Engineering Ethics and Management Decision-Making

This thesis explores the vital intersection of engineering ethics and management decision-making, emphasizing the need for ethical considerations in engineering practices to ensure responsible and sustainable outcomes. Engineering ethics encompasses a set of moral principles guiding the professional conduct of engineers, essential for maintaining public safety, welfare, and trust. The study investigates the application of three major ethical theories—deontological ethics, utilitarianism, and virtue ethics—in engineering contexts. Additionally, it examines decision-making models, including the rational decision-making model, bounded rationality, and intuitive decision-making, highlighting their integration with ethical principles. Through detailed case studies such as the Challenger disaster and the Volkswagen emissions scandal, the thesis illustrates the real-world implications of ethical and managerial failures. These case studies underscore the importance of prioritizing ethical considerations and the catastrophic consequences of neglecting them. The research culminates in proposing a comprehensive framework for ethical decision-making in engineering management, consisting of four steps: ethical awareness, ethical judgment, ethical intent, and ethical action. This framework aims to systematically incorporate ethics into engineering decisions, supported by tools such as ethical checklists, decision trees, and ethical risk assessment models. The thesis concludes by emphasizing the critical role of an ethical culture within engineering organizations and the need for ethical leadership and accountability mechanisms. Recommendations include fostering an ethical culture, implementing ethical frameworks, encouraging ethical leadership, and enhancing oversight and accountability. The study also identifies areas for future research, including cross-cultural ethical practices, the impact of emerging technologies, and longitudinal studies on the long-term effects of ethical decision-making frameworks.