The aim of this paper is to demonstrate how economic growth stimulates business-service providers to develop new service varieties, which, in turn, enhance the productivity of business-service buyers. This creates a coevolutionary process where service suppliers and customers interact, leading to an increase in the number of differentiated service offerings. We introduce a framework for local economies, wherein business-service sectors evolve in response to local demand potential, while non-business-service sectors grow based on each economy's supply potential. Business service growth is more rapid in local economies with higher demand potential, while non-business-service sectors expand faster in areas where the business-service supply potential is greater. A key assumption is that business service firms operate in a monopolistic competition environment, where an increase in business-service capacity leads to an expansion in the variety of services offered. This, in turn, enhances the diversity of service offerings in municipalities with strong demand potential. Additionally, service providers not only deliver innovation-related information to client firms but also unintentionally disseminate knowledge within the region, fostering knowledge spillovers among firms.

This paper analyzes city system dynamics, based on a theoretical framework relating interaction potentials to agglomeration economies and density externalities. It employs new historical time series data on population size of cities in Sweden over two centuries (1810-2010) and introduces two schematic growth factors: (i) the intra-city potential and (ii) the extra-city potential located in in rings encircling each city. The first factor is measured by each city's population size, while the second is a vector of distance-discounted population size for each of a city's urban rings. In this way, we can explain a city's growth as a function of its interaction potential inside the city, as well as inside the first, second hand third ring. A robust finding is that cities with large ring potentials follow different development paths than those with small ring potentials. We also find clear evidence of structural change between the two centuries 1810-1910 and 1910-2010. In the first period, city growth is positively impacted by the size of the intra-city potential, whereas the same potential dampens or reduces the growth in the second period. Moreover, the ring potentials outside the city tend to switch from having negative growth stimulation in the first period to having positive stimulation in the second period.

Production theory has remained substantially unchanged since the publication of the theory of production by Frisch (Theory of production, D. Reidel, Dordrecht, 1928; Nord613 Tidskr Tek Økon 1:12–27, 1935). The theory is based on the idea of a firm deciding on the possible input and output combinations of a single unit of production. His theory was substantially copied in contributions by Carlson (A study on the pure theory of production, University of Chicago, Chicago, 1939) and Schneider (Einführung in die Wirtschaftstheorie. 4 Bände, Mohr, Tübingen, 1947), and later by practically all textbooks in microeconomics. The idea is to model the firm as a “black box” in which a finite number of externally purchased inputs are transformed into a finite number of outputs to be sold in the market(s). Most of the time, the prices are externally determined. Often, the production process is summarized by some simplified production function as, for example, in the form of a CES function. Another and conceptually richer approach is the formulation of an activity analysis model. In the latter case, simple internal interdependencies can be included. In this paper, we indicate how internal interdependencies can also be modeled within a special CES framework. In recent decades, there has been a remarkable growth in the number of production units of firms such as IKEA, Walmart and Apple to name a few such global networking firms. Most of the analysis of these network firms has been modeled by logistics and other operations-research analysts (Simchi-Levi et al. 2008) and to a limited extent by researchers in business administration schools. Very little has been done in economics. We propose a modeling approach consistent with the microeconomic theory. 

This paper introduces a model framework which identifies the economic activity of each local economy (location) and observes the time distance between each pair of locations. Time distance for interaction inside local economies is taken as reference. Two models of location patterns are formulated on the basis of principles adhering to new economic geography (NEG). The first model describes how business service firms (classified into three levels of knowledge intensity) select locations with a favorable demand potential, depicting a location’s access to customer demand. The second model takes the location of business-service supply as given and describes how other firms select locations with a favorable supply potential, depicting the access to business-service supply. In order to calculate each location’s demand and supply potentials we need distance-decay parameters for interaction outside the local economy. When estimating the two models we develop an approach where the distance-decay (time sensitivity) parameters are determined endogenously as an integral part of estimating location choice parameters. The exercise can be appreciated as a test of NEG principles.

This paper explores the capacity to produce new knowledge proxied by patents granted in 18 industries in 11 European economies. For each industry in each country, the number of granted U.S. Patent and Trademark Office patents is recorded over the 1991–2005 period. Controlling for research and development, industry composition, and institutional setting, the paper shows that systematic differences in patent intensity exist between the studied countries, such that almost all industries are affected by country-specific conditions, suggesting that the countries’ innovation systems differ in efficiency. The countries with the highest R&D efficiency are Sweden and Finland, followed by the Netherlands and Germany.