Accounting - Research Publications
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ItemIs Financial Reporting Still Useful? Australian Evidence(Wiley, 2019-03-01)There has been recent and growing criticism of the usefulness of financial reporting for investors, particularly the annual financial statements. In response, the IASB is pursuing several projects aimed at improving the relevance of financial information. To inform the IASB’s work, we investigate, using a mixed‐method approach, the extent and nature of the use of annual financial statements by equity investors. We examine the relevance of financial reporting for equity valuation in Australia across time. We find that financial reporting (specifically, reported net income, shareholders’ equity, and operating cash flows) remains relevant for investment decisions. We further support this finding with evidence from field interviews that provide insight into how and why financial statements are used by equity investors. The field evidence also demonstrates that no one financial statement dominates in investor decision making. Given the increasing availability of more timely, forward‐looking information from alternative sources, we examine the relevance of non‐GAAP financial information and other non‐financial information for investor decision making. We find that non‐GAAP financial information (as proxied by EBIT and EBITDA) is more value relevant than statutory measures. We further find a broad range of non‐financial information is utilized by investors in making investment decisions both as a ‘screen’ and for valuation purposes. Our findings inform regulators and other stakeholders as we provide evidence of the continuing relevance of financial statements and the complementary role of non‐GAAP financial and other information. Our evidence provides a rebuttal to the recent criticism.
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ItemExplanations as Discourse: Towards Ethical Big Data Analytics Services(Australasian Association for Information Systems and Australian Computer Society, 2020-01-01)Big data analytics uses algorithms for decision-making and targeting of customers. These algorithms process large-scale data sets and create efficiencies in the decision-making process for organizations but are often incomprehensible to customers and inherently opaque in nature. Recent European Union regulations require that organizations communicate meaningful information to customers on the use of algorithms and the reasons behind decisions made about them. In this paper, we explore the use of explanations in big data analytics services. We rely on discourse ethics to argue that explanations can facilitate a balanced communication between organizations and customers, leading to transparency and trust for customers as well as customer engagement and reduced reputation risks for organizations. We conclude the paper by proposing future empirical research directions.
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ItemKnowledge matters: Restrictiveness and performance with decision support(ELSEVIER, 2010-11)
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ItemTowards an integrated view of IT value measurement(Elsevier BV, 2010-03-01)