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The paper investigates the closure mechanisms and strategies of exclusion concerning the establishment and subsequent functioning of the Collegio dei Rasonati, the professional body of accountants that was established in Venice in 1581 and operated until the end of the 18th century.

The research design offers a critical longitudinal explanation of the emergence of the Collegio dei Rasonati as a professional body in the context of Venetian society by relying on the social closure theory elaborated by Collins (1975); Parkin (1979) and Murphy (1988).

The Collegio dei Rasonati was established to overcome the prerogatives of a social class in accessing the accounting profession. However, the pre-existing professional elites enacted a set of social closure strategies able to transform this professional body into a stronghold of their privileges.

As virtually all of the evidence concerning the admission examinations has been lost over time, the investigation is restricted to the study of the few examples that have survived. The main implication of the study concerns the understanding of some dynamics leading to neutralize attempts to replace class privileges with a meritocratic system.

The research investigates the structure of the rules of social closure revealing the possibility of an antagonistic relationship between different co-existing forms of exclusion within the same structure. Moreover, it highlights that a form of exclusion can be made of different hierarchical levels.

Accounting information systems are mainly rule-based, and data are usually available and well-structured. However, many accounting systems are yet to catch up with current technological developments. Thus, artificial intelligence (AI) in financial accounting is often applied only in pilot projects. Using AI-based forecasts in accounting enables proactive management and detailed analysis. However, thus far, there is little knowledge about which prediction models have already been evaluated for accounting problems. Given this lack of research, our study aims to summarize existing findings on how AI is used for forecasting purposes in financial accounting. Therefore, the authors aim to provide a comprehensive overview and agenda for future researchers to gain more generalizable knowledge.

The authors identify existing research on AI-based forecasting in financial accounting by conducting a systematic literature review. For this purpose, the authors used Scopus and Web of Science as scientific databases. The data collection resulted in a final sample size of 47 studies. These studies were analyzed regarding their forecasting purpose, sample size, period and applied machine learning algorithms.

The authors identified three application areas and presented details regarding the accuracy and AI methods used. Our findings show that sociotechnical and generalizable knowledge is still missing. Therefore, the authors also develop an open research agenda that future researchers can address to enable the more frequent and efficient use of AI-based forecasts in financial accounting.

Owing to the rapid development of AI algorithms, our results can only provide an overview of the current state of research. Therefore, it is likely that new AI algorithms will be applied, which have not yet been covered in existing research. However, interested researchers can use our findings and future research agenda to develop this field further.

Given the high relevance of AI in financial accounting, our results have several implications and potential benefits for practitioners. First, the authors provide an overview of AI algorithms used in different accounting use cases. Based on this overview, companies can evaluate the AI algorithms that are most suitable for their practical needs. Second, practitioners can use our results as a benchmark of what prediction accuracy is achievable and should strive for. Finally, our study identified several blind spots in the research, such as ensuring employee acceptance of machine learning algorithms in companies. However, companies should consider this to implement AI in financial accounting successfully.

To the best of our knowledge, no study has yet been conducted that provided a comprehensive overview of AI-based forecasting in financial accounting. Given the high potential of AI in accounting, the authors aimed to bridge this research gap. Moreover, our cross-application view provides general insights into the superiority of specific algorithms.

Considering the growing interests in managerial and accounting issues related to blockchain technology (BT), the study aims at identifying the main research venues in this specific field. In particular, the purpose is to understand the spatial and temporal production and distribution of research documents, highlighting the most relevant topics, the most influential authors and research.

This research carries out a bibliometric analysis of 189 research documents in the business, management and accounting areas. Data collection and refining is carried out from the Scopus database. The data analysis is based on a hybrid literature review approach using a descriptive bibliometric method, data analysis visualization (through VOSViewer software) and thematic analysis.

Results indicate that research studies focused on BT and accounting have been growing exponentially over the last three years, with authors who previously focused on generalist themes, and are now facing more specific issues. Through cluster analysis, the authors propose the framework of accounting domain and blockchain technology (ADOB) to systematize and visualize the map of current studies about the BT in the accounting domain.

The analysis highlights some aspects less investigated at the first research stage in the field of BT and accounting, such as the growing need of new accounting and control processes to address the practical issues of BT implementation and the need for education and training to stimulate a proper use of BT by accountants and practitioners.

This study is the first to adopt a bibliometric and thematic analysis to investigate BT in the accounting domain. The authors provide significant insights that could guide and foster the use of BT for accountants and practitioners, defining future research lines and a research agenda for academic researchers.

This study aims to analyse whether theories and views of classical Islamic scholars are widely adopted as references in Islamic accounting and finance (IAF), Islamic economics (IE) and Islamic business management (IBM) research studies as part of their contribution to solving current economic and financial problems.

The research adopts a qualitative meta-analysis methodology using NVivo 12 with selected data from 474 international journal articles published between 1981 and 2021. The study considers 172 IAF articles, 111 IE articles and 191 IBM articles.

The results of the study show that the use of theories and views of classical Islamic scholars is not widespread among the examined research papers. The findings show that 90% of researchers tend to acquire modern economics, management, psychological and sociological theories instead of classical theories. Both modern and classical theories have been discussed in the studied articles namely agency theory, stakeholders' theory, ḥisbah (accountability), maqāṣid al-Sharīʿah (objectives of Islamic law) and waʿd (unilateral promise). The gaps prevail not only in the taxonomy of terms but also in the choice of paradigm references. It is found that 66% of the 474 journal articles adopt a positivist paradigm, followed by interpretivism (19%), post-structuralism (9%) and critical orientation (6%).

This paper considers only ABS ranking journal articles. Future research may consider other journal articles from different ranking groups such as Scopus or Thomson & Reuters.

The paper sheds light on how Islamic educational institutions can develop strategies for the Integration of Knowledge (IOK) in their curriculum.

This paper helps to shape the Muslims' way of thinking within an Islamic worldview which will lead to an Islamic way of expressing knowledge, skill and behaviour.

This paper contributes to the model of IOK that has been deliberated among Islamic universities, especially those that develop IAF, IE and IBM studies.

The current review aims to examine the growth trajectory, most influential documents, intellectual and conceptual structure of the literature regarding gender issues in family business research.

The bibliometric analysis was performed using 224 documents from 1991 to 2020 extracted from the Web of Science database.

The review finds that this field's knowledge grew exponentially during the last three decades, mainly after 2003 and the last several years. Based on the co-citation analysis, three major research lines are identified: “Women's challenges and opportunities in the family business”, “Gender diversity in the family business corporate board”, and “Gender and family SMEs management.” The temporal co-word analysis reveals that “Gender diversity in the family business corporate board” is the latest research line.

By reviewing prominent cited references and documents that cited them, the authors provide the landscapes and research gaps of three major research lines for further development.