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Virtual communication curbs creative idea generation

Nature volume 605, pages 108–112 (2022)Cite this article

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A Publisher Correction to this article was published on 07 June 2022

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Abstract

COVID-19 accelerated a decade-long shift to remote work by normalizing working from home on a large scale. Indeed, 75% of US employees in a 2021 survey reported a personal preference for working remotely at least one day per week1, and studies estimate that 20% of US workdays will take place at home after the pandemic ends2. Here we examine how this shift away from in-person interaction affects innovation, which relies on collaborative idea generation as the foundation of commercial and scientific progress3. In a laboratory study and a field experiment across five countries (in Europe, the Middle East and South Asia), we show that videoconferencing inhibits the production of creative ideas. By contrast, when it comes to selecting which idea to pursue, we find no evidence that videoconferencing groups are less effective (and preliminary evidence that they may be more effective) than in-person groups. Departing from previous theories that focus on how oral and written technologies limit the synchronicity and extent of information exchanged4,5,6, we find that our effects are driven by differences in the physical nature of videoconferencing and in-person interactions. Specifically, using eye-gaze and recall measures, as well as latent semantic analysis, we demonstrate that videoconferencing hampers idea generation because it focuses communicators on a screen, which prompts a narrower cognitive focus. Our results suggest that virtual interaction comes with a cognitive cost for creative idea generation.

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Fig. 1: Laboratory experiment set-up.
Fig. 2: Eye gaze results by modality.

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Data availability

The data (raw and cleaned) collected by the research team and reported in this Article and its Supplementary Information are available on Research Box (https://researchbox.org/282), except for the video, audio recordings and transcripts of participants, because we do not have permission to share the participants’ voices, faces or conversations. The cleaned summary data for the field studies are available in the same Research Box, but the raw data must be kept confidential, as these data are the intellectual property of the company. The Linguistic Analysis database is available online (https://liwc.wpengine.com/). Extended Data Tables 1–5 and Extended Data Figs. 2 and 3 are summary tables and figures, and the raw data associated with these tables are on Research Box (https://researchbox.org/282). Source data are provided with this paper.

Code availability

All custom code used to clean and analyse the data is available at Research Box (https://researchbox.org/568). The Linguistic Analysis database is available online (https://liwc.wpengine.com/). OpenFace is available at GitHub (https://github.com/TadasBaltrusaitis/OpenFace).

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Acknowledgements

We thank B. Ginn, N. Hall, S. Atwood and M. Nelson for help with data collection; M. Jiang, Y. Mao and B. Chivers for help with data processing; G. Eirich for statistical advice; M. Brucks, K. Duke and A. Galinsky for comments and insights; and J. Pyne and N. Itzikowitz for their partnership.

Author information

Authors and Affiliations

  1. Marketing Division, Columbia Business School, Columbia University, New York, NY, USA

    Melanie S. Brucks

  2. Marketing Division, Stanford Graduate School of Business, Stanford University, Stanford, CA, USA

    Jonathan Levav

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  1. Melanie S. Brucks
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  2. Jonathan Levav
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Contributions

M.S.B. supervised data collection by research assistants at the Stanford Behavior Lab in 2016–2021. M.S.B. and J.L. jointly supervised data collection by the corporate partner at the field sites. These data were analysed by M.S.B. and discussed jointly by both of the authors.

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Correspondence to Melanie S. Brucks.

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The authors declare no competing interests.

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Nature thanks Brian Uzzi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data figures and tables

Extended Data Fig. 1 Materials and example data for room recall measure in the second batch of data collection in the lab.

(a) Photo demonstrating the prop placement in the lab room. Five props were expected (props consistent with a behavioural lab schema): a filing cabinet, folders, a cardboard box, a speaker, and a pencil box; and five props were unexpected (props inconsistent with a behavioural lab schema): a skeleton poster, a large house plant, a bowl of lemons, blue dishes, and yoga ball boxes. (b) Participant example of the data materials. After leaving the lab space, participants recreated the lab room on a piece of paper containing the basic layout of the room and then numbered each element. We then asked participants to list the identity of each element on a Qualtrics survey. A condition- and hypothesis-blind research assistant categorized each listing into one of the ten props and removed any other responses. We then counted how many expected and unexpected props were remembered by each participant.

Extended Data Fig. 2 Room recall mediates the effect of communication modality on idea generation.

