Policy Advice Derived from Simulation Models

When advising policy we face the fundamental problem that economic processes are uncertain. Consequently, policy can err. In this paper we show how the use of simulation models can reduce policy errors by inferring empirically reliable and meaningful statements about economic processes. We suggest that policy is best based on so-called abductive simulation models, which help to better understand how policy measures can influence economic processes. We show that abductive simulation models use a combination of theoretical and empirical analysis based on different data sets. By way of example we show what policy can learn with the help of abductive simulation models, namely how policy measures can influence the emergence of a regional cluster.Policy Advice, Simulation Models, Uncertainty, Methodology

Policy Advice Derived From Simulation Models

When advising policy we face the fundamental problem that economic processes are connected with uncertainty and thus policy can err. In this paper we show how the use of simulation models can reduce policy errors. We suggest that policy is best based on so-called abductive simulation models, which help to better understand how policy measures can influence economic processes. We show that abductive simulation models use a combination of theoretical and empirical analysis based on different data sets. This helps inferring empirically reliable and meaningful statements about how policy measures influence economic processes. By way of example we show how research subsidies by the government influence the likelihood that a regional cluster emerges.Policy Advice, Simulation Models, Uncertainty, Methodology

Standard-Setting and Knowledge Dynamics in Innovation Clusters

Extensive research has been conducted on how firms and regions take advantage of spatially concentrated assets, and also why history matters to regional specialisation patterns. In brief, it seems that innovation clusters as a distinctive regional entity in international business and the geography of innovation are of increasing importance in STI policy, innovation systems and competitiveness studies. Recently, more and more research has contributed to an evolutionary perspective on collaboration in clusters. Nonetheless, the field of cluster or regional innovation systems remains a multidisciplinary field where the state of the art is determined by the individual perspective (key concepts could, for example, be industrial districts, innovative clusters with reference to OECD, regional knowledge production, milieus & sticky knowledge, regional lock-ins & path dependencies, learning regions or sectoral innovation systems). According to our analysis, the research gap lies in both quantitative, comparative surveys and in-depth concepts of knowledge dynamics and cluster evolution. Therefore this paper emphasises the unchallenged in-depth characteristics of knowledge utilisation within a cluster's collaborative innovation activities. More precisely, it deals with knowledge dynamics in terms of matching different agents´ knowledge stocks via knowledge flows, common technology specification (standard-setting), and knowledge spillovers. The means of open innovation and system boundaries for spatially concentrated agents in terms of knowledge opportunities and the capabilities of each agent await clarification. Therefore, our study conceptualises the interplay between firm- and cluster-level activities and externalities for knowledge accumulation but also for the specification of technology. It remains particularly unclear how, why and by whom knowledge is aligned and ascribed to a specific sectoral innovation system. Empirically, this study contributes with several descriptive calculations of indices, e.g. knowledge stocks, GINI coefficients, Herfindahl indices, and Revealed Patent Advantage (RPA), which clearly underline a high spatial concentration of both mechanical engineering and biotechnology within a European NUTS2 sample for the last two decades. Conceptually, our paper matches the geography of innovation literature, innovation system theory, and new ideas related to the economics of standards. Therefore, it sheds light on the interplay between knowledge flows and externalities of cluster-specific populations and the agents' use of such knowledge, which is concentrated in space. We find that knowledge creation and standard-setting are cross-fertilising each other: although the spatial concentration of assets and high-skilled labour provides new opportunities to the firm, each firm's knowledge stocks need to be contextualised. The context in terms of 'use case' and 'knowledge biography' makes technologies (as represented in knowledge stocks) available for collaboration, but also clarifies relevance and ownership, in particular intellectual property concerns. Owing to this approach we propose a conceptualisation which contains both areas with inter- and intra-cluster focus. This proposal additionally concludes that spatial and technological proximity benefits standard-setting in high-tech and low-tech industries in very different ways. More precisely, the versatile tension between knowledge stocks, their evolution, and technical specification & implementation requires the conceptualisation and analysis of a non-linear process of standard-setting. Particularly, the use case of technologies is essential. Related to this approach, clusters strongly support the establishment of technology use cases in embryonic high-tech industries. Low-tech industries in contrast rather depend on approved knowledge stocks, whose dynamics provide better and fast accessible knowledge inputs within low-tech clusters.innovation clusters, standard-setting, knowledge externalities and flows, knowledge alignment, mechanical engineering, biotechnology

Horizontal and Vertical Multiple Implementations in a Model of Industrial Districts

In this paper we discuss strategies concerning the implementation of an agent-based simulation of complex phenomena. The model we consider accounts for population decomposition and interaction in industrial districts. The approach we follow is twofold: on one hand, we implement progressively more complex models using different approaches (vertical multiple implementations); on the other hand, we replicate the agent-based simulation with different implementations using jESOF, JAS and plain C++ (horizontal multiple implementations). By using both different implementation approaches and a multiple implementation strategy, we highlight the benefits that arise when the same model is implemented on radically different simulation environments, comparing the advantages of multiple modeling implementations. Our findings provide some important suggestions in terms of model validation, showing how models of complex systems tend to be extremely sensitive to implementation details. Finally we point out how statistical techniques may be necessary when comparing different platform implementations of a single model.Replication of Models; Model Validation; Agent-Based Simulation

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).

