Øivind Strand

The Swedish system of innovation: Regional synergies in a knowledge-based economy

Based on the complete set of firm data for Sweden (N = 1,187,421; November 2011), we analyze the mutual information among the geographical, technological, and organizational distributions in terms of synergies at regional and national levels. Using this measure, the interaction among three dimensions can become negative and thus indicate a net export of uncertainty by a system or, in other words, synergy in how knowledge functions are distributed over the carriers. Aggregation at the regional level (NUTS3) of the data organized at the municipal level (NUTS5) shows that 48.5% of the regional synergy is provided by the 3 metropolitan regions of Stockholm, Gothenburg, and Malmo/Lund. Sweden can be considered a centralized and hierarchically organized system. Our results accord with other statistics, but this triple helix indicator measures synergy more specifically and quantitatively. The analysis also provides us with validation for using this measure in previous studies of more regionalized systems of innovation (such as Hungary and Norway).

“Brain Drain” or “Brain Gain”? Students’ Loyalty to their Student Town: Field Evidence from Norway

In the global economy regions fight a two-front “war” to attract young people. On the one hand, they compete against more urban areas because young people leave home to study and do not return to their home region (“brain drain”). On the other hand, they struggle to attract new residents, students and entrepreneurs to their local region (“brain gain”). The context is a student town of a strong industrial region characterized by a net export of young people and an increasing demand for highly qualified labour. The purpose is to gain insight into how student loyalty to a student town may be enhanced. A partial least square path modelling approach is used to estimate a structural equation model of student town loyalty. One finding is that the creation of student town satisfaction has more influence on student town loyalty than reputation building. “Social activity” is the most important loyalty driver. This antecedent is mediated through student town satisfaction and reputation, as well as university college reputation. The town municipalities and the university college should thus be coordinated in their effort to increase student town loyalty to bring down the “brain drain” and increase the “brain gain” in the region.

Economic and technological complexity: A model study of indicators of knowledge-based innovation systems

The Economic Complexity Index (ECI; Hidalgo and Hausmann, 2009) measures the complexity of national economies in terms of product groups. Analogously to ECI, the Patent Complexity Index (PatCI) can be developed on the basis of a matrix of nations versus patent classes. Using linear algebra, the three dimensions—countries, product groups, and patent classes—can be combined into a measure of “Triple Helix” complexity (THCI) including the trilateral interaction terms between knowledge production, wealth generation, and (national) control. THCI can be expected to capture the extent of systems integration between the global dynamics of markets (ECI) and technologies (PatCI) in each national system of innovation. We measure ECI, PatCI, and THCI during the period 2000–2014 for the 34 OECD member states, the BRICS countries, and a group of emerging and affiliated economies (Argentina, Hong Kong, Indonesia, Malaysia, Romania, and Singapore). The three complexity indicators are correlated between themselves; but the correlations with GDP per capita are virtually absent. Of the worlds major economies, Japan scores highest on all three indicators, while China has been increasingly successful in combining economic and technological complexity. We could not reproduce the correlation between ECI and average income that has been central to the argument about the fruitfulness of the economic complexity approach.

Extending Economic Complexity Index to a Ternary Complexity Index

Economic complexity measures have been constructed on the basis of bilateral country-product network data. In this study, we submit a Ternary Complexity Index (TCI), which explicitly incorporates technological complexity as a third dimension, measured in terms of patents. TCI is based on Lotka-Volterra equations and thus the evolution of an innovation eco-system can be specified unambiguously. We perform model calculations based on empirical data and simulate the diachronic extensions. The results suggest that TCI improves on Hidalgo & Hausmann’ and Tacchella et al. measures as an indicator of future economic growth.

What is the effect of synergy provided by international collaborations on regional economies

In the present paper, we analyze the effect of international collaboration on regional markets. We compare two Norwegian counties with very different profiles in terms of how international or regional cooperation affects the synergy generated among the geographical, technological, and organizational distributions of firms. This synergy is much larger in the rural region with international industry than in the region with a strong knowledge infrastructure. International firms can take the role of knowledge brokers in lagging regions with weak knowledge institutions. The methodological contribution of this study is that we translate the synergy (abstractly measured in bits of information) into more familiar economic terms, such as turnover for the special case of domestic-foreign collaborations. The analysis is based on Norwegian data, as Norway is a small country with an open and export-oriented economy. Data for Norway is publicly available in great detail. The Triple-Helix synergy caused by firms with foreign ownership is a new indicator of the international contribution to the efficiency of the innovation system in a region. The indicator can also be interpreted as a measure of the attractiveness of regional industries to international corporations, which entails the perspective of international technology transfer and the access of regional industry products to global markets.

TECHNOLOGICAL INNOVATION CAPABILITY AND INTERACTION EFFECT IN A SCANDINAVIAN INDUSTRY CLUSTER

How do innovation ecosystems affect the technological innovation capabilities (TICs), as defined by Yam et al. (2004), and company performance? Empirical data was acquired through a survey of 75 maritime equipment suppliers in an industry cluster in Norway. Regression analysis was supplemented with partial least square methods in order to compensate for the low number of respondents. Significant effects were found for manufacturing and marketing capabilities on company performance. The results for organisational capability were method dependent. Learning, R&D, resource allocation and strategic capabilities were identified as insignificant. These results conflict with other studies that identified manufacturing capabilities as the only insignificant TIC construct. However, the findings are partially in line with studies that have questioned learning, organising, and resource capabilities as drivers for competitive advantages. The moderating effect of cluster interaction and manufacturing capability on performance is coherent with prior research, but further research is needed for a deeper understanding of these interaction effects.