The Trajectory of IT in Healthcare at HICSS: A Literature Review, Analysis, and Future Directions

Research has extensively demonstrated that healthcare industry has rapidly implemented and adopted information technology in recent years. Research in health information technology (HIT), which represents a major component of the Hawaii International Conference on System Sciences, demonstrates similar findings. In this paper, review the literature to better understand the work on HIT that researchers have conducted in HICSS from 2008 to 2017. In doing so, we identify themes, methods, technology types, research populations, context, and emerged research gaps from the reviewed literature. With much change and development in the HIT field and varying levels of adoption, this review uncovers, catalogs, and analyzes the research in HIT at HICSS in this ten-year period and provides future directions for research in the field

Big Data and Analytics: Issues and Challenges for the Past and Next Ten Years

In this paper we continue the minitrack series of papers recognizing issues and challenges identified in the field of Big Data and Analytics, from the past and going forward. As this field has evolved, it has begun to encompass other analytical regimes, notably AI/ML systems. In this paper we focus on two areas: continuing main issues for which some progress has been made and new and emerging issues which we believe form the basis for near-term and future research in Big Data and Analytics. The Bottom Line: Big Data and Analytics is healthy, is growing in scope and evolving in capability, and is finding applicability in more problem domains than ever before

Too old to Shop? A Comparative Analysis of the Engagement of Junior and Senior Customers in Social Commerce

With the continuous success of social media websites also social commerce rises in popularity. As increasing numbers of elderly consumers use social media, it is interesting to understand how elderly consumers engage in social commerce platforms. This study examines how different dimensions of customer engagement influence trust with young and older consumers. A survey was conducted to collect data from American consumers. Our results show that perceived enjoyment, satisfaction, and social commerce value have significant effects on consumers’ trust. Further, there are important differences regarding the respective effects between younger and older consumers. Our study contributes to the literature by clarifying the effect of customer engagement on trust in social commerce between young and elderly consumers. Our results can provide practitioners important guidelines regarding how to support consumers’ trust development in social commerce

Too old to Shop? A Comparative Analysis of the Engagement of Junior and Senior Customers in Social Commerce

With the continuous success of social media websites also social commerce rises in popularity. As increasing numbers of elderly consumers use social media, it is interesting to understand how elderly consumers engage in social commerce platforms. This study examines how different dimensions of customer engagement influence trust with young and older consumers. A survey was conducted to collect data from American consumers. Our results show that perceived enjoyment, satisfaction, and social commerce value have significant effects on consumers’ trust. Further, there are important differences regarding the respective effects between younger and older consumers. Our study contributes to the literature by clarifying the effect of customer engagement on trust in social commerce between young and elderly consumers. Our results can provide practitioners important guidelines regarding how to support consumers’ trust development in social commerce

The Tale of e-Government: A Review of the Stories that Have Been Told So Far and What is Yet to Come

Since its first appearance, the concept of e-Government has evolved into a recognized means that has helped the public sector to increase its efficiency and effectiveness. A lot of research has therefore been done in this area to elaborate on the different aspects encompassing this concept. However, when looking at the existing e-Government literature, research mostly focuses on one specific aspect of e-Government and there are few generic publications that provide an overview of the diversity of this interdisciplinary research field over a longer term period. This study analyzes the abstracts of eight e-Government journals from 2000 to 2016 by means of a quantitative text mining analysis, backed by a qualitative Delphi approach. The article concludes with a discussion on the findings and implications as well as directions for future research

High-performance Diagnosis of Sleep Disorders: A Novel, Accurate and Fast Machine Learning Approach Using Electroencephalographic Data

While diagnosing sleep disorders by physicians using electroencephalographic data is protracted and inaccurate, we report promising results from a novel, fast and reliable machine learning approach. Our approach only needs an electroencephalographic recording snippet of 10 minutes instead of eight hours to correctly classify the disorder with an accuracy of over 90 percent. The Rapid Eye Movement sleep behavior disorder can lead to secondary diseases like Parkinson or Dementia. Therefore, it is important to classify the disorder fast and with a high level of accuracy - which is now possible with our approach

Development of a Machine Learning Based Algorithm To Accurately Detect Schizophrenia based on One-minute EEG Recordings

While diagnosing schizophrenia by physicians based on patients' history and their overall mental health is inaccurate, we report on promising results using a novel, fast and reliable machine learning approach based on electroencephalography (EEG) recordings. We show that a fine granular division of EEG spectra in combination with the Random Forest classifier allows a distinction to be made between paranoid schizophrenic (ICD-10 F20.0) and non-schizophrenic persons with a very good balanced accuracy of 96.77 percent. We evaluate our approach on EEG data from an open neurological and psychiatric repository containing 499 one-minute recordings of n=28 participants (14 paranoid schizophrenic and 14 healthy controls). Since the fact that neither diagnostic tests nor biomarkers are available yet to diagnose paranoid schizophrenia, our approach paves the way to a quick and reliable diagnosis with a high accuracy. Furthermore, interesting insights about the most predictive subbands were gained by analyzing the electroencephalographic spectrum up to 100 Hz

Open Data Diffusion for Service Innovation: An Inductive Case Study on Cultural Open Data Services

Information Systems research on Open Data has been primarily focused on its contribution to e-government inquiries, government transparency, and open government. Recently, Open Data has been explored as a catalyser for service innovation as a consequence of big claims around the potential of such initiatives in terms of additional value that can be injected into the worldwide economy. Subsequently, the Open Data Services academic conversation was structured (Lindman et al. 2013a). The research project presented in this paper is an interpretive case study that was carried out to explore the factors that influence the diffusion of Open Data for new service development. This paper contributes to this debate by providing an interpretive inductive case study (Walsham 1995) of a tourism company that successfully turned several city authorities’ raw open datasets into a set of valuable services. Results demonstrate that 16 factors and 68 related variables are the most relevant in the process of diffusion of open data for new service development. Furthermore, this paper demonstrates the suitability of Social Constructionism and interpretive case study research to inductively generate knowledge in this field

Governance of Offshore IT Outsourcing at Shell Global Functions IT-BAM Development and Application of a Governance Framework to Improve Outsourcing Relationships

The lack of effective IT governance is widely recognized as a key inhibitor to successful global IT outsourcing relationships. In this study we present the development and application of a governance framework to improve outsourcing relationships. The approach used to developing an IT governance framework includes a meta model and a customization process to fit the framework to the target organization. The IT governance framework consists of four different elements (1) organisational structures, (2) joint processes between in- and outsourcer, (3) responsibilities that link roles to processes and (4) a diverse set of control indicators to measure the success of the relationship. The IT governance framework is put in practice in Shell GFIT BAM, a part of Shell that concluded to have a lack of management control over at least one of their outsourcing relationships. In a workshop the governance framework was used to perform a gap analysis between the current and desired governance. Several gaps were identified in the way roles and responsibilities are assigned and joint processes are set-up. Moreover, this workshop also showed the usefulness and usability of the IT governance framework in structuring, providing input and managing stakeholders in the discussions around IT governance