Global Review and Negative Citation System

In an age of exponential research growth and digital dissemination, maintaining the quality and integrity of academic publishing has become increasingly challenging, particularly in the technology and information systems domains. Rising submission volumes, constrained reviewer capacity, and mounting concerns about plagiarism, bias, and unethical authorship practices strain traditional peer review models. Moreover, the lag between submission and publication can leave innovative ideas vulnerable to unauthorized use, especially when rejected manuscripts are inadequately protected. This study introduces a technology-enabled, multi-phase framework that integrates two core concepts: the Global Review model and the Negative Citation mechanism. The Global Review model advocates for an interdisciplinary, semi-open peer review process that combines traditional editorial oversight with transparent, structured dialogue among verified reviewers. Drawing inspiration from existing open peer review systems (e.g., OpenReview, JOSS), our approach enhances accountability through threaded reviewer discussions, dynamic accreditation of reviewers, and flexible options for identity disclosure based on context and risk. An editorial moderation layer is embedded to counterbalance crowd-sourced decision-making, ensuring nuanced evaluations rather than binary up/down voting. The Negative Citation mechanism, while still in development, is conceptualized not as a punitive tool but as a method for post-publication quality monitoring. It provides a formal process for documenting well-substantiated critiques of published work, encouraging methodological rigor, and deterring malpractices without suppressing academic risk-taking. Recognizing ethical concerns, the system includes safeguards such as dispute resolution pathways, structured reporting guidelines, and independent ethical review panels. Grounded in the principles of open science, this model builds on and differentiates itself from existing platforms by emphasizing scalability, reviewer inclusivity, and balanced oversight. This paper critically engages with current literature and platforms, highlights challenges with reviewer incentives, and proposes a phased pilot implementation in conference tracks or special issues to evaluate feasibility and impact. We argue that this integrated framework can foster a more transparent, timely, and ethical research culture—one that not only protects the originality of ideas but also rebuilds trust in the academic publishing system

Experiential Learning in the Metaverse: Implications for Workplace Training

In an era of rapid technological advancement and shifting work modes, the need for innovative, effective, and scalable corporate training solutions has become increasingly important. This paper explores how the Metaverse can serve as a transformative environment offering more personalised, engaging, and effective training experiences. Drawing on Kolb’s Experiential Learning Theory (ELT), the study examines how the elements of the Metaverse — such as immersion, interactivity, and persistence — can enhance skill acquisition, knowledge retention, employee engagement, and organisational learning outcomes. Through the analysis of nine case studies across sectors (telecommunications, retail, hospitality, manufacturing, consulting and social services), we identify three dominant models of Metaverse-based training: risk-free learning environments, digital twin integration, and immersive skill development platforms. The findings highlight the ability of these training programs to enable experiences that support both technical and interpersonal skill development. Benefits include reduced training time, increased learner satisfaction, improved performance metrics, and global scalability. However, successful implementation is contingent upon addressing critical challenges including infrastructure demands, content development, accessibility, employee adaptation, health implications, and ethical concerns such as data privacy and inclusivity

The Role Of Repair In Healthcare Infrastructures: A Case Study Of A Large-Scale Product Acquisition

In this paper, we explore how infrastructures are repaired following abrupt breakdowns triggered by large product acquisitions. Contemporary digitalization processes often involve the acquisition of off-the-shelf products and the sudden replacement of significant portions of the infrastructure. As illustrated in our empirical case, these abrupt transitions require costly, long-lasting, and often unanticipated repair efforts. Through an exploratory case study, we investigate the acquisition and implementation of a large healthcare system in Norway. Our findings highlight the challenges of infrastructure repair, particularly the chaotic and counterproductive nature of initial repair activities. Actors spend a significant amount of time mobilizing the management of repair tasks. While repair is highly collaborative, our study also reveals its competitive aspects. By shedding light on the complexities and challenges of repair in contemporary digitalization processes, our findings contribute to a deeper understanding of the dynamics of repair efforts

Collaborative Writing and Information Systems Curriculum in the Age of AI: Research-in-Progress

Since the fall of 2022, generative artificial intelligence (AI) tools have transformed teaching and learning. Faculty in the age of AI are challenged to design learning experiences that both engage students in the classroom and result in an increase in student knowledge and skills development. Information Systems (IS) programs are particularly challenged to equip students with both technical and soft skills necessary to succeed in workplaces that will increasingly utilize AI. Collaborative learning experiences offer one possible opportunity to the challenges presented by generative AI tools. Therefore, this work seeks to examine student perceptions of multimodal collaborative writing in the age of AI. Specifically, this research-in-progress outlines a plan for the design of IS course work and activities that require the adoption of multimodal collaborative writing as a part of classwork as well as plans to learn more about how to engage students with course concepts and soft skills development through written communication in the time of generative AI. The findings of this research-in-progress work should have important implications for both education and research

Foundations of Practical Analytic Skills: An Examination of Undergraduate Business Students’ Self-Efficacy Using Excel

Microsoft Excel remains the primary spreadsheet software for numerical processing, computation, data analytics, and reporting in business schools across the United States. Given that Excel proficiency is a critical competency for business graduates, it also remains imperative that Excel skills are addressed as an essential component of the undergraduate business curriculum. Furthermore, Excel skills are also a critical issue in Information Systems education due to Excel’s widespread use in end-user computing for business analytics and reporting. This study applies Bandura’s self-efficacy theory to investigate how students’ self-assessment of their Excel skills influences their confidence in solving business problems with Excel. A total of 113 undergraduate business students completed surveys which measured perceived Excel skills and self-efficacy. The study employed both qualitative and quantitative methods to analyze the findings. T-tests results revealed significant gender differences in Excel usage. Furthermore, differences in Excel proficiency were found among students in face-to-face and online courses. Multiple regression analysis showed a positive correlation between higher self-rated Excel skills, job-related Excel performance, and overall self-efficacy in using Excel. The findings offer implications for educators to further understand and enhance students’ Excel self-efficacy within the business curriculum as a principal tool for quantitative and analytical reasoning

A FRAMEWORK FOR DATA SPACE ADOPTION INTEGRATING DATA SOVEREIGNTY AS A TECHNICAL FACTOR

Digital transformation allows organizations to increase data transparency, but unfortunately, organizations still encounter obstacles to data sharing as they fear the loss of control over data. Data spaces as cross-organizational data infrastructures can potentially enhance organizations\u27 control over their data. However, the adoption of data spaces has yet to be fully investigated. Therefore, this study attempts to address this gap by applying a Design Science Research (DSR) approach for developing an artefact to support the adoption of data spaces. We designed and evaluated the framework through expert interviews. As a result, we propose a final data space adoption framework comprising 14 factors originating from the Technological-Organizational-Environment (TOE) framework. The framework contributes to the existing body of knowledge regarding influencing factors and supports the adoption of data spaces integrating data sovereignty within organizations