To read this content please select one of the options below:

Leveraging knowledge discovery and knowledge visualization to define the “inner areas”: an application to an Italian province

Valentino Moretto (Links Management and Technology SpA, Lecce, Italy and is PhD student at the Department of Engineering for Innovation, University of Salento, Leece, Italy)
Gianluca Elia (Department of Engineering for Innovation, Universita del Salento, Lecce, Italy)
Gianpaolo Ghiani (Department of Engineering for Innovation, Universita del Salento, Lecce, Italy)

Journal of Knowledge Management

ISSN: 1367-3270

Article publication date: 1 February 2022

Issue publication date: 2 November 2022

386

Abstract

Purpose

Starting from a critical analysis of the main criteria currently used to identify marginal areas, this paper aims to propose a new classification model of such territories by leveraging knowledge discovery approaches and knowledge visualization techniques, which represent a fundamental pillar in the knowledge-based urban development process.

Design/methodology/approach

The methodology adopted in this study relies on the design science research, which includes five steps: problem identification, objective definition, solution design and development, demonstration and evaluation.

Findings

Results demonstrate how to exploit knowledge discovery and visualization to obtain multiple mappings of inner areas, in the aim to identify good practices and optimize resources to set up more effective territorial development strategies and plans. The proposed approach overcomes the traditional way adopted to map inner areas that uses a single indicator (i.e. the distance between a municipality and the nearest pole where it is possible to access to education, health and transportation services) and leverages seven groups of indicators that represent the distinguishing features of territories (territorial capital, social costs, citizenship, geo-demography, economy, innovation and sustainable development).

Research limitations/implications

The proposed model could be enriched by new variables, whose value can be collected by official sources and stakeholders engaged to provide both structured and unstructured data. Also, another enhancement could be the development of a cross-algorithms comparison that may reveal useful to suggest which algorithm can better suit the needs of policy makers or practitioners.

Practical implications

This study sets the ground for proposing a decision support tool that policy makers can use to classify in a new way the inner areas, thus overcoming the current approach and leveraging the distinguishing features of territories.

Originality/value

This study shows how the availability of distributed knowledge sources, the modern knowledge management techniques and the emerging digital technologies can provide new opportunities for the governance of a city or territory, thus revitalizing the domain of knowledge-based urban development.

Keywords

Citation

Moretto, V., Elia, G. and Ghiani, G. (2022), "Leveraging knowledge discovery and knowledge visualization to define the “inner areas”: an application to an Italian province", Journal of Knowledge Management, Vol. 26 No. 10, pp. 2743-2771. https://doi.org/10.1108/JKM-10-2021-0773

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

Related articles