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Current prices, future estimates, and price statistics cannot reflect specific transaction experience generated by enterprise management. Instead, overt transaction data in accounts continue to constitute evidence of management decision-actions, even after apportioned among fiscal periods. And the interrelation of enterprise capital employed productively, and the income generated by its use, will continue whether or not accounts are kept. Yet, the significance of factual integrity for enterprise transaction experience is strongly influenced by the functional logic inherent in accounting.

The purpose of this paper is to contribute to a better, empirically grounded and theoretically informed understanding of data analytics (DA) use and nonuse in accounting for decision-making. To that end, it explores the links between accounting logic, commercial logic and DA use in financial due diligence (FDD).

The paper reports the findings of a case study of DA use in the FDD practice of a Big Four accounting firm in Sweden (Pseudonym: DealCo). The primary data comprises semistructured interviews, observations and additional meetings. Institutional logics is mobilized as method theory.

First, accounting logic and commercial logic both drove and hindered DA use in DealCo’s FDD practice in different ways. Second, conflicting prescriptions for DA use existed mostly within commercial logic rather than between accounting logic and commercial logic. Third, accounting logic and commercial logic, as perceptual and conceptual filters, seemed to shape DealCo’s advisors’ understanding of DA and give rise to an efficiency-centric DA logic. This logic, in turn, as a high-level model of how to use DA in the context of FDD, governed DA use broadly.

The paper draws attention to direct and indirect links between accounting logic and commercial logic, on the one hand, and DA conceptions and use, on the other hand. It, thereby, advances prior theorization of DA use in accounting for decision-making.

Purpose: Analysis and systematisation of global trends in the transformation of DSSs from the standpoint of solving their global and local problems and determining the central axioms of setting up and supporting business processes in DSSs.

Need of the Study: Decision Support Systems (DSSs) are the basis of doing business in an enterprise by automating business processes, keeping accounting and reducing various risks associated with complexity, labour-intensiveness, slow execution time and, therefore, potential loss of profit. In recent decades, the rapid development of DSSs has led to the emergence of complex enterprise information system architectures. At the same time, many local business processes are not implemented or are partially implemented. In Ukraine, such techniques include VAT accounting.

Methodology: The study is based on the literature analysis, Internet resources and practical experience obtained during the SAP ERP system implementation projects. Particular attention is paid to developing information systems architecture to solve the problems enterprises face during their growth. Thanks to the analysis of the example of the realisation of the Internet sales process and the induction method, the axioms of automation of business processes in accounting systems were formed.

Findings: Regardless of the qualitative and quantitative transformation, modern DSSs still cannot solve all the enterprise’s problems, mainly due to the use of paper documents and the diversity of national legislation. By the example of the SAP ERP system, the optimal implementation of the business process of VAT liabilities was proposed by Ukrainian legislation for sales below cost price.

Practical Implications: Compliance with the established axioms of automation of business processes will reduce the cost of resources for their implementation, maintenance and correction of potential errors and, therefore, will provide an opportunity to process more transactions. Implementing the proposed algorithm for calculating VAT liabilities in SAP ERP for sales below the cost price will simplify the existing process and enable the fulfilment of other requirements within the framework of current legislation.

This study aims to focus on the five most relevant and discursive emerging technologies in accounting (cloud computing, big data and data analytics, blockchain, artificial intelligence (AI) and robotics process automation [RPA]). It investigates the adoption and use of these technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey.

The study investigates the adoption and use of emerging technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey. This study considers the said nature and characteristics of emerging technologies and proposes a model using the factors that have been found to be significant and most commonly investigated by existing prior technology-organization-environment (TOE)-related technology adoption studies. This survey applies the TOE framework and examines the influence of significant and most commonly known factors on Canadian firms’ intention to adopt the said emerging technologies.

Study results indicate that Canadian accounting professionals’ self-assessed knowledge (about these emerging technologies) is more theoretical than operational. Cloud computing is highly used by Canadian firms, while the use of other technologies, particularly blockchain and RPA, is reportedly low. However, firms’ intention about the future adoption of these technologies seems positive. Study results reveal that only the relative advantage and top management commitment are found to be significant considerations influencing the adoption intention.

