The Transformation of Accounting Information Systems Curriculum in the Last Decade

Accounting information systems (AIS) are an extremely important component of accounting and accounting education. The purpose of the current study is to examine the transformation of accounting information systems (AIS) curriculum in the last decade. The motivation for this research comes from the vast advances made in the world of information technology (IT) and information systems (IS). The specific research questions addressed in the current study are: (1) how has AIS curriculum changed in the 18 years since SOX? (2) How has AIS curriculum adjusted in recent years with the emergence of the new hot-button topic big data/data analytics? Overall, this study finds that the core of AIS curriculum has not significantly changed over the last decade. However, more emphasis is being placed on topics such as enterprise wide systems/ERP, IT audits, computer fraud, and transaction-processing. Related, several new topical coverages have been introduced such as business analysts and big data/data analytics. The key contribution of this paper is to provide accounting students and accounting educators with useful information regarding the most significant shifts in AIS over the last decade and insight into the most valuable current AIS topics

Decision support for firm performance by real options analytics

This paper develops a real options decision support tool for raising the performance of the firm. It shows how entrepreneurs can use our intuitive tool quickly to assess the nature and type of action required for improved performance. This exploits our estimated econometric relationship between precipitators of entrepreneurial opportunities, time until exercise, and firm performance. Our 3D chromaticity plots show how staging investments, investment time, and firm performance support entrepreneurial decisions to embed, or to expedite, investments. Speedy entrepreneurial action is securely supported with this tool, without expertise in econometric estimation or in formulae for real options valuation

Strategic business management : from planning to performance

https://egrove.olemiss.edu/aicpa_guides/2682/thumbnail.jp

Determinants of analytics-based managerial decision-making

This study investigates how managerial decision-making is influenced by Big Data analytics, analysts’ interaction skills and quantitative skills of senior and middle managers. The results of a cross-sectional survey of senior IT managers reveal that Big Data analytics (BDA) creates an incentive for managers to base more of their decisions on analytic insights. However, we also find that interaction skills of analysts and – even more so – managers’ quantitative skills are stronger drivers of analytics-based decision-making. Finally, our analysis reveals that, contrary to mainstream perceptions, managers in smaller organizations are more capable in terms of quantitative skills, and they are significantly more likely to base their decisions on analytics than managers in large organizations. Considering the important role of managers’ quantitative skills in leveraging analytic decision support, our findings suggest that smaller firms may owe some of their analytic advantages to the fact that they have managers who are closer to their analysts – and analytics more generally

How can SMEs benefit from big data? Challenges and a path forward

Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd.Peer ReviewedPostprint (author's final draft

Performance measurement : challenges for tomorrow

This paper demonstrates that the context within which performance measurement is used is changing. The key questions posed are: Is performance measurement ready for the emerging context? What are the gaps in our knowledge? and Which lines of enquiry do we need to pursue? A literature synthesis conducted by a team of multidisciplinary researchers charts the evolution of the performance-measurement literature and identifies that the literature largely follows the emerging business and global trends. The ensuing discussion introduces the currently emerging and predicted future trends and explores how current knowledge on performance measurement may deal with the emerging context. This results in identification of specific challenges for performance measurement within a holistic systems-based framework. The principle limitation of the paper is that it covers a broad literature base without in-depth analysis of a particular aspect of performance measurement. However, this weakness is also the strength of the paper. What is perhaps most significant is that there is a need for rethinking how we research the field of performance measurement by taking a holistic systems-based approach, recognizing the integrated and concurrent nature of challenges that the practitioners, and consequently the field, face

Determinants of analytics-based managerial decisionmaking

This study investigates how managerial decision-making is influenced by Big Data analytics, analysts’ interaction skills and quantitative skills of senior and middle managers. The results of a cross-sectional survey of senior IT managers reveal that Big Data analytics (BDA) creates an incentive for managers to base more of their decisions on analytic insights. However, we also find that interaction skills of analysts and – even more so – managers’ quantitative skills are stronger drivers of analytics-based decision-making. Finally, our analysis reveals that, contrary to mainstream perceptions, managers in smaller organizations are more capable in terms of quantitative skills, and they are significantly more likely to base their decisions on analytics than managers in large organizations. Considering the important role of managers’ quantitative skills in leveraging analytic decision support, our findings suggest that smaller firms may owe some of their analytic advantages to the fact that they have managers who are closer to their analysts – and analytics more generally

The Impact of Disruptive Technologies in Finance and Accounting: A Systematic Literature Review

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business IntelligenceThe digital transition era, marked by a strong evolution of Information Technologies, and its massive expansion towards all products, services, and sectors, has changed all known methods for carrying out and conducting all sorts of professional practices. Within the scope of accounting activities and transactions related to accounting, various tasks have started to be automatized with the help of Artificial Intelligence and Machine Learning. Hence, no longer existing the need of spending time on some of the repetitive day-to-day tasks, professionals in these areas will have more time and freedom to perform predictive business analysis, to collect and report financial data, which will most likely become vital to assist decision-making and possible attraction of new investments. As such, there is a clear link between accounting and the emergence of disruptive technologies, which indicates an interesting research area for accounting information systems researchers. What is the impact of disruptive technologies in accounting practices? What is the role played by accountants to work alongside their digital colleagues? What are the skills that accountants may have to be future proof in an ever-changing digital environment? This dissertation aims to answer these questions by following a qualitative and exploratory approach, through a systematic literature review. The analysis reveals that the impact of disruptive technologies in finance and accounting can be summarized in four main domains, Strategic Management, Technology Innovation, Business Acumen and Operations and Accounting Provision. We review the content of recent academic literature regarding the relationship between disruptive technologies and accounting and highlight research gaps and opportunities for future research

Technology Diffusion in Tax: An Examination of Tax Analytics and Automation Routinization

This study examines the use of tax analytics and automation (TAA) technologies in corporate tax departments. We investigate the factors that influence the degree to which TAA technologies are used as an integral part of the tax department’s processes. A survey of tax professionals from Fortune 1000 companies was conducted to gain an understanding of the level of TAA routinization that exists in their corporate tax departments. This study extends the research literature on assimilation of innovative technologies by using a unique sample in a tax department setting. We adapt a technology diffusion model from Zhu, Kraemer and Xu (2006) and predict that factors related to technological, organizational and environmental contexts are related to the degree of routinization of TAA technologies. Results indicate that the context factors of technology integration, managerial obstacles, and regulatory environment are all related to the level of TAA technology used by corporate tax departments