Agent modelling of cluster formation processes in regional economic systems

The subject matter of this research is the processes of the spontaneous clustering in the regional economy. The purpose is the development and approbation of the modeling algorithm of these processes. The hypothesis: the processes of spontaneous clustering in the social and economic environment are supposed to proceed not linearly, but intermittently. The following methods are applied: agent imitating modeling with an application of FOREL and k-means algorithms. The modeling algorithm is realized in the Python 3 programming language. The course regularities of clustering processes in the region are revealed: 1) the clustering processes are intensifying, the production uniformity is increasing; 2) the increase of the level of production uniformity leads to the leveling of customer behavior; 3) the producers of high-differentiated production reduce the level of its differentiation or leave the cluster; 4) the stages of steady functioning are illustrative for clustering processes, their change is followed with arising of bifurcation points; 5) the activation of clustering processes in regional economy leads to the revenue increase of the cluster participants, each of producers and of consumers, and to the growth of synergetic effect values. These results testify the nonlinearity of processes of clustering and ambiguity of their effects. The following conclusions have been drawn: 1) a modeling of the processes of spontaneous clustering in regional economy has showed that they proceed not linearly, a steady progressive development is followed with leaps; 2) the clustering of regional economy leads to the growth of the efficiency indicators of activities of cluster-concerned entities; 3) initiation and activation of the clustering processes requires a certain environment

Agent modelling of cluster formation processes in regional economic systems

The subject matter of this research is the processes of the spontaneous clustering in the regional economy. The purpose is the development and approbation of the modeling algorithm of these processes. The hypothesis: the processes of spontaneous clustering in the social and economic environment are supposed to proceed not linearly, but intermittently. The following methods are applied: agent imitating modeling with an application of FOREL and k-means algorithms. The modeling algorithm is realized in the Python 3 programming language. The course regularities of clustering processes in the region are revealed: 1) the clustering processes are intensifying, the production uniformity is increasing; 2) the increase of the level of production uniformity leads to the leveling of customer behavior; 3) the producers of high-differentiated production reduce the level of its differentiation or leave the cluster; 4) the stages of steady functioning are illustrative for clustering processes, their change is followed with arising of bifurcation points; 5) the activation of clustering processes in regional economy leads to the revenue increase of the cluster participants, each of producers and of consumers, and to the growth of synergetic effect values. These results testify the nonlinearity of processes of clustering and ambiguity of their effects. The following conclusions have been drawn: 1) a modeling of the processes of spontaneous clustering in regional economy has showed that they proceed not linearly, a steady progressive development is followed with leaps; 2) the clustering of regional economy leads to the growth of the efficiency indicators of activities of cluster-concerned entities; 3) initiation and activation of the clustering processes requires a certain environment

Knowledge-based industry and regional growth

One of the most important but less understood phenomena in the beginning of the 21st century has been a shift toward knowledge-based economic activity in the comparative advantage of modern industrialized countries. Two broad trends has been observed in the global economy. That is, the output from the world's science and technology system has been growing rapidly and the nature of investment has been changed (MILLER, 1996). The relative proportions of physical and intangible investment have changed considerably with the relative increase of intangible investments since the 1980s. In addition, there has been increased complementarity between physical and intangible investments and more important role of high technology in both kinds of investment (MILLER, 1996). Even in the newly industrialized countries, the growth of technology intensive industries, the increase of R&D activities and the growth of the knowledge intensive producer services have been common feature in recent years. In this change of the structure of productive assets, the role of knowledge is well recognized as the most fundamental resources in recent years (OECD, 1996; WORLD BANK, 1998). The development of information and communication technology (ICT) and globalisation trend have promoted this shift toward knowledge-based economy

Managing stimulation of regional innovation subjects’ interaction in the digital economy

The reported study was funded by RFBR according to the research project No. 18-01000204_a, No. 16-07-00031_a, No. 18-07-00975_a.Purpose: The article is devoted to solving fundamental scientific problems in the scope of the development of forecasting modeling methods and evaluation of regional company’s innovative development parameters, synthesizing new methods of big data processing and intelligent analysis, as well as methods of knowledge eliciting and forecasting the dynamics of regional innovation developments through benchmarking. Design/Methodology/Approach: For regional economic development, it is required to identify the mechanisms that contribute to (or impede) the innovative economic development of the regions. The synergetic approach to management is based on the fact that there are multiple paths of IS development (scenarios with different probabilities), although it is necessary to reach the required attractor by meeting the management goals. Findings: The present research is focused on obtainment of new knowledge in creating a technique of multi-agent search, collection and processing of data on company’s innovative development indicators, models and methods of intelligent analysis of the collected data. Practical Implications: The author developed recommendations before starting the process of institutional changes in a specific regional innovation system. The article formulates recommendations on the implementation of institutional changes in the region taking into account the sociocultural characteristics of the region’s population. Originality/Value: It is the first time, when a complex of models and methods is based on the use of a convergent model of large data volumes processing is presented.peer-reviewe

