Strategic Analysis in the Public Sector Using Semantic Web Technologies

Author:

Lorvão Antunes António1ORCID,Barateiro José2ORCID,Cardoso Elsa3ORCID

Affiliation:

1. LNEC - National Laboratory for Civil Engineering, Lisbon, Portugal and ISCTE - Instituto Universitário de Lisboa, Lisbon, Portugal

2. Faculdade de Ciência e Tecnologia, University of Algarve, Faro, Portugal

3. ISCTE - Instituto Universitário de Lisboa, Lisboa, Portugal and CIES-Iscte, Lisboa, Portugal

Abstract

This article addresses the complex challenges that public organizations face in designing, implementing, and evaluating their strategies, where public interest and regulatory compliance often intertwine with strategic objectives. This research investigates the application of ontologies in the field of public sector strategy management to enhance the capacity of organizations to make informed data-driven decisions, efficiently allocate resources, and effectively navigate the intricate landscape of the public sector. The LNEC - National Laboratory for Civil Engineering’s strategy is used as an exploratory case study. Semantic web technologies are used to perform strategy analysis, including validating the strategy formulation and supporting the strategy execution by assessing performance indicators, verifying the design of cause-and-effect relationships between strategic objectives, and monitoring and empirically validating these relationships. The increased interoperability of these technologies enables information sharing across systems and organizations. Following the strategy analysis, recommendations are provided, leading to a more robust and data-driven strategic management approach, enabling accurate, traceable, and continuous monitoring of an organization’s strategy. Theoretical and practical implications are discussed, along with limitations and future work. This research offers a blueprint for public sector organizations seeking to optimize their strategies, foster transparency, and deliver more effective services to the public they serve.

Funder

Portuguese Foundation for Science and Technology

Publisher

Association for Computing Machinery (ACM)

Reference44 articles.

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