Lamieri, Marco and Ietri, Daniele (2004): Innovation creation and diffusion in a social network: an agent based approach.
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Market is not only the result of the behaviour of agents, as we can find other forms of contact and communication. Many of them are determined by proximity conditions in some kind of space: in this paper we pay a particular attention to relational space, that is the space determined by the relationships between individuals. The paper starts from a brief account on theoretical and empirical literature on social networks. Social networks represent people and their relationships as networks, in which individuals are nodes and the relationships between them are ties. In particular, graph theory is used in literature in order to demonstrate some properties of social networks summarised in the concept of Small Worlds. The concept may be used to explain how some phenomena involving relations among agents have effects on multiple different geographical scales, involving both the local and the global scale. The empirical section of the paper is introduced by a brief summary of simulation techniques in social science and economics as a way to investigate complexity. The model investigates the dynamics of a population of firms (potential innovators) and consumers interacting in a space defined as a social network. Consumers are represented in the model in order to create a competitive environment pushing enterprises into innovative process (we refer to Schumpeter’s definition): from interaction between consumers and firms innovation emerges as a relational good.
|Item Type:||MPRA Paper|
|Original Title:||Innovation creation and diffusion in a social network: an agent based approach|
|Keywords:||Innovation; small world; computational economics; network; complexity|
|Subjects:||L - Industrial Organization > L2 - Firm Objectives, Organization, and Behavior > L20 - General
L - Industrial Organization > L1 - Market Structure, Firm Strategy, and Market Performance > L10 - General
C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling
O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes
D - Microeconomics > D2 - Production and Organizations > D24 - Production ; Cost ; Capital ; Capital, Total Factor, and Multifactor Productivity ; Capacity
|Depositing User:||Marco Lamieri|
|Date Deposited:||13. Oct 2006|
|Last Modified:||16. Feb 2013 08:09|
Cowan, R., & Jonard, N. (1999). Network structure and the diffusion of knowledge. MERIT Research Memorandum(99-028). Gilbert, N., & Terna, P. (2000). How to build and use agent-based models in social science. Mind & Society, 1, 57-72. Hayek, F. A. (1937). Economics and knowledge. Economica(IV). Langton, C. (1992, agosto). Vita artificiale. Sistemi Intelligenti, IV (2), 189-245. Parisi, D. (2001). Simulazioni. la realt`a rifatta nel computer. Il Mulino. Polanyi, M. (1967). The tacit dimension. Routledge and Kegan, London. Schumpeter, J. (1934). The theory of economic development: An inquiry into profits, capital, credit, interest and the business cycle. Harvard University Press, Cambridge Mass. Tesfatsion, L. (2002). Agent-based computational economics: Growing economies from the bottom up. ISU Economics Working Paper(1). Watts, D. J. (1998). Small worlds: The dynamics of networks between order and randomness. Princeton Studies in Complexity.