1 Globalization and the Impact of Globalization
1.1 Globalization
Globalization is the process of international integration arising from the interchange of world views, products, ideas and other aspects of culture.[i] Advances in transportation and telecommunications infrastructure, including the rise of the telegraph and its posterity the Internet, are major factors in globalization, generating further interdependence of economic and cultural activities.[ii]
The term globalization has been increasingly used since the mid-1980s and especially since the mid-1990s.[iii] The concept of globalization 'emerged from the intersection of four interrelated sets of "communities of practice": academics, journalists, publishers/editors, and librarians.' [iv] Economists were central in this early stage. In 2000, the International Monetary Fund (IMF) identified four basic aspects of globalization: trade and transactions, capital and investment movements, migration and movement of people, and the dissemination of knowledge.[v] Further, environmental challenges such as climate change, cross-boundary water and air pollution, and over-fishing of the ocean are linked with globalization.[vi] Globalizing processes affect and are affected by business and work organization, economics, socio-cultural resources, and the natural environment.
1.2 Impact of Globalization
From the above summary of globalization we can see that globalization has already impacted many different aspects in our lives, e.g. in terms of politics, economics, culture, environments and technologies, etc.
The term globalization has been increasingly used since the mid-1980s and especially since the mid-1990s.[iii] The concept of globalization 'emerged from the intersection of four interrelated sets of "communities of practice": academics, journalists, publishers/editors, and librarians.' [iv] Economists were central in this early stage. In 2000, the International Monetary Fund (IMF) identified four basic aspects of globalization: trade and transactions, capital and investment movements, migration and movement of people, and the dissemination of knowledge.[v] Further, environmental challenges such as climate change, cross-boundary water and air pollution, and over-fishing of the ocean are linked with globalization.[vi] Globalizing processes affect and are affected by business and work organization, economics, socio-cultural resources, and the natural environment.
1.2 Impact of Globalization
From the above summary of globalization we can see that globalization has already impacted many different aspects in our lives, e.g. in terms of politics, economics, culture, environments and technologies, etc.
What I would like to focus in this article are mainly on the following aspects:
1.2.1 In Terms of Economics
Economic globalization primarily comprises the globalization of production and finance, markets and technology, organizational regimes and institutions, corporations and labour.[vii]
On the one hand globalization has radically increased incomes and economic growth in developing countries and lowered consumer prices in developed countries, on the other hand it also changes the power balance between developing and developed countries and has an impact on the culture of each affected country. And the shifting location of goods production has caused many jobs to cross borders, requiring some workers in developed countries to change careers. This has caused more connections between different regions of this world.
1.2.2 In Terms of technologies
Globalization also accelerates the change of technology. Every day it seems that a new technological innovation is being created. The pace of change occurs so rapidly many people are always playing catch up, trying to purchase or update their new devices. Technology is now the forefront of the modern world creating new jobs, innovations, and networking sites to allow individuals to connect globally.
Under the influence of globalization, the emerging technology - Big Data Technology, has been applied to various industries around the world rapidly. SOCAP defines Big Data as “the productive use of data in units of measure that far exceed megabytes and gigabytes.” While this is a broad definition, the idea behind Big Data is crystal clear: use the information that customers are already generating to provide them with better, more targeted – and ultimately more profitable – services and products.
1.2.3 In Terms of migration and movement of people
As the globalization began to develop faster and faster, the migration and movement of people between different countries became more and more often. People employed by multinational companies and connected through a global system of networking and production, immigrant workers, transient migrant workers, telecommuting workers, and those in export-oriented employment or contingent work and other precarious employment need to travel more, due to the impact of globalization. And the others moves to other countries, due to better living conditions, better education, better medical care, more ssecurity or family links.
These increasing movements have brought huge opportunities for the tourism industry, especially airlines and car rental companies, etc.
2 Globalization and tourism
Tourism involves flows of goods, services, and people on a global scale. Therefore we could say that it is a visible expression of globalization itself. The global aspect of tourism processes makes some of the aspects of the tourism market more intensive and at the same time of a broader scope – competition, protection of cultural resources, dependence on external entities, demands for market information. Under these circumstances internationalization is becoming a main strategic option of tourism development for tourism companies. How to compete on a world stage, how to overcome long distance and reach people who have purchasing power and desire to travel require global perspective and technology.
