{"id":3231,"date":"2022-05-05T18:49:06","date_gmt":"2022-05-05T16:49:06","guid":{"rendered":"https:\/\/eaa-online.org\/arc\/events\/"},"modified":"2022-10-13T14:39:10","modified_gmt":"2022-10-13T12:39:10","slug":"2023-xjtlu-ai-and-big-data-in-accounting-and-finance-research-conference-and-the-bar-special-issue","status":"publish","type":"event","link":"https:\/\/eaa-online.org\/arc\/events\/2023-xjtlu-ai-and-big-data-in-accounting-and-finance-research-conference-and-the-bar-special-issue","title":{"rendered":"2023 XJTLU AI and Big Data in Accounting and Finance Research Conference and the BAR special issue"},"content":{"rendered":"
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Overview
\nThere is a growing literature in accounting and finance applying machine learning methods for data analysis, examining the usefulness of those methods, and assessing the impact on decision making and investment. To better understand the challenges and opportunities of this emerging research area, XJTLU, International Business School (IBSS) will dedicate the 2023 AI and Big Data in Accounting and Finance Research conference with the BAR special issue.<\/p>\n

The ultimate objective of this conference and special issue is to improve our usage of the large and growing financial data sources, our understandings of financial information align with the innovative data analytic techniques. The proposed special issue allows BAR to assemble cutting edge research in Accounting and Finance that apply AI or ML methods to ask and examine research questions that could not otherwise be examined.<\/p>\n

Topics:
\nThe committee welcomes studies that provide cutting-edge insights into current research work related with the theme of the conference. Specific topics and research questions can include but are not limited to use various machine learning methods to improve the quality and dimension of data analysis in accounting and finance, and also to understand how traditional problems related to accounting and finance can be addressed by innovative computational methods, and whether those approaches are able to uncover more valuable information such as learning data patterns, predicting occurrences, capturing firm characteristics, determining asset prices, forecasting returns and etc.<\/p>\n

Publication Opportunities
\nThe British Accounting Review will publish a special issue on AI and Big Data in Accounting and Finance Research. The BAR is a well-established international journal that publishes original scholarly papers across the whole spectrum of accounting and finance (http:\/\/ees.elsevier.com\/bar\/<\/a>). BAR\u2019s 2020 CiteScore (7) and Impact Factor (5.577) rank BAR top 2 and 3 respectively among accounting journals as well as 7 in accounting and finance. It\u2019s rated A* in ABDC Journal Quality Guide.
\n(Link:\u00a0https:\/\/www.journals.elsevier.com\/the-british-accounting-review\/<\/a>)<\/p>\n

In the submission, authors should indicate if they wish their paper to be considered for publication in a special issue of British Accounting Review (BAR). This is a \u201cno-fault\u201d submission option: if the submission is not accepted in the conference, the authors can still submit it to a regular issue of the journal at a later date as if it were never submitted. Acceptance in the conference does not guarantee final publication. Attending the conference is not a pre-condition for the submission to this special issue. All submissions are subject to the normal review process.<\/p>\n

Submission
\nExtended abstracts or full papers are to be submitted to
\nEmail:\u00a0jia.zhai@xjtlu.edu.cn<\/a>
\nPlease put \u201cAI and Big Data in Accounting and Finance\u201d in the subject line and indicate whether you would like the submission to be considered by the British Accounting Review special issue.
\nSubmission link to the journal:\u00a0https:\/\/www.editorialmanager.com\/ybare\/default1.aspx<\/a><\/p>\n

Submission Deadline: Jan 2023
\nAuthors will be notified by March 2023
\nVirtual Conference: 25-26 May 2023<\/p>\n

Conference organizing committee:
\n– Chair: Dr Jia Zhai
\n– Co-Chairs: Professor Jorg Bley (Professor in Finance, Dean of International Business School Suzhou, XJTLU), Professor Michael Chng (Professor in Finance, IBSS, XJTLU)
\n– Coordinator: Dr Yi Cao (University of Edinburgh Business School)<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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