Exploring the social reporting practices of public schools: survey and cluster analysis of the Italian educational system^*

* Although the results of this research paper are a team effort, Domenico Raucci wrote Sections 1; 2; 3; 5; Domenico Raucci and Stefano Agostinone wrote Section 3.1; Domenico Raucci and Lara Tarquinio wrote Section 6; Stefano Agostinone wrote Section 4.2; while all authors wrote Sections 4.1 and 4.3 with an equal contribution.

ABSTRACT

Reforms in the Italian educational sector have led schools to become more accountable. Social Reporting (SR) is an effective response to stakeholders’ increasing demand for information and an innovative public accountability tool for Italian Public Schools (IPSs). Using a survey and cluster analysis, our study investigates current awareness and adoption of SR practices to improve the accountability of IPSs. The results show that SR practices are still underused and that IPSs fall into two main groups: “early movers”, which are highly sensitive to this tool and will employ it earlier, and “latecomers”, which show less awareness.

KEYWORDS:

• Public school accountability
• social reporting practices
• Italian public schools

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Acknowledgements

The authors wish to acknowledge the comments and suggestions received from Prof. Carol Tilt (Editor of Accounting Forum) as well as from the anonymous reviewers.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

* Although the results of this research paper are a team effort, Domenico Raucci wrote Sections 1; 2; 3; 5; Domenico Raucci and Stefano Agostinone wrote Section 3.1; Domenico Raucci and Lara Tarquinio wrote Section 6; Stefano Agostinone wrote Section 4.2; while all authors wrote Sections 4.1 and 4.3 with an equal contribution.

1 See L. 59/1997; D.Lgs. 59/1998; D.P.R. 275/1999; D.P.R. 347/2000; D.I. 44/2001; D.L. 165/2001; L. 107/2015.

2 Unlike hierarchical clustering, k-means clustering requires the number of resulting clusters, k, to be specified prior to analysis. Thus, it will produce k different clusters of greatest possible distinction.

3 Other methods, both hierarchical and not-hierarchical, provide the same results as the complete linkage method.

4 Questionnaire is available on request.