Knowledge transfer in a tourism destination: the effects of a network structure

Tourism destinations have a necessity to innovate to remain competitive in an increasingly global environment. A pre-requisite for innovation is the understanding of how destinations source, share and use knowledge. This conceptual paper examines the nature of networks and how their analysis can shed light upon the processes of knowledge sharing in destinations as they strive to innovate. The paper conceptualizes destinations as networks of connected organizations, both public and private, each of which can be considered as a destination stakeholder. In network theory they represent the nodes within the system. The paper shows how epidemic diffusion models can act as an analogy for knowledge communication and transfer within a destination network. These models can be combined with other approaches to network analysis to shed light on how destination networks operate, and how they can be optimized with policy intervention to deliver innovative and competitive destinations. The paper closes with a practical tourism example taken from the Italian destination of Elba. Using numerical simulations the case demonstrates how the Elba network can be optimized. Overall this paper demonstrates the considerable utility of network analysis for tourism in delivering destination competitiveness.Comment: 15 pages, 2 figures, 2 tables. Forthcoming in: The Service Industries Journal, vol. 30, n. 8, 2010. Special Issue on: Advances in service network analysis v2: addeded and corrected reference

The influence of topology and information diffusion on networked game dynamics

This thesis studies the influence of topology and information diffusion on the strategic interactions of agents in a population. It shows that there exists a reciprocal relationship between the topology, information diffusion and the strategic interactions of a population of players. In order to evaluate the influence of topology and information flow on networked game dynamics, strategic games are simulated on populations of players where the players are distributed in a non-homogeneous spatial arrangement. The initial component of this research consists of a study of evolution of the coordination of strategic players, where the topology or the structure of the population is shown to be critical in defining the coordination among the players. Next, the effect of network topology on the evolutionary stability of strategies is studied in detail. Based on the results obtained, it is shown that network topology plays a key role in determining the evolutionary stability of a particular strategy in a population of players. Then, the effect of network topology on the optimum placement of strategies is studied. Using genetic optimisation, it is shown that the placement of strategies in a spatially distributed population of players is crucial in maximising the collective payoff of the population. Exploring further the effect of network topology and information diffusion on networked games, the non-optimal or bounded rationality of players is modelled using topological and directed information flow of the network. Based on the topologically distributed bounded rationality model, it is shown that the scale-free and small-world networks emerge in randomly connected populations of sub-optimal players. Thus, the topological and information theoretic interpretations of bounded rationality suggest the topology, information diffusion and the strategic interactions of socio-economical structures are cyclically interdependent

On the institutional innovation process : EU regulation through an evolutionary lens

The focal point of this paper is the study of the process of emergence of novel institutions and the identification of factors that may influence the outcome of this process. We view inst accepted sets of rules that influence We consider regulations as endogenously emerging institutions that evolve in accordance to other socioeconomic factors and analyze the regulatory process at each of its stages adopting an evolutionary approach. Evidence shows that the regulatory process resembles the innovation process as it can be viewed as a process of knowledge accumulation and transmission that is facilitate empirically contextualized in the European political system, the detergents industry and specific regulations formed at European level. Data is drawn by secondary resour of public and private stakeholders participating in the processEvolutionary theory, Institutions, Regulation, Policy

The influence of topology and information diffusion on networked game dynamics

This thesis studies the influence of topology and information diffusion on the strategic interactions of agents in a population. It shows that there exists a reciprocal relationship between the topology, information diffusion and the strategic interactions of a population of players. In order to evaluate the influence of topology and information flow on networked game dynamics, strategic games are simulated on populations of players where the players are distributed in a non-homogeneous spatial arrangement. The initial component of this research consists of a study of evolution of the coordination of strategic players, where the topology or the structure of the population is shown to be critical in defining the coordination among the players. Next, the effect of network topology on the evolutionary stability of strategies is studied in detail. Based on the results obtained, it is shown that network topology plays a key role in determining the evolutionary stability of a particular strategy in a population of players. Then, the effect of network topology on the optimum placement of strategies is studied. Using genetic optimisation, it is shown that the placement of strategies in a spatially distributed population of players is crucial in maximising the collective payoff of the population. Exploring further the effect of network topology and information diffusion on networked games, the non-optimal or bounded rationality of players is modelled using topological and directed information flow of the network. Based on the topologically distributed bounded rationality model, it is shown that the scale-free and small-world networks emerge in randomly connected populations of sub-optimal players. Thus, the topological and information theoretic interpretations of bounded rationality suggest the topology, information diffusion and the strategic interactions of socio-economical structures are cyclically interdependent

