[Show description][Hide description] DESCRIPTION: In regions whose industrial structure is organized around one or more large firm corporations, the best practices of small and medium enterprises (SMEs) depend on where firms are located in the supply chain. This paper studies 351 SMEs in the Antofagasta Region in Chile between 2007 and 2008, where multinational and public mining companies are the drivers of the local economy and the government is promoting the formation of a mining cluster. Structural equation model (SEM) is used to show that first-tier SME mining suppliers, directly related to large corporations, follow business practices that promote international certification, quality control and investment in innovation, while in contrast second-tier SMEs are more focused on avoiding insolvency and client orientation. These results cast doubt on the formation of a mining cluster in the region and suggest the need for differentiated policies in these two groups of SMEs, especially those related to knowledge transfer.
[Show abstract][Hide abstract] ABSTRACT: This paper investigates a new emerging phenomenon in the debate of knowledge-based economic growth called “bridging knowledge to commercialization”. The paper considers commercialization of knowledge as a complex and a multi-faceted phenomenon and aims to highlight “the good”, “the bad” and “the challenging” in commercialization of knowledge from a taxonomic perspective. The paper has four objectives: (1) to examine the emerging concepts in bridging knowledge to commercialization while addressing related issues in the literature and to offer a conceptual framework on the basis of a typology of metaphores for knowledge; (2) to highlight the societal benefits of commercialization of knowledge in a regional development context; (3) to underline the value conflicts and differences in culture and perspectives in the valuation of knowledge in order to better understand the commercialization process; and (4) to highlight the challenges for academia, industry and government while describing the critical framework conditions that are needed to effectively foster commercialization of knowledge. While addressing the academic, societal, spatial, cultural and ethical implications of knowledge commercialization, the paper highlights retrospects and prospects from regional development perspective.
The Annals of Regional Science 04/2013; 50(2). DOI:10.1007/s00168-012-0510-8 · 1.03 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This article focuses on entrepreneurship in economic geography and aims at a systematic investigation of regional variation
in knowledge-based entrepreneurial activity. We develop and test a three-phase structural model for regional systems of entrepreneurship after introducing a systems approach to entrepreneurship. The model is built upon the absorptive capacity theory of knowledge
spillover entrepreneurship that identifies new knowledge as one source of entrepreneurial opportunities and human capital
as the major source of entrepreneurial absorptive capacity. Based on data of US metropolitan areas, we find that entrepreneurial
absorptive capacity is a critical driving force for knowledge-based entrepreneurial activity. We also find that high technology
and cultural diversity contribute to the vibrancy of regional systems of entrepreneurship.
[Show abstract][Hide abstract] ABSTRACT: Context: Online social networks and the Web 2.0 technologies embedded in these sites are creating an environment in which individuals can communicate and share information in ways that were previously not possible. Such websites are providing an unprecedented and growing collection of data on individual behavior that is very rich in detail. This includes information on with whom, when and where people interact, and more generally, what their activity patterns look like in time and space, and even what their sentiment or preferences are at specific moments and locations. Knowledge Gaps: There is a burgeoning body of literature that draws upon social media data and more broadly information collected via mobile communications devices (e.g., cell phone trajectories) to model and understand particular aspects of human behavior, including mobility patterns and social and spatio-temporal interaction. Yet, very little of this research has examined how and to what extent the spatio-temporal activity patterns revealed by these new forms of data vary across metropolitan areas, especially after controlling for relevant city-specific characteristics such as the size, density, composition or demographic profile of a city. While we recognize that the study of space-time activity patterns itself is not new, there are some gaps in the literature that should be noted. First, most analyses have been confined to a select set of cities – i.e., those that have conducted travel diaries or activity-based surveys. Due to inconsistencies in the format and type of information collected from such surveys, comparative analyses are problematic. Second, few studies have looked explicitly at the simultaneous integration of space, time and social (inclusive of cyber socialization) interaction, and the complex mobility patterns that arise from this behavior. Lastly, unlike location sharing services data, the information provided by travel behavior surveys tend to capture only mobility patterns arising from the primary residents of a city and not