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In a virtual interconnected digital space, the metaverse encompasses various virtual environments where people can interact, including engaging in business activities. Machine learning (ML) is a strategic technology that enables digital transformation to the metaverse, and it is becoming a more prevalent driver of business performance and reporting on performance. However, ML has limitations, and using the technology in business processes, such as accounting, poses a technology governance failure risk. To address this risk, decision makers and those tasked to govern these technologies must understand where the technology fits into the business process and consider its limitations to enable a governed transition to the metaverse. Using selected accounting processes, this study aims to describe the limitations that ML techniques pose to ensure the quality of financial information.

A grounded theory literature review method, consisting of five iterative stages, was used to identify the accounting tasks that ML could perform in the respective accounting processes, describe the ML techniques that could be applied to each accounting task and identify the limitations associated with the individual techniques.

This study finds that limitations such as data availability and training time may impact the quality of the financial information and that ML techniques and their limitations must be clearly understood when developing and implementing technology governance measures.

The study contributes to the growing literature on enterprise information and technology management and governance. In this study, the authors integrated current ML knowledge into an accounting context. As accounting is a pervasive aspect of business, the insights from this study will benefit decision makers and those tasked to govern these technologies to understand how some processes are more likely to be affected by certain limitations and how this may impact the accounting objectives. It will also benefit those users hoping to exploit the advantages of ML in their accounting processes while understanding the specific technology limitations on an accounting task level.

The purpose of this study is to extend the Fraud Diamond Theory to celebrity Special Purpose Acquisition Companies (SPACs) and investigate their post-Initial Public Offering (IPO) stock market performance.

After obtaining a sample of celebrity SPACs from the Spacresearch.com database, fraud risk characteristics were obtained from Lexis Nexus searches. Buy and hold abnormal returns were calculated for celebrity SPACs versus a small-cap equity benchmark for time intervals after IPO, and multiple regression analysis was performed to examine the relationship between fraud risk features and post-IPO returns.

Celebrity SPACs exhibit Fraud Diamond characteristics and significantly underperform a small-cap stock portfolio on a risk-adjusted basis after IPO.

This study only examines celebrity SPACs that conducted IPOs on the NYSE and NASDAQ/AMEX and does not include those that are traded on the Over the Counter Bulletin Board (OTCBB).

Celebrity endorsement of SPAC vehicles attracts investors who may not be properly informed regarding the risk characteristics of SPACs. Accordingly, investors should be warned that celebrity SPACs underperform a small-cap equity portfolio and exhibit significant elements of fraud risk.

The use of celebrity endorsement as a marketing device to attract investment in SPACs has regulatory implications.

To the best of the authors’ knowledge, this paper is the first to examine the fraud risk characteristics and post-IPO performance of celebrity SPACs.

The purpose of this paper is to give an overview of artificial intelligence (AI) and other AI-enabled technologies and to describe how COVID-19 affects various industries such as health care, manufacturing, retail, food services, education, media and entertainment, banking and insurance, travel and tourism. Furthermore, the authors discuss the tactics in which information technology is used to implement business strategies to transform businesses and to incentivise the implementation of these technologies in current or future emergency situations.

The review provides the rapidly growing literature on the use of smart technology during the current COVID-19 pandemic.

The 127 empirical articles the authors have identified suggest that 39 forms of smart technologies have been used, ranging from artificial intelligence to computer vision technology. Eight different industries have been identified that are using these technologies, primarily food services and manufacturing. Further, the authors list 40 generalised types of activities that are involved including providing health services, data analysis and communication. To prevent the spread of illness, robots with artificial intelligence are being used to examine patients and give drugs to them. The online execution of teaching practices and simulators have replaced the classroom mode of teaching due to the epidemic. The AI-based Blue-dot algorithm aids in the detection of early warning indications. The AI model detects a patient in respiratory distress based on face detection, face recognition, facial action unit detection, expression recognition, posture, extremity movement analysis, visitation frequency detection, sound pressure detection and light level detection. The above and various other applications are listed throughout the paper.

Research is largely delimited to the area of COVID-19-related studies. Also, bias of selective assessment may be present. In Indian context, advanced technology is yet to be harnessed to its full extent. Also, educational system is yet to be upgraded to add these technologies potential benefits on wider basis.

First, leveraging of insights across various industry sectors to battle the global threat, and smart technology is one of the key takeaways in this field. Second, an integrated framework is recommended for policy making in this area. Lastly, the authors recommend that an internet-based repository should be developed, keeping all the ideas, databases, best practices, dashboard and real-time statistical data.

