IS enables organizations to improve their productivity, streamline their business processes, and better understand the challenges and opportunities facing their business. These benefits can further accrue to individuals and organizations when they adopt and use the systems. While the benefits of IS are multifarious, IS adoption remains challenging. The far-reaching consequences of IS motivate research examining the antecedents of successful IS adoption both at individual and organizational levels. To examine the complexity of IS adoption, we undertook an interpretive case study of SBR adoption in Australia. We contend that SBR’s context in Australia offers distinctive perspectives on the complexity of IS adoption. We found that IS adoption decisions can be based on both constructivist and ecological rationalities. Our findings can provide insight in improving understanding of the benefits of SBR and have implications for companies, regulators, standard setters, and the accounting profession, more generally.
The volume of freely available accounting information is rapidly becoming overwhelming. To be useful, information needs to be delivered to users in a suitable, relevant, and understandable form. Interactive data visualisation (IDV) can help address this need for useful information by organising accounting information, especially financial reports, into forms with these qualities. Given both their prevalence and their likelihood of being future users of IDV, the purpose of this research is to examine the appropriateness of IDV for non-professional investors' use when they access accounting information. This research uses a 2 × 2 experimental approach involving 404 participants representing non-professional investors from diverse demographic backgrounds. This research suggests that IDV mitigates non-professional investors' restricted investment capabilities by presenting information that is more salient, thus reducing non-professional investors' cognitive effort. This combination allows such investors to better perform both simple and multipart investment tasks. By integrating three information systems' fit perspectives (i.e. task technology, information quality, and cognitive), this research explains IDV's suitability and fit within the accounting domain. We also discuss how the findings can inform practice and span interdisciplinary research into data and information visualisation.
Singapore Health Services, or SingHealth in short, is Singapore’s largest public health organisation. SingHealth was established in the year 2000 with ‘the aim to deliver consistently high-quality care that is appropriate and accessible to patients’. Since its inception, SingHealth has introduced numerous digital innovations to strengthen its business model and healthcare delivery. These include investments in mobile applications such as HealthBuddy and MyCare, which are widely used by patients in Singapore to manage their medical appointments, order their medication and monitor their health, which can all be done remotely. With the Covid-19 pandemic, SingHealth introduced Swabot which helped carry out automated nasal swabs at Covid-19 testing sites; Doctor Covid, which is a chatbot hosted on Telegram, an online messaging application that helps to improve care for Covid-19 patients in community care settings; and an AI-based tool called the Community-Acquired Pneumonia and Covid-19 AI Predictive Engine, which can determine the severity of pneumonia in Covid-19 patients based on chest x-ray images. SingHealth’s investments in information systems and technologies have enabled SingHealth to improve its operations, provide better healthcare delivery to patients, better manage doctors’ and nurses’ workload, and address the various challenges posed by the Covid-19 pandemic. This case examines how digital technologies revolutionised SingHealth’s workflows and processes, resulting in better quality healthcare for patients, and will be helpful for healthcare organisations looking to leverage on technology and health informatics for optimum healthcare delivery.
Extant research in accounting information systems has identified the link between information presentation and users’ performance. XBRL can markedly help enhance information presentation for users through its ability to address issues of the semantic meaning of financial information while making such information machine readable. This study, therefore, posits that non-professional investors will benefit from their interaction with XBRL-based financial statements. Information enhancement permitted by XBRL is considered to fit with non-professional investors’ needs, meaning that XBRL will improve data and information quality (DIQ) within financial statements. This paper will study whether or not higher non-professional investors’ perceived DIQ of XBRL leads to better decision making performance. When making decisions, several factors may also arise due to human cognitive limitations and bounded rationality, for example, perceived uncertainty, heuristic, and perceived fit. This study posits that XBRL will help reduce non-professional investors’ uncertainty, help improve non-professional investors’ heuristic processing, and help support non-professional investors’ investment analysis. To address the aforementioned issue, an experiment will be used to manipulate financial statement presentations (XBRL versus non-XBRL) and task type (selective versus integrative) to help provide evidence of non-professionals’ interactions with XBRL-based financial statements. In addition, non-professionals’ perceptions of, and performance changes brought about by such financial statements, will be investigated. The findings of this research are expected to provide a more refined understanding about the use of XBRL-based financial statements as well as the practical benefits of XBRL to help improve non-professional investors to arrive at better decisions. The result of this study may also suggest several courses of action, such as developing more useful and helpful features of XBRL-based financial statement, as well as data and information enhancement permitted by XBRL to facilitate non-professional investment task analysis, leading to improved performance.
Business Intelligence (BI) has received wide recognition in the business world as a tool to address ‘big’ data-related problems, to help managers understand their businesses and to assist them in making effective decisions. To date, however, there have been few studies which have clearly articulated a theoretically grounded model that explains how the use of BI systems provides benefits to organisations, or explains what factors influence the actual use of BI systems. To fully achieve greater decision-making performance and effective use of BI, we contend that BI systems integration with a systems user’s work routine (dependence on the systems) is essential. Following this argument, we examine the effects of system dependent use along with effective use (infusion) on individual’s decision-making performance with BI. Additionally, we pro-pose that a fact-based decision-making culture, and data quality of source systems are constraints factors that impact on BI system dependence and infusion. We adopt a quantitative method approach. Specifically, we will conduct a two-wave cross-sectional survey targeting 400 North American BI users who describe themselves as both using a BI system and making decision using data from the system. We expect to make an important theoretical contribution to BI literature by providing a model that explains the dimensions of actual BI system use, and makes a practical contribution by providing insights into how organisational external constraints facilitate BI dependence and infusion in the pursuit of BI-enabled performance gain.
XBRL has the ability to provide financial statements with improved data information quality (DIQ). Contextual and representational DIQ are relevant to perceptual and decision factors of nonprofessional investors when they interact with XBRL-based financial statements and make investment decisions. The author posits that XBRL-based financial statements with improved contextual and representational DIQ will positively influence nonprofessional investors' DIQ perceptions, resulting in better alignment with decision factors (i.e., uncertainty, heuristic, task, technology, and individual characteristics) to achieve better informed investment decisions. This research will use a web-based experiment to empirically test the proposed hypotheses. The results of this research are expected to contribute to the theoretical understanding of the links between XBRL enhanced DIQ, users' perceptions, decision factors, and investment outcome performance. Establishing whether there are links between XBRL and improved DIQ, and whether improved DIQ aligns with decision factors, will make a practical contribution by benefiting nonprofessional investors through better informed investment decisions.
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