Data-driven Strategic Process in the Hospitality Industry: Studying Hotel consumers’ purchase intention through web analytics.

Abstract

This study investigates the transformative impact of data-driven strategies on the hospitality industry, with a specific emphasis on the utilization of big data for measuring consumer purchase intention. Through the utilization of big data, hospitality firms may depict detailed customer profiles, forecast demand patterns, and enhance service quality, thereby optimizing resource allocation and sustaining competitiveness. This research particularly examines the relationships among trust, brand orientation, and engagement attitude concerning online purchase intention among hotel consumers, employing Partial Least Square Structural Equation Modeling (PLS-SEM) on web analytics data. Leveraging web analytics tools such as Google Analytics enables firms to quantify customer purchase intention and subsequently acquire insights to enhance the efficiency and effectiveness of their strategic decision-making processes. Although the primary focus of this study is on the hospitality industry, its findings bear relevance for other industries as well. Indeed, in the contemporary complex environment characterized by pervasive Internet usage, an increasing number of firms operating in various industries are increasingly challenged to develop data-driven strategies to reach, maintain and renew their competitive advantages.