Zheng Xiang, Virgina Tech
HOW TO CITE:
Xiang, Z. (2017). Tourism innovations through big data analytics. In AIRTH Encyclopedia of Innovation in Tourism and Hospitality. Retrieved: <insert-date>, from http://www.airth.global
Due to the widespread adoption of information technology such as smartphones and wearables by consumers and advances in hardware, software, storage, sensors, and networking, big data is being generated at tremendous speed in our society. Big data come in different forms and sources including Internet traffic, mobile transactions, online user-generated content, business transactions, and various sensor systems embedded in the environment. Generally speaking, analytics can be defined as the discovery and communication of meaningful patterns in data. Although conventional statistical tools are widely utilized, the process of analytics often involves a combination of statistics, computer programming and data visualization to quantify findings to generate and communicate useful insights, predictions, and decisions for business problems. Big data analytics, therefore, aims to discover novel patterns and business insights that can meaningfully and, oftentimes in real time, complement traditional approaches of research such as focus group studies and consumer surveys.
Relevance for tourism innovation
Travel and tourism is a field with huge potential in developing big data analytics. Particularly, as an experience-based product the design and development of tourism requires a profound understanding of what today’s travelers need and want, how they move through and interact with physical and social spaces, and what leads to their enjoyment, happiness, and the realization of personal values. The focus on creating this knowledge increasingly relies upon our capabilities to capture, store, measure, and interpret data generated through different stages of the travel process in a timely fashion. In recent years, we have seen progress in several important areas of big data analytics, ranging from mapping the digital footprint of travelers to understanding their sentiments and preferences using online user-generated content. This will likely serve as the scientific foundation for tourism innovations in the future.
Xiang, Z., & Fesenmaier, D. R. (Eds.). (2016). Analytics in Smart Tourism Design: Concepts and Methods. Springer.