Globalization presents tons of opportunities for tourism industry, such as cheaper and faster transportation, more cultural exchange stimulating desire to learn other cultures, more information tools for planning a trip far away from home. With the fast growth of information technology and its application in tourism industry, the efficiency and service quality have been greatly increased. New information technology like big data has provided more possibilities for each player in the industry, which could be challenges as well.
3 Big Data and Tourism in the context of globalization
We are going to examine how Big Data could make a difference for 4 different players in the tourism industry as follows:
3.1 Big Data and Car Rental Industry
One of the industries which benefitted most from the growing globalization is car rental industry. The increasing transnational business activities and the increasing migration and movement of people have played a significant role in the growth of global car rental industry. According to a new market report published by Transparency Market Research "Car Rental Market - Global Industry Analysis, Size, Share, Growth, Trends and Forecast, 2013 - 2019," global car rental market was valued at USD 36.89 billion in 2013, growing at a CAGR of 13.6% from 2014 to 2019 to account for USD 79.46 billion in 2019.[viii] Today, the market is expanded and diversified not only in developed countries but also in the emerging economies, such like India, Brazil and China etc.
In the present scenario, car rental industry has become very technologically oriented. And Big Data Technology becomes a big support for the modern Car Rental Industry gradually.
3.1.1 Company Hertz as a good example
With over 8300 business locations in 146 countries globally, company Hertz is one of the world’s largest car rental companies. Recently it started to work together with IBM (e.g. company Mindshare, an IBM Partner) to use IBM data analytics tooling (driving by the big data technology) and has obtained in a short time frame a competitive advantage over its global competitors.
Before the cooperation with IBM, Hertz has traditionally kept it's finger on the pulse of it's customers with customer satisfaction surveys. And what’s the problem? How should Hertz analyze all these information and understand what customers were trying to tell them through these surveys?
“Hertz gathers an amazing amount of customer insight daily, including thousands of comments from web surveys, emails and text messages. We wanted to leverage this insight at both the strategic level and the local level to drive operational improvements,” said Joe Eckroth, Chief Information Officer, the Hertz Corporation. Mindshare, a partner of IBM, realized there was an opportunity for Hertz: not only could the company address its need to understand its customers better, but also how it could take efforts to enhance its relationship with its customers.
Here's how Mindshare helped Hertz to address it's customer satisfaction challenges and enhance it's customer engagement activities by using IBM’s big data analysis:
Ø Enhanced the manner in which Hertz gathered customer sentiment surveys by centralizing the process.
Ø Allowed Hertz's analysis to occur in half the previous time, giving the company the ability to respond quickly to customer’s feedback
Ø Provided Hertz insights which allowed it to take immediate action on problem areas
Here is an example - while evaluating the solution, Hertz was able to identify a potential area for improvement in Philadelphia: surveys indicated that delays were occurring for returns during specific times of the day. By investigating this situation, Hertz was able to quickly adjust their staffing levels at the Philadelphia office during those peak times, ensuring a manager was present to resolve any issues. This enhanced Hertz's performance, and increased customer satisfaction, all by parsing the volumes of data being generated from multiple sources. This tangible example of Big Data providing real returns, convinced Hertz to move forward with the IBM/Mindshare Big Data solution.[ix]
3.1.2 Some other areas that Big Data can be helpful for Car Rental Industry
Big data can also be helpful for Car Rental Industry in following aspects:
Customer Relationship
After the emergence of big data technology, by combining internal and external databases like rental history, purchasing history or spending habits with publicly available information, car rental companies can learn a whole lot about their customers’ preferences on a macro level easily.
They can then recommend suitable vehicles for their customers according to their previous car choices as well as according to the recorded rental places and time periods. Thus the customer relationship will be improved and more business profit can be achieved.
Vehicle Management
With the support of big data technology, car rental companies can allocate and arrange their vehicles better and more efficiently. For example, by using the big data analysis, a car rental company can know it easily what type of vehicles would be preferred by what kind of customers in which country / in which place (e.g. at airport or in the city, etc.). This allows the better usage of the internal resources of the car rental companies.
3.2 Big Data and tourism attraction companies
Big data technology is widely used by the tourist attraction companies to expand its business and visibility in a global range. Regions, especially remote ones or third world where tourism is the pillar industry, more urgently need the assistance of Internet technology and big data application to get to know the industry, develop products and improve service. Moreover, big data technology also should be used to ensure the orderly operation of destination companies and safety of visitors.
