Temi e medodologie di ricerca nell'area Management control : stato dell'arte e prospettive
165-170 p.
This issue of the journal formally establishes a new section to host methodological discussions, as well as invited and reviewed articles, in order to interpret the current situation and critically evaluate the perspectives on research topics and methodologies in the management accounting and control area. Particularly, the objective of this new section of the journal is to discuss how to strengthen the process of internationalization of research, while preserving the basic values of Italian accounting theory, also in the methodological side, i.e. maintaining the integrated inductivedeductive method of research. The author specifically contemplates the increasingly relevant role that the analytical demonstrations of the research hypotheses plays, with an experimental approach characteristic of the hard sciences.
Particularly, the research hypotheses are often based on causeeffect relationships in a truefalse logic, with reference to the available data bases or to data collected on a sample basis, often neglecting the accuracy of such data. Even the language used is increasingly the mathematical one, which is not suitable for the scientific communication in our community because the mathematical language neglects the qualitative variables, the interpretation of the data and the understanding of the multiple nonlinear causeeffect relationships. Regarding the research topics, the relevant issues appear to be no longer the topics that are related to the understanding of business complexity, but rather those that may apply best to the use of correlation analysis; in fact, the focus is on the quantitative methods, considered a priori better, and this increasingly determines the detachment from the business reality. [Publisher's text].
Fa parte di
Management Control : 2, 2021-
Articoli dello stesso fascicolo (disponibili singolarmente)
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Informazioni
Codice DOI: 10.3280/MACO2021-002009
ISSN: 2239-4397
PAROLE CHIAVE
- Research methodology, Quantitative methods, Qualitative methods, Data accuracy