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This study aims to examine the role of Australian casinos in facilitating money laundering and Chinese capital flight.

The reports and transcripts of evidence from government inquiries into money laundering in Australian casinos are integrated with analyses of Asian transnational crime.

Money laundering in Australian casinos is linked to transnational crime and Chinese capital flight. A central finding is that junket operators play a key role in facilitating money laundering. The casinos are particularly exposed to criminal influences in the Chinese very important person gambling market, since they have used junket operators and underground banks, many of whom are closely linked to major Chinese criminal groups from Hong Kong and Macau.

Very little information is available on money laundering in Australian casinos and this research has relied on the government inquiries that have been conducted over the past two years on the subject.

The author’s focus on money laundering in Australian casinos in the context of Asia-Pacific transnational crime is important for Federal and state government regulators grappling with the rapidly changing money laundering issues. The government inquiries recognised that the money laundering was related to transnational crime, but did not have the time and resources to explore the topic. The paper provides state government casino regulators and financial crime regulators with a broader international perspective to anticipate future money laundering and crime pressures facing Australia’s casinos.

Money laundering in Australian casinos has had devastating social implications on the community. My research helps to focus attention on the problems of transnational crime and money laundering.

Little research has examined the linkages between casinos and transnational crime. This study has found that Australian casinos were used to launder the proceeds of illegal drug trafficking and to facilitate Chinese capital flight. While casinos have been forced by damming government inquiries to tighten anti-money laundering controls, it is likely that there will be pressure to relax these controls in the future because of competitive pressure from other casinos in the Asia-Pacific region.

The reality of domestic violence does not disappear when people enter the digital world, as abusers may use technology to stalk, exploit, and control their victims. In this chapter, we discuss three unique types of technological abuse: (1) financial abuse via banking websites and apps; (2) abuse via smart home devices (i.e., “Internet of Things” abuse); and (3) stalking via geo-location or GPS. We also argue pregnancy and wellness apps provide an opportunity for meaningful intervention for pregnant victims of domestic violence.

While there is no way to ensure users' safety in all situations, we argue thoughtful considerations while designing and building digital products can result in meaningful contributions to victims' safety. This chapter concludes with PenzeyMoog's (2020) “Framework for Inclusive Safety,” which is a roadmap for building technology that increases the safety of domestic violence survivors. This framework includes three key points: (1) the importance of educating technologists about domestic violence; (2) the importance of identifying possible abuse situations and designing against them; and (3) identifying user interactions that might signal abuse and offering safe interventions.

The authors examine the role of analysts’ prior experience of forecasting for firms exposed to epidemics on analysts’ forecast accuracy during the COVID-19 pandemic.

The authors examine the impact of analysts’ prior epidemic experience on forecast accuracy by comparing the changes from the pre-COVID-19 period (calendar year 2019) to the post-COVID period extending up to March 2023 across HRE versus non-HRE analysts. The authors consider a full sample (194,980) and a sub-sample (136,836) approach to distinguish “Recent” forecasts from “All” forecasts (including revisions).

The study's findings reveal that forecast accuracy for HRE analysts is significantly higher than that for non-HRE analysts during COVID-19. Specifically, forecast errors significantly decrease by 0.6% and 0.15% for the “Recent” and “All” forecast samples, respectively. This finding suggests that analysts’ prior epidemic experience leads to an enhanced ability to assess the uncertainty around the epidemic, thereby translating to higher forecast accuracy.

The finding that the expertise developed through an experience of following high-risk firms in the past enhances analysts’ performance during the pandemic sheds light on a key differentiator that partially explains the systematic difference in performance across analysts. The authors also show that industry experience alone is not useful in improving forecast accuracy during a pandemic – prior experience of tracking firms during epidemics adds incremental accuracy to analysts’ forecasts during pandemics such as COVID-19.

The study findings should prompt macroeconomic policymakers at the national level, such as the central banks of countries, to include past epidemic experiences as a key determinant when forecasting the economic outlook and making policy-related decisions. Moreover, practitioners and advisory firms can improve the earning prediction models by placing more weight on pandemic-adjusted forecasts made by analysts with past epidemic experience.

The uncertainty induced by the COVID-19 pandemic increases uncertainty in global financial markets. Under such circumstances, the importance of analysts’ role as information intermediaries gains even more importance. This raises the question of what determines analysts’ forecast accuracy during the COVID-19 pandemic. Building upon prior literature on the role of analyst experience in shaping analysts’ forecasts, the authors examine whether experience in tracking firms exposed to prior epidemics allows analysts to forecast more accurately during COVID-19. The authors find that analysts who have experience in forecasting for firms with high exposure to epidemics (H1N1, Zika, Ebola, and SARS) exhibit higher accuracy than analysts who lack such experience. Further, this effect of experience on forecast accuracy is more pronounced while forecasting for firms with higher exposure to the risk of COVID-19 and for firms with a poor ex-ante informational environment.

The purpose of this study is to examine whether and how analysts’ foreign ancestral origins would have an effect on analysts’ earning forecasts in particular and ultimately on firms’ information environment in general.

By inferring analysts’ ancestral countries based on their surnames, this study empirically examines whether analysts’ ancestral countries affect their earnings forecast errors.

Using novel data on analysts’ foreign ancestral origins from more than 110 countries, this study finds that relative to analysts with common American surnames, analysts with common foreign surnames tend to have higher earnings forecast errors. The positive relation between analyst foreign surnames and earnings forecast errors is more likely to be observed for African-American analysts and analysts whose ancestry countries are geographically apart from the USA. In contrast, this study finds that when analysts’ foreign countries of ancestry are aligned with that of the CEOs, analysts exhibit lower earnings forecast errors relative to analysts with common American surnames. More importantly, the results show that firms followed by more analysts with foreign surnames tend to exhibit higher earnings forecast errors.

Taken together, findings of this study are consistent with the conjecture that geographical, social and ethnical proximity between managers and analysts affect firms’ information environment. Therefore, this study contributes to the determinants of analysts’ earnings forecast errors and adds to the literature on firms’ information environment.

Merchant and Van der Stede (2006) produced a comprehensive analysis of 24 years (1981–2004) of field-based accounting research. This study aims to analyse how the publication of field research in accounting has changed since 2005. In addition, it aims to analyse contributions from specific individuals, institutions and countries, and whether the field studies have contributed to accounting research and textbooks.

The authors identified and classified 1,115 field-based accounting articles published in 14 accounting journals from 2005 to 2022 to uncover any changes. Thereafter, bibliometric analysis was conducted using data from SciVal.

The results show several significant changes. Firstly, the growth of field studies has more than trebled as nearly all journals published at least some field studies. Secondly, field research is no longer as confined to management accounting as before. It is gaining increasing traction in auditing, financial accounting and corporate social responsibility (CSR). Thirdly, while interview-based accounting research was clearly the most popular, the fastest growth was seen in mixed-methods non-management accounting research. While public sector management control case studies and content analysis of CSR were the most popular topics of interview-based studies, audits were the most popular topic in mixed-methods research. Authors based in large universities in large English-speaking countries have been most productive, followed by authors based in Europe and Asia. Based on citation analysis, the field studies have contributed to academic research substantially more than to textbooks.

An analysis of changes and trends improves the understanding of what has happened in accounting research and the development over time.