Study findings confirm some results presented in earlier studies but provide additional insights from a new perspective, that of accounting professionals in Canada. The first limitation relates to the respondents. Although accounting professionals provided valuable insights, their responses are personal views and do not necessarily represent the views of other professionals within the same firm or the official position of their accounting departments or firms. Therefore, the exclusion of diverse viewpoints from the same firm might have negatively impacted the results of this study. Second, this study sample is limited to Canada-based firms, which means that the study reflects only the situation in that country. Third, considering the research method and the limit on the number of questions the authors could ask, respondents were only asked to rate the impact of these five technologies on the accounting field and to clarify which technologies are used.

This study’s findings confirm that the organizational intention to adopt new technology is not primarily based on the characteristics of the technology. In the case of emerging technology adoption, the decision also depends upon other factors related to the internal organization. Furthermore, although this study found no support for the effect of environmental factors, it fills a gap in the literature by including the factor of vendor support, which has received little attention in prior information technology (IT)/ information system (IS) adoption research. Moreover, in contrast to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study findings may serve as a guide for researchers, practitioners, firms and other stakeholders, particularly technology providers, interested in learning about emerging technologies’ adoption and use in Canada and/or in a relevant context. Contrary to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study provides insights into the said technologies’ actual adoption and improves the awareness of firms and stakeholders to the effect of some constructs that influence the adoption of these emerging technologies in accounting.

This paper aims to discuss the viewpoint that Big Data’s major impacts on the accounting community will be changes in consumers’ demand of accounting data and its impact on decision-making. Big Data is leading consumers to prefer more atomized (not summarized but rather reduced to discrete units), reconfigurable and transparent accounting data that they can combine into their own structures to meet their own decision-making needs. Consequently, consumers will demand digital goods that are less static, and summarized.

This paper discusses the strategic shift to what is referred to as “indirect data,” and develops a model that helps explain “how” and “why” Big Data may impact this change in consumer digital demand.

There are many evolving Big Data opportunities associated with the shift in consumer demand for more atomized, reconfigurable and transparent accounting data that are discussed in this paper, including strategic capability, auditing, performance measurement and reporting, standardization and education.

This paper provides a discussion of the evolving opportunities of the relationship that is created by a strategic shift in the type of digital goods consumers of information, specifically decision-makers, will demand, as well as the potential impacts on the accounting community.

Big Data analytics (BDA) and its implications for the accounting profession continue to be a key issue that requires more research and evaluation. As a result, the purpose of this study is to evaluate the impact of BDA on financial reporting quality, as well as to assess the accounting challenges associated with Big Data. It provides qualitative evidence from Canada.

This study used a qualitative approach to ascertain the thoughts and perceptions of auditors, financial analysts and accountants at Canadian audit and accounting firms in BDA and its impact on financial reporting quality, using semi-structured interviews. To obtain their consent to participate in the interview, 127 auditors, financial analysts and accountants from Canadian audit and accounting firms were initially approached. The final number of respondents was 41, representing a response rate of 32%.

The authors’ findings underscored the relevance of Big Data and BDA in affecting financial report quality and revealed that BDA had a significant effect on improving financial reporting quality. Big Data improves accounting reporting and expert judgment by providing professional. In summary, participants agreed that when analytical methods in Big Data are implemented effectively, businesses may possibly achieve a variety of benefits, including customized goods, simplified processes, improved risk assessment process and, finally, increased risk management.

The authors’ findings indicate that BDA may help predict investment returns and risks, estimate future investment opportunities, forecast revenues, detect fraud and susceptibility early and identify economic growth opportunities. As a result, auditors, financial analysts, accountants, investors and other strategic decision-makers should be aware of these findings to make informed choices.

Big Data has become the norm in recent years; accountants and other decision-makers have struggled to analyze massive amounts of data. This limits their capacity to profit from such data even more. Therefore, this study is motivated by the lack of research on Big Data’s influence on financial report quality.

Accounting education is re-inventing itself as technology impacts the practical aspects of accounting in the real world and education tries to keep up. Big Data and data analytics have begun to influence elements of accounting including audit, accounting preparation, forensic accounting and general accountancy consulting. The purpose of this paper is to qualitatively analyse the current skills provision in accounting Masters courses linked to data analytics compared to academic and professional expectations of the same.

The academic expectations and requirements of the profession, related to the impact of Big Data and data analytics on accounting education were reviewed and compared to the current provisions of this accounting education in the form of Masters programmes. The research uses an exploratory, qualitative approach with thematic analysis.

