The present study maps and classifies industrial districts in Portugal, identifying the features of specialization and the current capacity of industrialization. It employs an adaptation of the algorithm developed by Canello and Pavone (2016) in 308 Portuguese municipalities based on six phases....

The increasing turbulence of the economic environment leads to changes in the business style, and adapting to this new style requires a cluster approach. In this sense, the goal of the research relates to determining the impact of the cluster internal and external interaction on innovative...

Purpose - This paper aims to address research gaps with regard to the relationship between market orientation and marketing performance when small- and medium-sized enterprises (SMEs) are located within a service cluster. The three main objectives of this research are to determine the effect...

As many establishments are embedded in regional economic structures, their competitive advantages also depend on local conditions. In many regions, these are shaped by regional clusters. Hence, for more than two decades, clusters have attracted a great deal of attention from regional economics...

The processing and transformation of natural resources into completed and semi-finished products is the primary function of industry in each nation's economy. There is no denying the significance of industry and sectoral classification of the economy, but the slow development and extension of...

High-growth firms have been widely studied in advanced countries, but little is known about such stellar performers in Africa. Using establishment-level data from Ethiopia, this paper finds that the incidence of high-growth firms stands at an average of 7 percent, a figure comparable to that of...

Studies on open innovation (OI) have highlighted the importance of inter-organizational knowledge networks. However, little is known about OI networks established by family firms, and their roles in such knowledge networks. By focusing on one of the most important Italian footwear clusters, this...

In machine learning and data science literature, clustering is the task of dividing the observations (data points) into several categories in such a way that data points falling into one group are being dissimilar than the data points falling to the other groups such that the variation within a...

The ordinary spectrum is restricted in its applications, since it is based on the second-order moments (auto- and cross-covariances). Alternative approaches to spectrum analysis have been investigated based on other measures of dependence. One such approach was developed for univariate time...