As the COVID-19 is a relatively recent phenomenon, such a comprehensive review does not exist in the extant literature to the best of the authors’ knowledge. The review is rapidly emerging literature on smart technology use during the current COVID-19 pandemic.

The purpose of the study is to identify cybersecurity threats that hinder the adoption of digital banking and provide sustainable strategies to combat cybersecurity risks in the banking industry.

Systematic literature review guidelines were used to conduct a quantitative synthesis of empirical evidence regarding the impact of cybersecurity threats and risks on the adoption of digital banking.

A total of 84 studies were initially examined, and after applying the selection and eligibility criteria for this systematic review, 58 studies were included. These selected articles consistently identified identity theft, malware attacks, phishing and vishing as significant cybersecurity threats that hinder the adoption of digital banking.

With the country’s banking sector being new in this area, this study contributes to the scant literature on cyber security, which is mostly in need due to the myriad breaches that the industry has already suffered thus far.

Money laundering (ML) is a major criminal offence stemming from unethical practices by personnel on the ground at Chattogram Port, an important import and export facility in Bangladesh. Because money can be more easily laundered through imports, it is necessary to investigate the dubious process in this sector. This study aims to identify the items most regularly used for easy ML and the factors contributing to their vulnerability.

This research uses a qualitative approach and analyses information from primary sources. Data is obtained from customs officials, port authority personnel, importers and customs brokers through semi-structured questionnaires. Although there are many techniques for ML, this study only found three most overwhelming: under-invoicing, over-invoicing and misdeclaration. A few case studies have been used based on newspaper reports and the internet to triangulate the qualitative data.

Four import items – food products, garments, capital machinery and chemicals – have a higher risk of ML. This study also revealed that money launderers prefer under-invoicing food and garment items. Misdeclaration is more commonly associated with capital machinery and chemical items. Over-invoicing, on the other hand, is only prevalent in government purchases. The port authorities need to pay particular attention to these issues.

As ML is an ongoing activity that changes over time, the findings of this research are circumscribed by the data collected at a single point in time. Additionally, this research did not consider alternative laundering methods.

The research results can provide a basis for creating effective anti-money laundering (AML) strategies to assist with sustainable economic growth.

Developing effective AML measures can help combat corruption and establish good governance in the country and support human well-being.

This paper presents original research findings based on technical analysis. The Chattogram Port Authority and the National Board of Revenue have accepted and used the main findings in a collaborative action plan to tackle ML. The Bangladesh Bank, the country’s central bank, has also incorporated the necessary guidelines and regulations into the Money Laundering Prevention Act, 2012.

This paper aims to examine the relationship between board structure and risk-taking, exploring how this association is influenced by advanced technologies in the banking sector.

This study uses a panel sample of 22 Pakistani banks from 2011 to 2018. To test the authors’ hypothesis, the authors use regression analysis with two-way cluster robust standard errors. Further, the authors also check the robustness of the authors’ findings using alternate proxies of board structure and bank risk-taking behavior. To address endogeneity concerns, the authors use the two-stage least square technique.

In the era of the Fourth Industrial Revolution, Pakistani banks’ digitalization is modeled by the presence of Temenos-T24/Oracle as their core banking system (software providing end-to-end operational integration). Its interactional effect with corporate governance is evaluated to implicate informed risk-taking by the board as a result of improved information access and analysis. The authors find that board size has a positive association with risk-taking, and the use of modern technology reshapes this association in the banking sector.

The contribution of this paper is twofold. First, the impact of board structure on bank risk-taking has not been extensively researched in Pakistan – a highly volatile and unpredictable economy. Second, the evaluation of the role of technology on bank risk is being researched for the very first time – a uniqueness of this paper.

The rise of cryptocurrencies and other digital assets has triggered concerns about regulation and security. Governments and regulatory bodies are challenged to create frameworks that protect consumers, combat money laundering and address risks linked to digital assets. Conventional approaches to confiscation and anti-money laundering are deemed insufficient in this evolving landscape. The absence of a central authority and the use of encryption hinder the identification of asset owners and the tracking of illicit activities. Moreover, the international and cross-border nature of digital assets complicates matters, demanding global coordination. The purpose of this study is to highlight that the effective combat of money laundering, legislative action, innovative investigative techniques and public–private partnerships are crucial.

