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The aim of this paper is to provide a new and simple approach to the empirical assessment of the internal efficiency of national regulatory authorities (NRAs) based on outcomes on regulated markets. Moreover, in order to illustrate this approach, the authors apply the proposed methodology to telecommunications.

First, this paper defines the production process of a NRA to identify correctly the inputs and the outputs of regulatory activity. Second, with reference to the telecommunications sector this paper provides estimates for the inputs and output identified. Third, by treating each NRA as a decision making unit (DMU) this paper carries out a data envelopment analysis (DEA) used in conjunction with a smoothed bootstrap technique.

This paper provides evidences that NRAs operating in new accession countries look more efficient in pursuing dynamic efficiency goals than (more experienced) NRAs operating in other European countries, while they are less efficient when the regulatory outcomes are measured in terms of retail efficiency.

The lack of data on NRAs' personnel and budget requires a cautious discussion of the results.

This paper enables one to get a better understanding of the effectiveness of different regulatory measures.

Once a measure of productive (internal) efficiency of a regulatory body has been obtained, it is then possible to embed this information in a more general analysis aimed at disentangling the effectiveness of regulatory measures from the ability (efficiency) of NRAs in putting them into force.

The evaluation of regulators' productive efficiency, as well as the identification of its determinants, has been almost completely neglected in the literature. With this paper we start to fill this gap.

The purpose of this paper is to present a framework for cultivating virtual communities of practice in distributed environments. The framework is based on the integration of knowledge artifacts and wearable technologies.

The proposed knowledge artifact is based on the correlation between conceptual and computational tools for the representation of different kinds of knowledge.

In this way, it is possible to make deeper the collaboration between knowledge seekers and contributors within the community, given that seekers and contributors share, at least in part, design choices at the knowledge modeling level.

A practical application of the framework has been described, to show its originality with respect to traditional knowledge management systems. In particular, it has been demonstrated how lurking phenomenon inside communities of practice can be significantly reduced. To this aim, opportune indexes have been defined from existing ones in literature.