James D. Westaby is an Associate Professor in the Program in Social-Organizational Psychology, Teachers College, Columbia University. He received his psychology degree from the University of Wisconsin - Madison (Honors Thesis Director: Leonard Berkowitz) and his Ph.D. in Social and Organizational Psychology from the University of Illinois at Urbana-Champaign (Dissertation Chair and Director: Harry Triandis and Marty Fishbein, respectively).

His research examines two main areas:

(1) Dynamic Network Theory

His first area of research examines how social networks influence human goal pursuit. This is a timely development given the ever increasing importance of social networks in our lives (socially and digitally). Further, this scholarship is the first to formally integrate the science of social networks and human goal pursuit, which have been largely separated in the past, to explain human systems at various levels of analyses. After years in development, this work has culminated in the development of a new "dynamic network theory" of goal pursuit. This theory examines how a finite set of only 8 social network roles (goal strivers, system supporters, interactants, observers, goal preventers, supportive resistors, system negators, and system reactors) are responsible for goal achievement and performance in numerous domains. Empirical results have thus far supported major propositions in this meta-theoretical approach.

In this work, a variety of original concepts are introduced to explain human behavior, such as “network motivation” and the “network rippling of emotions.” The book integrates various phenomena that are often unduly separated by disciplines. For instance, at the micro level, it integrates research on human motivation, self-regulation, social conflict, dynamical processes, and cognitions about social networks. At a broader level, it explains the underlying dynamics involved in group and organizational formation, leadership, helping dynamics, and organizational learning. At a macro level, it illustrates key factors involved in anarchy, sovereignty, dark networks, and international relations. Lastly, the book introduces new methodologies and syntax, such as in “dynamic network charts,” to technically show how social networks influence goal pursuits in specific cases. It is hoped that readers will gain a novel and parsimonious way to explain highly complex forms of human behavior from a single unified theory.

This new theory has been recently published as a scholarly book by the American Psychological Association.

Reference:

Westaby, J. D. (2012). Dynamic Network Theory: How Social Networks Influence Goal Pursuit. American Psychological Association, Washington, DC.


(2) Behavioral Reasoning Theory

Prior to establishing dynamic network theory, Westaby created behavioral reasoning theory (BRT) to predict specific behaviors (Westaby, 2005). Generally speaking, BRT explains human behavior at the psychological level of analysis with the following mediation flow: Beliefs and Values ---> Reasons (i.e., for and against) ---> Global Motives (e.g., attitude, subjective norm, and perceived control) ---> Intention ---> Behavior. Direct effects from reasons to intention are also hypothesized, which can theoretically be driven by implicit, explicit, or automated processes. This proposition substantively extends previous work on behavioral intention theories, such as the theory of reasoned action (Fishbein & Ajzen, 1975; 2010) and theory of planned behavior (Ajzen, 1991), which have not accounted for the importance of people’s behavioral reasons. Various lines of experimental and correlational research has supported the newly proposed direct linkage between reasons and intentions in BRT (Wagner, 2010; Westaby, 2005; Westaby, Probst, & Lee, 2010; Zusman, 2009). In other words, BRT has explained unique variance in intentions over and above that explained by the traditional theories. BRT also accounts for post-decision dissonance effects, especially between behavioral activation and the further justification and rationalization of human behavior via subjective reasons. This can result in further behavioral commitment.

As for the theoretical link to dynamic network theory, the conceptualization of “goal striver activation” in dynamic network theory is analogous to an entity that has a strong intention to engage in a goal or behavioral pursuit. BRT (along with other decision making models as discussed in Chapter 1 of Westaby, 2012) can provide insight into the underlying decision-making factors that activate goal strivers in the first place. Thus, the theories are complementary. While BRT examines the initial decision making factors underlying goal strivers, dynamic network theory examines how these goal strivers (G) are implementing their roles in the context of other entities activating important roles in the broader social network (i.e., S, S`, G`, R, R`, I and O). Hence, dynamic network theory provides an integrative meta-theoretical framework that subsumes BRT, which allows dynamic network theory to explain a much broader range of human behavior and social complexities.
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