The focal point of this paper is Australia’s approach to law enforcement in the realm of digital assets. It underscores the pivotal role of robust confiscation mechanisms in disrupting criminal networks operating through digital means. The paper firmly asserts that staying ahead of the curve and maintaining an agile stance is paramount. Criminals are quick to embrace emerging technologies, necessitating proactive measures from policymakers and law enforcement agencies.

It is argued that an agile and comprehensive approach is vital in countering money laundering, as criminals adapt to new technologies. Policymakers and law enforcement agencies must remain proactively ahead of these developments to efficiently identify, trace and seize digital assets involved in illicit activities, thereby safeguarding the integrity of the global financial system.

This paper provides a distinctive perspective by examining Australia’s legal anti-money laundering and counterterrorism financing framework, along with its law enforcement strategies within the realm of the digital asset landscape. While there is a plethora of literature on both asset confiscation and digital assets, there is a noticeable absence of exploration into their interplay, especially within the Australian context.

In the evolving landscape of global remittances, this study systematically explores cryptocurrency's transformative impact on remittance services through a comprehensive literature review and bibliometric analysis.

Through meticulous PRISMA-guided analysis, the research identifies cryptocurrency technology as a pivotal force in enhancing remittance efficiency, reducing costs and broadening access contributing significantly to financial inclusion.

Findings revealed that cryptocurrency technology could significantly enhance remittance services, offering improved efficiency, reduced costs and increased accessibility. This suggests a transformative potential for financial inclusion, presenting a compelling case for broader adoption and regulatory support to leverage these benefits effectively.

By integrating recent research, this work underlines the urgent need for broader adoption and regulatory support to leverage these benefits effectively. It offers novel insights for institutions and policymakers, highlighting the potential for technology adoption in remittances to enhance financial inclusivity.

More cryptocurrency studies are needed to concentrate on remittance markets. Thus, this investigation constitutes a unique addition to the field. Additional investigation in this domain presents significant possibilities for future exploration and progress.

This study aims to examine the mediating effects of corporate governance mechanisms like the board of directors on the association between disruptive technology adoption by audit clients and the risk of material misstatements, including inherent risk and control risk. In particular, the authors study the mediating effects of board characteristics such as board size, independence and gender diversity.

Based on a sample of 100 audit clients listed on the FTSE 100 from 2015 to 2021, this study uses structural equation modelling to test the research objectives.

The findings indicate a significant and negative association between disruptive technology adoption by audit clients and inherent risk. However, there is no significant evidence observed for control risk. The utilisation of disruptive technology by the audit client has a significant impact on the board characteristics, resulting in an increase in board size, greater independence and gender diversity. The authors also find strong evidence that board independence mediates the association between disruptive technology usage and both inherent risk and control risk. In addition, board size and gender exhibit distinct and differential mediating effects on the association and across the two types of risks.

The study reveals that the significant role of using disruptive technology by audit clients in reducing the risk of material misstatements is closely associated with the board of directors, which makes audit clients place greater emphasis on the construction of effective corporate governance.

This study offers essential primary evidence that can assist policymakers and standard setters in formulating guidance and recommendations for board size, independence and gender quotas, ensuring the enhancement of effective governance and supporting the future of audit within the next generation of digital services.

With respect to relevant stakeholders, it is imperative for audit clients to recognise that corporate governance represents a fundamental means of addressing the ramifications of applying disruptive technology, particularly as they pertain to inherent and control risks within the audit client.

This study contributes to the existing literature by investigating the joint impact of corporate governance and the utilisation of disruptive technology by audit clients on inherent risk and control risk, which has not been investigated by previous research.

The Internet has changed consumer decision-making and influenced business behaviour. User-generated product information is abundant and readily available. This paper argues that user-generated content can be efficiently utilised for business intelligence using data science and develops an approach to demonstrate the methods and benefits of the different techniques.

Using Python Selenium, Beautiful Soup and various text mining approaches in R to access, retrieve and analyse user-generated content, we argue that (1) companies can extract information about the product attributes that matter most to consumers and (2) user-generated reviews enable the use of text mining results in combination with other demographic and statistical information (e.g. ratings) as an efficient input for competitive analysis.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The paper shows that combining different types of data (textual and numerical data) and applying and combining different methods can provide organisations with important business information and improve business performance.

The study makes several contributions to the marketing and management literature, mainly by illustrating the methodological advantages of text mining and accompanying statistical analysis, the different types of distilled information and their use in decision-making.