Predicting Consumer Adoption of Digital Menus in Restaurants: A Machine Learning Approach

The hospitality industry is going through a transformative phase with technological improvements such as digital payments, artificial intelligence (AI), virtual reality (VR), augmented reality, and many more. Among various technological innovations, digital menus have significantly transformed the restaurant industry. Key driving attributes affecting intentions of consumer to adopt technologies in the hospitality sector, especially in restaurant establishments, remain underexplored. To fill this research gap, the present research study's objective is to investigate the key factors that drive consumers' intention to adopt digital menus over traditional paper-based menus in restaurant establishments. The study used a structured questionnaire and collected 773 responses by capturing critical information on consumer behavior on technology adoption. The study also integrated one of the machine learning techniques, random forest classifier in order to predict the key driving factors in the adoption of digital menus in restaurants. The findings provide actionable insight to restaurant operators and technological developers, informing numerous ways to create digital menus that align with customer likes and preferences. In addition, this study also provides valuable information to the field of academia by giving in-depth knowledge on consumer behavior on digital technology adoption in the restaurant sector.