Randomized trial investigates AI performance management strategies in telework, suggesting a new socio-technical framework.
Key Points
This research aims to design an AI-driven performance management system that improves teleworking efficacy while promoting employee autonomy and well-being.
Conducted a mixed-methods study with Canadian public servants, including a survey of 176 participants and machine learning analysis of over 205,000 tweets.
Performed document analysis of federal and provincial teleworking policies and semi-structured interviews with Government of Canada employees.
Utilized logistic regression to evaluate survey data and identify predictors of teleworking success.
Identified organizational support, workplace socialization, and attitudes as key predictors of successful teleworking, overshadowing the role of digital skills or monitoring.
Found that employee isolation poses a measurable risk to teleworking effectiveness.
Developed a socio-technical framework outlining three layers: technological, organizational, and human-centered.