The Next Normal for Teaming - Transitioning Out of COVID-19

尽管远程工作在过去几十年里越来越受欢迎，但在2019冠状病毒病暴发后，远程工作变得尤为重要。许多国家被迫下令就地安置或保持社会距离，以减缓疾病的传播，迫使各组织迅速过渡到远程工作。尽管2019冠状病毒病的爆发具有破坏性，但它提供了一种全球性的、非自愿的准实验。在规模（迫使许多组织完全远程操作）和范围（影响全球的组织）方面，工作的转变是前所未有的。个人被迫适应新的工作安排，这改变了他们日常工作和其他生活活动和责任的方式。然而，即使我们接受了“新常态”，我们也有机会——实际上也有义务——考虑在我们摆脱COVID-19的过渡过程中，作为正在进行的准实验的一部分出现的做法和经验，我们可能希望保留哪些做法和经验，因为它们的有效性。换句话说，我们可以从“新常态”的经历中学到什么，以帮助我们在摆脱COVID-19的过程中塑造“下一个常态”？为了回答这个问题，该项目将使用调查和服务器端数据，这些数据是工作人员在疫情期间的不同时间点使用数字技术进行协作时收集的。这个项目植根于“团队支持”的观点。突然转向全虚拟会议，以及数字通信技术的使用，提高了员工对技术提供的支持的认识，例如，随时了解同事正在做什么（可见性支持）或他们知道什么以及他们彼此之间关系的性质（关联支持）。技术支持是团队合作的基础，使基本行为成为可能，如跨越边界、集体领导和激励。我们调查了对数字协作技术提供的支持的高度认识在多大程度上能够推动员工参与团队行为，从而产生更好的团队成果。从这项调查中获得的见解将有助于识别和隔离因COVID-19期间突然转向远程工作而引发的做法，但随着我们从COVID-19过渡到工人有能力重返工作场所，我们必须考虑保留这些做法。本项目利用项目团队在2019冠状病毒病期间和之前收集的团队数据，扩大这些来源，以便在再次有可能亲自工作时包括新一波数据收集（“下一个常态”）。此外，该项目将通过半结构化访谈和两波工人一般调查来补充纵向现场调查。该项目将应用一系列先进的网络分析，包括指数随机图模型（ERGMs）和关系事件建模（REM）。访谈数据将使用扎根理论方法进行分析，以确定有助于和阻碍团队合作的实践。这种混合方法纵向设计使探索关于虚拟团队的研究问题和测试假设成为可能，从而提高我们可以从危机中虚拟团队的强制准实验中学到的基本知识，这应该为我们从大流行过渡到更好的团队实践和结果提供信息。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Though remote work has grown in popularity for several decades, it has never been more critical than in the aftermath of COVID-19. Many countries were forced to order shelter-in-place or social distance to slow the spread of the disease forcing organizations to rapidly transition to remote work. While the onset of COVID-19 was disruptive, it has provided a worldwide, if involuntary, quasi experiment. The shift in work was unprecedented in terms of scale (forcing many organizations to operate completely remotely) and scope (affecting organizations across the globe). Individuals were forced to adapt to their new work arrangements, which changed how they go about their day-to-day jobs and other life activities and responsibilities. However, even while we come to terms with the “new normal,” we have the opportunity - and indeed an obligation - to consider what practices and experiences that emerged as part of the ongoing quasi experiment we may want to retain, by virtue of their efficacy, as we transition out of COVID-19. In other words, what can we learn from our experiences in the “new normal” that will help shape the “next normal” as we transition out of COVID-19? To answer this question, this project will use survey and server-side data collected as workers team together using digital technologies at different points through the pandemic. This project is rooted in a “teaming affordances” perspective. The sudden shift to all-virtual meetings, and use of digital communication technologies, has heightened workers’ awareness of the affordances provided by technologies, for example, to be kept updated on what their colleagues are doing (visibility affordance) or what they know and the nature of their relationships with one another (association affordance). Technology affordances serve as the foundation for teamwork, enabling essential behaviors such as boundary spanning, leading collectively, and motivating. We investigate the extent to which a heightened awareness of the affordances provided by digital collaboration technologies has the ability to nudge workers to engage in teaming behaviors that lead to better team outcomes. Insights from this investigation will make it possible to identify and isolate practices that were triggered by the sudden shift to remote work during COVID-19, but which we must consider retaining as we transition out of COVID-19 and workers have the ability to physically return to the workplace. This project leverages teaming data collected by the project team during and prior to COVID-19, expanding these sources to include a new wave of data collection once in-person work is again possible (“The Next Normal”). Additionally, the project will complement longitudinal field surveys with semi-structured interviews and two waves of a general survey of workers. The project will apply a range of advanced network analytics, including exponential random graph models (ERGMs) and relational event modeling (REM). The interview data will be analyzed using grounded theory methodologies in order to identify practices that help and hinder teaming. This mixed-method longitudinal design makes it possible to explore research questions and test hypotheses about virtual teaming that advance fundamental knowledge on what we can learn from this forced quasi experiment on virtual teaming in a crisis that should inform better teaming practices and outcomes as we transition out of the pandemic.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.