James D. Westaby is a Full 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 formally integrates 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 culminated in the development of dynamic network theory (Westaby, 2012). This theory examines how a finite set of only eight 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. See Westaby, Pfaff, and Redding’s (2014) American Psychologist article for most recent developments and areas for future research. See Westaby, Woods, and Pfaff (2016) for applications of the framework to group and social interaction analysis. See Westaby and Shon (2017) for new advances using computational sciences and computer simulations applying the theory.

The theory also provide a variety of original concepts to explain human complexities, such as the “network rippling of emotions” and “dynamic network intelligence. Various phenomena that are often unduly separated by disciplines are integrated in the original formulation. For instance, at the micro level, the theory 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. And at a macro level, it illustrates key factors involved in anarchy, sovereignty, dark networks, and international relations. Lastly, the theory uses various new methodologies, such as dynamic network charts, to assess how social networks influence goal pursuits in specific cases. This provides a highly quantitative approach to assessing dynamic networks systems and their overall characteristics. It is hoped that scholars, researchers, and practitioners will gain a novel and parsimonious way to explain highly complex forms of human behavior from a unified theory.

(2) BEHAVIORAL INTENTION RESEARCH

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 possible, which can theoretically be driven by implicit, explicit, or automated processes. These propositions substantively extend 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 explicitly addressed behavioral reasons. BRT also accounts for post-decision dissonance effects, especially between behavioral activation and the further justification and rationalization of human behavior via subjective reasons. Theoretically, this can result in further behavioral commitment. Numerous studies have supported or used propositions in the theory.

As for the theoretical link to dynamic network theory, the conceptualization of goal striving behavior in dynamic network theory is analogous to an entity that has a strong intention to engage in a goal or behavioral pursuit. BRT can provide insight into the underlying decision-making factors that activate goal striving 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 are implementing their roles in the context of other entities activating important roles in the broader social network. Hence, dynamic network theory provides an integrative meta-theoretical framework that subsumes BRT, which allows dynamic network theory to explain a broader range of human behavior and social complexities. However, Westaby, Pfaff, and Redding (2014) illustrate specific ways to integrate the two frameworks via “network intention modeling” at the individual level, which future research needs to investigate.