Accounting - Research Publications

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    Australian Listed Entities: Recognised intangible assets and key audit matters
    Pinnuck, M ; Wallis, M ; Li, A ; Lee, E ; Waters, A ; Mattocks, R (Australian Accounting Standards Board and Auditing and Assurance Standards Board, 2023)
    The AASB-AUASB published a joint research report (with Professor Matthew Pinnuck and Dr Mark Willis) that aims to understand the significance of recognised intangible assets on the balance sheets of Australian listed entities. This Report explores the frequency, magnitude and nature of intangible assets recognised by the Australian Securities Exchange (ASX) listed entities on their balance sheets. This Report also identifies the frequency of key audit matters (KAMs) related to intangible assets in auditor’s reports to provide insights into the areas that auditors are focusing on, possibly due to the complexity of the accounting requirements. Through a review of the financial statements from 2010 to 2021, this Report finds that: • with the exception of micro-mining entities, the majority of Australian entities recognised some intangible assets on their balance sheets; • the level of investment in intangibles for the majority of entities, as a percentage of total assets, is relatively low. However, there are some entities that recognised a significant level of intangibles as a percentage of total assets; • there is a wide variety of category descriptions used to present intangible assets, possibly impeding both comparability and a precise understanding of the nature of the intangible asset; • intangibles are the most frequent KAM subject matter, suggesting a substantial fraction of auditors' resources to assure such information, despite the relatively low level of recognised intangibles.
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    Insights into Key Audit Matters 31 December 2022 to 30 September 2023 reporting in Australia
    Pinnuck, M ; Wallis, M ; Ghandar, A ; Pateman, Z (CAANZ Chartered Accountants Australia and New Zealand, 2024)
    A report on the frequency and nature of the reporting of key audit matters (KAM) in auditors’ reports of Australian Stock Exchange (ASX) listed entities that issued financial statements in 2023
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    Submission to the Australian Competition and Consumer Commission (ACCC) Supermarkets Inquiry 2024-25
    Pinnuck, M ( 2024)
    The ACCC supermarkets inquiry has an interest in whether there is effective competition between supermarkets and the broader competitive dynamics. If competition is effective then supermarkets should be making ‘normal’ profits. However, very little evidence has been provided as to what normal profits should be. To provide a benchmark we analyse the profitability of Australian supermarkets against the largest supermarkets in OECD countries across the 3-year period 2021 to 2023.
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    XBRL and the qualitative characteristics of useful financial information
    Birt, JL ; Muthusamy, K ; Bir, P (Emerald, 2017-05-02)
    Purpose: eXtensible Business Reporting Language (XBRL) is an internet-based interactive form of reporting language that is expected to enhance the usefulness of financial reporting (Yuan and Wang, 2009). In the UK and the USA, XBRL is mandatory, and in Australia, it is voluntarily adopted. It has been reported that in the not too distant future, XBRL will be the standard format for the preparation and exchange of business reports (Gettler, 2015). Using an experimental approach, this study assesses the usefulness of financial reports with XBRL tagged information compared to PDF format information for non-professional investors. The authors investigate participants’ perceptions of usefulness in relation to the qualitative characteristics of relevance, understandability and comparability. Design/methodology/approach: This paper uses an experimental approach featuring a profit-forecasting task to determine if participants perceive XBRL-tagged information to be more useful compared to PDF-formatted information. Findings: Results reveal that financial information presented with XBRL tagging is significantly more relevant, understandable and comparable to non-professional investors. Originality/value: The authors address a gap in the literature by examining XBRL usefulness in Australia where XBRL adoption will be mandated within the not too distant future. Currently, the voluntary adoption of XBRL by preparers and users is low, possibly, because of a lack of awareness about XBRL and its potential benefits. This study yields significant implications for the accounting regulators in creating more awareness on the benefits of using XBRL and to create an impetus for XBRL adoption.
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    The Effect of Organizational Climate on Sell-side Analyst Turnover and Performance
    Chua, WF ; Kuang, YF ; Wu, YA (Wiley, 2023)
    This paper investigates whether and how organizational climate (OC) in brokerage firms affects analyst turnover and performance. We find that firms with a lower-rated OC have a higher likelihood of analyst turnover. Also, when analysts leave and switch brokerage firms, they are more likely to move to a firm with a higher-rated OC and will deliver more accurate forecasts after switching firms. However, the performance improvements in better-rated OC firms are significant only for the initial years of the analysts’ employment in the new firms. We also show that OC-related analyst turnover negatively affects the performance of incumbent analysts, especially for those non-All-Star incumbent analysts, while these adverse performance effects are also transitory and last for two years only. Thus, our findings indicate that OC only has a short-lived effect on the behaviour of both leaving and remaining analysts, which challenges the long-held assumption that investments in a positive OC will always be associated with lower employee turnover and higher individual performance. We explain our results as arising from the high levels of labour mobility within the brokerage industry and the transparency of analyst forecasts as a public performance measure.