3.2.1 Carrying ability prediction
Simply put, carrying capacity is a measure of the maximum number of tourists that can use a tourism resource (which could be a resort, beach, attraction, town or any other kind of tourism destination), when there is no emergency, like natural disasters or big political events. For a country with big population and strong needs for travelling during holidays, like China, it is wise for tourist destination companies to use big data to predict an approximate number of visitors in peak seasons in order to make transportation within scenic area, accommodation and other arrangement beforehand. We have bloody experience of “New Year's Eve Stampede in Shanghai”--- On December 31, 2014, a deadly stampede occurred in Shanghai, near Chen Yi Square on the Bund, where around 300,000 people had gathered for the New Year celebration. 36 people were killed and there were 49 injured, 13 seriously. If the administration of Shanghai stampede used big data to predict the number of visitors and took steps to limit the flowrate, the tragedy would not happen. But the reality is such events occurs time from time, in amusement parks, mountains, beaches, etc.
The precondition for making profits is to make sure all the customers can have a safe travel environment. No matter how beautiful the scenery is, how exciting your project is, or how unique the sight is, prediction and controlling of number of visitors is the priority. After guaranteeing the security of visitors, the comfort of tourists should be taken into consideration, such as the frequency of shuttle buses/cable cars with the scenic areas, the inventory of food and water, and so forth.
3.2.2 New business exploration:
Beyond simply managing and leveraging owned data streams, attraction companies need to consider how to use other indications of consumer preferences and lifestyles:
Take the photos being posted on social media, like Facebook and Wechat for instance. Would the traveler sharing snaps from a trip to Mount Huang be interested in information about Mount Lu? If shown on a mountain bike, would that individual want to know more about local biking destinations or biking services in scenic spots? If shown standing in front of a car with a bicycle roof rack, wouldn’t a trunk rack be easier to use and avoid back problems down the road?
Also, overall macroeconomic data and economic data from other industries also can offer clues for tourism development companies. For example, with the boost of health care industry in recent year, which means Chinese people are more and more health-conscious, the tourism companies can take the advantage of the trend to develop “Farm Stay” projects or “Hot Spring” programs. And a hot TV reality show could give your new idea to promote your companies, like the TV show “Dad, where are we going” breeds “Family Fun” programs, like family sports meeting, family pottery making.
Big data and data analytics suggest that the future may belong to those firms that are sensitive enough to shape and deliver the consumer travel experience.
3.2.3 Personalization with combination of information
5 years before, Chinese people were mostly satisfied by package tour, one tour guide, same routing, same accommodation. But now due to increasing number of middle-class and high-class people in China, more and more people ask for a more personalized travel plan specially designed for themselves. For tourism corporations, they are required to provide a wide range of activities to cater for different needs. However, the feasibility is still a problematic issue. The use of big data can be a problem-maker or a problem solver.
Personalization is a key tenant of Big Data. With so much available information about a particular consumer, transaction or destination, the reality is it is difficult to integrate and manage all the information and make a suitable plan for VIPs.
In order to most effectively win at true personalization, large tourism companies must work across different channels to gather the myriad data points created by a consumer.
Information systems can be quite fragmented and even territorial, with records pertaining to a single customer showing up in reservation, post sales complaint, survey, loyalty and other systems, with little or no ability to weave together and form a complete customer profile. Therefore, companies tend to rely on one source of information and make decision. For example, the popularity of biking is increasing but the reason behind the phenomenon is citizens’ health condition is disappointing. So if the company develops difficult and energy-exhausting project, probably it will not be a good choice. However, different people have different health condition, so how many plans they have to develop and how to set the level are the questions.
Combining data from different in-house systems can help companies achieve new insights and make right decision.
3.2.4 Learning from competitors:
Big data also shows the ranking among competitors and the reasons why some are hot and some are ignored by tourists. For example, in Jiangxi province, there are two beautiful mountains, one is called Mount Lu and other one is Mount Sanqing. Although they are both unique and magnificent, Mount Lu are far more famous than the latter one. One of the reason is an early popular color movie “Love on Lushan Mountian” was shot in Mount Lu and tells a romantic love story happened in the mountain. So using big data to investigate the reason behind the phenomenon, the company of managing Mount Sanqing finally understands that they lose not because of the scenery itself but the advertisement. Therefore, it is heard that the authority is working on making a film about Mount Sanqing.
Various rankings reveal the trend---What is hot and what will be hot, and show reasons behind phenomena---Why this tourist destination is well-known and why that place is only visited by professional traveler.
