How Big Data Can Be Used for Tourism Recovery in Asia and The Pacific
The pandemic-driven surge in data collection offers major opportunities, and some risks, for the reopening of tourism in the region.
The pandemic hit tourism in Asia and the Pacific hard, but it also rapidly increased digitalization. The vast amounts of data collected every day – the ‘big data’ – in the tourism industry could be key to its successful revival.
Big data consists of large datasets of information that are created, stored, and visualized quickly. Typically, big data involves millions or even billions of data points that are collected in real-time which require an array of new skills compared to traditional smaller data sets.
In the tourism sector, big data is generated whenever, for example, consumers engage in online travel searches and for bookings using digital platforms such as online travel agencies and global reservation systems.
Once tourists start travelling, big data on travel habits can be collected. Properly processed and analyzed, big data can provide valuable insights into trends, consumer behaviors, and prospects.
Increasingly, Asian governments are tapping big data to not only promote tourism but also to formulate and implement tourism-related policies. The Tourism Authority of Thailand, for example, collaborated with Expedia in 2018, to run ads across Expedia’s numerous web platforms, which have 750 million views per month.
This helped attract more premium and first-time international tourists to Thailand, balance traffic flows during off-peak and high seasons, and disperse tourists to less-popular provinces.
In 2018, the Singapore Tourism Board developed a platform called Singapore Tourism Analytics Network (STAN) to gain deeper insights into data from their own sources, other government agencies, and partner industry big data providers.
By 2019, the network had integrated over 20,000 internal data domains and signed 15 data-sharing agreements with some of the largest data providers, such as Grab, Tencent, and Expedia. The Singapore Tourism Board was able to analyze key source markets and, for example, help retailers to better design campaigns and offer products.
As tourism is multi-dimensional, countries can use big data from various sources and share information across sectors to improve policies and services. In Thailand, smart sensors are being employed for ocean surveillance and safety, enabling lifeguards and other safety service personnel to better monitor the beaches, boat conditions, locations, and the weather.
Japan’s Regional Economy and Society Analyzing System creates easy-to-understand visualizations of a wide variety of economic and social data. Big data is compiled from government agencies and the private sector, allowing searches aimed at both macro-analysis, including changes in industrial structure and micro-analysis, determining how long tourists stay in popular spots or tracing the history of individual stores and offices in shopping areas.
Grid analysis is used to study spending habits of tourists by nationality to develop marketing strategies tailored to tourists’ reasons for visiting specific regions.
However, significant technological, organizational, institutional, and financial challenges remain related to the implementation and management of big data by governments. Data privacy, cybersecurity, and skills capacity gaps are among these challenges.
Increasingly, Asian governments are tapping big data to not only promote tourism but also to formulate and implement tourism-related policies.
As more people turn to online transactions, data privacy is arguably the most important issue governments must address in working with big data. Even as data privacy laws continue to evolve, they need to keep pace with innovations. The two best-studied applications of big data for destination management and product – credit card transactions and mobile location data –involve high data privacy concerns to protect against reidentification.
While the travel industry is increasingly digitalized, tourists are also becoming much more aware that a considerable amount of information about them is being collected. If they feel that an excessive amount of personal data is collected and infringing on their privacy, destinations might suffer a backlash and a drop in the number of visitors.
When it comes to the movement of personal information across borders, the Asia-Pacific Economic Cooperation created the Cross Border Privacy Rules (CBPR) system in 2011, to establish enforceable binding commitments to raise the overall standard of privacy protection. However, despite 10 years of existence, the system has only been fully adopted in nine destinations.
Closely related to data privacy concerns is cybersecurity, the practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks. Data breaches that include data fraud or theft and large-scale cyber-attacks, violate the safety and rights of individuals and are financially and reputationally expensive for data owners.
Skills-wise, shortages and mismatches of ICT professionals are already being felt in all categories of expertise. The International Information System Security Certification Consortium, a leading global association for cybersecurity professionals, reported a global gap of 3.1 million cybersecurity professionals in 2019, with the Asia and Pacific region accounting for 2.1 million. Sharing of big data held by the private sector is the most frequently cited emerging challenge. As for now, only a few countries have initiated policies to facilitate data sharing within the private sector and between government and the private sector.
Governments need to develop new policies to facilitate such exchange. Public–private partnerships are one compelling model for driving cross-sector data sharing and have been used by Singapore’s Tourism Board and Thailand’s Tourism Authority.
Another win-win opportunity for the private and public sectors is ride-hailing platforms. These platforms benefit from integrating publicly available open government big data, such as outages, weather, or public events, into their systems, helping them to optimize their operations, such as improved demand forecasting or dynamic pricing.
They produce an enormous volume of big data on transportation, traffic flows, and demand for services by locals and tourists, which are often not shared with the public sector, but would be highly useful for urban and tourism planning. Policies therefore need to encourage data reciprocity between the public and private sector.
As Asia and the Pacific emerges from the pandemic, the full utilization of big data for tourism by businesses and governments has become critical for recovery.