Behavioral and Decision Sciences Program

Penn’s Master of Behavioral and Decision Sciences (MBDS) is informed by contemporary theories and research methods of behavioral economics, decision sciences, network analysis and public policy. Our program equips students with theoretical and practical tools to address a variety of real-life problems, putting you ahead of the curve in a growing field of study.

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Now showing 1 - 10 of 18
  • Publication
    Optimal Bias: Truth-Seeking vs. Decision-Making
    (2019-08-09) Peterson, Jared
    At the foundation of current statistical practices and good decision making is the idea that there is a trade-off. Due to life’s uncertainties we must decide how good it is to be right and how bad it is to be wrong. Understanding the cost-benefits of being right or wrong helps us to understand systematic biases which may appear to be irrational on the surface but in actuality serve a rational function. Such an understanding may persuade decision-makers to introduce intentional bias into their decisions. Using the example of the Replication Crisis in Psychology, I will show that science is another form of decision-making which has intentional biases built in. Being consciously aware of this bias, and planning to have an optimal bias, will make for a healthier science.
  • Publication
    The Problem of Plastic Waste in China
    (2019-08-09) Qian, Chiyu
    Due to rapid economic growth in China, citizens are getting more and more used to littering plastic waste on the street, causing huge damages to the environment, and it is time to make some positive social change to curb this behavior. The individuals who litter on the street can have some social beliefs and expectations that are associated with their behavior. They are hypothesized to be lazier, to be more inclined to litter when they observe others litter, and to hold the belief that littering is a social good that can provide lower-income people with financial resources and job opportunities. littering behavior is diagnosed to be a social norm, custom, and descriptive norm in different circumstances. To diagnose this behavior further, I propose a one-month interview and survey with questions that cover all the components that would be necessary to measure from a social norm perspective. To intervene on this behavior, the possible policies that could work are economic incentives, economic punishments, public education, and public shaming.
  • Publication
    The Relationship between Complexity and Behavioral Bias
    (2019-08-09) Noel, Hamilton
    In the corporate workplace employees are routinely asked to do analysis of impacts, outcomes, demographics, and economic opportunities just to name a few. While these projects vary greatly in regard to their subject matter, they also vary in terms of complexity. Some are straightforward with few moving parts while others entail dozens of confounding variables and noise. Knowing that humans are not able to treat problems systematically and without bias, we propose the question: how do complexity and behavioral biases interact? Using case studies from an analysis done at an eCommerce company located in the Mountain West, this research found that different levels of complexity lend themselves to different behavioral biases. Complex problems create an environment where employees are more susceptible to creative interpretation, social pressure, and incentives. Less complex problems leave less room for creative interpretation but create situations where assumptions and findings are overstated.
  • Publication
    Ergodicity and You: Adaptive Heuristics in an Uncertain World
    (2019-12-02) Zovas, Justin
    Life requires making decisions under uncertainty. Facing complex, dynamic environments, decision-making processes should focus on the consequences of choices with time as a fundamental consideration. To that end, I recommend honing adaptive heuristics through trial and error while maintaining a margin of safety from ruin.
  • Publication
    Self-Oriented or Other-Oriented Empathic Concern Behind Altruism
    (2019-08-09) Yan, Zih-Yun
    It is hypothesized that empathic concern evokes altruistic motivation (Batson, 1991). As we can see in our daily life, stimulating empathy to the suffering is a common advertising strategy for charitable donation. While empathizing, we adopt the perspective of others and share their feelings so we can understand their need. Then, these empathic responses motivate us to have concern for others’ well-being and save them from any negative outcomes. However, whether altruistic behaviors are truly other-oriented or actually self-benefit motivated is still controversial. In this study, we focus on the empathy network in the human brain and use Multi- Voxel Pattern Analysis (MVPA) to provide new evidence in this debate. Adapting an established protocol of empathy-for-pain studies (Singer et al. 2004, 2006; Hein et al. 2010), we tested whether the neural activities of empathy can predict altruistic behaviors and how kin relationship modulate the willingness to take altruistic actions. In the experiment, daughters faced two types of conditions: in “Forced Choices” trials, subjects either passively received the shock or observed their mothers or strangers receiving the shock; in “Free Choices” trials, daughters had to actively decide whether to receive the shock themselves or to defer the shock to mothers and strangers. We find that when daughter chose to sacrifice themselves to receive the shock, the neural pattern in empathy network is more similar to when daughters themselves were in pain rather than observing others in pain. These finding suggest that altruistic choices are self-oriented process. We do not find a distinct neural pattern when subjects had to make the altruistic choices facing their mother or a stranger, however, the shock deferring rate to stranger is significantly higher than mother at the behavior level.