3.2.5 Privacy
Big data is double-edged sword. It helps tourists enjoy more customized and comfortable trips but also raise potential be to lose personal privacy. Actually, privacy is a paramount concern when it comes to Big Data. Avoiding privacy leakage is an essential component of successful Big Data implementation, and also ensures a significant level of trust on the consumer side.
3.3 Big Data and country tourism board
3.3.1 The role of country tourism board
Each country has a tourism board, or call it a tourism commission, administration, whatever. If you go to their websites, you could find introduction of the country’s culture, most famous scenes, transportation and accommodation details, even advertisements on some exhibition or promotion for certain activities. It almost looks like a travel agency’s website. However, in fact, a tourism board’s function is much broader than this.
So what does a tourism board do? Their main purpose of course is to maintain the sustainable and healthy growth of the country’s tourism industry. In the context of globalization, it also has the responsibility to promote the country’s culture and tourism services in the world market, as well as protect local culture and ecological environment. To be more specific, its main function includes:
1. Plan and coordinate the development of the tourism industry, setting up development policies and strategies. Of course after setting up the policies and regulations, it also need to supervise the implementation of those policies.
2. Communication and exchange in the global market, including organizing external publicity and significant promotional activities to promote and improve the country’s image.
3. Coordinating the development and protection of tourism resources on a country level. This includes instructing the layout and development of key tourism regions, destinations and routes.
4. Protecting interests of tourists and improving service quality of the industry. This includes setting up standards on tourism services and products.
5. Providing education and training services, collecting industrial data.
3.3.2 How big data could help country tourism boards to reach their goals
As we mentioned earlier, big data has provided new ways as well as challenges for each player in the industry, including the tourism boards. Let’s now examine how big data could help country tourism boards reach their goals.
First of all, although I put collecting industrial data in the last function of country tourism boards, it does not mean it is the least important one. In fact, it is the foundation of the implementation of all other functions of the country tourism boards. And this does not just start when big data emerges. Collecting and maintaining industrial data could said to be a traditional responsibility of country tourism boards. So you could almost imagine how much data they have accumulated through all these years. And how to make good use of these data becomes the natural question and even a great challenge for the tourism boards. Big data technology could address this problem perfectly.
Big data can help tourism boards understand tourists’ behavior and consumption habits in a much more organized way. For example, they could find out from the historical data the density of each tourism region and amount of consumption over years, including the changes and trends on different consumption categories. With these analysis, the tourism boards could make judgment on whether the development of each region is balanced enough. What’s more, with the knowledge of consumption habits and trends, tourism boards could make more scientific policies to lead more consumption in less developed regions.
In the global tourism market, big data could also play an important role on improving tourism boards’ effectiveness. For inbound tourism, which means the market where foreign tourists visiting the host countries, it is a bit similar with domestic market. Big data technology could help analyze the behavior and consumption habits of tourists from different countries. This lays the foundation for the tourism boards to formulate different policies for different countries. For example, from the historical data on visitors’ countries of origin and their tourism destinations, tourism boards could find out what kind of tourism destinations is more attractive to certain countries’ tourists. And they could make targeting marketing strategies or promotion in those countries. Another example could be the length of stay of different countries’ tourists in different tourism destinations. The analysis of these data could help the tourism boards better plan and organize tourism resources such as accommodation in different regions.
For outbound tourism, which means the market where host countries’ tourists visiting other foreign countries, big data could help to analyze host countries’ tourists behavior and consumption habits as well. For example, there are lots of reports recently on Chinese tourists’ inappropriate behaviors in foreign countries which raised international attention. Big data could provide more detailed analysis such as whether certain behavior is due to misunderstanding of the local culture or misleading of the travel agencies. Such analysis could help the tourism board to design focused education programs for the people or training programs of the tourism agents. With the developing of the economy, Chinese people’s purchasing power also increased. Chinese tourists spend substantial amount of money on purchasing all kinds of products in foreign countries. By using big data technology, the Chinese National Tourism Administration can find out where did Chinese tourists spend their money on mostly and even predict their consumption trends. The analysis could then provide guidance for domestic Chinese providers for the way of improvement in order to attract more oversea consumption back to the domestic market. This is another good example of the application of big data for country tourism boards.
Big data also helps on tourists interest protection. For example, it can help to analyze the violation models of different tourism service providers. Tourism boards could then use these analysis to formulate relevant regulations to better protect tourists’ interests.