This mediation model demonstrates that virtual participants remembered significantly fewer unexpected props in the experiment room and that this explains the effect of virtual interaction on creative idea generation. We ran an OLS regression for the a-link (communication modality predicting average recall of unexpected items per pair, n = 151 pairs, OLS regression, b = 0.42, s.e. = 0.17, t149 = 2.44, P = 0.016), and we ran a Negative Binomial regression for the b-link (number of average unexpected items recalled per pair predicting number of creative ideas generated, n = 151 pairs, Negative Binomial regression, b = 0.08, s.e. = 0.03, z = 2.48, P = 0.013). A mediation analysis with 10,000 nonparametric bootstraps revealed that recall of the room mediated the effect of modality on creative idea generation (95% confidence intervals of the indirect effect = −0.61 to −0.01). The total effect of modality condition on number of creative ideas generated was significant (n = 151 pairs, Negative Binomial regression, b = 0.15, s.e. = 0.07, z = 2.18, P = 0.030), but this effect was attenuated to non-significance when accounting for the unexpected recall mediator (n = 151 pairs, Negative Binomial regression, b = 0.12, s.e. = 0.07, z = 1.73, P = 0.083). See Supplementary Information C for model assumption tests of normality and heteroskedasticity. All tests are two-tailed and there were no adjustments made for multiple comparisons (for a discussion of our rationale, see Supplementary Information S).

Extended Data Fig. 3 Gaze mediates the effect of communication modality on idea generation.

This mediation model demonstrates that virtual participants spent less time looking around the room and that this explains the effect of virtual interaction on creative idea generation. We ran an OLS regression for the a-link (communication modality predicting average room gaze per pair, n = 146 pairs, OLS regression, b = −29.1, s.e. = 5.1, t144 = 5.69, P < 0.001), and we ran a Negative Binomial regression for the b-link (average room gaze per pair predicting number of creative ideas generated, n = 146 pairs, Negative Binomial regression, b = 0.003, s.e. = 0.001, z = 2.34, P = 0.020). A mediation analysis with 10,000 nonparametric bootstraps revealed that recall of the room mediated the effect of modality on creative idea generation (95% confidence intervals of the indirect effect = −1.14 to −0.08). The total effect of modality condition on number of creative ideas generated was significant (n = 146 pairs, Negative Binomial regression, b = 0.17, s.e. = 0.07, z = 2.36, P = 0.019), but this effect was attenuated to non-significance when accounting for the room gaze mediator (n = 146 pairs, Negative Binomial regression, b = 0.09, s.e. = 0.08, z = 1.20, P = 0.231). See Supplementary Information C for model assumption tests of normality and heteroskedasticity. All tests are two-tailed and there were no adjustments made for multiple comparisons (for a discussion of our rationale, see Supplementary Information S).

Extended Data Fig. 4 The effect of virtual communication on forward flow across the progression of idea generation.

There was a significant interaction between modality and the position of an idea in the pair’s idea sequence on forward flow score across all studies (linear mixed-effect regression, n = 9966 idea scores, interaction term: b = −0.01, s.e. = 0.01, t358 = −2.09, P = 0.038). At the beginning of the idea generation task, ideas generated by in-person and virtual pairs were similarly connected to past ideas generated by each pair. However, by the eleventh idea, ideas generated by in-person pairs began to exhibit significantly more forward flow (that is, the ideas were less semantically associated) compared to those of virtual pairs (linear mixed-effect regression, n = 9966 idea scores, simple effect of modality on forward flow at the 11th idea: b = −0.12, s.e. = 0.06, t621 = −2.00, P = 0.047). Thus, in-person pairs generate progressively more disconnected ideas relative to virtual pairs. See Supplementary Information D for model assumption tests of normality and heteroskedasticity. We truncated the graph at 30 ideas to provide the most accurate representation of the majority of the data. All tests are two-tailed and there were no adjustments made for multiple comparisons (for a discussion of our rationale, see Supplementary Information S).

Extended Data Fig. 5 Set-up for group size virtual study.

In the virtual-only study, we randomly assigned participants into groups of 2 or 4 people. Participants worked on a google sheet and were instructed to set up their screen such that half of their screen was the task and the other half of the screen was their zoom window. The self-view was hidden, and participants either saw one partner (2-person condition), or three teammates (4-person condition). Consent was obtained to use these images for publication.

Extended Data Table 1 Summary of the analyses in the main text
Full size table
Extended Data Table 2 Summary of idea generation analyses with alternative models
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Extended Data Table 3 Summary of our examination into the alternative processes by which modality of interaction (in-person vs virtual) could affect the production of creative ideas
Full size table
Extended Data Table 4 Analyses on Verbal and Nonverbal Behaviours
Full size table
Extended Data Table 5 Summary of group size virtual study results
Full size table

Supplementary information

Supplementary Methods

Sections A–C test the model assumptions. Sections D–J examine the alternative explanations mentioned in the main text and are summarized in Extended Data Figs. 7 and 8. Sections K–M detail additional data and tests examining generalizability. Sections P–Q discuss the limitations. Section R includes secondary analyses in the methods.

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Brucks, M.S., Levav, J. Virtual communication curbs creative idea generation. Nature 605, 108–112 (2022). https://doi.org/10.1038/s41586-022-04643-y

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