Communicating via Video Conferencing: The Mediating Effect of Member Influence Disparity on Task Performance

Abstract

Although geographically dispersed organizations increasingly rely on virtual platforms to collaborate, virtual communication can undermine key team processes and outcomes. Prior research has largely focused on individual-level explanations, such as cognitive strain or “Zoom fatigue,” for these challenges. We extend this literature by proposing that virtual communication also reinforces hierarchical structures by amplifying disparities in member influence during decision-making. In a controlled experiment comparing video conferencing and face-to-face teams, we find that disparities in member influence are significantly greater in virtual teams, which in turn reduces task performance. These findings highlight a critical, group-level mechanism through which virtual communication shapes communication patterns and outcomes, beyond previously identified individual-level factors. By identifying disparity in member influence as a key mediator, this study advances theory on virtual communication, group hierarchy, and decision-making and offers practical implications for reducing hierarchical distortions and fostering more equal-level conversations that enhance team effectiveness.

Keywords

hierarchy team dynamics video conferencing virtual communication

Rapid technological advances have shifted work toward remote collaboration and heavy reliance on video-conferencing tools.^1–4 Organizations use these platforms to enable synchronous coordination across locations.^3,4 Yet emerging research suggests that such communication may also have negative consequences.^1,2 A prominent individual-level mechanism is Zoom fatigue—physical and cognitive exhaustion from sustained platform use—which reduces attention and willingness to engage.^5–9

Beyond individual mechanisms, group-level structures matter. Hierarchy, defined as the rank-order relationships of influence and participation among group members, shapes team processes and outcomes.^10–13 In task-oriented groups, hierarchies often emerge and may be reshaped through status cues during group interactions.^13–17 While hierarchy can facilitate coordination and effectiveness,^17–19 it can also hinder collective decision-making by reducing communication engagement and fluency.^20–22

Video conferencing removes shared physical space,^23,24 limiting status-relevant cues. Drawing from status characteristics and expectation state theories as well as the communication science literature, we propose that this lack of shared space may reinforce early, cue-based hierarchies. These hierarchies may yield asymmetrical influence patterns—what we refer to as disparity in member influence—defined as the extent to which high- and low-status individuals differ in their engagement and influence over key team decisions during collaboration.^21,25 This disparity, we argue, is a central mechanism linking video conferencing to poorer performance in collective decision-making tasks.

Theoretical Background and Hypotheses

Absence of shared space in video conferencing and disparity in member influence

Although the rapid expansion of video conferencing during COVID-19 brought flexibility, lower costs, and remote access to talent,^26–30 it also reduced trust³¹ and hindered collaboration.^32,33 Prior research has primarily focused on individual-level factors—such as Zoom fatigue—to explain negative outcomes in virtual communication.^33,34 We extend this research by examining group-level hierarchical structures for two key reasons. First, hierarchy strongly shapes team processes and outcomes.^10–13 Second, the absence of shared physical space channels communication through limited technical features,^23,24 constraining rich verbal and nonverbal exchange. These constraints may make preexisting status cues more likely to persist unchallenged, thereby reinforcing hierarchical patterns and shaping subsequent team dynamics.

According to status characteristics and expectation states theories, in task-oriented situations, group members are motivated to assess each other’s characteristics and behaviors to form implicit judgments about who appears most competent to contribute.^13,35–37 These judgments tend to be self-reinforcing, shaping interaction patterns that maintain and amplify initial perceptions.^35–37 Individuals perceived as more competent (i.e., higher-status members) are more likely to speak up and lead, whereas those perceived as less competent often defer, limiting their engagement and influence.^21,35,36 This dynamic often reinforces pre-existing hierarchies and disparity in member influence within the group.

