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

• DOI: http://doi.org/10.1002/job.2256
• Author: Nale Lehmann‐Willenbrock,Ming Ming Chiu
• Published date: 01 November 2018
• Date: 01 November 2018

SPECIAL ISSUE ARTICLE

Igniting and resolving content disagreements during team

interactions: A statistical discourse analysis of team

dynamics at work

Nale Lehmann‐Willenbrock

1

|Ming Ming Chiu

2

1

University of Amsterdam, Amsterdam, The

Netherlands

2

The Education University of Hong Kong,

Hong Kong

Correspondence

Nale Lehmann‐Willenbrock, University of

Amsterdam, Amsterdam, The Netherlands.

Email: n.lehmann‐willenbrock@uva.nl

Summary

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 ver-

sus 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 per-

ceived 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.

KEYWORDS

disagreement,dynamic multilevel modeling, temporal team interactions, status, team viability

1|INTRODUCTION

Honest disagreement is often a good sign of progress.

M. Gandhi

Disagreements encompass a range of verbal behaviors that are

opposed to agreement (for an overview, see Angouri & Locher,

2012). In contrast to reflexive, uncritical agreements that can hinder

team problem solving (e.g., Aldag & Fuller, 1993; Esser, 1998; Leana,

1985), disagreements can help teams create better solutions through

integrating divergent perspectives and sparking new ideas (e.g., Jansen,

Van de Vliert, & West, 2004; Paulus & Brown, 2007). In this study, we

focus on rejections or contradictions of other members' contributions

without personal judgment (content disagreement). Content disagree-

ment can be crucial not only for superior team problem solving and

decision making but also for team and organizational effectiveness

more broadly (e.g., Ellis et al., 2003; Garvin, Edmondson, & Gino,

2008; Kellermanns, Floyd, Pearson, & Spencer, 2008; Van Offenbeek,

2001). As content disagreements can display and integrate different

perspectives, they can help team members learn about one another's

views, their interactions, and their organization (i.e., organizational

learning; e.g., Argyris & Schön, 1996; Edmondson, 2002; Senge, 1990).

Yet some studies offer an alternate view. For example, Van

Woerkom and Sanders (2010) report negative effects of disagreement

on opinion sharing in teams. We believe that there are four reasons for

such ambiguities in the literature, namely, (1) a lack of distinction

between disagreements on the one hand (i.e., behaviors at specific

points in team interactions) and emergent team conflict; (2) lack of dis-

tinction among different types of disagreements and their resolutions;

(3) lack of quantitative research on behaviors during actual

Received: 30 September 2016 Revised: 5 October 2017 Accepted: 13 November 2017

DOI: 10.1002/job.2256

1142 © 2017 John Wiley & Sons, Ltd. J Organ Behav. 2018;39:1142–1162.wileyonlinelibrary.com/journal/job

disagreements within temporal social interactions (cf. Garner, 2013);

and (4) inadequate statistical modeling of the interplay among individ-

ual attitudes, team attributes, and behavioral dynamics that trigger

disagreement occurrences. To resolve these ambiguities, we examine

disagreement episodes and resolutions as they unfold in real time dur-

ing regular team meeting interactions—rather than relying on aggrega-

tions of such behaviors or post hoc self‐reports. We draw from

psychological perspectives of disagreement and team interactions,

and we use quantitative methodology and statistical modeling to test

our hypotheses.

Importantly, disagreements within teams are not isolated occur-

rences. Instead, each disagreement begins and ends within social and

temporal contexts, so we must account for explanatory mechanisms

at multiple levels (team, individual, and behavioral or turn of talk level;

e.g., Chiu & Lehmann‐Willenbrock, 2016). The behaviors that shape

disagreement episodes at the behavioral level are nested in the individ-

uals who produce them, who in turn are nested in teams. Conse-

quently, disagreement episodes are affected by influences stemming

from the team context, from individual characteristics and attitudes,

and from temporal dynamics at the behavioral event level. Hence, we

integrate theory about team contextual factors, emergent team states,

and individual‐level influences on dynamic team interaction processes

in ongoing teams to develop a multilevel temporal account of disagree-

ment episodes in ongoing team interactions.

In terms of team contextual influences, we consider the role of

general team productivity levels and previously emerged team conflict

states (i.e., members' shared perceptions about task and relationship

conflict experienced to date; e.g., Maltarich, Kukenberger, Reilly, &

Mathieu, in press). Teams with superior productivity might capitalize

on disagreements to improve their performance or have greater confi-

dence to express their ideas (including conflicting ones), both of which

tend to yield more disagreements (e.g., Lovelace, Shapiro, & Weingart,

2001; Van Woerkom & Sanders, 2010). Furthermore, a team that

experiences greater intragroup conflict might (a) view disagreement

as socially acceptable and hence express more disagreements

compared to other teams (Weingart, Behfar, Bendersky, Todorova, &

Jehn, 2016) or (b) suffer more social embarrassments, fear the

consequences of fueling disagreements, and refrain from voicing

disagreements (for an overview, see Weingart et al., 2016).