Four themes were identified of the skills required for the effective use of Big Data and data analytics. These were: questioning and scepticism; critical thinking skills; understanding and ability to analyse and communicating results. Questioning and scepticism, as well as understanding and ability to analyse, were frequently cited explicitly as elements for assessment in various forms of accounting education in the Masters courses. However, critical thinking and communication skills were less explicitly cited in these accounting education programmes.

The research reviewed and compared current academic literature and the requirements of the professional accounting bodies with Masters programmes in accounting and data analytics. The research identified key themes relevant to the accounting profession that should be explicitly developed and assessed within accounting education for Big Data and data analytics at both university and professional levels. Further analysis of the in-depth curricula, as opposed to the explicitly stated topic coverage, could add to this body of research.

This paper considers the potential combined role of professional qualification examinations and master’s degrees in skills provision for future practitioners in accounting and data analysis. This can be used to identify the areas in which accounting education can be further enhanced by focus or explicit mention of skills that are both developed and assessed within these programmes.

The paper considers the interaction between academic and professional practice in the areas of accounting education, highlighting skills and areas for development for students currently considering accounting education and data analytics.

While current literature focusses on integrating data analysis into existing accounting and finance curricula, this paper considers the role of professional qualification examinations with Masters degrees as skills provision for future practitioners in accounting and data analysis.

Empirical accounting research frequently makes use of data sets with a time‐series and a cross‐sectional dimension ‐ a panel of data. The literature review indicates that South African researchers infrequently allow for heterogeneity between firms when using panel data and the empirical example shows that regression results that allow for firm heterogeneity are materially different from regression results that assume homogeneity among firms. The econometric analysis of panel data has advanced significantly in recent years and accounting researchers should benefit from those improvements.

New digital technologies are reshaping the business landscape and accounting work. This paper aims to investigate how incorporating more data and new data analytics (DA) tools impacts the role and use of judgment in financial due diligence (FDD).

The paper reports findings from a field study at a Big Four accounting firm in Sweden (“DealCo”). The primary data includes semi-structured interviews, observations and other meetings. Theoretically, it draws on Dewey’s The Logic of Judgments of Practise and Logic: The Theory of Inquiry and distinguishes between theoretical (what is probably true) and practical judgment (what to do).

In DealCo’s FDD practice, using more data and new DA tools meant that the realm of possibility had expanded significantly. To manage the newfound abundance and to use DA effectively, DealCo’s advisors invoked practical and theoretical judgments in different stages and areas of the data-driven FDD. The paper identifies four critical uses of judgment: Setting priorities and exercising restraint (practical judgment) and forming hypotheses and doing sense checks (theoretical judgment). In these capacities, practical judgment and theoretical judgment were essential in transforming raw data into actionable insights and, in effect, an indeterminate situation into a determinate one.

The study foregrounds the practical dimension of knowledge production for decision-making and contributes to a better understanding of the role, use and importance of accounting professionals’ judgment in a data-driven world.

For over a decade now, various stakeholders in accounting education have called for the integration of technology competencies in the accounting curriculum (Association to Advance Collegiate Schools of Business (AACSB), 2013, 2018; Accounting Education Change Commission (AECC), 1990; American Institute of Certified Public Accountant (AICPA), 1996; Behn et al., 2012; Lawson et al., 2014; PricewaterhouseCoopers (PWC), 2013). In addition to stakeholder expectations, the inclusion of data analytics as a key area in both the business and accounting accreditation standards of the AACSB signals the urgent need for accounting programs to incorporate data analytics into their accounting curricula. This paper examines the extent of the integration of data analytics in the curricula of accounting programs with separate accounting AACSB accreditation. The paper also identifies possible barriers to integrating data analytics into the accounting curriculum. The results of this study indicate that of the 177 AACSB-accredited accounting programs, 79 (44.6%) offer data analytics courses at either the undergraduate or graduate level or as a special track. The results also indicate that 41 (23.16%) offer data analytics courses in their undergraduate curriculum, 61 (35.88%) at the graduate level, and 12 (6.80%) offer specialized tracks for accounting data analytics. Taken together, the findings indicate an encouraging trend, albeit slow, toward the integration of data analytics into the accounting curriculum.