The Successful Transition to a Knowledge‐Based Development Path of a Less‐Developed Region

This paper presents the case of a less‐developed EU region—the Pomeranian region of Poland—that is, an example of the successful transformation from a command to market economy and the creation of a new knowledge‐based development path thanks to the upgrading of its innovation model. This successful transformation was based, in part, on the region's specific innovation policy and the activities of pro‐innovative institutions; however, other factors were also important such as the diversified structure of the region's economy. New knowledge‐based industries have developed in the region, while the potential of traditional industries that have gone through a restructuring, has been maintained. The factors that existed prior to the innovation model's transformation included such aspects as the high quality of human and social capital, a strong academic center, a high quality of life, and an open economy and society. Supply factors in the form of qualified personnel were crucial for the growth of employment in new industries and R&D that determined the improvement of the regional GDP per capita. Moreover, the transition to a knowledge‐based economy stimulated an increase in the concentration of population in the metropolitan area of Tri‐City.     

Behind the Pan‐European Convergence Path: The Role of Innovation,Specialisation and Socio‐economic Factors

The paper analyses the determinants of regional disparities in per capita gross domestic product (GDP) and their evolution over time in the enlarged European Union (EU). With reference to the literature it groups EU regions on the basis of three different factors—specialisation, socio‐economic features, and innovation. It then analyses regional disparities in per capita GDP (EU‐relative and country‐relative) across groups over 2004–2011 using both non‐parametric tools and traditional regression analysis with spatial effects. The paper finds that EU‐wide convergence actually conceals growing divergence across old member regions and within new members. Coming to the factors that lie at the heart of regional disparities, country factors lose importance for newcomers but become more important for older members, notwithstanding longstanding integration. Socio‐economic factors and innovation instead become increasingly important for all areas, socio‐economic factors lying at the heart of within‐country differences and innovation more of those between regions. Finally, specialisation appears to have a lower explanatory power.     

The Innovativeness and Heterogeneity of Foreign‐Invested High‐Tech Companies in Shanghai

China has taken a foreign direct investment‐based approach toward increasing its capital and knowledge base, and developing into an innovative economy. However, little quantitative evidence exists about the factors that drive innovations of foreign‐invested enterprises (FIEs) there. This paper uses survey data from high‐technology firms in Shanghai to discuss factors affecting their innovativeness. It takes the concepts of absorptive capacity, export orientation, and innovation‐related cooperation as a starting point. It highlights how the interplay of strategies and resources affects innovativeness and heterogeneity of FIEs. The most innovative FIEs are endowed with a strong human capital base and R&D activities, which at the same time target export markets and whose cooperative partners involve firms other than their parent company. The results underline the necessity to differentiate between the different types of FIEs when examining their innovativeness.     

Knowledge Networks in an Uncompetitive Region: SME Innovation and Growth

Knowledge networks are now recognised as a crucial element underlying the economic success and competitiveness of geographic locations, in particular regions. The aim of this paper is to assess the types of knowledge networks utilised and formed by knowledge‐based small‐ and medium‐sized enterprises (SMEs) in the relatively uncompetitive regional setting of Yorkshire and Humberside in the UK. It explores the relationship between knowledge networking activity and the levels of innovation and growth achieved by these SMEs. It is found that SMEs tend to utilise and value more knowledge networks with actors outside the region. However, more innovative SMEs possess a balance of inside and outside the region knowledge networks. Knowledge networking activity is sometimes negatively associated with growth, suggesting that networks with certain actors, such as public sector support agencies, may be formed by SMEs when they are facing competitive pressures. In terms of policy implications, the paper recommends a shift from the cluster policies implemented by many regional authorities to a regional innovation systems approach, focusing equally on the regional and more global dimensions of knowledge networks. It is concluded that regional public policy makers need to renew their efforts to support SMEs in creating and sustaining their knowledge networks.     

