The research introduces a modification to the commonly used Love and Breakup Letter Method (LBM), a qualitative tool for understanding consumer-brand relationships. Traditionally, LBM captures consumer feelings through love letters (positive sentiments) and breakup letters (negative sentiments).
However, this binary approach can miss more nuanced consumer attitudes, especially those involving constructive feedback or a desire to improve the product or service. The study applies this modified method, which includes a third category called 'intervention letters,' to explore how hotel guests relate to service robots.
These intervention letters allow consumers to express their wish to actively participate in enhancing the robot service rather than just expressing love or dissatisfaction. Findings from the study reveal that over half of the participants (52.72%) chose to write intervention letters, surpassing love letters (38.18%) and breakup letters (9.09%).
This indicates that many consumers are not just passively experiencing the service but are eager to engage and co-create better experiences. Moreover, participants spent more time writing intervention letters, suggesting deeper thought and involvement. Linguistic analysis using LIWC-22 software showed distinct differences among the letter types.
Intervention letters scored highest on analytic thinking, reflecting a practical, task-focused mindset. They also showed less self-focus compared to love and breakup letters. Love letters were more authentic and emotional, emphasizing feelings and personal connections, while breakup letters were more emotional but negative.
Word frequency analysis further highlighted these differences. Love letters frequently used emotional words like "love," "heart," and "moment," emphasizing specific positive experiences. Intervention letters used practical terms such as "guests," "service," and "improve," underscoring a focus on actionable feedback and service enhancement.
For hotel operators and service designers, these insights suggest that guests interacting with service robots are not only forming emotional bonds but also want to contribute to improving these interactions. Encouraging and facilitating such constructive feedback can foster stronger guest relationships and lead to more effective robot service improvements.
This approach can help hotels move beyond simply measuring satisfaction or dissatisfaction to actively engaging guests in co-creating their experiences. In summary, integrating intervention letters into consumer feedback methods provides a richer, more actionable understanding of guest attitudes toward service robots.
This can inform better design, training, and deployment strategies for robotic services in hospitality, ultimately enhancing guest satisfaction and operational effectiveness.