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Developing a Smart City Data Literacy Framework: Strategies for Mitigating Supply Chain Software Risks
Full text linkIt is broadly recognized that supply chain software data outputs lead to unauthorized network compromises (Enck & Williams, 2022) (Charles et al., 2023). Nevertheless, data generated by emergency management services (EMS), fire and public safety, and public healthcare supply chain software platforms present serious risks to the Smart City reliability. To survive, policymakers, Chief Information Security Officers (CISOs), Chief Data Officers (CDOs), and Information Security (InfoSec) scholars must rely on a constantly evolving Smart City workforce to identify potential InfoSec threats. The purpose of this study is to introduce a Smart City data literacy framework focused on identifying potential supply chain data compromises. The theoretical foundation of this paper is built on data literacy critical success factors, enterprises roles, and technology threat avoidance theories. This research establishes several pillars by comparing and contrasting data literacy competency principles across Federal Chief Information Officers Council (CIOC) agencies. Moreover, this study contributes to the InfoSec body of knowledge by describing the relationship between the CISO and CDO roles in data security
From Inspiration to Delegation: Examining Generative AI’s Role in Creative Design
Full text linkAs generative AI becomes more prevalent in design, questions arise about which factors prompt design professionals to delegate creative tasks to AI-based systems. This study investigates whether a generative AI-based system for early-stage design can evoke inspiration, a critical driver of creativity, and how that inspiration influences the willingness to delegate. We conducted a scenario-based online study with 208 participants, measuring two components of inspiration (being inspired by and being inspired to) and their effect on delegation. A mediation analysis indicated that users who feel stronger inspiration from AI stimuli were more inclined to entrust the system with design tasks. These findings advance IS research by highlighting the importance of domain-salient factors such as inspiration as a vital factor that bridges creative engagement and delegation processes, informing how AI can be meaningfully integrated into phases of design
Understanding Gen Z\u27s Vulnerability to Romance Scams
Full text linkAlthough they are digital natives, Gen Z is more vulnerable to cybercrimes like phishing, identity theft, romance scams, and cyberbullying than previous generations. As they enter the workforce, understanding their cybersecurity behaviors is crucial. This study explores factors behind Gen Z’s susceptibility to romance scams based on thematic analysis of interviews with 21 participants. Findings show that high trust in technology, emotional and social dynamics, and generational influences increase their vulnerability. While aware of security risks, Gen Z often remains uncertain about how to respond and seek support. Keywords Romance scams, Gen Z, Qualitative analysis, Thematic analysis
Impacts of Generative AI on Creative Work
Full text linkGenerative Artificial Intelligence (GenAI) is transforming creative industries by augmenting and challenging traditional artistic processes. This study explores the impacts of GenAI on creative work, examining both its potential benefits and disruptions. While GenAI enhances productivity, democratizes artistic tools, and enables new forms of human-AI collaboration, concerns about authorship, originality, and job displacement persist. Through a conceptual analysis grounded in Information Systems (IS) and creativity research, we identify key themes in GenAI\u27s integration into creative domains. Our findings highlight how GenAI supports divergent thinking, automates repetitive tasks, and lowers barriers to entry in artistic professions. However, ethical concerns surrounding intellectual property, over-reliance on AI, and homogenization of creative output remain significant challenges. We argue that responsible adoption and regulatory frameworks are essential to balancing innovation with artistic integrity. This paper contributes to IS and creativity literature by offering insights into how GenAI reshapes creative processes, labor markets, and artistic value
AI in Forecasting: A Missing Component in ERP Systems?
