Effects of robots’ appearance on guest service experiences

Abstract

ABSTRACT Robots are starting to replace human employees in the accommodation industry. It remains unclear how guests perceive robots. The study aims to evaluate the effectiveness of the humanoid and non-humanoid robots and to compare the guests’ perceptions. The data was collected by web digging and analyzed using text mining and machine learning. The results show that guests experience more positive emotions in non-humanoid robotic experiences. They also stated that they found both types of robot fun and interesting. However, guests have negative perceptions about the perceived usefulness and appearance of humanoid robots. According to the findings of the machine learning analysis, the neural network and logistic regression models show the best statistical performance in both datasets compared to other machine learning models. The study contributes to the literature through an investigation of guests’ opinions regarding robot types with the use of machine learning and text mining methods.