the behavior of transient visitors to that location. Study Objectives: The primary objectives of this study are to 1). understand how and to what extent location sharing services data approximate regional spatio-temporal activity patterns 2). develop a set of network-based metrics for characterizing the centrality and disorder of such activities in a region, and, 3). conduct a cross-city comparison using these metrics and related indicators of mobility.Data: To carry out the proposed research, we intend to use location services data collected over a five month period in 2010-11 (Cheng et al., 2011). This data provides information on user check-ins, or more specifically, where individuals indicate they are at different times of the day and week. Additional details on each individual’s status within the social networks that they belong are also included in the dataset. Methodology: The study methodology draws heavily on techniques from social network analysis, although concepts form landscape ecology, physics and geography are also utilized to capture different aspects of regional activity patterns. To gain an understanding of the types of activities that location sharing services data capture, we first conduct a correlation analysis using sector-based establishment data from the U.S. Census County Business Patterns. Correlations are examined at the zip code level. Second, using a space-time bipartite network topology, we derive a set of measures that characterize the centrality and disorder (entropy) of activities in a region, and that further can be decomposed to examine the spatial distribution of these characteristics. With individual location data aggregated to grid cells and summarized according to regular time intervals, we apply the technique to two U.S. metropolitan areas: Atlanta and Chicago.Significance: Implications for travel demand forecasting, epidemiological and information diffusion modelling and abnormal crowd detection (e.g., through “burstiness” analysis) will be drawn from the study.
[Show abstract][Hide abstract] ABSTRACT: This paper discusses two measures of Social Diversity that have appeared in the literature, the gay index and the Country of Birth (CoB) index, and compares their effects on regional innovative activity. We distinguish social diversity from tolerance or openness and argue that the gay index can be considered as a proxy for tolerance or openness, whereas the CoB index can better represent social diversity. According to our regression results, it is the CoB index (i.e., social diversity), not the gay index (i.e., tolerance or openness), that presents a significant and positive effect on innovation. Nevertheless, innovative activity in regions is still dominantly determined by local stocks of R&D capital and doctoral scientists and engineers.
International Journal of Foresight and Innovation Policy 05/2011; 7(1). DOI:10.1504/IJFIP.2011.040071
[Show abstract][Hide abstract] ABSTRACT: In this paper we explore how satellite images of global night lights from the years 2001 to 2007 can be used to estimate economic activity at the sub-regional level in the U.S., India and China. The night lights based estimates of economic activity are then spatially analyzed and compared with sub-regional economic indicators where available for selected years. For this purpose we have extended the standard bi-variate LISA (Local Indicators of Spatial Autocorrelation) to include bi-directional analysis. This bi-directional bi-variate analysis helps to identify those jurisdictions where night lights intensity can be used as a proxy for measuring sub-regional economic growth. We also briefly discuss two theoretical models that shed light on the geospatial patterns reflected by the night light data. The results are presented with a series of maps, charts and tables.
[Show abstract][Hide abstract] ABSTRACT: This article develops and tests an algorithm of spatial congruence based on geometric congruity of two spatial areal objects in the Euclidean plane. Spatial congruence is defined and thus evaluated as an increasing continuous function of congruity in the position, orientation, size, and shape of spatial objects, dependent upon scaling, translation, and rotation. Expansion-based geometric matching is used to seek the best match between the two objects of interest for the examination and differentiation of the congruence effects of their spatial and geometric properties, while the expansion-inflated size effect is deflated or filtered out accordingly. The use of both expansion and deflation not only allows for a trade-off between size and position, both of which are found substitutable for each other in congruence measurement, but also enables the congruence algorithm to be highly sensitive to differences or changes in these properties. Three geographical objects (the states of Texas, Mississippi, and Louisiana) are used to show how trade-offs among the four properties are manipulated by the congruence algorithm in a geographic information system (GIS) environment, ArcGIS®. In addition, three regular geometric objects are used to demonstrate how the congruence algorithm is sensitive even to small changes in each of the four properties of objects. The results show that the proposed congruence algorithm is capable of quantifying the extent of congruity between two spatial objects regardless of how they are related as described in topological relations.
