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Dissertation
Technology, risk, and uncertainty: advances, insights, and challenges in human-centered activities
Doctor of Philosophy (Ph.D.), Drexel University
May 2025
DOI:
https://doi.org/10.17918/00011001
Abstract
The business landscape is continually evolving and becoming more complex, with a strong focus on the intricacies of the human-tech nexus. In this technologically advanced era, the development of sustainable models that mitigate risks and disruptions is essential, particularly given the multifaceted 'ripple effects' stemming from human interactions. Motivated by these challenges, this dissertation employs analytical approaches, including stochastic optimization and machine learning, to investigate the interplay of risk with technological innovation and socioeconomic dynamics, concentrating on human-centered business activities. Building on this foundation, this dissertation first addresses the challenge of modeling randomness and uncertainties. This section presents techniques in stochastic modeling and machine learning to capture randomness and integrates these techniques into deployable analytical frameworks. The second section applies these frameworks to contemporary business contexts, including blockchain systems (and their derivatives) and logistics networks, emphasizing the randomness of human participation in shaping these domains. These case studies demonstrate the managerial benefits derived from modeling and applying human-related uncertainty in business systems. The third part of this dissertation introduces a series of new topics by exploring the responsible application of analytical models, focusing on sustainable practices that positively influence the future human-technology nexus. It advocates for fairness, privacy, and broader societal benefits through ethical business model design. Together, this dissertation advances the fields of technological innovation and information management by contributing to the application and development of business analytical tools that are sustainable and trustworthy.
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Details
- Title
- Technology, risk, and uncertainty
- Creators
- Lanqing Du
- Contributors
- Jinwook Lee (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- xviii, 212 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems); Bennett S. LeBow College of Business; Drexel University
- Other Identifier
- 991022058838704721