Chatbots are distinguished by their ability to simulate interactions between brands and users. However, there remains a notable lack of academic research addressing their relevance within sectors such as private healthcare. In this context, although chatbots are used for information retrieval, booking or canceling medical appointments, filing complaints, and processing payments, significant challenges persist concerning consumer trust and the limited engagement in their routine use. This study aims to analyze the factors influencing consumer satisfaction and engagement in this sector, with a particular emphasis on responsiveness, ubiquitous connectivity, and initial trust in chatbots. A non-probabilistic, convenience sample of 400 individuals was obtained, of which 330 responses were valid. Data were collected via a survey utilizing a 5-point Likert scale, and the results were analyzed through second-order structural equation modeling using the Smart PLS software. In this regard, all hypotheses were validated, offering a novel and meaningful perspective on the role of chatbots within the private healthcare sector.

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Determinants of Satisfaction and Initial Trust in Chatbots and Their Impact on Customer Engagement in the Private Healthcare Sector

  • Natalia Giselle Saldivar Espejo,
  • Sol Marina Vivanco Kassay,
  • Hector Mendoza Cuellar

摘要

Chatbots are distinguished by their ability to simulate interactions between brands and users. However, there remains a notable lack of academic research addressing their relevance within sectors such as private healthcare. In this context, although chatbots are used for information retrieval, booking or canceling medical appointments, filing complaints, and processing payments, significant challenges persist concerning consumer trust and the limited engagement in their routine use. This study aims to analyze the factors influencing consumer satisfaction and engagement in this sector, with a particular emphasis on responsiveness, ubiquitous connectivity, and initial trust in chatbots. A non-probabilistic, convenience sample of 400 individuals was obtained, of which 330 responses were valid. Data were collected via a survey utilizing a 5-point Likert scale, and the results were analyzed through second-order structural equation modeling using the Smart PLS software. In this regard, all hypotheses were validated, offering a novel and meaningful perspective on the role of chatbots within the private healthcare sector.