A shared physical space in face-to-face communication enables access to rich verbal and nonverbal cues,^38,39 allowing individuals to form more accurate judgments about one another’s competence.^28,37 In such settings, group members often closely observe one another, which can prompt them to reassess—and at times move beyond—preexisting status hierarchies.^21,37 Recent study suggests that group members may use social cues (i.e., leaders’ nonverbal signals toward lower-status members) to reassess initial status hierarchies, thereby encouraging those members’ active participation and reducing influence disparities.²¹

In contrast, video conferencing environments lack this shared space, limiting access to status-relevant cues.^23,24,40 With reduced visibility and mental capacity, members may anchor on salient early cues and have fewer opportunities—or less motivation—to revisit initial competence judgments, allowing early hierarchies to persist and disparities to widen. In addition, structural features of video conferencing platforms may further constrain lower-status members. Difficulties in managing conversational turn-taking and the visual prominence of dominant speakers (e.g., speaker view, spotlight features) can amplify higher-status voices while obscuring lower-status participants, thereby exacerbating influence disparities rooted in the initial status hierarchy. Thus, we predict: Hypothesis 1:

In a group meeting context during video conferencing, the disparity in member influence will be higher than in a group meeting engaging face-to-face conferencing.

The impact of disparity in member influence on team performance in a virtual setting

This disparity may be a key pathway that can explain why virtual communication often leads to negative team processes and outcomes in collective decision-making tasks. The literature on collective intelligence and idea elaboration suggests that groups perform better when all members freely share ideas, consider one another’s perspectives, and integrate them into the task.^41,42 Productive communication requires members to be motivated to actively exchange and process diverse, task-relevant information.^43,44

However, when higher-status members dominate and lower-status members remain passive, this disparity in influence can discourage the latter from contributing diverse perspectives.²¹ As discussions increasingly revolve around higher-status opinions, the quality of group communication and outcomes is likely to decline.^21,42 Accordingly, we expect greater disparities in member influence in virtual communication to hinder balanced exchanges and, in turn, reduce team performance: Hypothesis 2:

Team performance in video conferencing will be lower than that in face-to-face conferencing.

Hypothesis 3:

Disparity in member influence mediates the impact of video conferencing on team performance.

Methods

Participants and task

One hundred and 50 undergraduates (96 males, 54 females) from three Korean universities participated. Each group consisted of three participants: one project leader and two group members. To introduce initial status cues, participants first completed an intellectual task individually (see Procedure for details). Gender composition varied across teams (mixed- and same-gender). All participants were Korean nationals.

After completing an intellectual task, participants engaged in a group decision-making exercise, serving as consultants at Best Solution Consulting firm.⁴⁵ They were asked to rank the profitability of five food products based on the information provided (i.e., Cosmo Explosion, Whitey, Zen, Treasure Island, and Business Class). The task aimed to provide recommendations to clients regarding which food product would generate the highest profit.

In line with Stasser and colleagues’ procedures,⁴⁶ all participants received identical background information about the client, while product-specific information was distributed differently across members. In this design, we adapted and translated a hidden-profile task in which critical information about the best option was spread across members, making active information sharing essential to identify the correct choice.^47,48 If one member (e.g., the leader) dominated the discussion, groups were less likely to reach the optimal solution.

Procedure

This study had four phases. In Phase 1, participants were randomly assigned to either the video conferencing (n = 25 groups) or face-to-face condition (n = 25 groups). Before participating, those in the video condition received a Zoom link, while those in the face-to-face condition were given a lab address. Participants were then placed in groups of three and completed a 10-minute intellectual task with 15 questions on history, geography, science, philosophy, and general knowledge. This task was designed to create a salient status cue based on perceived performance differences.

In Phase 2, participants were informed that group roles were determined by individual task scores, with the highest scorer designated as leader and the others as members. This framing was designed to legitimize the leader’s role and signal competence, thereby establishing an initial status hierarchy prior to interaction. In reality, leaders were randomly assigned, allowing us to examine whether hierarchies in video conferencing groups were more likely to persist when initially cued by status than in face-to-face groups.

In Phase 3, each participant was placed in an individual room (or Zoom breakout room) to review information about food products and rank them by expected profitability. This task was completed independently, without interaction. Participants then met face-to-face or via Zoom to discuss the information and produce a joint ranking, which we used to assess group performance. Participants’ roles were clearly indicated by name tags or Zoom names, and all discussions were videotaped to measure disparities in member influence.