  • Publication
    Behavioral Science in Business: How to Successfully Apply Behavioral Science in A Corporate Setting
    (2019-08-09) Lindemann, Justin
    Over the past several years, behavioral science has slowly begun to creep its way out of the shadows and into the spotlight of the private sector. This transition has been facilitated in no small part by the efforts of academia and the proliferation of literature that offers a window into the countless ways in which behavioral science can help organizations guide people towards better outcomes. While companies are beginning to recognize the value of behavioral science, the application of this research is still in its infancy. Based on interviews with a number of practitioners, in addition to my own experience, this paper presents a basic road map that aspiring practitioners can follow as they set out to apply behavioral science in their own organizations. To simplify what is often an ambiguous topic, I have defined “behavioral problems” to mean any business challenge that involves people, while “behavioral solutions” can be distilled down to any solution that fixes these problems. The liberal interpretation of these terms highlights the broad reach that behavioral science can have in the corporate world.
  • Publication
    Improving Medication Adherence Programs with Behavioral Science
    (2019-08-09) Dean, Danielle
    Medication nonadherence is a significant global problem that results in higher mortality and healthcare costs. There has been a recent increase in digital health companies that aim to facilitate behavior change to encourage and promote healthy behaviors, with medication adherence being a key focus for many. This paper identifies several behavioral drivers associated with medication nonadherence and identifies key components in program design where behavioral science should be considered in order to make a strong lasting impact. This paper also presents a framework for incorporating behavioral science concepts in health program design and outlines a methodology for testing and validating results. I also explore a case study identifying a digital health program that has successfully utilized behavioral science to improve program design and increase the desired behavior. The purpose of this paper is to provide a low-cost framework for incorporating behavioral science into medication adherence program design to increase efficacy in behavior change and ultimately improve individual quality of life and lower overall societal healthcare costs.
  • Publication
    Give Me a Good Reason: Exploring Tightness-Looseness as a Framework for Norms-Nudges
    (2019-08-09) Wu, Tiffani
    Identifying a relevant and specific reference group can often prove challenging when designing a norm-nudge, but not including a relevant reference group can also potentially cause a norm-nudge to backfire even when there are appeals to high social proximity. A potential solution explored in this capstone is incorporating tight-loose frameworks in normative messages as a means of evoking a sense of social proximity without necessarily specifying a reference group. A pilot study examining charitable giving using these tight-loose frameworks is conducted to see whether adding these frameworks increases pro-social norm compliance. While preliminary results suggest that there is no significant difference in norm compliance when a tight-loose framework is used, there is some evidence which suggests that presenting tightly (loosely) framed messages to tightly (loosely)-minded individuals may increase the likelihood that they will donate to the charity. Future research on the importance of tightness-looseness as a context to consider when designing norm-nudges is encouraged.
  • Publication
    Leveraging Behavioural Science in Insurance: A Systematic Review
    (2019-08-09) Raghuram, Anuradha
    Over the past decade, the U.S. insurance industry has faced stagnant growth due to limited technological advancement, information asymmetry and waning customer satisfaction. Collectively, these factors, among many other structural drivers, impede incumbent players to attract and retain their customer base. In recent years, a number of insurance technology “insurtech” firms have emerged, seeking to disrupt and make existing activities within the insurance value chain more efficient, primarily through digital innovation. The discussion in this white paper is structured twofold. First, I walk through the current U.S. insurance landscape, innovations, and challenges within the value chain. In particular, I focus on the underwriting and claims activities in the context of property & casualty insurance. Second, I illustrate how behavioural science serves as a valuable use-case to improve customer engagement and retention. Through a combination of meta-study methods and case studies, I identify five key areas of behavioural change: reducing switching behaviour, managing uncertainty, increasing trust, encouraging accurate information disclosure, and providing customer autonomy. Exploration of behavioural science in insurance has meaningful implications for industry players, not only in terms of diagnosing biases, but also in terms of how they can elicit positive behavioural change in the long-run.
  • Publication
    Made of Millions: An Evidence-Based Management Approach Using Behavioral Science to Reduce Mental Health Stigma in the Workplace
    (2019-08-09) Soloperto, Gina
    Made of Millions is a New York-based global advocacy nonprofit that uses art, media and technology to democratize mental health knowledge and access to care to reduce stigma. (Made of Millions, 2019) This capstone incorporates behavior science into an evidence-based management (Briner, et al., 2009) model to understand how competitive environments and social proximity can shape our altruistic preferences (Dimant, Hyndman, 2019) to inform a behavioral intervention design aimed at reducing mental health stigma within a target workplace population. This paper integrates existing behavioral evidence, including underlying factors causing stigma and strategies to confront it with three key additional variables: Professional expert data (facts and figures surrounding workplace mental health); Organizational (internal) data, and Stakeholder values and concerns (expressed needs and challenges from those who may be affected by the intervention). With this holistic perspective of the problem, we will identify the optimal behavioral drivers informing our intervention design proposal. The goal of this intervention is to answer the question of how using behavioral insights can reduce mental health stigma in the workplace, increase social proximity, and improve greater access to resources and care.