STUDENT RESEARCH PRESENTATIONS
“Dark Side of AI Risks and Ethical Concerns”
Sustainable Influencer Services Meet Luxury: A Risky Match.
Abayomi, Olushola and Noordeen, Abdul Rahman , (2025). ICIS 2025 TREOS. 31
Darby, V ., Shin, H., & Eastman, J.K. (2025). 39(9), 1281-1298. https://doi.org/10.1108/JSM-07-2025-0506 ( AMS 2025 )
Artificial Intelligence (AI) has become a transformative force, permeating nearly every sector with the potential to revo - lutionize decision-making, automation, and service delivery. Weak AI, tailored for specific tasks; In contrast with general AI or Artificial General Intelligence (AGI), is capable of human-like cognition, offers significant promise but also carries profound societal risks (Hendrycks & Mazeika, 2022). This research-in-progress investigates the dark side of AI, highlight - ing risks such as job displacement, privacy violations, and ethical challenges, while proposing pathways for balanced gov - ernance. AI’s rapid diffusion generates systemic risks. Automation threatens routine-intensive occupations, with evidence suggesting widening inequality and polarization in labor markets (Chen et al., 2022). Privacy concerns intensify as AI-en - abled systems collect massive datasets, often without informed consent, creating potential for misuse and surveillance (Murdoch, 2021; Radanliev et al., 2024). Ethical risks include algorithmic bias, opaque decision-making, and reinforce - ment of societal inequities (Vallor & Bekey, 2017). These interconnected risks create feedback loops where unemployment, data exploitation, and algorithmic control may exacerbate social instability. This Technology, Research, Education, and Opinions (TREO) seeks feedback to refine theoretical framing and methodological design. Insights from ICIS participants will inform the final survey instrument, literature review expansion, and interview protocol development. Our goal is to advance a socio-technical understanding of AI risks and propose adaptive governance mechanisms that align AI deploy - ment with human values, protecting fairness, privacy, and societal well-being.
This study examines the influence of luxury consumption by sustainable influencers. Studies have examined the social costs of luxury consumption regarding how luxury brand consumers are perceived by observers. However, how it applies to sustainable influencers is underexplored. Using a 2 x 2 experiment design, we test the effect of luxury consumption by sustainable influencers on consumer’s behavioral intentions. The results show that there is an interaction between the type of influencer (i.e., non-sustainable vs. sustainable) and brand consumption (i.e., non-luxury vs. non-luxury) such that when sustainable influencer displays luxury consumption, audiences’ social media intention and word-of-mouth (WOM) inten - tion decrease, while this effect is not found when a sustainable influencer is not luxury consumers. This study offers im - portant theoretical and managerial implications to sustainable influencers who rely on visual content featuring him/her - self in content creation and luxury brand managers seeking to collaborate with influencers associated with sustainability.
Deciphering the Dynamics: AI’s Influence on Employee Decision-Making.
Pallepogu, J. P. (2025, Feb–Mar). 20th Doctoral Conference in Management ( ANVESH 2025 ), Nirma University, Ahmedabad, India.
Entrepreneurial Self-Efficacy as a Necessary Condition for Venture Success.
The rise of artificial intelligence (AI) is transforming organizational decision-making by enabling employees to process vast datasets, automate routine tasks, and focus on higher-order thinking. While integrating AI into workplace deci - sion-making processes offers significant potential, it is important to address challenges related to trust, cognitive load, and ethical considerations to ensure its effective implementation. This research will investigate the impact of AI adop - tion on employee decision-making, focusing on how cognitive load, AI sophistication, and trust influence decision qual - ity. The study will build on Agency Theory and Bounded Rationality Theory to explore AI’s role as a decision-support tool that mitigates cognitive limitations, and fosters trust through transparency, explainability, and ethical alignment. Amixed-methods approach will be employed, combining a systematic literature review, qualitative interviews, and quan - titative surveys to validate hypotheses and identify patterns. The findings are anticipated to reveal that well-designed and ethically governed AI systems build trust, mitigate risks, and improve decision quality. By proposing a conceptual model, this study will enhance scholarly understanding of AI’s implications in the workplace while offering practical strategies to optimize employee engagement and decision-making in an AI-driven landscape. It will bridge academic and practical per - spectives, addressing trust and ethical concerns critical for sustainable AI integration and providing insights to improve productivity and employee well being.
Ballard, L.A., Morgan, K.J. , Phelan, S.E., & Roman, J.R. (2025). Presented at the Annual meeting of the Southern Management Association (SMA) in Greenville, SC.
Entrepreneurial self-efficacy (ESE) has been widely studied as a predictor of entrepreneurial outcomes, yet the mecha - nism through which ESE influences performance remains underexplored. Drawing on Bandura’s concept of efficacy-based foreclosure, we propose that ESE operates as a necessary condition for venture success. Entrepreneurs with insufficient confidence systematically exclude higher performance pathways from consideration, creating cognitive ceilings that ex - ternal resources cannot overcome. Using Necessary Condition Analysis (NCA) on three years of panel data from the Na - tional Survey of Military-Affiliated Entrepreneurs(2020–2022), we find that ESE functions as a bottleneck constraining what performance levels are possible. The necessity relationship holds consistently across cohorts, ESE dimensions, and demographic subgroups, with ESE thresholds increasing progressively at higher performance magnitudes. These findings reframe ESE from a factor that contributes to success to one that constrains it. We conclude by offering insights on how entrepreneurship education and support programs might use these findings to sequence interventions.
Cybersecurity-Induced Stress in Nursing: The Impact of Security Protocol on Healthcare Professionals
Brown, T. T. , Robinson, S. M., & Vaezi, R. ( AMCIS 2025 ).
This research study is geared towards investigating demands made by cybersecurity protocols placed on healthcare profes - sionals, focusing on nurses as the sample group. With technology, a principal component of many patient care protocols, rising cybersecurity threats require stringent protocols to protect patient data, potentially affecting the daily responsibil - ities of healthcare staff. As front line workers, nurses face a unique overlap of demands. The nurse’s role in direct patient care has now intersected with complex cybersecurity policies, procedures, and protocols, which our study will examine in relation to Security Related Stress.
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