3.4 Big Data and airlines
The impact of Big Data to the airline ticket industry is from three perspectives: customers, agency and airline company.
3.4.1 For customers
The application of big data could help to reduce the expense on ticket. With globalization people go out for traveling become more and more often, so airlines also developed very fast during these years. Stand on the client perspective, there is a common sense that it is cheaper if book the ticket earlier, however, the truth is it is not. As a product, airline ticket, for the same journey, same seats class, however the price is totally different. So some company developed a system to collect huge amount of price information of airlines and have those information analyzed which could be used to predict the trend of the price fluctuation. The most successful company is Forecast, the company have collected ten thousands billion price recording to predict the price of airline ticket and the precise rate is as high as 75%. It is estimated that the customer could spend less than 50$ for single ticket through the Forecast system. By using the system, the client could find that the price on Friday and Saturday is always high and sometime is very cheap which shows not the early the better.
3.4.2 For agents
The application of big data could help to provide customized products to each fragment market. With the globalization and development of transportation, the competition between agents is obviously higher and higher, so how to utilize the technology of Big Data become the advantage for many companies especially for those big OTA. By collecting the data, the agents could integrate whole consume chain products and reengaged to derivate new products and by tracing the consumption they could get the feedback immediately and response to the client quickly. Furthermore, with new technology of APP, the company could reach and cover every corner of the market and interact with the potential clients easily by pushing some promotion message and advertising, the customer could give their individual plan and requirements to the company by the tool easily. So with the technology, they could not only provide much more customized products and service to customer but also could do much better on interaction with the clients and do better clients service work.
3.4.3 For airlines company
To some extend the implement of Big Data in some place will reduce the profit of Airlines Company, however, airlines are striving to make fully use of their Customer Royalty Program as well by collecting the consumption data to provide services from miles exchange ticket to miles exchange commodities. Since the application of Big Data, the value of CRP is emerging like a cash bull that could generate continues cash. By collecting the data, the company could sell the miles to hotels, credit card companies and shopping malls, some leading company like Canadian Airlines even separate the CRP out and established a new company to IPO, some of them like Qantas sell part of the share to some other industry company (Woolworths) to get the trasindustry cooperation which have been a brand new business model give us big space to imagine.
4 Conclusion
After the emerging of Big Date, the industry have changed the logic of business development, some of them begin to think integration and segmentation rather than wait for the customer, if the Data could be utilized and new products and services are stimulated, thus they surly will become leading companies in the industry.
On the other hand, country tourism boards as government agencies, are entities traditionally function with rich data. Big data provides an innovative way to manage and make use of the rich data in a global context. However, whether they can successfully implement big data technology depends on a lot of conditions such as willingness, financial support, skilled personnel, etc.
We believe that with the great support of emerging technologies, especially the big data technology, the future tourism industry will become more and more efficient and convenient for the customers.
References:
[i] Albrow, Martin and Elizabeth King (eds.) (1990). Globalization, Knowledge and Society London: Sage. ISBN 978-0803983243 p. 8. "...all those processes by which the peoples of the world are incorporated into a single world society."
[ii] Stever, H. Guyford (1972). "Science, Systems, and Society". Journal of Cybernetics 2 (3): 1–3. doi:10.1080/01969727208542909.
[iii] Google Books Ngram Viewer: Globalization https://books.google.com/ngrams/graph?content=globalization&year_start=1900&year_end=2008&corpus=15&smoothing=3&share=&direct_url=t1%3B%2Cglobalization%3B%2Cc0
[iv] James, Paul; Steger, Manfred B. (2014). "A Genealogy of globalization: The career of a concept". Globalizations 11 (4): 424.
[v] International Monetary Fund. (2000). "Globalization: Threats or Opportunity." 12 April 2000: IMF Publications.
[vi] Bridges, G. (2002). "Grounding Globalization: The Prospects and Perils of Linking Economic Processes of Globalization to Environmental Outcomes". Economic Geography 78 (3): 361–386. doi:10.2307/4140814.
[vii] James, Paul; Gills, Barry (2007). Globalization and Economy, Vol. 1: Global Markets and Capitalism. London: Sage Publications.
[viii] https://www.linkedin.com/pulse/20140707102103-221228539-global-car-rental-market-size-and-share-2013-2019
[ix] “How big data is giving Hertz a big advantage”
www-01.ibm.com/software/ebusiness/jstart/portfolio/hertzCaseStudy.pdf