In Phase 4, after ranking the products, participants moved to individual rooms (or Zoom breakout rooms) and completed a questionnaire to assess whether the communication setting manipulation was successful and whether they understood their assigned roles. For example, they indicated whether the team discussion took place via video conferencing or face-to-face in response to the question, “In what setting did today’s team discussion occur?” Finally, participants were debriefed on the study’s purpose.

Measures

Disparity in member influence

We assessed disparity in member influence using a coding scheme adapted from Shim and colleagues.²¹ Two independent coders, blind to the hypotheses, evaluated each video-recorded team interaction on a 1–5 scale, where 1 indicated equal influence and 5 indicated that one member exerted substantially greater influence. Coders followed a scheme based on prior work with three behavioral indicators: (1) talking time, (2) decision-making and suggestions, and (3) leading discussions.^21,25 Based on these indicators, coders assessed the extent to which one member spoke more, made more decisions and suggestions, and guided the discussion (e.g., “I think it is a waste of time to keep talking about this issue”), while the others listened more, hesitated to contribute, and deferred to their partner (e.g., “I think that is a good idea”). Each point on the 5-point scale was anchored with behavioral descriptions. Coders reviewed the scheme beforehand and applied it while watching the videos, ensuring that disparity scores reflected systematic, behaviorally grounded assessments. Interrater reliability was good (ICC1 = 0.61, ICC2 = 0.76, p < 0.001; mean r_wg = 0.86), so the ratings were averaged to compute an overall score.^49–51

Team performance index

Group performance was assessed by comparing the group’s ranking of five products with the correct ranking. Differences across products were summed (range = 0–12, lower scores = better performance) and subtracted from 12 to yield an index in which higher scores reflected superior performance.

Dominance of the leader

To assess whether the disparity in member influence observed in the video conferencing condition was primarily driven by the assigned leader, we recruited two additional independent coders, blind to the hypotheses. They rated video recordings of team discussions on the extent to which the leader, relative to other members, shaped and dominated the conversation (e.g., “The team leader dominated the overall discussion during the task”; 1 = strongly disagree, 7 = strongly agree). Intercoder reliability was good (ICC1 = 0.67, ICC2 = 0.79, p < .001; mean r_wg = 0.82), so we averaged their ratings.

Results

Table 1 presents the means, standard deviations, and correlations for all measures. A post-hoc sensitivity analysis (G*Power 3.1; α = 0.05) based on the observed effect size and sample size yielded power = 0.95, indicating adequate sensitivity for the focal comparison.⁵²

Table 1.

Means, Standard Deviations, and Correlations

Variable	Mean	SD	1	2	3
1. Type of communication context^a	0.50	0.50
2. Task performance	5.88	2.82	−0.36^*
3. Disparity in member influence	2.04	0.83	0.34^*	−0.40^**
4. Dominance of the leader	3.06	1.11	0.60^**	−0.42^**	0.58^**

Type of communication context (1 = video conferencing, 0 = face-to-face conferencing).

*p < 0.05, ^** p < 0.01.

Manipulation checks

The manipulation of communication context (i.e., video conferencing vs. face-to-face) was successful, χ² [1, n = 50] = 150, p < 0.001.

Disparity in member influence

Consistent with H1, in the video conferencing groups, disparity in member influence was higher (M = 2.32, SD = 0.86) than in the face-to-face conferencing groups (M = 1.76, SD = 0.71), t(48) = 2.50, p = 0.016, d = 0.71.

Task performance

Consistent with H2, group performance was lower in the video conferencing groups (M = 4.88, SD = 2.71) than in the face-to-face conferencing groups (M = 6.88, SD = 2.65), t(48) = −2.636, p = 0.011, d = 0.74.

Mediation analyses

H3 predicted that the negative effect of video conferencing on group performance would be mediated by disparity in member influence. We tested this mediation hypothesis with the PROCESS macro, specifying Model 4.⁵³ As expected, the relative indirect effect of video conferencing on group performance was significant (β = −0.59, SE = 0.31, 95 percent bias-corrected CI = [−1.29, −0.06]). H3 was supported.

