A Mixed-Method and NLP Assisted Analysis of Chatbot Usage in the Hospitality Industry using Correlation and Word2Vec

In the evolving landscape of the hotel sector, chatbots are increasingly pivotal for elevating guest experiences and operational efficiency. This study explores the nuanced dynamics between chatbots and key variables in Hospitality Management. Examining perceptions of Job Opportunities reveals a statistically significant moderate negative correlation (r = -0.256, p = 0.01), indicating that as belief in chatbots creating new jobs rises, the anticipation of needing new skills decreases. While chatbots may foster employment in development and maintenance, traditional hospitality roles may see diminished expectations. The Chatbots and Job Elimination analysis shows a weak negative correlation (r = -0.191, p = 0.057), signifying uncertainty about the relationship between chatbots and concerns about job elimination. Focusing on Tasks, the correlation between Chatbot Suitability and Customer Service is moderately negative (r = -0.203, p = 0.043), suggesting that perceiving chatbots as suitable for routine tasks doesn’t necessarily translate to improved customer service. Chatbots may face challenges meeting complex customer needs despite excelling in routine tasks. Further, the correlation between Chatbot Task Automation and Operational Efficiency is moderately negative (r = -0.222, p = 0.026), implying that perceiving chatbots as task automation doesn’t guarantee enhanced operational efficiency. In exploring Satisfaction, both Chatbots and Employee Satisfaction and Chatbots and Customer Satisfaction reveal weak negative correlations (r = -0.190, p = 0.058), providing inconclusive evidence about the relationship between chatbots and satisfaction levels. The data underscores the potential of chatbots to digitize work but acknowledges persistent concerns about job displacement and their impact on customer and staff satisfaction. Qualitative responses were analyzed using word2vec for capturing word embeddings and an open coding technique. Findings indicate that while chatbots prove beneficial for daily hotel operations and addressing repetitive customer inquiries, there is a preference for human-to-human communication in handling immediate concerns.