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When AI Gets It Wrong: Investigating the Effects of Output Inaccuracy on User Trust and Continuance Intentions
Get PDFArtificial Intelligence (AI) systems are increasingly embedded in high-impact decision-making contexts such as healthcare, hiring, and financial services. While much of the literature has focused on explainability and fairness, fewer studies have examined how users respond when AI outputs are inaccurate. Given that real-world AI is probabilistic and often imperfect, understanding how output inaccuracy affects trust and continu-ance intentions is critical for designing robust and trustworthy systems. Drawing on trust calibration theory (Lee & See, 2004) and information systems continuance models (Bhattacherjee, 2001), this study investigates how users adjust their trust after experiencing incorrect AI out-puts and whether transparency mechanisms such as confidence scores or uncertainty indicators can mitigate trust erosion. We theorize that output inaccuracy undermines perceived system reliability, reducing both trust and intention to continue using the AI. However, if the system acknowledges its limitations or flags uncer-tain results, users may calibrate their trust more appropriately and remain engaged. We propose a 2x2 between-subjects experiment involving participants interacting with a decision-support AI system in a simulated task (i.e., evaluating résumés). The two factors are: (1) AI Output Accuracy (accurate vs. inaccurate) and (2) Transparency Mechanism (present vs. absent). Dependent variables include trust, perceived reliability, and continuance intention. The study will assess changes in trust over time and explore whether users override or defer to AI recommendations after errors occur. Controls variables will include in-dividual characteristics such as algorithm aversion and propensity to trust. This research offers three contributions. First, it extends trust-in-AI literature by examining user responses to inaccuracy. Second, it examines transparency mechanisms that may buffer the negative effects of errors on trust. Third, it provides practical guidance for AI designers seeking to build systems that retain user trust de-spite the inevitable failures in complex, real-world AI applications
Deepfake Detection Using CNN-LSTM and Multimodal Analysis: A Hybrid AI Approach
Get PDFThe quick evolution of artificial intelligence and generative models has made it possible to produce hyper-realistic fake media, also known as deepfakes. Although such technology has potential uses in entertainment and education, it is a major threat when used for misinformation, identity theft, or defamation. This research fills the critical need for strong and scalable detection mechanisms by investigating multimodal deep learning methods to identify deepfakes in real-world applications. This work provides an in-depth comparison of different deep learning models, including convolutional neural networks (CNNs), long short-term memory (LSTM) networks, and transformer models for the detection of fake video content. The uniqueness of this work lies in its focus on multimodal information, examining visual and auditory features for better detection. The models are trained and tested on benchmarking datasets like FaceForensics++ and the Deepfake Detection Challenge (DFDC), maintaining diversity and realism while testing. This work\u27s experimental results prove that multimodal methods far exceed unimodal models, especially in identifying subtle forgeries under adverse conditions like compression and occlusion. Out of the configurations tried, a hybrid model integrating ResNet-50 for visual frames and Bi-LSTM for audio streams achieved an accuracy rate of 94.6% on the DFDC test set and exhibited excellent generalizability. In addition, our research identifies key issues in actual deployment, including adversarial attacks, dataset bias, and computational cost. To address these, we introduce methods such as data augmentation, domain adaptation, and model compression without severely degrading performance
Do Perceptions of Digital Technology Advances Affect Knowledge-Hiding Behavior? A Study in the United States
Get PDFBackground: Diverging from prior information system (IS) research that investigates the impact of information technology (IT) usage and its correlates of technostress and techno-insecurity, we examine the role of employees’ perceptions of IT advancement and its relationship to their work behaviors. Drawing on conservation of resources (COR) theory, we propose that if employees perceive their jobs may be replaced by smart technology, artificial intelligence, robotics, and algorithmic (STARA) technologies—that is, if they have a high perceived STARA awareness—then their knowledge-hiding behavior will be elicited via feelings of job insecurity.
Method: We conducted a two-wave survey in the United States with an interval of one month using Connect-Cloud Research’s sampling system. Referencing the Automation Risk Score from the website Will Robots Take My Job? (https://willrobotstakemyjob.com/), we obtained a sample of 165 participants of a wide distribution of possibilities for job replacement by STARA technologies.