Dominance of the leader

Team leaders in the video conferencing groups dominated the overall discussion more (M = 3.72, SD = 1.08) than those in the face-to-face conferencing groups (M = 2.40, SD = 0.66), t(48) = 5.22, p < 0.001, d = 1.47.

General Discussion

Amid the rapid expansion of video conferencing, this study investigates how communication modality shapes group dynamics, demonstrating that persistent disparities in member influence in virtual teams can undermine task performance relative to face-to-face groups.

Theoretical Contributions

Our findings contribute to research on communication, group dynamics, and team performance. First, we propose a group-level mechanism for why video conferencing can impair performance. Whereas prior work has emphasized individual-level explanations such as cognitive strain or Zoom fatigue, our study identifies disparity in member influence as a key group-level process that constrains effective discussion. We show that hierarchical structures crystallized in virtual settings can limit lower-status members’ engagement, producing suboptimal performance.

We also extend understanding of how virtual communication shapes hierarchy by integrating online communication research with status characteristics and expectation states theories. While hierarchy formation and evolution have been extensively studied in face-to-face interaction, little is known about how they unfold online. We argue that the lack of shared space in video conferencing hinders members’ ability to observe competence cues, making teams more likely to preserve pre-assigned hierarchies rather than revise them through interaction. This reinforces influence disparities, with higher-status individuals dominating discussion and lower-status members deferring.

These findings may resemble prior work on the social identity model of deindividuation effects (SIDE model),⁵⁴ which argues that computer-mediated communication can foster deindividuation, stronger group norms, and polarization.⁵⁵ Yet SIDE emphasizes that such effects require visual anonymity, whereas in our study participants were visually (and aurally) salient to one another. We propose that the absence of co-presence in a shared physical space—rather than anonymity—amplifies hierarchical structures, rendering non-leaders more passive and ultimately leading to poorer performance than in face-to-face groups.

Practical Implications, Limitations, and Future Directions

This research offers insights for organizations navigating remote work and virtual collaboration. Our findings suggest that video conferencing can inadvertently reinforce preexisting status hierarchies, creating disparities in member influence that limit idea diversity and undermine performance. To counteract these effects, leaders may adopt strategies such as structured turn-taking, rotating discussion roles, and informal interactions that highlight members’ diverse skills and reduce reliance on initial status cues.^56,57

Several limitations should also be noted. First, we did not conduct an a priori power analysis due to logistical challenges in recruiting groups for simultaneous sessions. Second, our study focused exclusively on Zoom; other platforms may shape team dynamics differently, particularly across cultures. Finally, we did not examine leadership styles, which may interact with status cues to amplify or reduce disparities in virtual teams. Future research could explore how different leadership approaches influence these dynamics.

Authors’ Contributions

H.K.: Conceptualization, methodology (equal), investigation, writing—original draft preparation. S.-H.S.: Conceptualization (supporting), methodology (equal), writing (equal), review and editing (equal). S.J.(G.)A.: Conceptualization (supporting), writing (supporting), review and editing (equal). S.L.: Conceptualization, methodology, resources, writing—reviewing and editing, supervision, project administration and funding acquisition.

Footnotes

Acknowledgment

This work is based on the Master’s Thesis by HongKeun Kim, submitted to KAIST and supervised by So-Hyeon Shim and Sujin Lee. Please address correspondence regarding this article to So-Hyeon Shim (sshim@cau.ac.kr) or Sujin Lee (sujinlee@kaist.ac.kr).

Author Disclosure Statement

The authors declare that they have no conflicts of interest related to this study or its publication. In addition, the authors confirm that no AI services were used to generate or edit any part of the article or its associated data.

Funding Information

This work was supported by the National Research Foundation of Korea (NRF) under the BK21 FOUR program (for Sujin Lee), and by the Chung-Ang University Research Grants in 2024 (for So-Hyeon Shim).