Innovative and Competitive Structure of Regional Economies in Turkey

Regional development theories have experienced a transition from Keynesian state‐led economic development models to development based on public–private partnerships, innovation, industrial districts, etc. With the increasing concern for innovative milieu, products, process, organizational, and institutional innovations have assumed an important place in regional development policies. All these regional development paradigms have formed the basis of the initiation of a new process in regional development called the new regionalism, which includes cumulative efforts to revitalize local economic growth. In this paper, we identify technological levels of 26 NUTS 2‐level regions according to the Organisation for Economic Co‐operation and Development (OECD)'s classification. Then, we develop an innovation and competitiveness index for Turkey by employing principal component analysis. In conclusion, we formulate some workable policy solutions and suggestions for regional economies in Turkey. According to the results, Istanbul is the most innovative and competitive region in Turkey. Ankara is becoming a regional knowledge cluster, thanks to its strong R&D infrastructure and highly qualified researchers.     

Emerging geography of technological innovation in China's ICT industry: Region,inter‐firm linkages and innovative performance in a transitional economy

This study critically evaluates the relevance of the existing theory of technological innovation to the case of China's information and communications technology industry. Based on a large‐scale questionnaire survey conducted in China's three most important city‐regions, namely, Beijing, Shanghai and Shenzhen, where the core of China's information and communications technology industry is located, this study reveals a significant regional variation in technological innovation in a political economy undergoing marketisation and globalisation. This research has found no significant relationship between the innovative performance of firms and the extent of production linkages; nor was there a significant knowledge exchange among firms. A further analysis has identified the significant role played by government purchases, research and development capital input and export propensity in the process of technological innovation. The findings of this research cast doubts over the prevailing theory of ‘new economic geography’ in which soft and unbounded relational assets have been overemphasised at the expense of some solid and bounded actors and agents that are pivotal to technological innovation in a developing economy.     

Endogenous Processes in European Regional Growth: Convergence and Policy

The traditional empirical approaches to the analysis of economic growth,cross‐section and panel data regressions are substantially uninformative withrespect to the issue of convergence. Whether national or regional economies appear to converge in terms of per capita income or productivity levels (the so‐called β‐convergence) critically depends on the way in which the empirical model is specified. Traditional specifications witness a disproportionate presence of proxies for forces leading towards divergence among the conditioning variables. It is therefore hardly surprising that these analyses find a positive and statistically significant value for the estimate of the speed of convergence. A more constructive use of cross‐section and panel data regressions is in the analysis of the determinants of growth. The present paper therefore builds on recent work on the role of different growth determinants (Cheshire and Carbonaro 1996) and analyses the growth performance of 122 Functional Urban Regions (FURs)over the period 1978–1994. This model explicitly recognizes growth as amultivariate process. In this new formulation it incorporates a spatialized adaptation of Romer's endogenous growth model (Romer 1990), developing the work of Magrini (Magrini 1997). Magrini's model originated from the view that technological knowledge has a very important tacit component that has been neglected in formal theories of endogenous growth. This tacit component, being the non‐written personal heritage of individuals or groups, is naturally concentrated in space. As a result, technological change is profoundly influenced by the interaction between firms and their local environments. The present paper reports the results of the estimation of a fully specified model of regional growth in per capita income. Particular attention is played to the role of research and development (R&D) activities, and to the influence of factors such as Universities that shape the local environments and have important policy implications. These results are then applied to quantifying the scope for policy to influence the growth process. Several simulations are presented deriving alternative growth outcomes across European regions that would have been obtained if those variables over which policy might have control—including the contribution of human capital—had had alternative values reflecting the realistic scope of policy makers' influence. The implications for convergence/divergence in regional per capita income levels are then analyzed using a Markov chain approach (Quah 1993 and 1996; Magrini 1999).     

