Let's talk with chatbots: an appraisal–coping perspective on frontline employees in public services
Tiziana Russo Spena, Carmine Sergianni, Roberta De FilippisPurpose
This study examines how frontline employees (FLEs) in public service organisations appraise and engage with chatbot technologies in everyday service work. It investigates how employees interpret chatbots as public service resources and how these appraisals shape engagement with chatbot-mediated service delivery.
Design/methodology/approach
The study adopts an interpretive qualitative design based on 33 semi-structured interviews with FLEs from 17 public service organisations. Data were analysed through directed qualitative content analysis with inductive refinement, informed by willingness-to-collaborate research and an appraisal–coping perspective.
Findings
The findings show that employees' engagement with chatbots develops through two connected orientations. The willingness to interact reflects employees' initial appraisal of chatbots in relation to information reliability, bounded autonomy, communicative appropriateness, professional judgement and service-task fit. The willingness to collaborate depends on the organisational conditions that make chatbot-mediated work manageable, including rules, role boundaries, monitoring, training, continuing support and human intervention. Coping responses explain why employees may support chatbot use while also limiting their engagement when time, staffing or technological confidence are insufficient.
Originality/value
The study advances public service management research by showing how the value of chatbots as public service resources depends on employee appraisal, service-task fit and organisational conditions. It also contributes to research on human–AI collaboration by distinguishing willingness to interact from willingness to collaborate in chatbot-mediated public service work and by linking this distinction to coping responses in frontline practice.