Autori: Manlio Del Giudice,Maria Rosaria Della Peruta, Vincenzo Maggioni

Articolo in rivista

Titolo rivista: Journal of Knowledge Management

Volume: Vol. 19 No. 3, pp. 611-625

Editore: Emerald Group Publishing Limited




This paper aims to investigate, inside the private sector of transport, a model for the diffusion of knowledge-sharing technologies with non-uniform internal influence that has been developed by Easingwood et al. (1983).


The authors performed an empirical evaluation of the performances of the model by Easingwood et al. (1983) by analyzing data gathered from almost 230 taxi drivers joining two of the biggest taxi brokers operating in the Southern Italian city of Naples.


Such an analysis reveals that the model by Easingwood et al. (1983) provides an excellent agreement with the empirical data and allows to obtain interesting predictions on the future evolution of the sector performances in terms of increasing use of knowledge-sharing technologies within the taxi drivers’ community of practice (CoP).

Research limitations/implications

In particular, the authors show that a unique solution always exists, which is defined on the whole (positive) set of times and, in the long run, tends to a steady-state equilibrium. A first limit of the present research is certainly the use of a sample restricted to the taxi companies from only one city: future investigations should consider a larger sample by interviewing taxi companies from multiple regions as well. Another limit is that the model performed does not take into account all the factors influencing the diffusion of knowledge-sharing technologies within the CoP. Finally, the research design is not considering the impact of the diffusion of knowledge-sharing technologies on the customer relationship management.


The research shows the application of a valid model both for evaluating the diffusion of technologies for sharing knowledge within a CoP and for estimating its development trend. It represents the first original study in Italy that empirically investigates the diffusion of technological innovations for the knowledge management in an industry typically dominated by tacit codes of knowledge-sharing: the taxi companies.

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