A knowledge hub to enhance the learning processes of an industrial cluster

Industrial clusters have been defined as ?networks of production of strongly interdependent firms (including specialised suppliers), knowledge producing agents (universities, research institutes, engineering companies), institutions (brokers, consultants), linked to each other in a value adding production chain? (OECD Focus Group, 1999). The industrial clusters distinctive mode of production is specialisation, based on a sophisticated division of labour, that leads to interlinked activities and need for cooperation, with the consequent emergence of communities of practice (CoPs). CoPs are here conceived as groups of people and/or organisations bound together by shared expertise and propensity towards a joint work (Wenger and Suyden, 1999). Cooperation needs closeness for just-in-time delivery, for communication, for the exchange of knowledge, especially in its tacit form. Indeed the knowledge exchanges between the CoPs specialised actors, in geographical proximity, lead to spillovers and synergies. In the digital economy landscape, the use of collaborative technologies, such as shared repositories, chat rooms and videoconferences can, when appropriately used, have a positive impact on the development of the CoP exchanges process of codified knowledge. On the other end, systems for the individuals profile management, e-learning platforms and intelligent agents can trigger also some socialisation mechanisms of tacit knowledge. In this perspective, we have set-up a model of a Knowledge Hub (KH), driven by the Information and Communication Technologies (ICT-driven), that enables the knowledge exchanges of a CoP. In order to present the model, the paper is organised in the following logical steps: - an overview of the most seminal and consolidated approaches to CoPs; - a description of the KH model, ICT-driven, conceived as a booster of the knowledge exchanges of a CoP, that adds to the economic benefits coming from geographical proximity, the advantages coming from organizational proximity, based on the ICTs; - a discussion of some preliminary results that we are obtaining during the implementation of the model.

Intermediate Institutions for Interactive Learning Processes in a Governance Perspective: the Case of Aeronautic Industry in Campania Region.

The present paper presents the results of the empirical analysis on fifteen enterprises and twenty no-industrial organizations involved at different level in the Aeronautical Cluster in the Campania Region. Information and data on the selected sample are colleted both by a study of the industrial sector, and also by suitable questionnaires and interviews, that the authors have submitted to the entrepreneurs and to the top managers of either the enterprises or the no-industrial organizations. The authors have focalized their study by applying the SWOT analysis on the following issues: • the cluster’s structure by analysing the relational skill developed by single actors of the cluster and by their impact on the innovation capacity of the enterprises; • the effectiveness of cluster’s governance strategies and how different actors actually participate to the local development processes of the aeronautical industrial sector. On these bases the authors wanted to deduce possible policy options for different kind of actors to optimize the cluster’s governance. Particularly they will describe in the present paper some indications to: 1) the SME’s that present strong relations with customers but low integration with large part of the others actors, i.e. with no-customers enterprises; 2) the large enterprises related to the industrial policies and to the suppliers' governance; 3) the policy makers at local level and the intermediate institutions for a better support of the local enterprises. In fact, the research results are based on the conscientious awareness that the analyzed sector is at a critical point, for which it is necessary that all the actors involved put together their efforts in order to steer and to direct the development process, both by identifying participative mechanisms at local level and also by strengthening those exogenous elements which are able to promote local development. Obviously only part of the criticisms can be solved at local and national level and some of them can be solved only partially. This observation opens the question of policy at the international level which can be determinate only with a more exhaustive integration into transnational networks. The research described in the present paper has been undertaken within the framework of the project: “IKINET – International Knowledge and Innovation Network†(EU FP6, N° CIT2-CT-2004-506242).

Revisiting the Gaia hypothesis: Maximum Entropy, Kauffman's 'Fourth Law' and physiosemeiosis

Recently, Kleidon suggested a restatement of the Gaia hypothesis based on Maximum Entropy approaches to the Earth system. Refuting conceptions of Gaia as a homeostatic system, Gaia is seen as a non-equilibrium thermodynamic system which continuously moves away from equilibrium, driven by maximum entropy production which materializes in hierarchically coupled mechanisms of energetic flows via dissipation and physical work. I propose to relate this view with Kauffman's 'Fourth Law of Thermodynamics', which I interprete as a proposition about the accumulation of information in evolutionary processes. Then, beyond its use in the Kleidon model, the concept of physical work is expanded to including work directed at the capacity to work: I offer a twofold specification of Kauffman's concept of an 'autonomous agent', one as a 'self-referential heat engine', and the other in terms of physiosemeiosis, which is a naturalized application of Peirce's theory of signs emerging from recent biosemiotic research. I argue that the conjunction of these three theoretical sources, Maximum Entropy, Kauffman's Fourth Law, and physiosemeiosis, allows to show that the Kleidon restatement of the Gaia hypothesis is equivalent to the proposition that the biosphere is a system of generating, processing and storing information, thus directly treating information as a physical phenomenon. I substantiate this argument by proposing a more detailed analysis of the notion of hierarchy in the Kleidon model. In this view, there is a fundamental ontological continuity between the biological processes and the human economy, as both are seen as information processing and entropy producing systems. As with other previous transitions in evolution, the human economy leverages the mechanisms by which Gaia moves further away from equilibrium. This implies that information and natural resources or energy are not substitutes, i.e. the knowledge economy continues to build on the same physical principles as the biosphere, with energy and information being two aspects of the same underlying physical process. --Gaia,non-equilibrium systems,Fourth Law,work,Peirce,triadism,hierarchy,economic growth

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