Investigating the team adaptation process in two laboratory experiments (N = 144 teams, n = 504 participants), we found no benefits for teams with team adaptation experience (vs. without) nor for ...teams with external team adaptation experience (vs. with internal experience). Collective experience under routine and nonroutine conditions seems to provide teams with the resources to adapt. We further found that executing the team adaptation process did not always lead to high team performance; different team performance requirements might explain these findings. We discuss how our experimental findings can extend our understanding of team adaptation toward new boundary conditions.
There is a long history, dating back to the 50 s, which examines the manner in which team roles contribute to effective team performance. However, much of this work has been built on
teams working ...together for short periods of time under conditions of minimal stress. Additionally, research has been conducted with little attention paid to the importance of temporal factors, despite repeated calls for the importance of considering time in team research (e.g., Mohammed et al., 2009). To begin to understand team roles and how temporal aspects may impact the types of team roles employed when teams are working in extreme mission critical environments, the current manuscript uses a data-driven, bottom-up approach. Specifically, we employ the use of retrospective historical data as our input and a historiometric approach (Simonton, 2003). Source documents consist primarily of autobiographies, memoires, biographies, and first-hand accounts of crew interaction during spaceflight. Critical incidents regarding team interaction were extracted from these source documents and independently coded for team roles by two trained raters. Results of the study speak to the importance of task and social roles within teams that are predominantly intact and operating in extreme environments where mistakes can be life threatening. Evidence for the following task (i.e., coordinator, boundary spanner, team leader, evaluator, critic, information provider, team player, and innovator) and social roles (i.e., team builder, nurturer, harmonizer, entertainer, jokester, and the negative roles of attention seeker and negativist) were found. While it is often task roles that receive the greatest attention, results point to the importance of not neglecting the socioemotional health of the team (and the corresponding roles). Results also indicated that while some roles were consistently enacted independent of temporal considerations (e.g., mission length), the degree to which others were enacted varied across missions of differing lengths. Additionally, based on the current sample we see the following trends: (1) increased enactment of the team builder role as mission duration increases, (2) prominence of the entertainer role, and (3) increased emphasis on the visionary/problem solver role on missions over 2 years.
Although interactive technologies increasingly shape teamwork, their relationship with team effectiveness (inputs, processes, emergent states, and outputs) remains unclear. To provide an overview of ...this relationship, we systematically reviewed empirical articles from Work and Organizational Psychology (WOP) and Human-Computer Interaction (HCI). To bring the two disciplines closer, we analysed 37 papers that validated the effects of interactive technologies, focusing on the type and characteristics of these technologies, the psychological mechanisms that they intended to support, and the methodological information of the conducted studies. We found that interactive technologies had mainly positive effects on various team effectiveness components (e.g., action team processes and task-related outputs), especially when they allowed team members to be physically close to each other or to have the option to interact synchronously. Nevertheless, the picture remains incomplete (e.g., limited evidence about affect-related properties and outputs), with several methodological limitations (e.g., mainly experimental studies with student teams). We discuss ways to shape the existing technological potential for effective team functioning, especially for affective and implicit psychological mechanisms. We highlight the need for interdisciplinary research and present an exemplary approach as an inspiration for WOP and HCI to work together and move beyond the boundaries of each single discipline.
Abstract Given that AI is becoming an increasingly active participant in work teams, this study explores how team trust emerges in human–AI teams compared to human–human teams. Adopting a multi‐level ...approach, we conducted two experimental studies ( N Study1 = 247 two‐member teams and N Study2 = 106 three‐member teams, 828 individuals overall) and investigated how team composition (with AI or human team members) impacts interpersonal trust (affective and cognitive) and thus team trust. In two‐member teams, interpersonal trust via perceived trustworthiness and not via perceived similarity was lower in human–AI teams compared to human–human teams. Exploratory findings showed that team identification and cognitive interpersonal trust were also lower in two‐member human–AI teams than in human–human teams. However, in three‐member teams, we found no differences in team trust via interpersonal trust between the two team types. Instead, our findings revealed that perceived trustworthiness and perceived similarity increased interpersonal trust and, in turn, team trust for both team types. With this research, we showed that underlying theories and evidence of team trust in human‐only teams can enhance understanding of human–AI teams, though the results indicated certain differences that call for further investigation.
As a response to the lack of quantitative and reliable
measures of the team adaptation process, the aim of the present study was to
develop and validate an instrument for assessing the four phases of ...the team
adaptation process as described by Rosen and colleagues (2011). Two trained raters and two subject
matter expert groups contributed to the development of four behaviorally
anchored rating scales (BARS) that span across the spectrum of team processes
involved in each team adaptation phase. To validate the four BARS, two different
trained raters assessed independently the team adaptation phases of 66
four-person teams. The validation study provided empirical support for the
BARS' psychometric adequacy. The BARS measures overcame the common middle
anchor problem, showed sensitivity in differentiating between teams and between
the four phases, showed evidence for acceptable reliability, construct, and
criterion validity, and supported the theoretical team adaptation process
assumptions. The study contributes to research and praxis by enabling the direct
assessment of the overall team adaptation process, thereby facilitating our
understanding of this complex phenomenon. This allows the identification of
behavioral strengths and weaknesses for targeted team development and
comprehensive team adaptation studies.