References

Brucks

, Levav

. Virtual communication curbs creative idea generation. Nat, 2022; 605(7908):108–112; doi: 10.1038/s41586-022-04643-y

Horvát

EÁ

, Uzzi

. Virtual collaboration hinders a key component of creativity. Nat, 2022; 1(3):42–53; doi: 10.1038/d41586-022-00126-2

Cogliser

, Gardner

, Trank

, et al. Not all group exchange structures are created equal: Effects of forms and levels of exchange on work outcomes in virtual teams. J Leadersh Organ Stud, 2013; 20(2):242–251; doi: 10.1177/1548051812472370

Klitmøller

, Lauring

. When global virtual teams share knowledge: Media richness, cultural difference and language commonality. J World Bus, 2013; 48(3):398–406; doi: 10.1016/j.jwb.2012.07.023

Riedl

. On the stress potential of videoconferencing: Definition and root causes of Zoom fatigue. Electron Mark, 2022; 32(1):153–177; doi: 10.1007/s12525-021-00501-3

Fosslien

, Duffy

. How to combat Zoom fatigue. Harv Bus Rev, 2020; 29(1):1–6.

Shockley

, Gabriel

, Robertson

, et al. The fatiguing effects of camera use in virtual meetings: A within-person field experiment. J Appl Psychol, 2021; 106(8):1137–1155; doi: 10.1037/apl0000948

Wiederhold

. Connecting through technology during the coronavirus disease 2019 pandemic: Avoiding “Zoom Fatigue. Cyberpsychol Behav Soc Netw, 2020; 23(7):437–438; doi: 10.1089/cyber.2020.29188.bkw

Williams

. Working through COVID-19: ‘Zoom’ gloom and ‘Zoom’ fatigue. Occup Med, 2021; 71(3):164; doi: 10.1093/occmed/kqab041

10.

Anderson

, Brown

. The functions and dysfunctions of hierarchy. Res Organ Behav, 2010; 30:55–89; doi: 10.1016/j.riob.2010.08.002

11.

Bunderson

, Van Der Vegt

, Cantimur

, et al. Different views of hierarchy and why they matter: Hierarchy as inequality or as cascading influence. AMJ, 2016; 59(4):1265–1289; doi: 10.5465/amj.2014.0601

12.

Hays

, Bendersky

. Not all inequality is created equal: Effects of status versus power hierarchies on competition for upward mobility. J Pers Soc Psychol, 2015; 108(6):867–882; doi: 10.1037/pspi0000017

13.

Ridgeway

, Walker

. Status Structures. In: Sociological Perspectives on Social Psychology. ( Cook

, Fine

, House

. eds) Cambridge University Press: USA; 1995; pp. 281–311.

14.

Gruenfeld

, Tiedens

. Organizational Preferences and their Consequences. In: Handbook of Social Psychology. ( Fiske

, Gilbert

, Lindzey

. eds.) John Wiley & Sons: USA; 2010; pp. 159–178.

15.

Tiedens

, Ellsworth

, Mesquita

. Sentimental stereotypes: Emotional expectations for high-and low-status group members. Pers Soc Psychol Bull, 2000; 26(5):560–575; doi: 10.1177/0146167200267004

16.

Bales

. Interaction Process Analysis: A Method for the Study of Small Groups. Addison-Wesley: Chicago; 1950.

17.

Halevy

, Chou

, Galinsky

. A functional model of hierarchy: Why, how, and when vertical differentiation enhances group performance. Organ Psychol Rev, 2011; 1(1):32–52; doi: 10.1177/2041386610380991

18.

Tiedens

, Unzueta

, Young

. An unconscious desire for hierarchy? The motivated perception of dominance complementarity in task partners. J Pers Soc Psychol, 2007; 93(3):402–414; doi: 10.1037/0022-3514.93.3.402

19.

Keltner

, Van Kleef

, Chen

, et al. A reciprocal influence model of social power: Emerging principles and lines of inquiry. Adv Exp Soc Psychol, 2008; 40:151–192; doi: 10.1016/S0065-2601(07)00003-2

20.

Greer

, Van Bunderen

, Yu

. The dysfunctions of power in teams: A review and emergent conflict perspective. Res Organ Behav, 2017; 37:103–124; doi: 10.1016/j.riob.2017.10.005

21.

