Behavioral Processes in Long-Lag Interventions

Dale T. Miller; Jennifer E. Dannals; Julian  Zlatev

Article | Perspectives on Psychological Science | May 2017

Behavioral Processes in Long-Lag Interventions

by Dale T. Miller, Jennifer E. Dannals and Julian Zlatev

Abstract

We argue that psychologists who conduct experiments with long lags between the manipulation and the outcome measure should pay more attention to behavioral processes that intervene between the manipulation and the outcome measure. Neglect of such processes, we contend, stems from psychology's long tradition of short-lag lab experiments where there is little scope for intervening behavioral processes. Studying process in the lab invariably involves studying psychological processes, but in long-lag field experiments it is important to study causally relevant behavioral processes as well as psychological ones. To illustrate the roles that behavioral processes can play in long-lag experiments we examine field experiments motivated by three policy-relevant goals: prejudice reduction, health promotion, and educational achievement. In each of the experiments discussed we identify various behavioral pathways through which the manipulated psychological state could have produced the observed outcome. We argue that if psychologists conducting long-lag interventions posited a theory of change that linked manipulated psychological states to outcomes via behavioral pathways, the result would be richer theory and more practically useful research. Movement in this direction would also permit more opportunities for productive collaborations between psychologists and other social scientists interested in similar social problems.

Keywords: Field Experiments; interventions; behavioral mediation; theories of change; longitudinal studies; Behavior; Research; Change; Theory;

Format: Print

Find at Harvard

Citation:

Miller, Dale T., Jennifer E. Dannals, and Julian Zlatev. "Behavioral Processes in Long-Lag Interventions." Perspectives on Psychological Science 12, no. 3 (May 2017): 454–467.

Biases influence important decisions, but little is known about whether and how individuals try to exploit others’ biases in strategic interactions. Choice architects—that is, people who present choices to others—must often decide between presenting choice sets with positive or certain options (influencing others toward safer options) versus presenting choice sets with negative or risky options (influencing others toward riskier options). We show that choice architects’ influence strategies are distorted toward presenting choice sets with positive or certain options across thirteen studies involving diverse samples (executives, law/business/medical students, adults) and contexts (public policy, business, medicine). These distortions appear to primarily reflect decision biases rather than social preferences, and they can cause choice architects to use influence strategies that backfire.

Article | Academy of Management Annals | 2019

Brokerage and Brokering: An Integrative Review and Organizing Framework for Third Party Influence

Nir Halevy, Eliran Halali and Julian Zlatev

Brokerage and brokering are pervasive and consequential organizational phenomena. Prevailing models underscore social structure and focus on the consequences that come from brokerage—occupying a bridging position between disconnected others in a network. By contrast, emerging models underscore social interactions and focus on brokering—the behavioral processes through which organizational actors shape others’ relationships. Our review led us to develop a novel framework as a means to integrate and organize a wide range of theoretical insights and empirical findings on brokerage and brokering. The Changing Others’ Relationships (COR) framework captures the following ideas that emerged from our review: (a) Different triadic configurations enable different forms of brokering, which in turn produce distinct effects on others’ relationships; (b) brokering is a multifaceted social influence process that can take the form of intermediation (connecting disconnected others) or modification (changing others’ preexisting relationships); (c) comparing social relations, for instance prebrokering versus postbrokering, reveals a broker’s impact; (d) brokering can influence others’ relationships positively or negatively; and (e) information and incentives are two principal means through which individuals change others’ relationships. Overall, the current review integrates multiple streams of research relevant to brokerage and brokering—including those on structural holes, organizational innovation, boundary spanning, social and political skill, workplace gossip, third-party conflict managers, and labor relations—and links each of the emergent themes identified in the current review to promising directions for future research on brokerage and brokering.

Keywords: brokerage; brokering; social interactions; Organizations; Relationships; Power and Influence; Framework;

Citation:

Halevy, Nir, Eliran Halali, and Julian Zlatev. "Brokerage and Brokering: An Integrative Review and Organizing Framework for Third Party Influence." Academy of Management Annals 13, no. 1 (2019): 215–239. View Details

Cite View Details Find at Harvard Read Now

Current theories suggest that people understand how to exploit common biases to influence others. However, these predictions have received little empirical attention. We consider a widely studied bias with special policy relevance: the default effect, which is the tendency to choose whichever option is the status quo. We asked participants (including managers, law/business/medical students, and US adults) to nudge others toward selecting a target option by choosing whether to present that target option as the default. In contrast to theoretical predictions, we find that people often fail to understand and/or use defaults to influence others, i.e., they show “default neglect.” First, in one-shot default-setting games, we find that only 50.8% of participants set the target option as the default across 11 samples (n = 2,844), consistent with people not systematically using defaults at all. Second, when participants have multiple opportunities for experience and feedback, they still do not systematically use defaults. Third, we investigate beliefs related to the default effect. People seem to anticipate some mechanisms that drive default effects, yet most people do not believe in the default effect on average, even in cases where they do use defaults. We discuss implications of default neglect for decision making, social influence, and evidence-based policy.

Faculty & Research

Behavioral Processes in Long-Lag Interventions

Abstract

Citation:

About the Author

More from the Author