Is an Emoji Worth a Thousand Words? The Effect of Emoji Usage on Nonprofessional Investors’ Perceptions

Emojis act as non-verbal cues to disambiguate and communicate affect and are increasingly used in online corporate disclosures. Emotion work, a concept founded in social psychology, suggests that individuals adjust their behavior as emotions are evoked or suppressed. Despite the growing evidence that emojis may influence judgments and decisions due to their deliberate expression of context and affect, the accounting research community has yet to investigate emojis’ impact. We experimentally explore whether emojis can soften nonprofessional investors’ perceptions of bad news or enhance perceptions of good news. We find that emojis modestly suppress participants’ positive emotions on positive news, influencing their investment-related judgments and decision-making. Subsequent data collection fails to replicate the initial findings in a less experienced participant pool, suggesting that investing experience may play a role. Our study enhances our understanding of the unintended consequences of emojis and introduces a sociology-based principle into the accounting literature.

Attended Process Automation in Audit: A Framework and A Demonstration

This study responds to an increasing need for research on Robotic Process Automation (RPA) in external auditing, especially research that concerns auditors’ roles in an RPA-enabled audit workflow. Since more than half of the audit tasks require certain levels of auditors’ judgment and cannot be fully automated (e.g., Abdolmohammadi 1999), audit automation should include attended automation, in which auditors work alongside and interact with automation routines. This paper adopts the Design Science Research (DSR) approach and proposes an Attended Process Automation (APA) framework that guides the implementation of attended automation in audits. This paper also demonstrates the APA framework by applying it to the planning process for Single Audits, a government-required external audit for beneficiaries of funding. The APA framework emphasizes auditors' vital role in an automated audit workflow in providing professional judgments that are currently irreplaceable by automation.

A Picture Is Worth a Thousand Journal Entries: Accounting Graph Topology for Auditing and Fraud Detection

Although journal entries are an important component of modern accounting, existing research and practice in auditing and fraud detection have not fully exploited the information made available by the double-entry mechanism. This paper proposes a theory-based methodology, accounting graph topology, to visualize journal entries and explicate within- and between-entry relationships. Grounded in cognitive fit theory and graph theory, this methodology can help auditors identify potential internal control issues and problematic transactions for further investigation. We illustrate the benefits of accounting graph topology by applying it to a case study.

Exploring Antecedents of Peoples' Intention to Use Smart Services in Smart City Environment: An extended UTAUT Model

ABSTRACT The Indian government is currently developing scalable and sustainable smart city infrastructures to address the urbanization problem in India. However, the smart city project will only be successful if the people accept and use smart services. Therefore, this study investigates peoples’ acceptance of smart services using a modified unified theory of acceptance and use of technology model (UTAUT). The results demonstrate that performance expectancy, effort expectancy, and attitude are significant factors in peoples’ usage intention toward smart services. Furthermore, the study tested the moderating effect of task-technology fit and perceived risk on the relationship between performance expectancy, effort expectancy, and attitude and usage intention. The study’s findings will help decision-makers and professional accountants to understand and implement robust accounting processes responsible for selecting the right digital tools for the right reasons to enhance peoples’ usage intention in a smart city environment.

The Role of Construal Alignment in Enterprise Risk Management

According to the Committee of Sponsoring Organizations (COSO 2017), two important elements of an organization’s enterprise risk management (ERM) framework are its risk management philosophy, and its risk appetite and tolerance. Based on Construal Level Theory (CLT), we posit that the effectiveness of ERM depends on the extent of alignment (non-fit or fit) between mental representations (high versus low construal) of those two ERM elements. We test our hypothesis across two risk cases: safety and confidentiality. Results of our experiment suggest that employees are more proactive when there is a construal fit between the emphasis placed on a firm’s risk management philosophy and its expression of the key risk indicators (KRIs). This benefit is observed in the confidentiality case, but not in the safety case. Implications are discussed.

Information Security Assurance and the Role of Security Configuration Management: Substantive and Symbolic Perspectives

This paper explores whether IT and audit professionals have different perceptions of the substantive and symbolic perspectives of information security assurance and the role of security configuration management (SCM) using a mixture of qualitative and quantitative approaches. Importance performance analysis (IPA) is utilized to identify differences in perceived importance and perceived controllability from both substantive and symbolic perspectives between these two professional groups. Our results suggest that SCM plays a vital role in maintaining consistency between the IT and audit professionals by enhancing their confidence in controlling and managing information security control sets. IPA also helps determine an information security program's strengths and weaknesses and supports remedial strategic actions more efficiently. Implications for both research and practice are discussed.

Applications of Data Analytics: Cluster Analysis of Not-for-Profit Data

ABSTRACT: Since data analytics enables data exploration and the uncovering of hidden relationships, in this study we use cluster analysis to gain more insight into governmental data and financial reports. This research initiative is performed using the Design Science Research (DSR) methodology, where we develop and apply an appropriate artifact. We apply our artifact to two different datasets: the first uses the U.S. states’ financial statements, and the second utilizes survey results from the Volcker Alliance about states’ budgeting performance. In both applications, we demonstrate how clustering may be used on governmental data to gain new insights about financial statements and budgeting. This study contributes to the literature in two ways: First, the two applications bring advanced data mining techniques into the not-for-profit domain; and second, the results provide guidance for auditors, academics, regulators, and practitioners to use clustering to gain more insights.

A View from the CISO: Insights from the Data Classification Process

Data security is a critical concern for organizations. In a rush to protect data, some IT managers overlook the important first step of data classification and instead focus on implementing the strictest controls on all data to reduce risk. To investigate organizational processes surrounding data classification, we conduct interviews with 27 CISOs in 23 organizations. We develop a model that identifies the common themes of data classification and their interrelationships. The most common driver for data classification is compliance with data privacy regulations and security standards. Collaboration and employee education are essential to the process. Increases in employee awareness of data security risk and improvements in data hygiene are outcomes. Challenges to data classification include the increase in IT landscape complexity, maintenance of an accurate data inventory, immaturity of automated tools, limited resources, and user compliance. Our model provides insights for practitioners and identifies areas of interest for researchers.