Brackbill, Liu, Seitz, Zhang Receive Ackoff Fellowships

Research Area: 

Annenberg doctoral students Devon Brackbill, Jiaying Liu, Holli Hitt Seitz, and Jingwen Zhang have received the Russell Ackoff Doctoral Student Fellowship Award for 2015 from the Wharton Risk Management and Decision Processes Center.    

The Fellowships provide funding for doctoral research on human decision making. The research fellowships are named in honor of an endowment provided to the Wharton School by the Anheuser-Busch Charitable Trust.  Russell Ackoff, Professor Emeritus of Management Science life's work was dedicated to furthering the understanding of human behavior in organizations.  It is in the spirit of continuing this legacy by supporting doctoral training that the fellowships have been named.   The fellowships provide financial support for the students to conduct specific research projects. In addition to supporting the cost of research, one of the goals of the Ackoff awards is to foster a sense of community among scholars at Penn involved in research on decision making.   

Each student’s research projects are:  

Devon Brackbill:  Designing Collaboration Networks to Improve Collective Problem Solving

Abstract: This project focuses on the effects of network efficiency on collective problem solving. Using computation modeling and Internet experiments, this project seeks to identify the network principles governing the emergence of collective intelligence. Recent advances in network theory suggest that information diffusion in complex networks can unexpectedly reduce the overall quality of group performance.  The theoretical mechanism behind this is that less efficient communication networks encourage more people to independently search for solutions to the problem.  This increases the information diversity of the group as a whole. For more complex problems, greater diversity is the key to success since it increases the chances that the group will find a better solution before arriving at a consensus.  While it is a compelling thesis, attempts to evaluate this theory empirically have been inconclusive due to limitations of scale and design.  This project uses novel computational and experimental techniques to study the effects of network efficiency on collective problem solving within large empirical networks.

Jiaying Liu: When Do Boomerang Effects Happen? The Role of Normative Appeals and Processing Styles on Attitude Change among People Likely to be Skeptical about A Message

Abstract: Social norms are group-held rules for appropriate and acceptable behaviors, values and beliefs of its members. The role of social norms in explaining and predicting human cognitions and behaviors has long been controversial. The persuasive messages that applied normative appeals have had mixed successes in changing cognitions and behaviors in empirical tests, and sometimes that implicit normative content might even produce boomerang effects. On the other hand, as the depth of deliberation is often considered as key to attitude change, it is likely that different deliberation levels will also affect the influence of normative appeals. This study aims to investigate how the interactions between processing styles and normative appeals might affect people’s decision making and response to persuasive communication, and particularly, which combination of the two factors might produce boomerang effects among established smokers who are more likely to be skeptical about an anti-smoking message. In addition to more traditional explicit attitude measures, implicit attitude changes will also be assessed to help understand whether and under what circumstances social norms might operate in an automatic or unconscious fashion.

Jingwen Zhang: Developing an Online Social Network Physical Activity Intervention for Young African American Women to Reduce Risks for Chronic Diseases

Abstract: Descriptive social norm describes what is typical or normal. The tendency to follow others offers an information-processing advantage and a decisional shortcut when one is choosing how to behave in a given situation. However, descriptive norms have been underappreciated as a source of decision making and behavior change both in theory and in practice. Social networks are particularly important in shaping descriptive norms because people construct normative beliefs based on their observations of others’ behaviors in the accessible social networks. Online social network interventions have great potential to construct social networks, allowing people to connect and interact with other people who are engaging in the targeted behavior through real-time updates, thus shaping descriptive norms in favor of the targeted behavior in a dynamic and sustainable way. This project aims to develop an online social network physical activity intervention for young African American women, a population that continues to account for a disproportionate amount of chronic-disease mortality in the United States and that reports low levels of physical activity.

Holli Hitt Seitz: The Effects of Mammography Narratives in Online News Commentary on Breast Cancer Risk Perceptions and Screening Intentions

Abstract:  The inclusion of user comments following news stories has become standard practice for many online news sources, and these comments may contain personal narratives, in which readers share personal experiences related to the news topic.  While prior research suggests that narratives can be memorable and persuasive, the effect of personal narratives in comments on readers is not well understood.  This is of particular importance when the subject matter is a controversial and potentially confusing health topic, such as changing guidelines for mammography.   This research examines the effects of personal mammography narratives appearing in user-generated online news comments on young female readers’ breast cancer risk perceptions, mammography perceptions, and intentions to be screened for breast cancer.