International Journal of Geographical Information Science 02/2011; 25(1):113-130. DOI:10.1080/13658811003766928 · 1.66 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Recent studies on ethnic entrepreneurship have pointed at an increasing share of migrants in urban small- and medium-sized
entrepreneurial businesses. These migrant activities are crucial to the urban economy in many countries, as they employ a
significant part of the workforce. The main objective of our study is to identify success conditions of ethnic entrepreneurship
by using concepts from social capital and human capital from the literature on empirical factors that are responsible for
successful ethnic entrepreneurship. The empirical part of the paper is based on a survey questionnaire among migrant entrepreneurs
in the city of Amsterdam in the Netherlands and in Fairfax, County in the state of Virginia in the US. We present an overview
of cultural, ethno-psychological and motivational aspects that contribute to the understanding of similarities and differences
between ethnic entrepreneurs in both locations. The analysis is structured around several dimensions of social and human capital
including personal and business characteristics, and network participation for improving business performance. The findings
of the two studies are compared to explore a possible correspondence in business performance patterns. The research tool used
to assess performance is Data Envelopment Analysis (DEA), a technique for comparative efficiency analysis in various types
of corporate organizations. Finally, concluding remarks are presented and possible extensions of the analysis are suggested.
The Annals of Regional Science 01/2011; 46(3):661-689. DOI:10.1007/s00168-009-0351-2 · 1.03 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Investigation of the determinants of entrepreneurship has been extensively pursued by academics in many disciplines. Two dominant
but alternative approaches to understanding these determinants have been used. The first systematically studies individual
entrepreneurs in an effort to identify characteristics or tendencies common to successful entrepreneurs. The second examines
the role of various hypothesized structural attributes and conditions across regions in an effort to explain variation in
levels of entrepreneurial activities. Both approaches reveal considerable insight into how and why entrepreneurial activities
emerge, yet much remains unanswered as no study exists to confirm or refute the evidence pertaining to the manifestation of
the psychological characteristics found at the individual-level at the meso or regional level.
[Show abstract][Hide abstract] ABSTRACT: Over the past two decades or so the emphasis in regional economic development theory has shifted from a focus primarily on
exogenous factors to an increasing focus on endogenous factors. Traditional regional economic development approaches were erected on neo-classical economic growth theory, based
largely on the Solow (1956, 2000) growth model. The new approach – while recognizing that development is framed by exogenous
factors – attributes a much more significant role for endogenous forces. In this context, a suite of models and arguments
that broadly convey the new growth theory have been directed towards endogenous factors and processes (see, e.g., Johansson et al. 2001).
[Show abstract][Hide abstract] ABSTRACT: In this paper we explore how satellite images of global night lights from year 1992 to 2003 can be used to estimate economic activity at the sub-regional level in the US and China. The night lights based estimates of economic activity are then spatially analysed and compared with subregional economic indicators where available for selected years. We also briefly discuss two theoretical models that shed light on the geospatial patterns reflected by the night light data. The results are presented with a series of maps, charts and tables.
Resumen. En este artículo exploramos el uso potencial de imágenes de satélite de la iluminación nocturna global desde 1992 a 2003 para estimar la actividad económica a escala subregional en los EE.UU. y en China. A continuación se analizan espacialmente las estimaciones de la actividad económica basadas en la iluminación nocturna y se comparan con los indicadores económicos subregionales disponibles para los años del estudio. Discutimos también brevemente dos modelos teoréticos que podrían ilustrar los patrones geoespaciales que reflejan los datos de iluminación nocturna. Los resultados se presentan junto con una serie de mapas, gráficos y cuadros.
Regional Science Policy & Practice 11/2010; 3(2). DOI:10.2139/ssrn.1705438
[Show abstract][Hide abstract] ABSTRACT: In this paper we develop an exploratory non-parametric clustering model of spatial and/or spatio-temporal phenomena based on Kolmogorov entropy. The methodology will be tested using quarterly HPI (Housing Price Index) data for 350 plus cities in the US from the Federal Financing and Housing Administration (FHFA), an agency of HUD (US Dept of Housing and Urban Development). This multivariate data will be also analyzed with Principal Component Analysis (PCA) techniques to identify key regions involved in creating the housing bubble and its spread to the rest of cities.
Studies in Regional Science 04/2010; 42(1). DOI:10.2139/ssrn.1590309