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This paper contributes to the field of public services’ performance measurement systems by proposing a benchmarking-based methodology that improves the effective use of big and open data in analyzing and evaluating efficiency, for supporting internal decision-making processes of public entities.

The proposed methodology uses data envelopment analysis in combination with a multivariate outlier detection algorithm—local outlier factor—to ensure the proper exploitation of the data available for efficiency evaluation in the presence of the multidimensional datasets with anomalous values that often characterize big and open data. An empirical implementation of the proposed methodology was conducted on waste management services provided in Italy.

The paper addresses the problem of misleading targets for entities that are erroneously deemed inefficient when applying data envelopment analysis to real-life datasets containing outliers. The proposed approach makes big and open data useful in evaluating relative efficiency, and it supports the development of performance-based strategies and policies by public entities from a data-driven public sector perspective.

Few empirical studies have explored how to make the use of big and open data more feasible for performance measurement systems in the public sector, addressing the challenges related to data quality and the need for analytical tools readily usable from a managerial perspective, given the poor diffusion of technical skills in public organizations. The paper fills this research gap by proposing a methodology that allows for exploiting the opportunities offered by big and open data for supporting internal decision-making processes within the public services context.

This paper aims to extend the knowledge of eXtensible Business Reporting Language (XBRL) to synthesize what 20 years of accounting and business literature on XBRL suggests about the effective improvement from its implementation in financial reporting.

A systematic literature review and bibliometric analysis of 142 articles resulted in the identification of 5 primary research streams: adoption issues; financial reporting; decision-making processes, market efficiency and corporate governance; audit and assurance issues; and non-financial reporting.

The results reveal a scarcity of studies devoted to explicating the consequences of XBRL implementation on financial reporting outside the SEC’s XBRL mandate and listed companies’ contexts. Also, some papers’ results question the usefulness of the language on the decision-making process. The overall lack of literature concerning the impact of XBRL on financial statement preparers, especially with reference to SMEs, is evident. Moreover, the consequences on corporate governance choices and the relevant internal decision-making processes are rarely debated.

The findings are useful for users of companies’ financial disclosure policies, particularly for regulators who manage XBRL implementation in countries where XBRL has not yet been adopted as well as for others working in specific areas of financial disclosure, such as non-financial reporting and public sector financial reporting.

This study differs from previous literature on XBRL as it focuses on a wider period of analysis and offers a unique methodology – combination of bibliometric and systematic review – as well as a business perspective for deepening XBRL.