My research focuses on heuristics and biases, specifically overconfidence. In the past, I explored and defined shared decision-making as a confounder of investor overconfidence. I reassessed the connection between excessive confidence and gender within the financial realm. In addition, I shed light on the impact of overconfidence on preschoolers and kindergartners by using a novel experimental setting with an innovative video intervention.
Below is a list of selected past and current research:
Peer-Reviewed Journal Article:
Piehlmaier, D.M. (forthcoming in Financial Innovation). Overconfidence and the Adoption of Robo-Advice.
Objective: The study sheds light on the motivation of innovators and early adopters to utilize a novel financial service to invest. The results of a series of robust generalized linear and structural models suggest that these consumers are excessively confident in their financial knowledge. Overconfidence increases the propensity to use automated financial advice and outperforms any income or risk aversion effect in this process. Causality is established with an instrumental approach and supported with a nonparametric matching function.
Piehlmaier, D.M. (forthcoming in SAGE Research Methods). Bot Detection in Online Studies and Experiments.
Objective: Semi- or fully automated response tools, also called bots, decrease data quality and reliability in online studies that rely on crowdsourced data (e.g., MTurk). This publication describes how two online studies were conducted on a crowdsourcing platform in anticipation of bot responses. Specifically, it offers insights into the study design process, the selection of appropriate survey questions and bot traps, as well as the ex-post analysis and filtering of bot responses. Best practices are identified and potential pitfalls explained. The description should aid readers in designing anticipatory online studies and experiments to increase their data quality, validity, and reliability.
Piehlmaier, D.M. (forthcoming in the Handbook of Research on Customer Loyalty). The Impact of Missing Data on the Predictability of Customer Loyalty Models.
Objective: This chapter explores missing data in customer loyalty research in order to proactively assess and handle incomplete observations. Three types of missingness are defined and differentiated. Ad hoc, likelihood, and chained equation approaches are discussed and theoretically as well as empirically compared. Lastly, the chapter provides hands-on techniques to solve missing data problems in customer loyalty research.
Piehlmaier, D.M. (2020). Overconfidence among young decision-makers: assessing the effectiveness of a video intervention and the role of gender, age, feedback, and repetition. Nature Scientific Reports, 10(1), 1-10.
Objective: This exploratory study utilizes primary data from 60 participants aged 4 - 6 and their caregivers. The experiment involves a game theoretical gambling task and a video intervention. The aim is to examine the presence of excessive confidence and its potential impact on young decision-makers.
Warmath, D., Piehlmaier, D. and Robb, C., 2019. The impact of shared financial decision making on overconfidence for married adults. Financial Planning Review, 2(1), p.e1032.
Objective: This study uses secondary data from 1,371 married investors and primary data from 320 married panelists to test whether sharing with someone in the household decreases overconfidence. It is argued that the perception of shared ownership of money partially explains the decrease in overconfidence among investors who share financial decisions.
Piehlmaier, D. (2014). Irrational and Overrated: Is Our Unrealistic Self-Perception Connected to Educational Achievements?. Anchor Academic Publishing.
Piehlmaier, D. (2012). Overconfidence-A Matter of Education?. Grin Verlag.
Piehlmaier, D. (2022). The Effect of Cooperative Decision-Making on Investor Overconfidence. Revise and resubmit to (omitted journal) ABS 4*.
Objective: This study examines the impact of shared decision-making on investor overconfidence. It analyzes nationally representative data from 2,000 US investors, approximately 6,400 US consumers, and 239 experimental subjects to answer the question whether investors who share the decision-making responsibility are less affected by the overconfidence bias than those who decide on their own.
Piehlmaier, D. (2022). Gender and Investor Overconfidence. Revise and resubmit to (omitted journal) ABS 4*.
Objective: This paper revisits the issue of a possible gender effect on investor overconfidence. Information from more than 30,000 respondents was used to assess whether excessive confidence in one’s financial knowledge can be associated with a specific gender after controlling for primary vs secondary decision-making.
Warmath, D., Piehlmaier, D. (2019). Does Financial Education Increase Financial Skill?. To be submitted to ABS 4* journal
Objective: This longitudinal study uses an experimental design to test the effectiveness of traditional financial education to increase financial skills and dominant intertemporal behavior among college students.
Piehlmaier, D. (2018). Head Against the Wall: The Connection Between Concussions and Overconfidence.
Objective: This study sheds light on the influence of overconfidence on the propensity to experience a concussion and the likelihood to report it. Information from two datasets with a total of around 1,000 athletes was used to analyze these aspects. The research project is part of the Minds Matter Challenge from the NCAA and the Department of Defense.
Piehlmaier, D. (2018). The Realism of Overconfidence: A Study on the Role of Visualization.
Objective: This experimental study analyzes the impact of visual clues on the decision-making process. It uses a novel clinical trial design to test whether graphical representations of a given situation increase the accuracy and/or confidence in a person's decision under uncertainty.