The Conceptualization of Team Flow

Hout, Jef J. J. van den; Davis, Orin C.; Weggeman, M.C.D.P.

doi:10.1080/00223980.2018.1449729

Cited by 62 publications

(72 citation statements)

References 114 publications

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“…A concept with a high potential for fostering team effectiveness is the concept of team flow ( van den Hout et al, 2018 ). Team flow is a shared experience of flow, characterized by the pleasant feeling of absorption in an optimally challenging activity ( Peifer and Engeser, 2021 ), and of optimal team-interaction during an interdependent task ( van den Hout et al, 2018 ). Research on team flow is still scarce and particularly lacking for virtual teams.…”

Section: Introductionmentioning

confidence: 99%

“…A concept with a high potential for fostering trust and team effectiveness is the concept of team flow ( van den Hout et al, 2018 ). Previous research already indicated that the concept of flow can be a meaningful antecedent of trust in virtual settings ( Bilgihan et al, 2015 ), whereby the presence of flow increased the perception of trust.…”

Section: Introductionmentioning

confidence: 99%

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The Symphony of Team Flow in Virtual Teams. Using Artificial Intelligence for Its Recognition and Promotion

et al. 2021

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More and more teams are collaborating virtually across the globe, and the COVID-19 pandemic has further encouraged the dissemination of virtual teamwork. However, there are challenges for virtual teams – such as reduced informal communication – with implications for team effectiveness. Team flow is a concept with high potential for promoting team effectiveness, however its measurement and promotion are challenging. Traditional team flow measurements rely on self-report questionnaires that require interrupting the team process. Approaches in artificial intelligence, i.e., machine learning, offer methods to identify an algorithm based on behavioral and sensor data that is able to identify team flow and its dynamics over time without interrupting the process. Thus, in this article we present an approach to identify team flow in virtual teams, using machine learning methods. First of all, based on a literature review, we provide a model of team flow characteristics, composed of characteristics that are shared with individual flow and characteristics that are unique for team flow. It is argued that those characteristics that are unique for team flow are represented by the concept of collective communication. Based on that, we present physiological and behavioral correlates of team flow which are suitable – but not limited to – being assessed in virtual teams and which can be used as input data for a machine learning system to assess team flow in real time. Finally, we suggest interventions to support team flow that can be implemented in real time, in virtual environments and controlled by artificial intelligence. This article thus contributes to finding indicators and dynamics of team flow in virtual teams, to stimulate future research and to promote team effectiveness.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Symphony of Team Flow in Virtual Teams. Using Artificial Intelligence for Its Recognition and Promotion

et al. 2021

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“…In the management science and organizational behavior literatures, teams are defined as: two or more individuals who perform organizationally relevant tasks, share at least one common goal, interact socially, have task interdependence, maintain and manage boundaries and roles, and are embedded in a larger organizational context that sets objectives, boundaries, constraints on the team, and influences exchanges with other teams (Kozlowski and Bell, 2003). Teams include features such as collective ambition, common goals, alignment of individual goals, high skill differentiation, open communication, safety, and mutual commitment (van der Hout et al, 2018). While teams operate as distinguishable (and measureable) work units partially independent of (but subsumed within) the organization, the organization constrains and sets the overall objectives of the team (Kozlowski and Bell, 2003).…”

Section: What Can We Learn From Human Teams?mentioning

confidence: 99%

“…Second, how can researchers enable team-level flow, peak performance, and positive psychological experiences such as cohesion within HATs? Team flow is an emergent topic within team sciences and requires volitional attention and action toward team goals/activities (van der Hout et al, 2018). How can we establish and maintain unit cohesion with the introduction of machines as teammates?…”

Section: Research Gapsmentioning

confidence: 99%

Human–Autonomy Teaming: Definitions, Debates, and Directions

et al. 2021

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Researchers are beginning to transition from studying human–automation interaction to human–autonomy teaming. This distinction has been highlighted in recent literature, and theoretical reasons why the psychological experience of humans interacting with autonomy may vary and affect subsequent collaboration outcomes are beginning to emerge (de Visser et al., 2018; Wynne and Lyons, 2018). In this review, we do a deep dive into human–autonomy teams (HATs) by explaining the differences between automation and autonomy and by reviewing the domain of human–human teaming to make inferences for HATs. We examine the domain of human–human teaming to extrapolate a few core factors that could have relevance for HATs. Notably, these factors involve critical social elements within teams that are central (as argued in this review) for HATs. We conclude by highlighting some research gaps that researchers should strive toward answering, which will ultimately facilitate a more nuanced and complete understanding of HATs in a variety of real-world contexts.

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“…as well as generating a sense of unity(Van den Hout et al, 2018) are vital. Correspondingly, LSP workshops place an emphasis on equal participation in order to include each member's perspective, knowledge and experience.…”

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confidence: 99%

Alone but together: flow experience and its impact on creative output in LEGO® SERIOUS PLAY®

Zenk

Primus

Sonnenburg

2021

EJIM

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PurposeDo LEGO® SERIOUS PLAY® (LSP) workshops result in improved experience of flow components as well as higher levels of creative output than traditional meetings (MEET)? This research studies the extent to which LSP, as a specialized material-mediated and process-oriented cocreative workshop setting, differs from MEET, a traditional workshop setting. Hypotheses for differences in individual flow components (autotelic behavior, happiness, balance), group flow components (equal participation, continuous communication) and creative output were developed and tested in a quasi-experimental comparison between LSP and MEET.Design/methodology/approachThe study was conducted with 39 practitioners in six teams from various industries. In total, 164 observations were collected during two workshops using the Experience Sampling Method. The creative output was assessed by peer evaluations of all participants, followed by structural analysis and quantitative group comparisons.FindingsThe results show that two components of individual flow experience (autotelic behavior, happiness) were significantly higher in LSP, and one of the components of group flow experience (continuous communication) was, as expected, significantly lower. Regarding creative output, the LSP teams outperformed the MEET teams. The study suggests that a process-oriented setting that includes time for individuals to independently explore their ideas using a different kind of material in the presence of other participants has a significant influence on the team result.Practical implicationsLSP can improve the components of participants' flow experience to have an impact on the creative output of teams. In cocreative settings like LSP, teams benefit from a combination of alone time and high-quality collaborative activities using boundary objects and a clear process to share their ideas.Originality/valueThis is the first quasi-experimental study with management practitioners as participants to compare LSP with a traditional and widespread workshop approach in the context of flow experience and creative output.

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The Conceptualization of Team Flow

Cited by 62 publications

References 114 publications

The Symphony of Team Flow in Virtual Teams. Using Artificial Intelligence for Its Recognition and Promotion

The Symphony of Team Flow in Virtual Teams. Using Artificial Intelligence for Its Recognition and Promotion

Human–Autonomy Teaming: Definitions, Debates, and Directions

Alone but together: flow experience and its impact on creative output in LEGO® SERIOUS PLAY®

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