Management Science in Hospitality and Tourism: Theory, Practice and Applications

Monitoring and Forecasting Tourist Activities with Big Data

Bing Pan and Yang Yang

Abstract

This chapter provides a conceptual framework on leveraging various sources of big data to monitor and forecast tourist activities and discuss the potential sources for big-data forecasting. Managing and governing a complex system is notoriously a daunting task that requires a sound knowledge of the structural and dynamic characteristics of the system. The system evolves continuously redefining its configuration and functions; it may exhibit an intricate mix of ordered and disordered behaviors and show emergent phenomena which are generally surprising and, at times, extreme. Statistical physics is one of the fundamental fields of physics, and employs statistical methods for addressing physical problems that concern systems with a large number of components. A reliable model, especially when dealing with a complex system, needs continuous interactions between researchers and empirical issues. The object of study in nonlinear dynamics is a time series that contains a certain number of quantities related to some behavior of the system under investigation.

Keywords

Research topic

AI and Big Data

Research method

Geographic area

Additional links for this paper

ResearchGate

Publisher Website

Web of Science

HOW TO CITE

Pan, B. and Yang, Y. (2016). “Monitoring and Forecasting Tourist Activities with Big Data” In M. Uysal, Z. Schwartz & E. Sirakaya-Turk, E. (eds), Management Science in Hospitality and Tourism: Theory, Practice and Applications. (pp. 43-62) Taylor & Francis.

Additional Reads

2026

Comparative Advantage

Theories and Models in Tourism and Hospitality Research

2026

Customer gratitude and employee work behaviors

TOURISM MANAGEMENT

2026

Together through thick and thin: How does the survival of neighboring restaurants matter?

INTERNATIONAL JOURNAL OF HOSPITALITY MANAGEMENT