BIG DATA ON
TRAVEL & TOURISM
Introduction
The rapid development of technology resulted in the emergence of the technology bundle, Industry 4.0. This technology bundle tends to result in a strong influence on varieties of industrial sectors including Travel & Tourism. Amongst the multiple technologies clustered under Industry 4.0, the application of Big Data is increasingly gaining acceptance within the Travel & Tourism industry. The Travel & Tourism industry is further benefitted by this Big Data Analysis in terms of the associated industries such as the Hospitality Sector using this technique for their respective business growth.
Collection of Big
Data
The application of
Big Data in the tourism industry relates to systemically Extracting,
Processing and Visualizing relevant data sets for
the organized business management of the industry (Centobelli and Ndou, 2019).
Big Data in
Travel & Tourism
The range of data
collected from the industry for its efficient processing includes Destination
Information, Travel & Hospitality News, Hotel & Restaurant Details,
Social Data, Transportation Data, Event Details, Tourist Data and Government
Schemes.
Destination Information: Place of Visit, Rules & Regulation
Travel & Hospitality News: Latest developments of the industry, Major investments for development, start of new tourist spots.
The usual size of Big
Data is several Terabytes and Petabytes depending on the range of data
collected. Considering the size of the data, the collection of Big Data from
the tourism industry poses to be a challenge for Data Scientists. In this
regard, extracting data can be progressed using techniques such as Web
Scraping and Internal & External
Resources (Mazanec, 2020). The concept of Web
Scraping relates to the efficient formulation of a script for the extraction of
data from travel & tourism focussed websites. On the other side, the aspect
of internal research relates to an in-house collection of data from reservation
management software and accounts & services book. Furthermore, the external
research for data collection includes seeking the contribution of tourism
boards and third-party data providers.
Implication of Big
Data Analysis
The foremost
application of results generated by the analysis of Big Data from the Travel
& Tourism industry relates to concerning market research. The aspect of
market research plays a vital role in the growth and development of the
industry. In this regard, the prolonged analysis of Big Data, collected from
reliable sources results in the identification of potential areas, requiring
the attention of industry leaders for development (Li et al. 2020). As for an instance, the analysis of
customer-oriented data reveals the dynamic purchasing behaviour of the
customers in the Travel & Tourism Industry. Contextually, the potential
market leaders can improve their customer attention attraction strategies by adding
Lucrative Discounts, Surprise Gifts and Combo Offers. Furthermore, the
range of information, revealed by the Big Data Analysis can fuel the
uninterrupted progress of the tourism research for a prolonged duration.
Big Data in Tourism Research (Source: Li et al. 2018)
The dedicated
contribution of the hospitality sector plays a vital role in the growth and
development benefit of this Travel & Tourism industry. In this regard, the
concerned market leaders can deploy suitable techniques for the analysis of the
collected data to reveal extensive customer-oriented information (Ardito et al. 2019). Such information aids the reputed hospitality
organizations to improve their overall service by availing suitable amenities
to the visitors and tourists, during their stay.
The application of
Big Data in the Travel & Tourism Industry results in the overall
improvement of the industry. This is evident as the travel, as well as
transportation companies across the world, tend to utilize the relevant Data
Analytics method for analysing purchasing behaviour of the travel enthusiast as
well as the explorers (Xia et al. 2021). Furthermore, the
detailed analysis of such data can reveal the overall travel behaviour of
specific demographics. The effective utilization of these findings can
encourage the concerned companies to introduce lucrative offers for the benefit
of the target demographics. This is mutually beneficial for travel enthusiasts
as well as the concerned market leaders of the travel & tourism industry.
The rapid development of technology resulted in the emergence of
an innovative trend. This trend relates to electronic Word-of-Mouth
(eWoM), which catalyses the consistent growth and development of the
travel & tourism sector (Ahmad et al. 2019). This growth and
development are further supported by the aspect of Big Data Analysis. This is
because, Big Data Analysis tends to encourage market leaders of the Travel
& Tourism industry to analyse eWoM related to various products and
services, offered by the Travel & Tourism Industry to its customers. This
process of Big Data Analysis is progressed by Web Scraping
and social media listening (Welch and Widita, 2019). The wide acceptance of Big
Data Analysis within the Travel & Tourism industry is enhanced by the dedicated
contribution of reputed firms such as Datahut. The sole
objective of such companies relates to the presentation of scraped information
from multiple platforms in the form of a structured dataset for the growth
benefit of enterprise-grade data extraction platforms.
Conclusion
The deployment of Big
Data Analysis in the Travel & Tourism Industry is a cost-effective
procedure in terms of applying suitable strategies and human intellect to the
possible extent. The outcome generated from such procedures can result in
market benefit for reputed companies of the industry. The engagement of the
suitable tactics for supporting Big Data Analysis in the Travel & Tourism
industry results in uninterrupted growth and development of the industry for a
prolonged duration. The leading companies of the Travel & Tourism industry manage
to collaborate with reputed companies, offering the service of Big Data
Analysis and thereby improving their position in the market for a prolonged
duration.
Ahmad,
H., Hamad, A.G., Raed, H. and Maram, A.H., 2019. The impact of electronic word
of mouth on intention to travel. International Journal of Scientific
and Technology Research, 8(12), pp.1356-1362.
Ardito,
L., Cerchione, R., Del Vecchio, P. and Raguseo, E., 2019. Big data in smart
tourism: challenges, issues and opportunities. Current Issues in
Tourism, 22(15), pp.1805-1809.
Centobelli,
P. and Ndou, V., 2019. Managing customer knowledge through the use of big data
analytics in tourism research. Current Issues in Tourism, 22(15),
pp.1862-1882.
Li, H.,
Hu, M. and Li, G., 2020. Forecasting tourism demand with multisource big
data. Annals of Tourism Research, 83, p.102912.
Li, J., Xu, L., Tang, L., Wang, S. and Li, L.,
2018. Big data in tourism research: A literature review. Tourism
Management, 68, pp.301-323.
Mazanec,
J.A., 2020. Hidden theorizing in big data analytics: With a reference to
tourism design research. Annals of Tourism Research, 83,
p.102931.
Welch,
T.F. and Widita, A., 2019. Big data in public transportation: a review of
sources and methods. Transport reviews, 39(6),
pp.795-818.
Xia, D., Jiang, S., Yang, N., Hu, Y., Li, Y., Li, H. and Wang, L., 2021. Discovering spatiotemporal characteristics of passenger travel with mobile trajectory big data. Physica A: Statistical Mechanics and its Applications, 578, p.126056.
Author: Komal
Keywords: # Big data#Travel#tour/#
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