Innovating in less developed regions: What drives patenting in the lagging regions of Europe and North America

Not all economically disadvantaged—“less developed” or “lagging”—regions are the same. They are, however, often bundled together for the purposes of innovation policy design and implementation. This paper attempts to determine whether such bundling is warranted by conducting a regional level investigation for Canada, the United States, on the one hand, and Europe, on the other, to (a) identify the structural and socioeconomic factors that drive patenting in the less developed regions of North America and Europe, respectively; and (b) explore how these factors differ between the two contexts. The empirical analysis, estimated using a mixed‐model approach, reveals that, while there are similarities between the drivers of innovation in North America's and Europe's lagging regions, a number of important differences between the two continents prevail. The analysis also indicates that the territorial processes of innovation in North America's and Europe's less developed regions are more similar to those of their more developed counterparts than to one another.     

European Regional Convergence Revisited: A Weighted Least Squares Approach

A plethora of past studies have concluded that unconditional β‐convergence is present in a broad sample of regions, implying that poor regions grow faster than rich ones. All these econometric studies tend to overlook the relative importance or size of each region in the national setting, treating all regional observations as equal. However, this assumption might lead to unrealistic or misleading results. Convergence analysis could be more meaningful if it included a weighting mechanism taking into account the size of regions. The aim of this paper is to investigate whether the inclusion of a weighting mechanism in β‐convergence analysis, giving more weight to larger regions and less to smaller ones, can result in sharply different implications for the regional convergence‐divergence process. For this reason, both unweighted ordinary least squares (OLS) and weighted least squares estimators are used in the analysis of regional (intra‐national) convergence within 10 European Union (EU) countries over the period 1990–2000. The comparison between the two methods reveals that when regions are appropriately weighted for their size, intra‐national divergence, rather than convergence found with the OLS approach, seems to be the dominant experience in the EU.     

Innovation in the periphery: Compensation and exploitation strategies

Recent research has challenged the urban bias in economic geography and innovation studies, showing that highly innovative and competitive firms are also located in peripheral regions. So far, however, analyses has focused on how firms innovate despite their unfavourable location and little has been said about the innovation benefits of peripheral areas. Hence, this article identifies different compensation and exploitation strategies adopted by firms in order to overcome regional innovation constraints and to reap innovation benefits found in the periphery. Drawing on 20 in‐depth qualitative interviews with innovative firms situated in the Austrian periphery, our analysis reveals that innovation in peripheral regions is the outcome of a combination of compensation and exploitation practices. The uptake and composition of these strategies depend on the firm and regional characteristics, with firm size being the most influential factor.     

Interpersonal trust,invention, and innovation across European regions

Many studies in economics and regional science claim a positive link between interpersonal trust and innovation by demonstrating a positive effect of trust on patenting. This contrasts many findings from organization level studies on trust and innovation, who report a variety of findings including inverted-U type relations. A possible explanation is that trust exhibits different roles in invention and innovation, as the former relies on knowledge commons while the latter directly embeds commercialization and the market context. This study attempts to reconcile the two set of findings by studying indicators of invention and innovation in relation to trust at the same unit of observation, by using the regional variation in Europe. I study the relationship between interpersonal trust and patent applications (a measure of invention), trademark applications (a composite indicator) and the share of innovative sales in turnover by SMEs (a direct indicator of commercialization), across European regions. I show that trust positively affects trademark applications with an effect that is comparable to that on patent applications. However, trust exhibits an inverted-U type relationship with innovative sales. Results collectively point to a strong role of trust in all three creative activities, including a negative effect at the higher end when the indicator is directly contingent on commercialization and sales. I also estimate the extent of spatial spillovers in the effect of trust on all three creative outcomes.     

From R&D to Innovation and Economic Growth in the EU

ABSTRACT Over the last two decades many European governments have pursued ambitious research and development (R&D) policies with the aim of fostering innovation and economic growth in peripheral regions of Europe. The question is whether these policies are paying off. Arguments such as the need to reach a minimum threshold of research, the existence of important distance decay effects in the diffusion of technological spillovers, the presence of increasing returns to scale in R&D investments, or the unavailability of the necessary socio‐economic conditions in these regions to generate innovation seem to cast doubts about the possible returns of these sort of policies. This paper addresses this question. A two‐step analysis is used in order to first identify the impact of R&D investment of the private, public, and higher education sectors on innovation (measured as the number of patent applications per million population). The influence of innovation and innovation growth on economic growth is then addressed. The results indicate that R&D investment, as a whole, and higher education R&D investment in peripheral regions of the EU, in particular, are positively associated with innovation. The existence and strength of this association are, however, contingent upon region‐specific socio‐economic characteristics, which affect the capacity of each region to transform R&D investment into innovation and, eventually, innovation into economic growth.     

