The Intellectual Development of Human-Computer Interaction Research: A Critical Assessment of the MIS Literature (1990-2002)

As one of the five research streams of the Management Information Systems (MIS) discipline, Human-Computer Interaction (HCI) was predicted to resurge in the post-millennium era. To date, however, few studies have either synthesized existing studies or drawn an overarching picture of this sub-discipline. This study delineates the intellectual development of HCI research in MIS by a multifaceted assessment of the published HCI articles over a period of 13 years (1990-2002) in seven prime MIS journals: MISQ, ISR, JMIS, Decision Sciences, Management Science, DATA BASE, and JAIS. Twenty-two specific questions are addressed to answer the following five general research questions about the HCI sub-discipline: (1) What constitutes its intellectual substance? (2) What relationships does it have with other disciplines? (3) What are its recent evolutions? (4) What are the patterns of publishing HCI studies in the primary MIS journals? And, (5) Who are its contributing members? We use classification approach to address these questions. Descriptive analyses, including co-occurrence and cross-facet analyses, depict the key relationships. Trend analyses demonstrate recent evolutions. We present number of areas for future research, along with a discussion of potential future directions for the sub-discipline. This study should be of interest to researchers in this sub-discipline, in the MIS discipline, and in other related disciplines for future research, collaboration, publication, and education. It should also be of interest to doctoral students to identify potential research topics for dissertation research and to identify academic institutions for future employment where such research is understood, appreciated, and encouraged

On Quality and Communication: The Relevance of Critical Theory to Health Informatics

Health information systems require long-term investment before they provide a socio-economic return, yet their implementation remains problematic, possibly because the claims made about them appear not to sit well with healthcare professionals’ practice. Health informatics should address these issues from a sound conceptual base, such as might be provided by critical theory, which seeks to identify hidden assumptions and ideologies. This discipline can provide a better understanding of the inner workings of socio-technical systems, with a view to improving them through the promotion of emancipation (allowing people to fulfill their potential). Critical theory can also shed light on the problems with health information systems and offer insight into remedies, for example, by relating Habermas’ theories about communication to feedback, a concept central to quality assurance (QA). Such analysis finds that QA’s principal practices can be interpreted as emancipatory but requires organizations to substantially change their behavior. An alternate approach is to install health information systems designed to support QA. Applying critical theory to these systems shows that they could become an active part of service delivery rather than static repositories of data, because they may encourage standardized conversations between all stakeholders about the important features of health care. Success will depend on access for all participants to data entry and analysis tools, integration with work practice, and use by staff and management in QA. These ideas offer new directions for research into and the development of health information systems. The next step will be to implement them and observe their technical and emancipatory properties

The ethical, legal and social implications of using artificial intelligence systems in breast cancer care

Breast cancer care is a leading area for development of artificial intelligence (AI), with applications including screening and diagnosis, risk calculation, prognostication and clinical decision-support, management planning, and precision medicine. We review the ethical, legal and social implications of these developments. We consider the values encoded in algorithms, the need to evaluate outcomes, and issues of bias and transferability, data ownership, confidentiality and consent, and legal, moral and professional responsibility. We consider potential effects for patients, including on trust in healthcare, and provide some social science explanations for the apparent rush to implement AI solutions. We conclude by anticipating future directions for AI in breast cancer care. Stakeholders in healthcare AI should acknowledge that their enterprise is an ethical, legal and social challenge, not just a technical challenge. Taking these challenges seriously will require broad engagement, imposition of conditions on implementation, and pre-emptive systems of oversight to ensure that development does not run ahead of evaluation and deliberation. Once artificial intelligence becomes institutionalised, it may be difficult to reverse: a proactive role for government, regulators and professional groups will help ensure introduction in robust research contexts, and the development of a sound evidence base regarding real-world effectiveness. Detailed public discussion is required to consider what kind of AI is acceptable rather than simply accepting what is offered, thus optimising outcomes for health systems, professionals, society and those receiving care