Economic Performance, Inter-Firm Relations and Local Institutional Engineering in a Computational Prototype of Industrial Districts

Industrial districts can be conceived as complex systems characterised by a network of interactions amongst heterogeneous, localised, functionally, integrated and complementary firms. In a previous paper, we have introduced an industrial district computational prototype, showing that the economic performance of an industrial district proceeds to the form through which firms interact and co-ordinate each others. In this paper, we use such computational framework to experiment different options of local institutional engineering', trying to understand how specific supporting institutions' could perform macro-collective activities, such as, i.e., technology research, transfer and information, improving the technological adaptation of firms. Is a district more than a simple aggregation of localised firms? What can explain the economic performance of firms localised into the same space? Could some options of 'local institutional engineering, improve the performance of a district? Could such options set aside the problem of how firms dynamically interact? These are questions explored in this paper

Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science

The paper deals with the use of empirical data in social science agent-based models. Agent-based models are too often viewed just as highly abstract thought experiments conducted in artificial worlds, in which the purpose is to generate and not to test theoretical hypotheses in an empirical way. On the contrary, they should be viewed as models that need to be embedded into empirical data both to allow the calibration and the validation of their findings. As a consequence, the search for strategies to find and extract data from reality, and integrate agent-based models with other traditional empirical social science methods, such as qualitative, quantitative, experimental and participatory methods, becomes a fundamental step of the modelling process. The paper argues that the characteristics of the empirical target matter. According to characteristics of the target, ABMs can be differentiated into case-based models, typifications and theoretical abstractions. These differences pose different challenges for empirical data gathering, and imply the use of different validation strategies.Agent-Based Models, Empirical Calibration and Validation, Taxanomy of Models

Standard-setting and knowledge dynamics in innovation clusters

Extensive research has been conducted on how firms and regions take advantage of spatially concentrated assets, and also why history matters to regional specialisation patterns. In brief, it seems that innovation clusters as a distinctive regional entity in international business and the geography of innovation are of increasing importance in STI policy, innovation systems and competitiveness studies. Recently, more and more research has contributed to an evolutionary perspective on collaboration in clusters. Nonetheless, the field of cluster or regional innovation systems remains a multidisciplinary field where the state of the art is determined by the individual perspective (key concepts could, for example, be industrial districts, innovative clusters with reference to OECD, regional knowledge production, milieus & sticky knowledge, regional lock-ins & path dependencies, learning regions or sectoral innovation systems). According to our analysis, the research gap lies in both quantitative, comparative surveys and in-depth concepts of knowledge dynamics and cluster evolution. Therefore this paper emphasises the unchallenged in-depth characteristics of knowledge utilisation within a cluster?s collaborative innovation activities. More precisely, it deals with knowledge dynamics in terms of matching different agents´ knowledge stocks via knowledge flows, common technology specification (standard-setting), and knowledge spillovers. The means of open innovation and system boundaries for spatially concentrated agents in terms of knowledge opportunities and the capabilities of each agent await clarification. Therefore, our study conceptualises the interplay between firm- and cluster-level activities and externalities for knowledge accumulation but also for the specification of technology. It remains particularly unclear how, why and by whom knowledge is aligned and ascribed to a specific sectoral innovation system. Empirically, this study contributes with several descriptive calculations of indices, e.g. knowledge stocks, GINI coefficients, Herfindahl indices, and Revealed Patent Advantage (RPA), which clearly underline a high spatial concentration of both mechanical engineering and biotechnology within a European NUTS2 sample for the last two decades. Conceptually, our paper matches the geography of innovation literature, innovation system theory, and new ideas related to the economics of standards. Therefore, it sheds light on the interplay between knowledge flows and externalities of cluster-specific populations and the agents? use of such knowledge, which is concentrated in space. We find that knowledge creation and standard-setting are cross-fertilising each other: although the spatial concentration of assets and high-skilled labour provides new opportunities to the firm, each firm?s knowledge stocks.need to be contextualised. The context in terms of ?use case? and ?knowledge biography? makes technologies (as represented in knowledge stocks) available for collaboration, but also clarifies relevance and ownership, in particular intellectual property concerns. Owing to this approach we propose a conceptualisation which contains both areas with inter- and intra-cluster focus. This proposal additionally concludes that spatial and technological proximity benefits standard-setting in high-tech and low-tech industries in very different ways. More precisely, the versatile tension between knowledge stocks, their evolution, and technical specification & implementation requires the conceptualisation and analysis of a non-linear process of standard-setting. Particularly, the use case of technologies is essential. Related to this approach, clusters strongly support the establishment of technology use cases in embryonic high-tech industries. Low-tech industries in contrast rather depend on approved knowledge stocks, whose dynamics provide better and fast accessible knowledge inputs within low-tech clusters

Improvement of acoustic emission technology for stress corrosion cracking

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonThis thesis investigates the advancement of Acoustic emission (AE) monitoring techniques and analysis methods that could be applied in the field of Structural Health Monitoring (SHM), with an emphasis on the use of advanced AE techniques to detect and locate damage and their application on the monitoring of corrosion and Stress corrosion cracking (SCC) in complex metallic structures. The work was divided into three main areas of research, which are an investigation into using FE (Finite Element) generated delta-T mapping to locate experimental AE signals on complex structures, source location of AE signals generated by corrosion and an experimental investigation into SCC damage locations on a metallic specimen.Lloyd's Register Foundation, Brunel University London and the National Structural Integrity Research Centre (NSIRC