Shim

S-H

, Livingston

, Phillips

, et al. The impact of leader eye gaze on disparity in member influence: Implications for process and performance in diverse groups. AMJ, 2021; 64(6):1873–1900; doi: 10.5465/amj.2017.1507

22.

Wolfe

, McGinn

. Perceived relative power and its influence on negotiations. Group Decis Negot, 2005; 14(1):3–20; doi: 10.1007/s10726-005-3873-8

23.

Carmody

, Mazzarello

, Santi

, et al. The effect of co-location on human communication networks. Nat Comput Sci, 2022; 2(8):494–503; doi: 10.1038/s43588-022-00296-z

24.

Song

, Berends

, Van Der Bij

, et al. The effect of IT and co-location on knowledge dissemination. J of Product Innov Manag, 2007; 24(1):52–68; doi: 10.1111/j.1540-5885.2006.00232.x

25.

Harrison

, Klein

. What’s the difference? Diversity constructs as separation, variety, or disparity in organizations. AMR, 2007; 32(4):1199–1228; doi: 10.5465/amr.2007.26586096

26.

Kier

, McMullen

. Entrepreneurial imaginativeness and new venture ideation in newly forming teams. J Bus Ventur, 2020; 35(6):106048; doi: 10.1016/j.jbusvent.2020.106048

27.

Lee

. Dynamics of symmetrical communication within organizations: The impacts of channel usage of CEO, managers, and peers. Int J Bus Commun, 2022; 59(1):3–21; doi: 10.1177/2329488418803661

28.

Burgoon

, Bonito

, Ramirez

, et al. Testing the interactivity principle: Effects of mediation, propinquity, and verbal and nonverbal modalities in interpersonal interaction. J Commun, 2002; 52(3):657–677; doi: 10.1093/joc/52.3.657

29.

Gibson

, Cohen

. Virtual Teams that Work: Creating Conditions for Virtual Team Effectiveness. John Wiley & Sons: San Francisco, CA; 2003.

30.

Henttonen

, Blomqvist

. Managing distance in a global virtual team: The evolution of trust through technology‐mediated relational communication. Strateg Chang, 2005; 14(2):107–119; doi: 10.1002/jsc.714

31.

Jarvenpaa

, Leidner

. Communication and trust in global virtual teams. J Comput Mediat Commun, 2006; 3(4):0; doi: 10.1111/j.1083-6101.1998.tb00080.x

32.

Gibbs

, Mengel

, Siemroth

. Employee innovation during office work, work from home and hybrid work. Sci Rep, 2024; 14(1):17117; doi: 10.1038/s41598-024-67122-6

33.

Falter

, Arenas

, Maples

, et al. Making room for Zoom in focus group methods: Opportunities and challenges for novice researchers (during and beyond COVID-19). Forum Qual Soc Res, 2022; 23(1); doi: 10.17169/fqs-23.1.3768

34.

Fauville

, Luo

, Queiroz

, et al. Video-conferencing usage dynamics and nonverbal mechanisms exacerbate zoom fatigue, particularly for women. Comput Hum Behav Rep, 2023; 10:100271; doi: 10.1016/j.chbr.2023.100271

35.

Berger

, Zelditch

. Status, Rewards, and Influence. Jossey-Bass: San Francisco, CA; 1985.

36.

Berger

, Cohen

, Zelditch

. Status characteristics and social interaction. Am Sociol Rev, 1972; 37(3):241–255.

37.

Bunderson

. Recognizing and utilizing expertise in work groups: A status characteristics perspective. Adm Sci Q, 2003; 48(4):557–591; doi: 10.2307/3556637

38.

Ransom

, LaGrant

, Spiteri

, et al. Face-to-face learning enhances the social transmission of information. PLoS One, 2022; 17(2):e0264250; doi: 10.1371/journal.pone.0264250

39.

Hadley

, Naylor

, Hamilton

AFDC

. A review of theories and methods in the science of face-to-face social interaction. Nat Rev Psychol, 2022; 1(1):42–54; doi: 10.1038/s44159-021-00008-w

40.

