School of Business and Management Department of Management 189 Judgment and Decision Making in Policy Supervisor: HAGMANN, David / MGMT Student: KWAN, Sum Yuet / ECOF WAI, Yuk Shan / IS Course: UROP1000, Summer UROP1000, Summer This survey-based research explores cognitive biases and heuristics that influence policy choices and examine the factors that shape the decision-making processes. The study utilizes the carbon tax policy as the controlled case and the geoengineering approach as the deviation case, employing a carefully designed survey to assess the impact of this nudge on people's level of support. Through a diverse and representative sample, participants are presented with information about the carbon tax policy and each of the four geoengineering approaches. This approach enables participants to gain insights into the potential benefits and drawbacks of each option independently. Following this information, participants are then asked to express their level of support for the combined policy, which consists of the carbon tax policy combined with one of the four geoengineering approaches, as presented by the random assignment. The four variations of geoengineering approaches are classified based on their riskiness and efficiency levels: - Low risk, High efficiency - High risk, High efficiency - Low risk, Low efficiency - High risk, Low efficiency We aim to understand the factors that influence decision-making processes by analyzing participants' responses. Policymakers can hence better design and implement policies that align with public preferences and societal objectives. Leading to more effective and widely supported policies in areas such as climate change mitigation. Judgment and Decision Making in Policy Supervisor: HAGMANN, David / MGMT Student: LIAO, Yi-tsen / ECOF Course: UROP1000, Summer People in minority groups may prefer to work for companies fairly treating diverse groups of employees. However, it’s been examined that people tend to overlook the pool population, forming false beliefs which lead to discriminatory practices in hiring process (Hagmann et al., 2022). This paper proposes that neglecting the gender representation in the pool will lead job applicants to draw inaccurate inferences about the company’s diversity, therefore, resulting in a suboptimal career decision. Meanwhile, companies may strategically create a diverse subordinate positions while limiting minority's opportunities in senior positions. Our pre-registered experiment (n = 600) found that people overestimated the career opportunity working for a hypothetical company by failing to incorporate the information from the pool where people are selected.
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