The impact of R&D and knowledge spillovers on the economic growth of Russian regions

Russia presents an interesting case of a country which has strived to implement innovation policies since the transition period but so far has achieved mixed results. This study aims to analyze the impact of knowledge production and knowledge spillovers on regional growth in Russia within a framework of endogenous growth models. Applying GMM and spatial error panel modeling techniques to Rosstat data for 80 Russian regions from 2005 to 2013, the authors test the hypothesis about the relevance of R&D and expenditure on technological innovations (H1) and the hypothesis about the relevance of knowledge spillovers (H2) on the growth rates of GRP per capita. Hypothesis 1 was confirmed while Hypothesis 2 was rejected, indicating the absorptive capacities of innovatively lagging regions were not high enough for effective adaptation of new technologies from technologically innovative regions. Inclusion of indicators related to additional channels of knowledge diffusion in regressions resulted in the relevance of FDI and imports of goods and services for regional growth. Results of the study could form the basis for developing innovation policies for the Russian regions.     

The elusive quest for balanced regional growth from Barlow to Brexit: Lessons from partitioning regional employment growth in Great Britain

The British Government’s economic strategy for post‐Brexit Britain of achieving balanced regional growth by “driving growth across the whole country” echoes the objectives set by the Barlow Report of 1940. The regional policies that followed the Barlow Report were heavily influenced by papers written for the Commission by G D A (later Sir Donald) MacDougall. The first of these papers was included as an appendix to the report itself and introduced the shift‐share methodology to the analysis of regional employment growth, and subsequently shown to be flawed. The second paper considered the urban hierarchy and growth but was never fully developed. Consequently post‐war regional policy focussed on the contribution of industrial structure to employment growth without fully taking into account the urban hierarchy or regional locations of that employment. This article replaces the flawed shift‐share methodology with multifactor partitioning (MFP) and applies it to regional employment growth for the period 1971‐2012, a span of special interest because it largely coincides with British membership of the European Union (EU). The deficiencies in the second paper are addressed by introducing allometry to measure the employment growth of each region relative to that of Great Britain and then regression analysis to relate the allometries to distance from London. The results of the two sets of analyses highlight the need for a multiple‐factor, comprehensive, and integrated approach to regional policy and provide a benchmark against which to gauge the success of Britain's post‐Brexit policy of driving future growth across the whole country.     

Evaluation of government‐supported provincial innovation competitiveness—Evidence from China

Government support plays a crucial role in enhancing regional innovation capabilities and creating distinctive innovation clusters. Using the innovation competitiveness indicators of the 31 provinces in China, this paper examines the provincial government collaboration and innovation competitiveness values through Super‐SBM data envelopment analysis and analytic hierarchy process. Then, the particle swarm optimization (PSO) algorithm is employed to relate government collaboration to innovation competition and cooperation among provinces in hope of exploring the developmental trends of innovation cluster optimization. Research findings show that only 25.8% of the provincial government support proves effective for regional innovation, and the competitiveness values of the provinces are generally low and need to be improved. By incorporating the role of government support into the innovation competition and cooperation among provinces, there has been a tendency of innovation activities clustering in innovative regions and three major clusters have formed. The trend of clustering will continue to evolve outwards so that the overall innovation level of China would be enhanced.     