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    Does stock market liberalization improve stock price efficiency? Evidence from China
    Chen, Y ; Huang, J ; Li, X ; Yuan, Q (Wiley, 2022-07)
    In this study, we examine whether liberalization of the stock market improves stock price efficiency using China's market liberalization pilot program as a shock. We find that investible firms exhibit a significant increase in price efficiency, as proxied by stock price non-synchronicity, after stock market liberalization. The results are robust to a series of tests and remain unchanged after we address the issue of endogeneity. We identify two channels through which price efficiency can be improved: better disclosure by firms and the incorporation of more information into stock prices through the trading activities of foreign investors. We also find that investment becomes more sensitive to prices, further indicating that stock prices have become more efficient. Finally, we find that stock price informativeness also increases.
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    Can knowledge based systems be designed to counteract deskilling effects?
    Arnold, V ; Collier, PA ; Leech, SA ; Rose, JM ; Sutton, SG (Elsevier BV, 2023-09-01)
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    Activist directors: determinants and consequences
    Gow, ID ; Shin, S-PS ; Srinivasan, S (SPRINGER, 2023-01-01)
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    The ChatGPT Artificial Intelligence Chatbot: How Well Does It Answer Accounting Assessment Questions?
    Wood, DA ; Achhpilia, MP ; Adams, MT ; Aghazadeh, S ; Akinyele, K ; Akpan, M ; Allee, KD ; Allen, AM ; Almer, ED ; Ames, D ; Arity, V ; Barr-Pulliam, D ; Basoglu, KA ; Belnap, A ; Bentley, JW ; Berg, T ; Berglund, NR ; Berry, E ; Bhandari, A ; Bhuyan, MNH ; Black, PW ; Blondeel, E ; Bond, D ; Bonrath, A ; Borthick, AF ; Boyle, ES ; Bradford, M ; Brandon, DM ; Brazel, JF ; Brockbank, BG ; Burger, M ; Byzalov, D ; Cannon, JN ; Caro, C ; Carr, AH ; Cathey, J ; Cating, R ; Charron, K ; Chavez, S ; Chen, J ; Chen, JC ; Chen, JW ; Cheng, C ; Cheng, X ; Christensen, BE ; Church, KS ; Cicone, NJ ; Constance, P ; Cooper, LA ; Correia, CL ; Coyne, J ; Cram, WA ; Curtis, A ; Daigle, RJ ; Dannemiller, S ; Davenport, SA ; Dawson, GS ; De Meyst, KJL ; Dell, S ; Demirkan, S ; Denison, CA ; Desai, H ; DeSimone, S ; Diehl, LM ; Dimes, R ; Dong, B ; Donnelly, A ; du Pon, A ; Duan, HK ; Duffey, A ; Dunn, RT ; Durkin, MP ; Dzuranin, AC ; Eberle, RM ; Ege, MS ; El Mahdy, D ; Esplin, A ; Eulerich, M ; Everaert, P ; Farah, N ; Farish, L ; Favere-Marchesi, M ; Fayard, D ; Filosa, JR ; Ford, M ; Franz, DR ; Fulmer, BP ; Fulmer, S ; Furner, ZZ ; Gantman, S ; Garner, S ; Garrett, J ; Geng, X ; Golden, J ; Goldman, W ; Gomez, J ; Gooley, M ; Granitto, SP ; Green, KY ; Greenman, CL ; Gupta, G ; Guymon, RN ; Hale, K ; Harper, CJ ; Hartt, SA ; Hawk, H ; Hawkins, SR ; Hawkins, EM ; Hay, DC ; Heinzelmann, R ; Henderson, CD ; Hendricks, BE ; Heninger, WG ; Hill, MS ; Holden, N ; Holderness, DK ; Holt, TP ; Hoopes, JL ; Hsieh, S-F ; Huang, F ; Huang, H-W ; Huang, T-C ; Huels, BW ; Hunter, K ; Hurley, PJ ; Inger, K ; Islam, S ; Ison, I ; Issa, H ; Jackson, AB ; Jackson, SC ; Janvrin, DJ ; Jimenez, PD ; Johanson, D ; Judd, JS ; Kawada, BS ; Kelton, AS ; Kern, S ; Kerr, JN ; Keune, MB ; Kim, M ; Knox, BD ; Kogan, G ; Kotb, A ; Krane, R ; Kremin, J ; Krieg, KS ; Kugel, J ; Kulset, EM ; Kuruppu, C ; LaDuca, G ; Lamberton, BA ; Lamboy-Ruiz, MA ; Lang, B ; Larocque, SA ; Larson, MP ; Lawson, BP ; Lawson, JG ; Lee, L ; Lenk, MM ; Li-Kuehne, M ; Liljegren, J ; Lin, Y-H ; Liu, W-P ; Liu, Z ; Lock, B ; Long, JH ; Loraas, T ; Lowensohn, S ; Loy, TR ; Lyngstadaas, H ; Maas, W ; MacGregor, JE ; Madsen, DØ ; Malone, CL ; Margolin, M ; Marshall, ME ; Martin, RM ; Mpofu, CM ; McCoy, C ; McGuigan, NC ; McSwain, DN ; Meckfessel, MD ; Mellon, MJ ; Melton, OS ; Mercado, JM ; Mitsuda, S ; Modugu, K ; Moehrle, S ; Chaghervand, AM ; Moffitt, K ; Moon, JS ; Muehlmann, B ; Murray, J ; Mwaungulu, ES ; Myers, N ; Naegle, JC ; Ndicu, MJ ; Nelson, AS ; Nguyen, AL ; Niederkofler, T ; Nikbakht, E ; O'Brien, AD ; Ogunade, KM ; O'Leary, D ; Oler, MJ ; Oler, DK ; Olsen, KJ ; Otalor, JI ; Outlaw, KW ; Ozlanski, ME ; Parlier, J ; Paterson, JS ; Pearson, CA ; Petersen, MJ ; Petra, ST ; Pickard, MD ; Pickerd, J ; Pinsker, R ; Plante, C ; Plečnik, JM ; Price, RA ; Quick, LA ; Raedy, J ; Raschke, R ; Ravenscraft, J ; Richardson, V ; Rixom, BA ; Robertson, JF ; Rock, I ; Romney, MA ; Rozario, A ; Ruff, MF ; Rupley, K ; Saeedi, A ; Saiewitz, A ; Salzsieder, LW ; Sarkar, S ; Saulls, M ; Scanlan, TA ; Schaefer, TJ ; Schaupp, D ; Schneider, GP ; Seebeck, A ; Sellers, RD ; Seto, SC ; Sevel, R-L ; Shan, Y ; Sherwood, MG ; Singorahardjo, M ; Skaftadottir, HK ; Skomra, J ; Smith, JL ; Smith, DO ; Smith, J ; Snow, MC ; Sommerfeldt, RD ; Sorensen, KB ; Sorensen, TL ; Spieler, AC ; Stallings, MA ; Stallings, L ; Stancill, A ; Stanley, JD ; Stefaniak, CM ; Stephens, NM ; Stewart, BW ; Stratopoulos, TC ; Street, DA ; Subedi, M ; Summers, SL ; Sundkvist, CH ; Synn, C ; Tadesse, A ; Tapis, GP ; Tassin, K ; Taylor, S ; Teal, M ; Teeter, R ; Tharapos, M ; Theis, JC ; Thomas, J ; Thompson, KS ; Thornock, TA ; Tietz, W ; Travalent, AM ; Trinkle, BS ; Truelson, JM ; Turner, MC ; Vagner, B ; Vakilzadeh, H ; van der Geest, J ; van Pelt, V ; Vandervelde, SD ; Vega, J ; Vera-Muñoz, S ; Villanueva, B ; Vincent, NE ; Wagener, M ; Walton, S ; Warne, RC ; Watanabe, OV ; Watson, D ; Watson, MW ; Weber, J ; Weirich, T ; West, AN ; Wilford, AL ; Wilson, AB ; Winrow, B ; Winrow, T ; Winrow, TS ; Wiseman, D ; Witte, AL ; Wood, BD ; Wood, J ; Woolley, D ; Wright, NS ; Wu, J ; Xiong, X ; Yatsenko, D ; Yazzie, CE ; Young, GM ; Zhang, C ; Zimmerman, AB ; Zoet, E (American Accounting Association, 2023-11-01)
    ABSTRACT ChatGPT, a language-learning model chatbot, has garnered considerable attention for its ability to respond to users’ questions. Using data from 14 countries and 186 institutions, we compare ChatGPT and student performance for 28,085 questions from accounting assessments and textbook test banks. As of January 2023, ChatGPT provides correct answers for 56.5 percent of questions and partially correct answers for an additional 9.4 percent of questions. When considering point values for questions, students significantly outperform ChatGPT with a 76.7 percent average on assessments compared to 47.5 percent for ChatGPT if no partial credit is awarded and 56.5 percent if partial credit is awarded. Still, ChatGPT performs better than the student average for 15.8 percent of assessments when we include partial credit. We provide evidence of how ChatGPT performs on different question types, accounting topics, class levels, open/closed assessments, and test bank questions. We also discuss implications for accounting education and research.