This is a response to Xin Zhong’s article: Big Data: Its possibilities for facilitating customised tourism for Chinese tourists
Big data is ‘hot’. Indeed, this era characterizes itself through digitalisation. We spend a lot of time profiling ourselves on social media and reading reviews about hotels, restaurants or holidays. Those activities enable companies to profile their customers. For them, that is what it is all about. Know your customer. The Big Names – such as Google, Facebook, but also their Chinese equivalent Renren or Baidu or Dutch companies like KLM or TUI – want to know your personal situation and interests. It gives them the opportunity to send you tailor made advertisements and offers. Zhong shows in his article that this type of data is valuable for the process of influencing people’s travel choices and, in the end, their travel behaviour.
Big data is relevant in a different context as well. It is commonly known that city tourism is increasing, especially for historical inner cities, such as Amsterdam, Venice and Barcelona, where the over-tourism discussion is familiar. Local authorities are discussing measures to create (more) liveable and sustainable environments for the inhabitants – while taking into account that tourist attractiveness is very important for the local economy.
What is the role of big data in that discussion? In the current situation a lot of the data is gathered, but it is still used too little in a cross-disciplinary and cross-sectional way. In my opinion, it is time to bridge the gap between Tourism and Mobility, providing more accurate information about the actual and expected travel times from door-to-door. In addition, information could be provided about the crowd density at certain places and attractions. In this process we can distinguish two steps.
The first step is, in line with Zhong, a pre-trip phrase. This often starts a few months before the visit. A tourist is looking for a destination and, later on, a hotel. In this situation we could provide the tourist with valuable information about her or his trip:
- Expected time of journey door-to-door (from origin to destination), using several modes, distinguishing public transport, taxi, cycling or shared services;
- CO2 emissions, promoting the most sustainable option to reach the destination.
- Best times to visit destinations / attractions.
This information, in addition to the reviews and costs – might influence tourists’ destination or hotel. Secondly, during thein-trip phrase, we should provide to the tourist with more and accurate information. Are there some possible delays, for instance because of bad weather or (expected) road works? We should provide the tourist with updated traffic information – using big data – including alternatives to reach the destination. Information can be provided about the number of people that are at a destination or attractions and/or travelling towards those places. The latter might enable tourists to make a more conscious choice about which places to visit at which times.
Bottom line, in my opinion, big data certainly is of value for both private as well as public organisations. The next step is to cross borders and combine Tourism and Mobility, to obtain new information, but also to add new mobility information to the decision process. That should be the next step in tourism hospitality!
