed knowledge. • Knowledge dynamics/NCEs. • Government action • Coordinated Strategic Thrust • Broaden the public sphere which will create better conditions for knowledge-based economic development. • Define the problem, let firms create solutions • Coordinated, predictable and transparent decision making

  23. Oil/other Wealth Investment Knowledge

  24. Feedback and change • A dynamic system • More recent revisions of • Competition • Exploration: 30 to 70 new players since 2000 • 300% increase in wildcat exploration drilling • Sources of income • Tax stimuli • Licensing • Exploration areas

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