Intelligent systems are increasingly entering the workplace, gradually moving away from technologies supporting work processes to artificially intelligent (AI) agents becoming team members. ...Therefore, a deep understanding of effective human-AI collaboration within the team context is required. Both psychology and computer science literature emphasize the importance of trust when humans interact either with human team members or AI agents. However, empirical work and theoretical models that combine these research fields and define team trust in human-AI teams are scarce. Furthermore, they often lack to integrate central aspects, such as the multilevel nature of team trust and the role of AI agents as team members. Building on an integration of current literature on trust in human-AI teaming across different research fields, we propose a multidisciplinary framework of team trust in human-AI teams. The framework highlights different trust relationships that exist within human-AI teams and acknowledges the multilevel nature of team trust. We discuss the framework's potential for human-AI teaming research and for the design and implementation of trustworthy AI team members.
Purpose
The purpose of this study was to investigate trust within human-AI teams. Trust is an essential mechanism for team success and effective human-AI collaboration.
Design/methodology/approach
In ...an online experiment, the authors investigated whether trust perceptions and behaviours are different when introducing a new AI teammate than when introducing a new human teammate. A between-subjects design was used. A total of 127 subjects were presented with a hypothetical team scenario and randomly assigned to one of two conditions: new AI or new human teammate.
Findings
As expected, perceived trustworthiness of the new team member and affective interpersonal trust were lower for an AI teammate than for a human teammate. No differences were found in cognitive interpersonal trust and trust behaviours. The findings suggest that humans can rationally trust an AI teammate when its competence and reliability are presumed, but the emotional aspect seems to be more difficult to develop.
Originality/value
This study contributes to human–AI teamwork research by connecting trust research in human-only teams with trust insights in human–AI collaborations through an integration of the existing literature on teamwork and on trust in intelligent technologies with the first empirical findings on trust towards AI teammates.
•The paper aims to assess the adoption of willow within a stylised CAP greening.•Proactive greening mechanisms enabling wide diffusion of willow are tested for Poland.•Small and mid-sized farm groups ...are the most sensitive to willow plantation.•Willow uptake is also high within livestock-oriented farm groups.•Willow is likely to be most grown in Mazowsze & Podlasie region.
Synergies between the Common Agricultural Policy (CAP) and the deployment of bioeconomy that induces resource-efficient and sustainable biomass production patterns are in the core of discussion for the new CAP in Poland. Proactive greening mechanisms likely to enable a large-scale diffusion of willow plantation are investigated in this respect, including diversification schemes combined with incentives making willow plantation more attractive to farmers. A comprehensive approach to modelling farm diversification options is therefore provided by means of an integrated bioeconomic framework which relies on linking the agricultural supply model AROPAj with the crop model STICS. The economic and environmental impacts related to the gross margin, land use change, nitrogen (N) fertiliser use, and greenhouse gas emissions, i.e. methane (CH4) and nitrous oxide (N2O), are assessed at the regional scale according to the type of farming and the economic size. Under current crop diversification conditions only 9% of farm groups (FG) may opt for willow, benefiting solely from diversification support whereas subsidising willow increases this percentage up to 20% and 45%, for a received allocation amount equal to € 100 ha−1 and € 200 ha−1, respectively. The uptake of willow is particularly high within small and middle-sized FG and within those specialising in grazing activities. Regarding the environmental impacts, the higher the number of required crops, the lower the N-fertiliser use, and in most cases, a coupled support policy (when willow plantation is subsidised) further reduces N-use, and consequently N2O emissions. Unlike grazing-oriented FG, crop-oriented FG tend to significantly increase their CH4 emissions due to the intensification of grazing activities. The countrywide coverage of the findings and their economic and spatial detail can support informed policies for sustainable bio-based activities development.
Integrating artificial intelligence (AI) into human teams, forming human-AI teams (HATs), is a rapidly evolving field. This overview examines the complexities of team constellations and dynamics, ...trust in AI teammates, and shared cognition within HATs. Adding an AI teammate often reduces coordination, communication, and trust. Further, trust in AI tends to decline over time due to initial overestimation of capabilities, impairing teamwork. Despite AI's potential to enhance performance in contexts like chess and medicine, HATs frequently underperform due to poor team cognition and inadequate mutual understanding. Future research must address these issues with interdisciplinary collaboration between computer science and psychology and advance robust theoretical frameworks to realize the full potential of human-AI teaming.
•Adding an AI teammate often reduces team coordination, communication, and trust.•Human-AI teams frequently underperform due to poor team cognition and mutual understanding.•Transparency and explainability of AI agents are crucial for building trust and shared cognition.•Researchers from computer sciences and psychology must collaborate to advance the field.•Future studies should focus on real-world use cases and establish a common taxonomy for HATs.
Purpose
The purpose of this study was to explore the team process-sequences executed within and across performance episodes and their relation to team performance. In doing so, this effort responds ...to the call for examining the temporal and dynamic aspects of teams.
Design/methodology/approach
Data (i.e. observations and audio recordings) was collected from the stand-up meetings of three high-performing Scrum teams across six points in time during two consecutive performance episodes (i.e. beginning, midpoint, end). After content coding the data, lag sequential analyses was used to examine patterns of executed team processes to determine whether particular process-sequences occurred significantly different from others.
Findings
Teams shifted between transition and action phase processes during performance episodes. During and across performance episodes, process-sequences primarily consisted of transition processes. When teams executed process-sequences consisting solely of action phase processes, their focus was on monitoring processes.
Research limitations/implications
This study hopes that the findings here will serve to spur researchers to more fully investigate the relationship between process-sequences and team performance across various team types. However, limitations (e.g. small sample size, unknown point of teams’ life cycle and focus on explicit team processes) should be taken into account when building on the present findings.
Originality/value
This study contributes to a better understanding of the temporal and dynamic nature of team processes by analyzing how the team process and process-sequences occur across time. In addition, this study moves beyond most studies that assess team processes as static retrospective perceptions and consider their natural ordering.
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