Fog Computing: A Taxonomy, Survey and Future Directions

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a great extent. To support the computational demand of real-time latency-sensitive applications of largely geo-distributed IoT devices/sensors, a new computing paradigm named "Fog computing" has been introduced. Generally, Fog computing resides closer to the IoT devices/sensors and extends the Cloud-based computing, storage and networking facilities. In this chapter, we comprehensively analyse the challenges in Fogs acting as an intermediate layer between IoT devices/ sensors and Cloud datacentres and review the current developments in this field. We present a taxonomy of Fog computing according to the identified challenges and its key features.We also map the existing works to the taxonomy in order to identify current research gaps in the area of Fog computing. Moreover, based on the observations, we propose future directions for research

Information Technology Platforms: Definition and Research Directions

The concept of an information technology (IT) related platform is broad and covers phenomena ranging from the operating system Linux to the Internet. Such platforms are of increasing importance to innovation and value creation across many facets of industry and daily life. There is, however, a lack of common understanding in both research and industry about what is mean by the term platform when related to IT. This lack of consensus is detrimental to research and knowledge development. Thus, the aims of this study are to: (i) provide a sound definition of the IT-platform concept by identifying its distinguishing dimensions; and (ii) identify important current research directions for the IT-platform concept. To achieve these aims a systematic literature review was undertaken with 133 relevant articles taken from major information systems journals, conferences, and business publications. The study contributes by providing a sound base for future research into IT-platforms.Comment: Research-in-progress ISBN# 978-0-646-95337-3 Presented at the Australasian Conference on Information Systems 2015 (arXiv:1605.01032

New Directions in Compensation Research: Synergies, Risk, and Survival

We describe and use two theoretical frameworks, the resource-based view of the firm and institutional theory, as lenses for examining three promising areas of compensation research. First, we examine the nature of the relationship between pay and effectiveness. Does pay typically have a main effect or, instead, does the relationship depend on other human resource activities and organization characteristics? If the latter is true, then there are synergies between pay and these other factors and thus, conclusions drawn from main effects models may be misleading. Second, we discuss a relatively neglected issue in pay research, the concept of risk as it applies to investments in pay programs. Although firms and researchers tend to focus on expected returns from compensation interventions, analysis of the risk, or variability, associated with these returns may be essential for effective decision-making. Finally ,pay program survival, which has been virtually ignored in systematic pay research, is investigated. Survival appears to have important consequences for estimating pay plan risk and returns, and is also integral to the discussion of pay synergies. Based upon our two theoretical frameworks, we suggest specific research directions for pay program synergies, risk, and survival

Modeling of the decision-supporting process on the possibility of concluding the contract on the therapeutic services provision. РОЗВИТОК АРХІТЕКТУР, ТЕОРЕМ ТА МОДЕЛЕЙ ВЛАСТИВОСТЕЙ РОЗПОДІЛЕНИХ СИСТЕМ ЗБЕРІГАННЯ ІНФОРМАЦІЇ

Today, we live in the world of information technologies, which have penetrated into all possible spheres of human activity. Recent developments in database management systems have coincided with advances in parallel computing technologies. In view of this fact, a new class of data storage has appeared, namely globally distributed non-relational database management systems, and they are now widely used in Twitter, Facebook, Google and other modern distributed information systems to store and process huge volumes of data. Databases have undergone a certain evolution from mainframe architecture to globally distributed non-relational repositories designed to store huge amounts of information and serve millions of users. The article indicates the drivers and prerequisites of this development, and also considers the transformation of models of properties of database management systems and theorems that formalize the relationship between them. In particular, the conditionality of the transition from the ACID property model to the BASE model is considered, which relaxes the requirements for data consistency, which is necessary to ensure the high performance of distributed databases with many replicas. In addition, a concise justification of the SAR and PACELC theorems, which establish mutually exclusive relationships between availability, consistency, and speed in replicated information systems, is provided, and their limitations are analyzed. The compatibility issues of the consistency models used by different non-relational data stores are noted, and, as an example, the possible consistency settings of the NoSQL databases Cassandra, MongoDB, and Azure CosmosDB are discussed in detail. The results of the evolution of distributed database architectures are summarized using the GSN (Goal Structuring Notation). Further directions of scientific research and ways of further developing globally distributed information systems and data repositories are also outlined