[AISWorld] Journal of IT Case and Application Research (JITCAR) Issue 22.3 now published

[Bansal, Gaurav]

It is my pleasure to present the third Journal of IT Case and Application Research (JITCAR) issue of the year 2020. JITCAR was founded in 1999 by Prof. Shailendra Palvia. This journal serves an important mission of publishing case-based research on applying information technology and information systems to organizational problems. Prof. Palvia, as a visionary, recognized early on the importance of case-based research and positioned JITCAR to address this important void by providing an outlet to promote and publish case-based research in the IT area.

This is the first issue in my editorship. I am honored to have been given this opportunity to serve as the Editor-in-Chief of JITCAR. Thanks to the outstanding work of outgoing editor Dr. Shailendra Palvia, I inherit a strong publication well-positioned for continued development and success. Dr. Palvia has guided JITCAR through numerous positive changes, oversaw substantial growth in the number of high-quality submissions, and attained a significant rise in the journal's visibility. JITCAR is recognized by the Australian Business Dean's Council and also included in the SCOPUS index. I thank him for his immensely valuable contribution to the JITCAR, and I am pleased he will remain on the Advisory Editorial Board to provide continued guidance as I pick up the pace.

I am grateful for the confidence placed in me by the Search Committee and for the support from the Editorial Board. I will work closely with our strong team of advisory editors, senior associate editors and global associate editors, our industry and book editors, our excellent global editorial review board, and reviewers to strengthen the journal's quality. I will work to further our team's efforts in positioning the JITCAR as a leading IT case study journal that is scientifically rigorous and academically relevant; and useful to academicians and practitioners.

The contents of this issue (22.3) are Editorial Preface article by Xin Xie, Keng Siau, and Fiona Fui-Hoon Nah; Research Case Article-1 coauthored by Wei Xie, Nikhil Mehta, and Prashant Palvia; Research Case Article-2 coauthored by Joe Flanagan, Gareth Huw Davies, Frederic Boy, and Daniele Doneddu; Expert Opinion report by Anshuman Tripathi; and Book Review by Bryan J. Hosack. The summary information on these items is as follows.



In the editorial preface article titled, "COVID-19 Pandemic - Online Education in the New Normal and the Next to Normal Centralization and Decentralization in ICT: Duality and Complementarity", the authors focus on explaining how the global COVID-19 pandemic has created a new normal that has enhanced opportunities for large scale implementation of online education. The authors argue that online education has its advantages and limitations as well. However, they suggest that by incorporating artificial intelligence and mobile education, online education will co-exist with traditional education to provide more education options, promote education equity, and enhance education innovation.



In the research case article-1 titled, "Value Co-Creation (VCC) Dimensions and Challenges in EHR Systems," the authors use the qualitative case study methodology to get an in-depth understanding of value co-creation in EHR systems. The authors gathered value co-creation perspectives of different business-unit heads within a large hospital system to identify the key values reciprocally co-created along with the challenges facing the implementation of EHR systems in a multi-unit EHR environment. The study provides a conceptual framework highlighting five VCC dimensions of EHR in multi-unit environments: system & data, information, process, relationship, and regulation.



In the research case article-2 titled "A Review of a Distributed High-Performance Computing Implementation," the authors present the case of Welsh Government, academia, and other regional stakeholders working together to realize a shared High-Performance Computing Wales (HPCW) system. The authors provide a smart specialization theory based on principles of public sector investment guidelines. The study also offers helpful guidelines for practitioners by highlighting important steps involved in the appraisal, monitoring, and evaluation of such initiatives.



The Expert Opinion report explores real hardware trojans' (HTs) economics, including examples from the Syrian radar breach to iPhone trojans sold on Amazon.com. The author Mr. Anshuman Tripathi, a Sloan-Fellow, argues that this is a highly under-research area. This paper provides rationale and examples and puts forth a case that only hybrid trojans are viable in the wild. The article also argues that in the current geopolitical context where data reigns supreme, all cyberattacks occur either for data/IP theft, a priority over trojan insertion, or insert HTs to facilitate control and data exfiltration.



Book review report by Bryan Hosack provides detailed coverage of the book titled, "You Look Like a Thing and I Love You: How Artificial Intelligence Works and Why It is Making the World a Weirder Place," authored by Janelle Shane in 2019. This book provides examples of how ML is currently used and potential pitfalls encountered as organizations rely more and more on ML to aid decision-making. Bryan's review effectively summarizes the book and highlights the five key principles of AI weirdness that Shane structures the book around - the danger of AI is not that it is too smart but that it is not smart enough; AI has the approximate brainpower of a worm; AI does not understand the problem you want to solve; But: AI will do exactly what you tell it to, or at least it will try its best, And AI will take the path of least resistance. The book provides an engaging introduction to AI and, more importantly, how it "thinks." Bryan suggests that the book's strengths are in an appropriate mix of technical detail coupled with examples that anyone can follow. Bryan further contends that the book delivers insight into how to effectively deploy AI and cautions against the key biases to watch out for when training an ML algorithm.





Respectfully,



Gaurav Bansal


______________________________________________________________
Gaurav Bansal, Ph.D.
Frederick E. Baer Professor of Business & Professor of MIS/Statistics
Association for Information Systems (AIS) Distinguished Member
Editor-in-Chief, Journal of IT Case and Application Research
UW-Green Bay
www.uwgb.edu/bansalg

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