The Identification of Industrial Clusters – Methodical Aspects in a Multidimensional Framework for Cluster Identification

We use a combination of measures of spatial concentration, qualitative input-output analysis and innovation interaction matrices to identify the horizontal and vertical dimension of industrial clusters in Saxony in 2005. We describe the spatial allocation of the industrial clusters and show possibilities of vertical interaction of clusters based on intermediate goods flows. With the help of region and sector-specific knowledge interaction matrices we are able to show that a sole focus on intermediate goods flows limits the identification of innovative actors in industrial clusters, as knowledge flows and intermediate goods flows do not show any major overlaps.industrial clusters, qualitative input-output-analysis, innovation interaction matrix

Clusters: Determinants and Effects

This memorandum surveys the empirical literature about the effects and determinants of clusters. It finds that clusters generally lead to more innovations, knowledge spillovers, faster diffusion of technologies and knowledge, and competitive advantages. The presence of a skilled labour force is the most important determinant for clusters. Other important factors for the existence of clusters are economies of scale and scope, knowledge spillovers, and competition from foreign competitors. Clusters appear to be especially important for small firms. Surprisingly, there is relatively little cooperation between these firms. Even though clusters are generally located near a knowledge institution, there is also relatively little cooperation between the cluster and the knowledge institution. Since clusters need skilled labour and competition, a good cluster policy may be no cluster policy at all. Instead, the government should look after an education system that produces a highly educated and skilled workforce, and stimulate competition by (further) opening markets to foreign competitors.

An Application of Clustering Analysis to International Private Indebtedness

This paper presents a procedure for clustering analysis that combines Kohone’s Self organizing Feature Map (SOFM) and statistical schemes. The idea is to cluster the data in two stages: run SOFM and then minimize the segmentation dispersion. The advantages of proposed procedure will be illustrated through a synthetic experiment and a real macroeconomic problem. The procedure is then used to explore the relationship between private indebtedness and some macroeconomic variables commonly used to measure macroeconomic performance. The experiences of thirty-nine countries in the early nineties are analyzed. The procedure outperformed others clustering techniques in the job of identifying consistent groups of countries from the economic and statistical viewpoints. It found out similarities in different countries concerning their respective levels of private indebtedness when added to well accepted parameters to measure macroeconomic performance.Vector quantization, Clustering, Self-Organizing Feature Map,Macroeconomic Performance, Private Indebtedness.

A cross impact methodology for the assessment of US telecommunications system with application to fiber optics development, volume 1

A cross impact model of the U.S. telecommunications system was developed. It was necessary to prepare forecasts of the major segments of the telecommunications system, such as satellites, telephone, TV, CATV, radio broadcasting, etc. In addition, forecasts were prepared of the traffic generated by a variety of new or expanded services, such as electronic check clearing and point of sale electronic funds transfer. Finally, the interactions among the forecasts were estimated (the cross impact). Both the forecasts and the cross impacts were used as inputs to the cross impact model, which could then be used to stimulate the future growth of the entire U.S. telecommunications system. By varying the inputs, technology changes or policy decisions with regard to any segment of the system could be evaluated in the context of the remainder of the system. To illustrate the operation of the model, a specific study was made of the deployment of fiber optics throughout the telecommunications system

Data mining for detecting Bitcoin Ponzi schemes

Soon after its introduction in 2009, Bitcoin has been adopted by cyber-criminals, which rely on its pseudonymity to implement virtually untraceable scams. One of the typical scams that operate on Bitcoin are the so-called Ponzi schemes. These are fraudulent investments which repay users with the funds invested by new users that join the scheme, and implode when it is no longer possible to find new investments. Despite being illegal in many countries, Ponzi schemes are now proliferating on Bitcoin, and they keep alluring new victims, who are plundered of millions of dollars. We apply data mining techniques to detect Bitcoin addresses related to Ponzi schemes. Our starting point is a dataset of features of real-world Ponzi schemes, that we construct by analysing, on the Bitcoin blockchain, the transactions used to perform the scams. We use this dataset to experiment with various machine learning algorithms, and we assess their effectiveness through standard validation protocols and performance metrics. The best of the classifiers we have experimented can identify most of the Ponzi schemes in the dataset, with a low number of false positives

ECONOMIC VALUATION ON CLIMATE CHANGE IN THE MARINE FISHERIES IN CILACAP, CENTRAL JAVA

The objective of this study is to estimate the impact of climate change in the marine capture fisheries in Cilacap, Central Java. Also to formulate the adaptation and mitigation strategies on the impacts of climate change. Data collection was done through multi-stages sampling. Samples of respondents were: 73 marine-fisher respondents, 43 collector respondents, and 100 consumer respondents, which were analyzed by descriptive statistics. In the aspect of production, there was a decrease in catch which caused severe losses in 26 respondents, an increase in length of trip which was vary from 1 day to 7 days, and changes in fishers spending, such as: change in cost of fuel, change in food & lodging cost, and change in productivity. Lack of production has led to a decrease in fish-stocks. Therefore availability and sustainability of fish-stock in the aspect of distribution became questionable, which influenced availability and affordability of fish in market (Aspect of consumption). Thus, enhancing the performance of extension institution was needed to anticipate the impact of climate change in marine fisheries sector. An ideal extension institution was made to enhance the performance of extension institution was made in order to estimate transaction cost of the policy. The result has shown the amount of information cost, policing cost and operational & maintenance cost to establish a successful program