Peper

, Wilson

, Martin

, et al. Avoid Zoom fatigue, be present and learn. NR, 2021; 8(1):47–56; doi: 10.15540/nr.8.1.47

41.

Hoever

, Van Knippenberg

, Van Ginkel

, et al. Fostering team creativity: Perspective taking as key to unlocking diversity’s potential. J Appl Psychol, 2012; 97(5):982–996; doi: 10.1037/a0029159

42.

Woolley

, Chabris

, Pentland

, et al. Evidence for a collective intelligence factor in the performance of human groups. Science, 2010; 330(6004):686–688; doi: 10.1126/science.1193147

43.

Nederveen Pieterse

, Van Knippenberg

, Van Dierendonck

. Cultural diversity and team performance: The role of team member goal orientation. AMJ, 2013; 56(3):782–804; doi: 10.5465/amj.2010.0992

44.

Van Knippenberg

, De Dreu

, Homan

. Work group diversity and group performance: An integrative model and research agenda. J Appl Psychol, 2004; 89(6):1008; doi: 10.1037/0021-9010.89.6.1008

45.

Mell

, Van Knippenberg

, Van Ginkel

. The catalyst effect: The impact of transactive memory system structure on team performance. AMJ, 2014; 57(4):1154–1173; doi: 10.5465/amj.2012.0589

46.

Stasser

, Titus

. Pooling of unshared information in group decision making: Biased information sampling during discussion. J Pers Soc Psychol, 1985; 48(6):1467–1478; doi: 10.1037//0022-3514.48.6.1467

47.

Tost

, Gino

, Larrick

. When power makes others speechless: The negative impact of leader power on team performance. AMJ, 2013; 56(5):1465–1486; doi: 10.5465/amj.2011.0180

48.

Stasser

, Stewart

. Discovery of hidden profiles by decision-making groups: Solving a problem versus making a judgment. J Pers Soc Psychol, 1992; 63(3):426–434; doi: 10.1037//0022-3514.63.3.426

49.

Bliese

. Within-Group Agreement, Non-Independence, and Reliability: Implications for Data Aggregation and Analysis. In: Multilevel Theory, Research, and Methods in Organizations. ( Klein

, Kozlowski

SWJ

. eds.) Jossey-Bass: San Francisco, CA; 2000; pp. 349–381.

50.

Kozlowski

SWJ

, Klein

. A Multilevel Approach to Theory and Research in Organizations: Contextual, Temporal, and Emergent Processes. In: Multilevel Theory, Research, and Methods in Organizations: Foundations, Extensions, and New Directions. ( Klein

, Kozlowski

SWJ

. eds.) Jossey-Bass: San Francisco, CA; 2000; pp. 3–90.

51.

LeBreton

, Senter

. Answers to 20 questions about interrater reliability and interrater agreement. Organ Res Methods, 2008; 11(4):815–852; doi: 10.1177/1094428106296642

52.

Faul

, Erdfelder

, Buchner

, et al. Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behav Res Methods, 2009; 41(4):1149–1160; doi: 10.3758/BRM.41.4.1149

53.

Hayes

. Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. The Guilford Press: New York, NY; 2013.

54.

Spears

, Lea

. Panacea or panopticon? The hidden power in computer-mediated communication. Commun Res, 1994; 21(4):427–459; doi: 10.1177/009365094021004001

55.

Lee

E-J

. Deindividuation effects on group polarization in computer-mediated communication: The role of group identification, public-self-awareness, and perceived argument quality. J Commun, 2007; 57(2):385–403; doi: 10.1111/j.1460-2466.2007.00348.x

56.

Fuchs

. Everyday Life and Everyday Communication in Coronavirus Capitalism. In: Communicating COVID-19: Everyday Life, Digital Capitalism, and Conspiracy Theories in Pandemic Times. Emerald Publishing Limited: Leeds; 2021; pp. 17–61.

57.

Walther

. Interpersonal effects in computer-mediated interaction: A relational perspective. Commun Res, 1992; 19(1):52–90; doi: 10.1177/009365092019001003