Shannon M. Cruz

Business communication scholars have long been interested in how micro-level interactions among employees and members shape the emergence of important macro-level outcomes, such as organizational network formation and norms. Yet, the availability of methods to study emergence has lagged, leaving authors with limited options for examining these dynamics directly. In this paper, we describe how agent-based modeling (ABM) can help address this challenge, both by supplementing existing research and prompting interesting new questions. In doing so, we provide a detailed, albeit highly simplified, example of an ABM focusing on various organizational and business communication dynamics, namely, leader-member exchange (LMX), message quality, and message quantity. The model is intended as an introduction for business communication researchers interested in incorporating ABM into their own research agendas or simply learning more. Because the organizational and business arenas are rife with emergent phenomena that have not yet been modeled or examined in a quantitative manner, we believe that this method holds widespread utility in generating new questions and insights.

Diffusion of innovations theory proposes that opinion leaders can enhance the success of science communication campaigns. Such strategies hinge on an assumption that target communities include well-connected and trusted members who need only be identified and recruited. However, sparse or difficult to engage communication networks may not meet this assumption, making opinion leader-based interventions ineffective or impossible. This project reviews two studies involving rural populations where attempts to identify opinion leaders failed. We leverage these examples to highlight barriers to community-based campaigns, theoretical implications for diffusion scholarship, and suggested strategies for communication scholars and practitioners encountering sparse or fragmented networks.

A core tenet underpinning the conception of contemporary information networks, such as social media platforms, is that users should not be constrained in the amount of information they can freely and willingly exchange with one another about a given topic. By means of a computational agent-based model, we show how even in groups of truth-seeking and cooperative agents with perfect information-processing abilities, unconstrained information exchange may lead to detrimental effects on the correctness of the group’s beliefs. If unconstrained information exchange can be detrimental even among such idealized agents, it is prudent to assume it can also be so in practice. We therefore argue that constraints on information flow should be carefully considered in the design of communication networks with substantial societal impact, such as social media platforms.

Green stormwater infrastructure (GSI) is recognized as a sustainable urban water management solution. However, community stewardship remains low for various reasons, many of which are socio-cognitive and context-specific. This research applies the Theory of Planned Behavior (TPB) to explore the role of knowledge, experience, attitudes, subjective norms, perceived behavioral control, and demographic factors in predicting residents’ GSI stewardship intentions. Through an online survey and multilevel regression modeling, we analyzed data from 418 participants across three U.S. cities: Baltimore, MD, Pittsburgh, PA, and Portland, OR. Results show that perceived behavioral control and subjective norms significantly predicted GSI stewardship intentions, while attitudes did not. GSI knowledge affected stewardship intentions while positively influencing all other TPB constructs, particularly perceived behavioral control. Demographics, including homeownership, income, political ideology, race, and housing type, influenced TPB constructs, particularly attitudes. Findings highlight the importance of resource accessibility, social influence, and targeted knowledge dissemination in promoting GSI stewardship.

Addressing climate change requires persuading political conservatives—many of whom remain skeptical of climate science—to support climate initiatives. A possible method of reducing conservatives’ resistance to such messages is to use a source that matches their political identity. We attempted to replicate previous findings that perceived oneness with the source may explain why source matching increases persuasiveness for both a targeted attitude and potentially related attitudes. We also tested the extent to which the source-matching effect was further moderated by audience ego-involvement in their political identity. Two studies using pretest–posttest designs were used to assess these hypotheses. Results replicated the importance of oneness in explaining the source-matching effect, but found ego-involvement to be an inconsistent moderator. The data were consistent with a path model summarizing these predictions for the source-matching effect and oneness with the source.

Several theoretical approaches suggest that a promising approach to designing effective, tailored persuasive messages may be to draw on insights from an audience’s shared cognitive structure. Specifically, a cognitive-structural approach to message design would suggest that messages targeting central concepts in an audience’s shared cognitive structure will have stronger persuasive effects than messages targeting more peripheral concepts. The present investigation, however, failed to provide support for this approach. The results of four studies revealed that attitude and semantic networks each provided a different estimate of cognitive structure and made competing claims about whether this structure differs for Republicans and Democrats. However, neither structure successfully predicted which messages would be most effective. Instead, both Democrats and Republicans were persuaded by a wide range of arguments targeting both central and peripheral concepts. The results have implications for future work on the role of cognitive structures in persuasion and theory-driven message development.

Communication science has been criticized for relying on WEIRD samples. One question that arises from such criticisms is whether core communication constructs and measures generalize to different demographic groups. In other words, are measures of common communication variables interpreted similarly across groups? In this study, we assess the measurement invariance of numerous scales that are used commonly in research on communication science across five U.S. racial groups, seven English-speaking countries across five continents, and four age groups that are recognized by the American Psychological Association. Results indicate that respondents from different racial, national, and age groups exhibited measurement invariance. That is, people with different backgrounds responded to scales in similar ways, thereby indicating that some core communication constructs might be generalizable across certain groups. The implications of these results are considered, while noting that the invariance framework used herein can be used to continue examining the problem of construct invariance.

The superdiffuser model predicts that the diffusion of a new behavior can be accelerated if superdiffusers (people who are connectors, persuaders, and mavens) are recruited to promote the behavior. We propose an expanded model where the importance of these traits varies by network structure and other network member characteristics. We assessed the plausibility of these proposed moderators using a simulation of an agent-based model in which each moderator was varied along with the superdiffuser traits of those initially seeded with the behavior. Analysis of the results of those simulations showed support for many, but not all, of the predictions as well as several surprising results that are suggestive for future empirical research.

Developing effective messages to promote climate action requires an understanding of how these messages are processed by different groups. Though the influence of partisan identity on this processing is well established, much less is known about the role of preexisting climate beliefs. Furthermore, scholars have recently raised the possibility that what appear to be partisan effects on message judgments may simply be byproducts of accuracy-driven differences in perceived source credibility. Three online experiments revealed evidence that speaks to these conversations. The results show that message source, political affiliation, and preexisting climate beliefs combine nonadditively to affect persuasion. Furthermore, their effects are mediated by perceived source credibility. However, the evidence also suggests that this pattern emerged not because accuracy goals drive different perceptions of credibility but because credibility judgments are equally susceptible to directional motivated reasoning.