Results: Our study results provide external validity for the STARA awareness scale and support the proposed hypotheses. Specifically, we find that STARA awareness is positively related to feelings of job insecurity and to knowledge-hiding behavior via feelings of job insecurity.
Conclusion: This study adds to the literature on technological development and knowledge management by highlighting that employees’ perceptions of IT advancement may have a consequential negative impact on their work behavior. We suggest that organizations in most Asia Pacific economies, which are still in earlier phases of AI integration, can leverage the temporal gap to implement proactive measures to mitigate negative consequences of such perceptions. Also, given that fear about uncertain technological changes can prompt self-serving responses, organizations should prioritize transparent communication to alleviate employees’ job insecurity and lower their knowledge-hiding behavior. Management should invest in human resource initiatives to address these concerns, especially for employees who are facing imminent displacement by new technologies
Digital Business & Consumer Insights on Emerging Social Media Platforms
Get PDFSocial media, enabled by various digital technologies, e.g., data analytics, blockchain, artificial intelligence, and augmented or virtual reality, has increasingly played a central role of monitoring, responding, optimizing, and influencing consumer behavior in digital business (Chou et al., 2025; Do et al., 2025). Since 2017, the immediate popularity of Douyin in China and later TikTok in the world brought the new paradigm of social media platforms by leveling down the threshold of video production and directing platform competition from celebrity/content centric to algorithm centric. Such a paradigm shift suggests new challenges and opportunities in digital business, i.e., constructing sustainable relationships among “content producers -- content consumers/customers -- businesses/brands”. The latest development of AI technologies also magnifies the significance of algorithms in content production, social medial platform competition and digital business models constructed over such platforms. Companies, brands and influencers are thus under huge pressure to understand the unique challenges and ecosystem of emerging social media platforms (Benbya et al., 2020) and to stay ahead of this powerful digital movement (Xie et al., 2022). This special section address the timely issues associated with emerging social media platforms and deepens the understanding of the latest opportunities and challenges for digital business and consumer insights in the Pacific Asia region (Jiang et al., 2019), by offering theoretical frameworks and practical strategies that bridge academic research with industry needs
The Impact of Broadcasters\u27 Emotions and Interaction Rituals on Viewers\u27 Purchase Intention
Get PDFBackground: The rise of live streaming has transformed the e-commerce landscape, enabling real-time interaction between broadcasters and viewers while enhancing immediacy, interactivity, and emotional engagement. Therefore, studying the emotional communication and interaction methods between broadcasters and viewers holds significant importance for improving live streaming sales.
Method: The study integrated the Interaction Ritual Chain and Emotional Labor Strategy to create the combined IRC-ELS model. We proposed four hypotheses and designed two studies, which successfully collected 300 and 245 valid questionnaires respectively. Three of the hypotheses received empirical support.
Results: The broadcasters\u27 emotional labor strategy significantly influence viewers\u27 consumption intention. Viewers\u27 emotional identification with the broadcaster mediates the effect of emotional labor strategy on consumption intention. Emotional identification also directly affects consumption intention. However, emotional interaction does not moderate the relationship between emotional labor strategy and emotional identification.
