Uncovering Uncertainty through Disagreement

Paletz, Susannah B. F.; Chan, Joel; Schunn, Christian D.

doi:10.1002/acp.3213

Cited by 19 publications

(5 citation statements)

References 79 publications

(140 reference statements)

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“…Content disagreements can enhance team learning and effective problem solving (e.g., Kellermanns et al, 2008;Paletz, Chan, & Schunn, 2016). However, disagreement is a complex phenomenon embedded in temporal interaction dynamics and influenced by attributes of behaviors, individuals, and teams.…”

Section: Discussionmentioning

confidence: 99%

Igniting and resolving content disagreements during team interactions: A statistical discourse analysis of team dynamics at work

Lehmann‐Willenbrock

Chiu

2017

J Organ Behavior

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Disagreements are integral to fruitful team collaboration but have rarely been studied within actual team interactions. We develop a temporal account of how disagreement episodes begin and are resolved during team interactions, testing explanatory factors at multiple levels: team context (team conflict states and team productivity), individual characteristics and perceptions (individual status and perceptions of team viability), and behavioral patterns (problem solving versus off-task communication) with a statistical discourse analysis of 32,448 turns of talk by 259 employees during 43 team meetings. As hypothesized, problem-solving behaviors (e.g., describing problems and proposing solutions) ignited content disagreements, often by participants who perceived greater team viability. In contrast, after off-task behaviors or talk by higher status team members, participants started fewer content disagreements. Moreover, content disagreements started by higher status individuals were more likely than those started by others to be resolved with agreements, especially via agreements with higher status individuals. Also, problem-solving behaviors facilitated the resolution of disagreement episodes with agreement, whereas off-task behaviors hindered them. Contrary to our hypotheses, team conflict states and productivity were not linked to starting or ending disagreements. We discuss the conceptual and methodological importance of capturing team interaction dynamics at work and derive practical implications for managing content disagreement.

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Section: Discussionmentioning

confidence: 99%

Igniting and resolving content disagreements during team interactions: A statistical discourse analysis of team dynamics at work

Lehmann‐Willenbrock

Chiu

2017

J Organ Behavior

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“…Both team disagreement and individual uncertainty rise and fall naturally over the course of conversations (Ball & Christensen, 2009;Chan et al, 2012;Christensen & Ball, 2016b;Paletz, Chan, & Schunn, 2016;Paletz, et al, 2011;McDonnell, 2012). Prior research on interactions between social and cognitive processes has often found important correlations between temporal dynamics of social/cognitive processes (e.g., conflicts sparking analogies during conversation; Paletz, Schunn & Kim 2013).…”

Section: Research Questions About Uncertainty and Conflict In Design mentioning

confidence: 99%

The dynamics of micro-conflicts and uncertainty in successful and unsuccessful design teams

2017

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What differentiates successful from unsuccessful design teams? Building on new research on design innovation that emphasizes interactions between social and cognitive processes, we investigated a potential distinguishing feature: Successful design teams may harness interpersonal conflicts (a social design process) to mitigate uncertainty (a cognitive design process). We analyzed temporal relationships between brief, expressed interpersonal disagreements and subsequent spoken individual uncertainty in 30 hours of conversations of 10 successful and 11 unsuccessful engineering product design teams. We discovered that microconflicts were followed by a relative reduction in uncertainty in successful design teams, whereas uncertainty rose after micro-conflicts in unsuccessful design teams, suggesting that interactions between conflict and uncertainty may be a differentiating factor for design team success.

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“…Providing some answers to the repeated calls for more dynamic research on team processes (e.g., Kozlowski, 2015 ) and on leader-follower interactions (e.g., Dinh et al, 2014 ), a number of recent studies have adopted a temporal approach and begun to study actual behavioral interactions in the workplace (e.g., Meinecke, Lehmann-Willenbrock, & Kauffeld, 2017 ; Paletz, Chan, & Schunn, 2016 ; Zijlstra, Waller, & Phillips, 2012 ). In particular, a small but growing research base investigates actual behaviors and behavioral patterns embedded in workplace interactions.…”

mentioning

confidence: 99%

Modeling Temporal Interaction Dynamics in Organizational Settings

Lehmann‐Willenbrock

Allen

2017

J Bus Psychol

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Most workplace phenomena take place in dynamic social settings and emerge over time, and scholars have repeatedly called for more research into the temporal dynamics of organizational behavior. One reason for this persistent research gap could be that organizational scholars are not aware of the methodological advances that are available today for modeling temporal interactions and detecting behavioral patterns that emerge over time. To facilitate such awareness, this Methods Corner contribution provides a hands-on tutorial for capturing and quantifying temporal behavioral patterns and for leveraging rich interaction data in organizational settings. We provide an overview of different approaches and methodologies for examining temporal interaction patterns, along with detailed information about the type of data that needs to be gathered in order to apply each method as well as the analytical steps (and available software options) involved in each method. Specifically, we discuss and illustrate lag sequential analysis, pattern analysis, statistical discourse analysis, and visualization methods for identifying temporal patterns in interaction data. We also provide key takeaways for integrating these methods more firmly in the field of organizational research and for moving interaction analytical research forward.

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Uncovering Uncertainty through Disagreement

Cited by 19 publications

References 79 publications

Igniting and resolving content disagreements during team interactions: A statistical discourse analysis of team dynamics at work

Igniting and resolving content disagreements during team interactions: A statistical discourse analysis of team dynamics at work

The dynamics of micro-conflicts and uncertainty in successful and unsuccessful design teams

Modeling Temporal Interaction Dynamics in Organizational Settings

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