Next, we consider the influence of individual perceptions of team

viability and individual status. Individuals who care more about the

long‐term future of their team (i.e., who experience high team viability,

e.g., Bell & Marentette, 2011) might be more likely than others to

invite ideas from others, identify flaws, and share alternatives—the lat-

ter two often foster disagreements. Furthermore, people are often

more likely to agree with a high‐status team member than a low‐status

one and less likely to disagree with the former than the latter (Chiu &

Khoo, 2003).

Moreover, temporal dynamics at the event level can influence

team behaviors in general (e.g., Chiu & Lehmann‐Willenbrock, 2016;

Lehmann‐Willenbrock, Chiu, Lei, & Kauffeld, 2017) and ignite or

resolve disagreements. Specific behaviors can create distinct momen-

tary conversational contexts that could influence the likelihoods of

starting or ending disagreements. Problem‐solving behaviors and

sequences (e.g., identifying problems and proposing solutions) might

invite alternate views, thereby starting disagreements but also helping

to resolve them. In contrast, off‐task behaviors and sequences (e.g.,

laughing or engaging in side conversations) might distract from the

central task to reduce tension, thereby reducing the likelihoods of both

starting a disagreement and ending an ongoing one.

To address these issues, we apply a multilevel, time‐series method,

statistical discourse analysis (SDA; Chiu, 2008b; Chiu & Lehmann‐

Willenbrock, 2016), to videotaped meeting conversations

(N= 32,448 turns of talk) in a sample of 43 real teams. Although

inspired by discourse analysis, SDA itself is a statistical method built

on ordinary least squares regression (see details in Chiu & Lehmann‐

Willenbrock, 2016). Our study contributes to the literature on work-

place dynamics, teams' temporal processes, and temporal dynamics

surrounding disagreements in three key ways. First, we introduce and

test a multilevel (team, individual, and turn of talk), time‐series, explan-

atory model for igniting verbally expressed disagreements, thereby

addressing repeated calls to study the temporal nature of team interac-

tions (e.g., Cronin, Weingart, & Todorova, 2011; Waller, Okhuysen, &

Saghafian, 2016). Second, we introduce and test a corresponding mul-

tilevel, time‐series, explanatory model for resolving a disagreement

with an agreement. Third, we disentangle disagreement behaviors

embedded in temporal team interaction sequences from emergent

conflict states, thus resolving ambiguities in the team conflict litera-

ture. As this study can inform our understanding of how teams ignite

and resolve disagreements at the behavioral level, it can yield impor-

tant insights for managing team dynamics—a critical leadership

challenge (e.g., Morgeson, DeRue, & Karam, 2010).

2|THEORETICAL BACKGROUND AND

HYPOTHESES

Team interactions are complex, temporal, multilevel phenomena.

Early work by McGrath (1984) described them as “patterned rela-

tions”(p. 11). They are complex because they (a) entail members' inter-

dependent acts (Marks, Mathieu, & Zaccaro, 2001, p. 357), (b) require

constant coordination among member contributions (e.g., Kolbe et al.,

2014), and (c) are at the core of teamwork itself (for an overview, see

Grossman, Friedman, & Kalra, 2017). Team interactions are inherently

temporal because team task accomplishment requires temporal

rhythms (e.g., Mohammed, Hamilton, & Lim, 2009; Zellmer‐Bruhn,

Waller, & Ancona, 2004), and team dynamics are temporally patterned

(e.g., Massey, Montoya‐Weiss, & Hung, 2003; see also Lehmann‐

Willenbrock & Allen, 2017). Finally, team interactions are multilevel

phenomena because their constituent behaviors are nested in temporal

behavioral contexts, in individuals, and in teams. Hence, discrete inter-

action events such as disagreement are subject to influences at the

behavioral event level, at the individual level, and at the team level.

Regarding multilevel influences on team interactions, research

insights to date are limited. Current multilevel thinking in team

research typically argues how emergent team states manifest upward

from individual‐level characteristics and interactions among individuals

(e.g., Kozlowski, Chao, Grand, Braun, & Kuljanin, 2013). This perspec-

tive is certainly helpful for understanding how emergent team con-

structs come into existence in the first place, yet it does not explain

LEHMANN‐WILLENBROCK AND CHIU 1143