25+ Years of Business Intelligence and Analytics Minitrack at HICSS: A Text Mining Analysis

This research project is inspired by the occasion of the 50th anniversary of the Hawaii International Conferences on Systems Sciences (HICSS). As the current co-chairs of the longest-running minitrack on Business Intelligence (BI), Business Analytics (BA) and Big Data (as it is currently known) at HICSS, we report on its 27-year history of relevant and interesting research. Our insights into the key research themes and their progress over time were obtained through a semantic text mining of all research publications included in this minitrack since 1990. We also illustrate a practical method of using a sophisticated text-mining tool (Leximancer) so that it could be replicated by other researchers interested in content analysis methods in other research fields

Introduction to Data, Text and Web Mining for Business Analytics Minitrack

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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

A Bibliometric Analysis of the HICSS Software Technology Track

The HICSS Software Technology track has a long tradition and many papers have been published as part of its history. Its impact in terms of citations, paper contributions, author share and community impact does not yet seem to have been investigated, though. In particular, software technology has evolved, and as it stands, it is of primary importance for mobile computing, the Internet-of-Things and Cyber-physical Systems. Hence, the development of these topics and the related impact of this track are of particular interest. In this paper, we present a bibliographic analysis as a first step towards such an investigation. We found that the history of the track is indeed noteworthy. Our results include finding a few extremely much cited papers, some curious tendencies, and a generally favourable outlook for HICSS. We found that indeed many papers in the history of this HICSS track addressed mobile technology and are highly cited. Together with providing insight into track, paper and author impact, we also raise questions worth of further investigation to understand the role of the HICSS Software Technology track and its impact on the academic field and society

Knowledge, Innovation, and Entrepreneurial Systems at HICSS

This paper presents an overview and history of the knowledge, innovation, and entrepreneurial systems (KIES) track and the knowledge and related systems research community at the Hawaii International Conference on System Sciences (HICSS). This community began as a task force that examined organizational memory in HICSS-27. It has since evolved into a mini-track, a research cluster, and, finally, a full research track that encompasses research knowledge, innovation, and entrepreneurial systems. In this paper, we acquaint knowledge system researchers with a research community that has leveraged HICSS to develop a rich history of high-quality scholastic inquiry in the knowledge system, knowledge management, innovation systems, entrepreneurial systems, organizational memory, and organizational learning research areas

Business Analytics Capabilities for Organisational Resilience

Nowadays, organizations are facing unique challenges created by different disruptions, including natural disasters, new technologies, regulatory changes, and more recently, a global pandemic. Consequently, the need to build, sustain, and continuously enhance Organizational Resilience (OR) is greater than ever. An ongoing process of building OR requires high-quality data and business analytics (BA) capabilities. In this paper we aim to investigate the yet-to-be explored link between BA and OR. We achieve this aim by conducting a multidisciplinary literature review on OR and BA, focusing on BA capabilities for OR. Based on our findings, we then propose a conceptual framework of BA capabilities for OR. In doing so, we also bring a well-established area of OR to the attention of BA researchers, as a critically important area for further BA research and practice

Cluster Analysis in Online Learning Communities: A Text Mining Approach

This paper presents a theory-informed blueprint for mining unstructured text data using mixed- and multi-methods to improve understanding of collaboration in asynchronous online discussions (AOD). Grounded in a community of inquiry theoretical framework to systematically combine established research techniques, we investigated how AOD topics and individual reflections on those topics affect formation of clusters or groups in a community. The data for the investigation came from 54 participants and 470 messages. Data analysis combined the analytical efficiency and scalability of topic modeling, social network analysis, and cluster analysis with qualitative content analysis. The cluster analysis found three clusters and that members of the intermediate cluster (i.e., middle of three clusters) played a pivotal role in this community by expressing uncertainty statements, which facilitated a collective sense-making process to resolve misunderstandings. Furthermore, we found that participants’ selected discussion topics and how they discussed those topics influenced cluster formations. Theoretical, practical, and methodological implications are discussed in depth