Conclusion: Through the IRC-ELS model, our research enriches the literature on broadcaster behavior and viewer consumption intention. It highlights the importance of broadcasters\u27 emotional communication. The findings can also provide Asian live streaming enterprises with applicable research results on broadcaster behavior, demonstrating universal relevance
Corporate Nomads: Working at the Boundary Between Corporate Work and Digital Nomadism
Get PDFDigital nomads are knowledge workers who leverage information technology (IT) to perpetually travel while working independently of any organizational membership. Corporate nomads are individuals who adopt a nomadic lifestyle but remain permanent employees, which places them in a field of tension between corporate work and digital nomadism—two conceptions of work previously deemed incompatible. To resolve this professional paradox, we conducted qualitative interviews with corporate nomads to better understand how they succeeded (or failed) in holding together two disparate fields with competing values and worldviews. Drawing on ideas from the boundary work literature, we developed a process model of boundary coworking in the context of corporate nomadism. The model incorporates the finding that corporate nomadism unfolds along three phases: (1) splintering, (2) calibrating, and (3) harmonizing. This requires mutual engagement in IT-driven boundary work from both the corporate nomad and their organizational environment. Consequently, corporate nomadism can be understood as an extreme form of “working from anywhere” in which individuals work as spatiotemporal outliers within otherwise settled organizational structures. Practitioners may find value in this study because it discusses managerial implications for recruiting, leading, and retaining corporate nomads
Who Counts? A Compassionate Critique of Stakeholder Theory in Information Systems
Get PDFStakeholder Theory (ST) provides a valuable lens for understanding how firms create value, but it also surfaces how an emphasis on power, legitimacy, and urgency can marginalize vulnerable groups. This commentary argues that IS scholars, by adhering to corporate-driven definitions of stakeholder legitimacy, risk entrenching systems of exclusion rather than challenging them. Firms prioritize principal stakeholders, and shareholders and IS research often mirrors these priorities, reinforcing structures that disadvantage those who would benefit most from inclusive digitization. Drawing on observations from an upskilling program embedded in a homeless shelter, this analysis highlights how IS scholarship can either perpetuate or dismantle marginalizing systems. By critically reflecting on whose interests are served in IS research and practice, this commentary calls for a shift toward more inclusive, justice-oriented approaches that extend beyond performative inclusion and address the structural barriers that exclude society’s most vulnerable
Strategic Cybersecurity Incident Response: A Practice-Oriented Framework Using Activity Theory and Strategy-as-Practice
Get PDFDespite increased cybersecurity awareness and investments in preventive controls, organizations remain vulnerable to cybersecurity incidents driven by increasingly sophisticated threats, such as Advanced Persistent Threats and AI-powered attacks. To navigate the evolving threat landscape, organizations should establish Incident Response (IR) management and develop strategies for it. However, existing IR research predominantly focuses on operational-level processes, people, and technologies, often neglecting the strategy that underpins the entire IR function. In this research-in-progress paper, we utilize the Activity theory and Strategy-as-Practice research to develop a practice-oriented framework that explains how strategic IR praxis emerges from organizational activities. This shifts IR strategy development toward practice-oriented frameworks, emphasizing the IR activity system (IR Practitioners, IR Artefacts, IR Practices, Organizational Context, Collective Structure and Cyber IR), IR outcome, and Strategic IR Praxis, rather than conventionally prioritizing performance metrics. The framework also provides a basis for future empirical work including case studies and focus groups
Red Lights, Blind Spots: Sex Work and Stigma in Information Systems
Get PDFSex work remains one of the most stigmatized and marginalized professions globally, often subject to legal, social, and ethical challenges. Despite this, advancements in Information and Communication Technologies (ICT) have led to significant changes in the ways sex workers conduct their professional activities, providing new opportunities for marketing, client interaction, financial transactions, and safety measures. However, these developments have not been widely explored within the field of Information Systems (IS) research. This paper addresses this gap by investigating the use of digital platforms among sex workers, focusing on how ICT impacts their professional activities, economic opportunities, and social networks. Through qualitative interviews with nine sex workers in Germany, conducted via Zoom to ensure privacy and security, the study highlights the ways in which digital tools shape their business strategies, risk management, and digital agency. The research also explores the institutional, legal, and societal barriers that prevent IS scholars from engaging in this subject. The paper contributes to IS research by advocating for a more inclusive approach, encouraging scholars to investigate the intersection of ICT and sex work, and to consider the role of technology in empowering marginalized communities
Unveiling the potential of metaverse in project management education
Get PDFThe Fourth Industrial Revolution (4IR), driven by technological advancements such as Artificial Intelligence (AI), has transformed industries, reshaping the skills required in the workforce. Project management education must adapt to these changes by integrating innovative teaching methods to prepare future professionals. This study explores the potential of the metaverse, an immersive virtual environment, to revolutionize project management education. By offering interactive, real-time simulations and personalized learning experiences, the metaverse enables learners to engage with complex project management scenarios beyond the limitations of traditional classrooms. This research combines a literature review and qualitative analysis of project managers\u27 perspectives to assess the benefits and challenges of incorporating the metaverse into educational curricula. The findings highlight the potential for enhanced engagement and the barriers to adoption, including technology access and learning curve concerns. The study concludes by proposing future research directions and addressing limitations regarding the scalability and effectiveness of metaverse-driven education in diverse project management contexts