Information Technology to the Rescue? : Explaining the Acceptance of Emergency Response Information Systems by Firefighters

Faculty/Professorship: Industrial Information Systems  
Author(s): Weidinger, Julian  ; Schlauderer, Sebastian ; Overhage, Sven
Title of the Journal: IEEE transactions on engineering management : EM
ISSN: 0018-9391
Corporate Body: IEEE
Publisher Information: New York, NY
Year of publication: 2021
Issue: Date of Publication: 11 January 2021
Pages: 1-15
Language(s): English
DOI: 10.1109/TEM.2020.3044720
Improving the efficacy of emergency responses with digital means is receiving increasing attention. Currently, several innovative information technologies and systems are being developed to raise the situation awareness of first responders like firefighters. Among them, emergency response information systems (ERIS) appear to provide a particularly promising platform, which helps to gather, analyze, and share relevant information during emergencies. However, the conditions under which firefighters accept or reject such systems remain unclear. Existing theories explain the acceptance of information technologies only on a general level that does not consider the specific usage constraints existing in the firefighter domain. To fill this literature gap, we propose a detailed, domain-specific acceptance model with factors that explain the acceptance of ERIS by firefighters. It combines findings of the user satisfaction and the technology acceptance literature and was developed based on the input of 82 domain experts. An evaluation of the acceptance model in a survey with 212 firefighters from Germany indicates that it is effective in predicting a firefighter's intention to use an ERIS. The identified acceptance factors provide guidance for the design and evaluation of ERIS, enabling the so far mostly theoretical benefits of ERIS to be transferred into practical applications more effectively.
Keywords: acceptance factors, emergency services, firefighter information technologies (FITs), model development, partial least squares, quantitative research
Peer Reviewed: Ja
International Distribution: Ja
Type: Article
Release Date: 21. January 2022