An AI-based decision support system for designing Knowledge-Based Development strategies

  • Authors:

  • Emmanouil Ergazakis;Kostas Ergazakis;Kostas Metaxiotis;E. Bellos;V. Leopoulos

  • Affiliations:

  • National Technical University of Athens, 9, Iroon Polytechniou Street, Zografou 15773, Athens, Greece.;National Technical University of Athens, 9, Iroon Polytechniou Street, Zografou 15773, Athens, Greece.;National Technical University of Athens, 9, Iroon Polytechniou Street, Zografou 15773, Athens, Greece.;National Technical University of Athens, 9, Iroon Polytechniou Street, Zografou 15773, Athens, Greece.;National Technical University of Athens, 9, Iroon Polytechniou Street, Zografou 15773, Athens, Greece

  • Venue:
  • International Journal of Intelligent Systems Technologies and Applications
  • Year:
  • 2008

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Abstract

In the new era of knowledge economy, knowledge and the processesto generate and manage it are considered as the most valuableassets of an organisation in the competitive business environment.Over the last years, intensive discussions have taken place aboutthe importance of Knowledge Management for the whole society,except from the business world. Today, there is a consensus amongresearcher's and practitioner's communities that the challengesfacing modern societies, call for development strategies that areknowledge-based. In this context, the theme of Knowledge Cities(KCs) came to the front. The review of literature reveals that theprocess of designing Knowledge-Based Development (KBD) strategiesfor KCs is complex and not appropriately supported by decisionsupport methodologies and/or intelligent systems. In this paper,the authors, based on a previously presented methodology for theformulation of a KBD strategy for KCs, propose an AI-based decisionsupport system for designing such strategies, by selecting andprioritising the most appropriate interventions and actions. Thesystem consists of two sub-systems: the first (developed using thetechnology of Expert Systems) assess the necessity of a particularintervention and proposes its most appropriate form. The secondprioritises the selected interventions based on Multi-CriteriaDecision Making. The authors also present the successfulpreliminary results of the systems pilot application to a Greekmunicipality.