AJIS Section Release: The Australasian Journal of Information Systems (AJIS) has just published 4 new articles in its Volume 28 Research Article section

Australasian Journal of Information Systems — 2024-05-15

The Australasian Journal of Information Systems (AJIS) has just published four new articles in its Research Article section of its volume 28:

(Why) Do We Trust AI?: A Case of AI-based Health Chatbots

Ashish Viswanath Prakash, Saini Das

ashish@iimtrichy.ac.in

doi: https://doi.org/10.3127/ajis.v28.4235

Automated chatbots powered by artificial intelligence (AI) can act as a ubiquitous point of contact, improving access to healthcare and empowering users to make effective decisions. However, despite the potential benefits, emerging literature suggests that apprehensions linked to the distinctive features of AI technology and the specific context of use (healthcare) could undermine consumer trust and hinder widespread adoption. Although the role of trust is considered pivotal to the acceptance of healthcare technologies, a dearth of research exists that focuses on the contextual factors that drive trust in such AI-based Chatbots for Self-Diagnosis (AICSD). Accordingly, a contextual model based on the trust-in-technology framework was developed to understand the determinants of consumers’ trust in AICSD and its behavioral consequences. It was validated using a free simulation experiment study in India (N = 202). Perceived anthropomorphism, perceived information quality, perceived explainability, disposition to trust technology, and perceived service quality influence consumers’ trust in AICSD. In turn, trust, privacy risk, health risk, and gender determine the intention to use. The research contributes by developing and validating a context-specific model for explaining trust in AICSD that could aid developers and marketers in enhancing consumers’ trust in and adoption of AICSD.

Sociotechnical perspectives of digital technologies in sustainable mining

Warren Gabryk, Rennie Naidoo

wgabryk@tuks.co.za

doi: https://doi.org/10.3127/ajis.v28.4369

This paper adopts an interpretive case study approach to understand the role of digital technologies in addressing seemingly contradictory sustainability goals in mining. The sociotechnical model of information systems was used as a framework to guide the analysis of twenty-five in-depth interviews with globally dispersed digital technology experts working collaboratively at an industry-leading hi-tech mining solutions company. The sociotechnical-led thematic analysis findings highlight the trade-offs experts face in balancing narrow technological imperatives and economic outcomes with broader sustainability goals. The analysis moves beyond the technological and economic to a harmonious perspective of social, human, environmental, and technological interactions. A visual thematic map is presented to aid practitioners in designing and optimally implementing digital technologies to simultaneously address the United Nations Sustainable Development Goals while prioritising business sustainability. We conclude by drawing from the proposed sociotechnical perspectives approach for digital sustainability to provide scholars with possible pathways for future responsible information systems research.

Machine Learning Based Decision-Making: A Sensemaking Perspective

Jingqi (Celeste) Li, Morteza Namvar, Ghiyoung P. Im, Saeed Akhlaghpour

m.namvar@business.uq.edu.au

doi: https://doi.org/10.3127/ajis.v28.4781

The integration of machine learning (ML), functioning as the core of various artificial intelligence (AI)-enabled systems in organizations, comes with the assertion that ML models offer automated decisions or assist domain experts in refining their decision-making. The current research presents substantial evidence of ML’s positive impact on business and organizational performance. Nonetheless, there is a limited understanding of how decision-makers participate in the process of generating ML-driven insights and enhancing their comprehension of business environments through ML outcomes. To enhance this engagement and understanding, this study examines the interactive process between decision-makers and ML experts as they strive to comprehend an environment and gather business insights for decision-making. It builds upon Weick’s sensemaking model by integrating ML’s pivotal role. By conducting interviews with 31 ML experts and ML end-users, we explore the dimensions of sensemaking in the context of ML utilization for decision-making. Consequently, this study proposes a process model which advances the organizational ML research by operationalizing Weick’s work into a structured ML-driven sensemaking model. This model charts a pragmatic pathway, outlining the interaction sequence between decision-makers and ML tools as they navigate through recognizing and utilizing ML, exploring opportunities, assessing ML model outcomes, and translating ML models into action, thereby advancing both the theoretical framework and its practical deployment in organizational contexts.