Examining Neighbourhood Effects in Regional Inequalities of Hungary: a GIS-Based Approach from Topological Relations to Neighbourhood Heterogeneity

There is an increasing number of popular works, which explain regional inequalities of the economy and the society with spatial location. Techniques like spatial autocorrelation or spatial clustering became basic methods of mainstream examinations. These methods put geographical location, or more precisely the neighbourhood effects, in the focus of the researches. The typical research questions originate from Waldo Tobler’s classical law of geography, namely that “everything is related to everything else, but closer things are more closely related”. According to the research assumptions, the regions that are neighbours in geographical space are usually similar to each other also in socio-economic sense. For the examination of neighbourhood effects, GIS (Geographical Information Systems) may serve as a quite useful tool. By the application of GIS programmes, the topological relation of the examined objects can be straightforwardly defined. Additionally results of examinations with different methodological approach can be also easily compared. This paper, on the one hand, introduces both different methods of defining neighbourhood relations and the application of GIS in determining contiguity. On the other hand, it reflects how varied or same consequences can be drawn by the application of these techniques. In the analysis of neighbourhood effects, the most deterministic factors of the Hungarian regional inequalities are examined: the level of personal income and the unemployment rate. The examination points out where stable social and regional clusters were formed in Hungary, in the mirror of the different methodological approaches

Clusters Of Innovative Firms: Absorptive Capacity In Larger Networks?

Firms are often compared in terms of their resources or capabilities (resource based view of the firm (Barney, 1991, 1997) dynamic capabilities (Eisenhardt & Martin, 2000) and their performance on knowledge transfer (Argote & Ingram, 2000), absorptive capacity and relative absorptive capacity. Innovative firms are often located with other firms in clusters, with relationships and networks that have developed over time or in response to particular drivers and conditions. This paper investigates assumptions related to innovative firms and their environments and brings together research relevant to individual firms, notions of absorptive capacity and findings about clusters of firms. Firm relationships in cluster configurations are discussed and a research agenda proposed

Complex networks analysis in socioeconomic models

This chapter aims at reviewing complex networks models and methods that were either developed for or applied to socioeconomic issues, and pertinent to the theme of New Economic Geography. After an introduction to the foundations of the field of complex networks, the present summary adds insights on the statistical mechanical approach, and on the most relevant computational aspects for the treatment of these systems. As the most frequently used model for interacting agent-based systems, a brief description of the statistical mechanics of the classical Ising model on regular lattices, together with recent extensions of the same model on small-world Watts-Strogatz and scale-free Albert-Barabasi complex networks is included. Other sections of the chapter are devoted to applications of complex networks to economics, finance, spreading of innovations, and regional trade and developments. The chapter also reviews results involving applications of complex networks to other relevant socioeconomic issues, including results for opinion and citation networks. Finally, some avenues for future research are introduced before summarizing the main conclusions of the chapter.Comment: 39 pages, 185 references, (not final version of) a chapter prepared for Complexity and Geographical Economics - Topics and Tools, P. Commendatore, S.S. Kayam and I. Kubin Eds. (Springer, to be published

A class of spatial econometric methods in the empirical analysis of clusters of firms in the space

In this paper we aim at identifying stylized facts in order to suggest adequate models of spatial co–agglomeration of industries. We describe a class of spatial statistical methods to be used in the empirical analysis of spatial clusters. Compared to previous contributions using point pattern methods, the main innovation of the present paper is to consider clustering for bivariate (rather than univariate) distributions, which allows uncovering co–agglomeration and repulsion phenomena between the different industrial sectors. Furthermore we present the results of an empirical application of such methods to a set of European Patent Office (EPO) data and we produce a series of empirical evidences referred to the the pair–wise intra–sectoral spatial distribution of patents in Italy in the nineties. In this analysis we are able to identify some distinctive joint patterns of location between patents of different sectors and to propose some possible economic interpretations

Differentiation of Modernization Processes in EU Countries and in Poland in Time and Space - Non Classical View

The aim of this paper is a typology of EU-countries from the point of view of their modernization measures, a diagnostics and an evaluation of changes in a sectoral structure of the employment in EU-countries. Against this background there are exposed changes in Polish economy in the period 1997-2008. There were used the multidimensional comparative analysis of the sequence separation of homogenous objects subsets (cluster analysis and quick cluster) and the little known in Poland, but popular in the US, measurement technique of sectoral changes in time - the shift share-technique to illustrate and verify empirically the theory of three sectors by A. Fisher, C. Clark i J. Fourastiè, orientated to the evaluation of the modernization process of EU-economies