From frustration to satisfaction: the effectiveness of chatbot communication styles in service recovery

Purpose Given the importance of chatbots in service failures recoveries, this paper aims to explore how chatbots, powered by advanced technologies to handle customer complaints with personalized and contextual responses. This study investigates the impact of artificial intelligence (AI) chatbot communication styles and blame attributions on customer perceptions of re-patronage intentions in airline service context. Design/methodology/approach A 2 (chatbot interaction style: social vs task-oriented) × 2 (blame attribution: high vs low) between-subject experimental design was conducted, data were collected from 382 participants (inspired by theories of social penetration, attribution and perceived justice). ANOVA and structural equation modeling was used to test the hypotheses. Findings This study demonstrates that blame attribution in chatbot-mediated service recovery critically shapes perceived service climate, whereas emoji implementation (social-oriented communication) provides limited value. Customer satisfaction areareth chatbot services is positively impacted by perceived justice, which also significantly increases re-patronage intentions. Furthermore, thoughtful chatbot design enhances service recovery efficacy, elevates satisfaction and strengthens loyalty, collectively optimizing customer experiences for airline operators. Originality/value This research pioneers a transformative paradigm in tourism service recovery, demonstrating that contextually calibrated communication substantially elevates perceived service climate across high and low blame-attribution failures. These findings deliver actionable frameworks for industry practitioners: Advanced chatbot systems optimize customer experiences, enhance operational efficiency and strengthen service recovery performance through dynamically calibrated communication strategies aligned with failure severity and attribution contexts.