“Use” as a Conscious Thought: Towards a Theory of “Use” in Autonomous Things

Gohar Khan, A Karim Feroz

karim.feroz@mga.edu

doi: https://doi.org/10.3127/ajis.v28.4611

The way users perceive and use information systems artefacts has been mainly studied from the notion of behavioral beliefs, deliberate cognitive efforts, and physical actions performed by human actors to produce certain outcomes. The next generation of information systems, however, can sense, respond, and adapt to environments without necessitating similar cognitive efforts, physical contact, or explicit instructions to operate. Therefore, by leveraging theories of consciousness and technology use, this research aims to advance an alternative understanding of the "use" associated with the next generation of IS artefacts that do not require deliberate cognitive efforts, physical manipulation, or explicit instructions to yield outcomes. The theory and proposed model were refined and validated through the burst detection technique, IS expert involvement (n=10), a pilot study (n=130), and end-user surveys (n= 119). Structural equating modelling techniques were employed to test the theory. We show that unlike the manually operated IS artefacts, the “use” of a fully autonomous artefact is a conscious thought rather than a physical activity of operating a system to produce certain outcomes. We argue that, unlike the traditional notions of use associated with manually operated technologies, conscious use is not characterized solely by behavioral beliefs stemming from logical and reflective cognitive and physical efforts (e.g., effort expectancy). We propose the notion of conscious use within the context of fully autonomous entities and empirically validate its measure. Additionally, we offer recommendations for future research directions in this area. The conceptualization of this new theory for fully autonomous IS artefacts adds significant academic value to the literature given the convergence of AI-based machine learning systems and cognitive computing systems.

AJIS Improvement: AJIS RSS/ATOM feed

Australasian Journal of Information Systems — 2015-11-12

You will now find an RSS/ATOM link box on the home page. Subscribe your outlook or other equipped email clinet and automatically receive advice of new articles.

AJIS Improvement: Automatic update of ORCID publication records

Australasian Journal of Information Systems — 2015-10-07

What this means for researchers More visibility for your work! AJIS supplies crossref with your ORCID identifier when registering publications ... as long as you have your ORCID details in your author record. This auto-update facility simply means that when we include the info crossref can update and add work(s) to your ORCID record automatically for you. You can still choose to hide/show whatever works you choose, and, of course, you’ll have the opportunity to authorize or switch off the integration completely (though future publications may trigger a new request). Overall, you’ll benefit from a more complete and up-to-date ORCID record to showcase your work.

AJIS Reviews: How to respond to reviewer comments

Australasian Journal of Information Systems — 2015-01-28

Responding to peer reviewer comments requesting for major revisions is indeed a daunting task for most authors! Although this requires a lot of effort, it contributes to improving your paper, making it worthwhile. This video provides some useful tips that will help you respond to peer reviewer comments effectively. http://www.editage.com/insights/how-to-respond-to-peer-reviewer-comments This video is provided by Editage Insights under a CC:BY-NC-SA license.

Tips for Avoiding Plagiarism

Australasian Journal of Information Systems — 2014-08-21

The RCC statement describes and clarifies some of the more common issues which give rise to allegations of scholarly misconduct. We strongly recommend that you read and distribute this statement.

AJIS Reviews: Advice on writing rejections

Australasian Journal of Information Systems — 2014-01-29

This is an interesting article which provides some advice on writing a high quality rejection. Bilbrey, E., et al. (2014). "A Novel Rubric for Rating the Quality of Retraction Notices." Publications 2(1): 14-26. When a scientific article is found to be either fraudulent or erroneous, one course of action available to both the authors and the publisher is to retract said article. Unfortunately, not all retraction notices properly inform the reader of the problems with a retracted article. This study developed a novel rubric for rating and standardizing the quality of retraction notices, and used it to assess the retraction notices of 171 retracted articles from 15 journals. Results suggest the rubric to be a robust, if preliminary, tool. Analysis of the retraction notices suggest that their quality has not improved over the last 50 years, that it varies both between and within journals, and that it is dependent on the field of science, the author of the retraction notice, and the reason for retraction. These results indicate a lack of uniformity in the retraction policies of individual journals and throughout the scientific literature. The rubric presented in this study could be adopted by journals to help standardize the writing of retraction notices.

Australasian Journal of Information Systems: Announcements

AJIS Section Release: The Australasian Journal of Information Systems (AJIS) has just published 4 new articles in its Volume 28 Research Article section

AJIS Improvement: AJIS RSS/ATOM feed

AJIS Improvement: Automatic update of ORCID publication records

AJIS Reviews: How to respond to reviewer comments

Tips for Avoiding Plagiarism

AJIS Reviews: Advice on writing rejections