ITC implementation in Romanian local public entities
The paper aims to identify the usefulness of the ITC in local public entities in order to get it closer to the civil society needs. The main objectives of the paper are the following: 1. to identify what kind of public financial and social information is useful for civil society; 2. to demonstrate in what extent the ITC development and e-disclosure is useful for the civil society. The main problem of the Romanian civil society is the lack of information access. The research uses an empirical approach through a quantitative methodology, based on surveys, to test the usefulness of the ITC implementation in local public entities for civil society. The methods choose in this paper are reliable for this empirical study that tries to identify at a national level the problems that could be solved with a better connection between local public entities and civil society through the medium of ITC. The results of the paper present the identification of civil society disclosure needs; measure the ITC usefulness for civil society needs. The key contribution of the paper is to identify the civil society needs regarding e-disclosure by the local public entities using a complete database of all the local public entities that have a site on the internet. Taking care of the civil society needs, the local public administration could develop a more efficient interface designed for the civil society through the medium of ITC.
Volume (Year): XVIII (2012)
Issue (Month): (May)
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- T. E. Cooke, 1998. "Regression Analysis in Accounting Disclosure Studies," Accounting and Business Research, Taylor & Francis Journals, vol. 28(3), pages 209-224, February.
- DING, Yuan & STOLOWY, Hervé & FU, Linghui & WANG, Huiwen, 2004.
"Disclosure and determinants studies : an extension using the divisive clustering method (DIV),"
Les Cahiers de Recherche
798, HEC Paris.
- Marie Chavent & Yuan Ding & Linghui Fu & Herve Stolowy & Huiwen Wang, 2006. "Disclosure and determinants studies: An extension using the Divisive Clustering Method (DIV)," European Accounting Review, Taylor & Francis Journals, vol. 15(2), pages 181-218.
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