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Accounting Perspectives provides a forum for peer-reviewed applied research, analysis, synthesis and commentary on issues of interest to academics, practitioners, financial analysts, financial executives, regulators, accounting policy makers and accounting students. Articles are sought from academics and practitioners that address relevant issues in any and all areas of accounting and related fields, including financial accounting and reporting, auditing and other assurance services, management accounting and performance measurement, information systems and related technologies, tax policy and practice, professional ethics, accounting education, and related topics. Without limiting the generality of the foregoing.

Intelligent Systems in Accounting, Finance and Management is a quarterly international journal which publishes original, high quality material dealing with all aspects of intelligent systems as they relate to the fields of accounting, economics, finance, marketing and management. In addition, the journal also is concerned with related emerging technologies, including big data, business intelligence, social media and other technologies. It encourages the development of novel technologies, and the embedding of new and existing technologies into applications of real, practical value. Therefore, implementation issues are of as much concern as development issues. The journal is designed to appeal to academics in the intelligent systems, emerging technologies and business fields, as well as to advanced practitioners who wish to improve the effectiveness, efficiency, or economy of their working practices. A special feature of the journal is the use of two groups of reviewers, those who specialize in intelligent systems work, and also those who specialize in applications areas. Reviewers are asked to address issues of originality and actual or potential impact on research, teaching, or practice in the accounting, finance, or management fields. Authors working on conceptual developments or on laboratory-based explorations of data sets therefore need to address the issue of potential impact at some level in submissions to the journal.