独创性
心理学
感情的
社会心理学
模式(遗传算法)
组织沟通
计算机科学
知识管理
社会学
机器学习
创造力
人类学
出处
期刊:Information Technology & People
[Emerald Publishing Limited]
日期:2021-10-29
卷期号:35 (6): 1744-1781
被引量:1
标识
DOI:10.1108/itp-02-2019-0064
摘要
Purpose One challenge facing the digitalized workplace is communication control, especially emotion regulation in which individuals try to manage their emotional experiences and/or expressions during organizational communication. Extant research largely focused on the facilitating role of a few media features (e.g. fewer symbol sets). This study seeks to provide a deeper understanding of media features that individuals, as receivers of negative emotions expressed by communication partners, could leverage to support regulating negative emotional communication in the workplace. Design/methodology/approach This study used qualitative research methods to identify media features that support regulating negative emotional communication at work. Data were collected using interviews and was analyzed using directed content analysis in which media features discussed in media synchronicity theory (MST) were used as the initial coding schema but the researcher was open to media features that do not fit with MST. Findings In addition to media features (and capabilities) discussed in MST, this study identified five additional media features (i.e. message broadcasting, message blocking, receiving specification, recipient specification and compartmentalization) and two underlying media capabilities (i.e. transmission control capability and participant control capability) that may support regulating negative emotional communication. Two major mechanisms (i.e. reducing or eliminating emotion regulation workload, and providing prerequisites or removing obstacles for emotion regulation) via which media features support emotion regulation were also identified. Originality/value This paper provides a more comprehensive understanding regarding communication media features that may support emotion regulation in particular and communication control in general. Findings of this study contribute to several literatures and may also transfer to other similar contexts.
科研通智能强力驱动
Strongly Powered by AbleSci AI