Full text linkThis paper investigates the current state and potential of Artificial Intelligence (AI) in forecasting within Enterprise Resource Planning (ERP) systems. While AI-driven forecasting offers significant advantages in accuracy and insight generation, its adoption within ERP platforms remains limited. We compare traditional forecasting models with advanced machine learning approaches across major ERP systems, revealing a significant gap in the integration of modern techniques. A case study demonstrates the substantial performance improvements achievable through AI-driven forecasting. By leveraging feature engineering and advanced models like XGBoost, we show significant gains in forecast accuracy compared to traditional methods. The findings highlight the transformative potential of AI in optimizing supply chains and improving decision-making within ERP systems, advocating for greater integration of machine learning techniques to unlock the full potential of AI-powered forecasting
The Cyber-Storm: NLP Adoption and the Escalating Risk of Cyberattacks
Full text linkAbstract Cyberattacks pose a significant risk, causing losses for organizations, and remain a major concern for stakeholders. The rapid advancement of artificial intelligence has driven organizations to adopt technologies such as Natural Language Processing (NLP) systems, often without fully understanding the associated security trade-offs. While NLP systems offer significant capabilities, they also introduce technological complexity, expand attack surfaces, and are prone to adversarial inputs. This study aims to conduct a pre- and post-NLP adoption analysis using firm-level data to examine whether NLP implementation leads to increased cyberattack risk. It further investigates how organizational and environmental factors moderate this relationship. By addressing these gaps, the study contributes to the cybersecurity and technology adoption literature and offers practical insights for balancing AI innovation with security resilience. Keywords NLP, AI, cyberattack, technological complexity, adversarial threats
Mobilizing for Gender Equality in Digital Spaces
Full text linkThe underrepresentation of women in digital spaces reinforces gender bias and ultimately shapes how decisions are made (Smith & Rustagi, 2021). The internet gender gap has been calculated to have cost low- and lower-middle-income countries $1 trillion USD in GDP over the past decade (Horvát & González-Bailón, 2024). Crowd mobilization is a powerful mechanism that can challenge injustice and inequalities. We are using an exploratory case study to identify and describe components of the mobilization process of volunteers specifically targeting the gender gap on Wikipedia through events called WikiGap. We detect a range of digital mobilization strategies along the two axis of recruitment and participation , and we describe the three archetypes Native, Hybrid and Beyond Native of mobilization. This study contributes to our understanding of digital crowd mobilization strategies (Phang et al., 2015; Horvát & González-Bailón, 2024)
The Paradoxical Impact of Generative AI on Agile Software Development Outcomes: A Process View
Full text linkEmerging literature on Generative AI (GenAI) enabled software development outlines a paradox: although GenAI-driven automation speeds up coding tasks, its adoption inadvertently worsens project-level outcomes such as software throughput and stability. We take a process lens and examine how GenAI tools interact with agile practices and hypothesize that this paradox is the result of the vicious cycle of developing higher quantities of code that is more complex and less integrable with existing code, requiring more rework and refactoring effort by developers. We develop a system dynamics model to capture the feedback loops and causal mechanisms underlying GenAI use in agile software projects over time. We plan to collect quantitative project data and qualitative insights from software developers to refine and validate our model. Through this study, we aim to illuminate how GenAI can both elevate individual-level performance and still undercut performance of the agile project, offering theoretical and practical implications
Generative AI-Powered Cybersecurity Threats: A Growing Concern
Full text linkWith the advancement of generative AI (GenAI) models, new cybersecurity risks have surfaced of which including threats such as GenAI-driven phishing and deepfakes. Exacerbating the issue herein is that existing security methods and frameworks largely struggle to address these evolving attack vectors, thus making the case for adaptive mitigation strategies. This study analyzes emerging GenAI cyber threats, real-world cases, and defense mechanisms, using thematic analysis to categorize risks and solutions. It highlights the need for further studies in developing advanced threat detection methods, fortifying AI governance, and interdisciplinary collaboration, and focusing on advancing explainable AI, adversarial training, and regulatory enforcement to balance security and innovation. This research aims to strengthen our defenses against GenAI cyber threats and safeguard our digital landscape
AI-Driven Improvements in Patient-Doctor Communication for Remote Consultations
Full text linkThe fast development of telemedicine has shown the value of medical chatbots in facilitating interaction between patients and doctors. This study examines ChatDoctor, a health chatbot optimized with LLaMA, to determine the medical diagnosis suggested by Artificial intelligence compared to a physician’s diagnosis. We employ 100,000+ user reviews and health chatbot conversations, applying Natural Language Processing (NLP) and Large Language Models (LLMs), to investigate patient interactions. Findings indicate that although chatbots improve access, patient engagement, and convenience, they also have accuracy and trust issues. Topic modeling identifies a contradiction in user experience, where positive comments highlight chatbot support and negative comments refer to response reliability problems. This research contributes to the Information Systems literature by demonstrating how LLMs enhance telehealth and provide valuable insights for improving chatbot design and patient-centered AI solutions. The results emphasize the need for sophisticated AI models that balance efficiency, clinical accuracy, and user demands