Internet development and the spatial optimization of regional productivity: Evidence from China

The rapid development of the Internet had a profound influence on the spatial distribution of economic output activities. On the basis of theoretical analysis, this study takes China's regions as research samples and construct a spatial econometric model to empirically analyze the impact of Internet development on regional productivity. The analysis reveals that the distribution of regional productivity in China had significant spatial correlation; regional productivity had positive spatial externalities; Internet development had significant promotion effects and positive spatial spillover effects to regional productivity, but the effects are heterogeneous in different subregions. The subregion analysis shows that the optimization effect of the Internet on regional productivity exhibits heterogeneity in different subregions. The threshold effect analysis reveals the increasing marginal effect of Internet development on regional productivity, and economic development and human capital supply are important factors restricting this marginal effect. Altogether, this study provides useful references on the positive effects of the Internet on regional productivity in the spatial dimension, and suggests that the policy makers can optimize the spatial distribution of regional productivity by promoting Internet access in various regions and narrowing the digital divide among regions.     

Innovation and Regional Growth in Mexico: 2000–2010

This paper looks at the factors driving regional growth in Mexico, paying special attention to the potentially growth‐enhancing role of innovation and innovation policy. The analysis combines innovation variables with indicators linked to the formation of adequate social conditions for innovation (the social filter), and spillovers for 31 Mexican states and the Mexico City capital district (the Distrito Federal) during the period 2000–2010. The results indicate that regional economic growth across Mexican states stems from direct investment in research and development (R&D) in areas with favorable social filters and which can benefit not only from knowledge spillovers, but also from being surrounded by rich neighbors with good social conditions. The results stress that, although Mexican innovation policy has been relatively well targeted in order to generate greater economic growth, its relatively modest size may have undermined the attainment of its main objectives.     

Regional Innovation Systems: Implications for Nonmetropolitan Areas and Workers in the South

ABSTRACT A public policy response to global competition is the creation of a geographic concentration of innovative activity (regional innovation systems [RIS]) that will enhance metropolitan economic development through knowledge spillovers, product development, and new firm spin‐offs. This article identifies three types of RIS in the thirteen southern states based on a cluster analysis of twenty indicators of innovative and entrepreneurial activity. Next, regression analysis is used to determine if the 1990–2000 growth rates of nonmetro county population, employment, and earnings were related to proximity to an RIS after controlling for other county characteristics associated with local economic development. The research findings indicate that nonmetro counties near an RIS experienced more rapid population and employment growth; however, changes in nonmetro growth rates varied by type of regional innovation system. In addition, proximity to an RIS had a stronger impact on nonmetro population change than on nonmetro job growth.     

Does Administrative Status Matter for Urban Growth? Evidence from Present and Former County Capitals in East Germany

Public sector activities are often neglected in the economic approaches used to analyze the driving forces behind urban growth. The institutional status of a regional capital is a crucial aspect of public sector activities. This paper reports on a quasi‐natural experiment on county towns in East Germany. Since 1990, East German cities have demonstrated remarkable differences in population development. During this same period, many towns have lost their status as a county seat due to several administrative reforms. Using a difference‐in‐differences approach, we compare the annual population development of former county capitals to population change in towns that have successfully held on to their capital status throughout the observed period. The estimations show that losing county capital status has a statistically significant negative effect on annual changes in population. This effect continues to increase over time after the respective reforms have been implemented.     

State Policies,Enterprise Dynamism,and Innovation System in Shanghai,China

ABSTRACT Today rapidly growing economies depend more on the creation, acquisition, distribution, and use of knowledge. As such, strategies for enhancing research and innovation capabilities have come to occupy a more important position in many developing nations, including China. Already the leading production center, and often seen as China's economic locomotive, Shanghai is striving aggressively to retain its national preeminence and has launched concerted efforts to increase local innovative output. The primary purpose of this paper is to understand how state‐led efforts have fared in promoting technology innovation. By situating the city in the national and global context, the paper shows that Shanghai has gained a substantial lead in developing an innovation environment with extensive global linkages and leading research institutions. Recent efforts in building up the research and innovation capacity of the enterprise sector have begun to show progress. Although firms are enthusiastic about its future as an innovation center, Shanghai continues to face challenges of inadequate protection of intellectual property, lack of venture capital investment, and the tightening supply of highly qualified knowledge workers.