@techreport{SiglFleischmannCardonetal.2023, type = {Working Paper}, author = {Sigl, Anna-Lena and Fleischmann, Carolin and Cardon, Peter and Aritz, Jolanta and Koße, Tamara}, title = {Speech-to-text technology for global virtual teams: A SWOT analysis}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:861-opus4-23270}, pages = {13}, year = {2023}, abstract = {Virtual team meetings are increasingly supported with advanced technology. This study investigates the extent to which Al-enabled speech technology can be useful for global virtual teams (GVT). A survey was conducted in GVTs in 2020 and 2021, when people's lives were primarily dominated by the pandemic. A transcription software was used to support the collaboration. A total of 530 survey responses were analyzed using a structured approach- qualitative content analysis. The data was structured using the SWOT framework that aimed at comprehensively answering the research question "To what extent is the use of Al-supported speech technology in GVTs useful?". Al-generated transcripts are helping to overcome language and time zone barriers in GVT. Yet, they also cause misunderstandings and impact openness of communication. Further results and implications for GVT are discussed.}, language = {en} }