Strategic technological determinant in smart destinations: obtaining an automatic classification of the quality of the destination
| DOI | https://doi.org/10.1108/IMDS-10-2021-0640 |
| Published date | 12 September 2022 |
| Date | 12 September 2022 |
| Pages | 2299-2330 |
| Subject Matter | Information & knowledge management,Information systems,Data management systems,Knowledge management,Knowledge sharing,Management science & operations,Supply chain management,Supply chain information systems,Logistics,Quality management/systems |
| Author | Sergio Díaz-González,Jesus M. Torres,Eduardo Parra-López,Rosa M. Aguilar |
Strategic technological
determinant in smart destinations:
obtaining an automatic
classification of the quality
of the destination
Sergio D
ıaz-Gonz
alez
Department of Computer and Systems Engineering, University of La Laguna,
San Crist
obal de La Laguna, Spain
Jesus M. Torres
Department of Computer and Systems Engineering, Faculty of Information Sciences,
University of La Laguna, San Crist
obal de La Laguna, Spain
Eduardo Parra-L
opez
Department of Business Management and Economic History,
University of La Laguna, San Crist
obal de La Laguna, Spain, and
Rosa M. Aguilar
Department of Computer and Systems Engineering, University of La Laguna,
San Crist
obal de La Laguna, Spain
Abstract
Purpose –Smart tourist destinations (STDs) make use of new technologies to facilitate and improve the
experience of tourists. So why not use these technologies to efficiently manage the destination? The aim of this
work is to define and implement a methodology that provides value to STDs by defining their most important
characteristics to monitor and quantify them automatically in real time.
Design/methodology/approach –The authors developed a conceptual framework to the smart tourism
approachpresented in previous studies, the latesttechnologies and the application of thesmart tourism system
(STS). Based on the focus group method with stakeholders from the tourism industry of the Spanish tourist
municipalityof Puertode la Cruz, theydefined the main KPIsfor a municipal STD.Likewise, theauthors specified
thenecessary technologiesto obtain,manage andrepresent thedata, and the methodfor quantifyingthe quality of
theSTD by using the AHPmethod. Lastly,they implementedthe frameworkfor the aforementionedmunicipality.
Findings –The implementation in a real context of the STS proposed for Puerto de la Cruz demonstrates its
validity and the possibility of adapting it to any other municipal destination. In addition, the authors
corroborate how this STS improves on other versions.
Originality/value –This paper provides a theoretical methodology to improve STD management and
implements it. Other studies have focused only on the theoretical aspect. Moreover, automated management
tools are emerging for STDs, but they lack the quality provided by the scientific approach employed herein.
Keywords Smart tourism, Smart destination, Smart business, Artificial intelligence, Data mining, Big data,
Smart tourism system, Analytical hierarchy process, Information and communication technology
Paper type Research paper
1. Introduction
According to reports from the World Travel and Tourism Council in 2020 (World Travel and
Tourism Council, 2020), the total contribution of travel and tourism to gross domestic product
(GDP) before the COVID-19 crisis in 2019 was 10.4% of GDP. If we focus on the impact of
tourism on employment, 10.3% of all jobs (direct and indirect) are derived from Travel and
Quality of the
destination
2299
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/0263-5577.htm
Received 21 October 2021
Revised 23 April 2022
19 August 2022
Accepted 21 August 2022
Industrial Management & Data
Systems
Vol. 122 No. 10, 2022
pp. 2299-2330
© Emerald Publishing Limited
0263-5577
DOI 10.1108/IMDS-10-2021-0640
Tourism. These numbers not only illustrate the enormous impact of tourism on the economy,
but also provide an insight into the extent of the environmental and sociocultural effects
produced by this multidimensional industry. Because of this, it is essential to implement
smart tourism destinations (STDs) that focus on improving the tourist experience by
identifying their characteristics, and through intelligent monitoring supported by the large
amount of data available today (Buhalis and Amaranggana, 2013).
Smart tourism destinations are the future, and once the optimal technological, social
and economic infrastructure required for smart tourism is in place, the broader tourism
industry can be further developed (Shafiee et al.,2019), especially in light of how the
COVID-19 pandemic has unleashed a series of complex challenges for tourism firms, and
exposed new perspectives in the relations between tourism and sustainable development
(Ioannides and Gyim
othy, 2020). To this end, public-private collaboration is essential to
create viable ecosystems for smart tourism, allowing for real-time measurements of user
experiences and the flexible adaptation of technology-driven business strategies (Gretzel
et al.,2015).
In this new tourism scenario, it is necessary to study and apply technological aspects. This
entails the application of artificial intelligence techniques to manage and extract information
from Big Data to add value to an STD (Vecchio et al., 2018). This means, improving the
definition of tourist profiles, their preferences, and attitudes so as to better adapt the
destination to the needs of tourists. In summary, to improve the decision-making of industry
stakeholders, and thus foster economic growth, resulting in the sustainable development of
tourism and cities together (Allam and Dhunny, 2019).
Therefore,themainobjectiveofthisworkistogenerateanddemonstratetheuseofa
methodology that, on the one hand, can be used to identify the key aspects of a municipal
tourist destination, and on the other, quantifies their quality. The result is an adapted and
improved model created by the State Mercantile Society for the Management of Innovation
and Tourism Technologies (SEGITTUR) (2022) called Smart Tourism System (STS) (2018).
A dashboard that groups the previously named characteristics can be used to better
analyze the characteristics and circumstances of a municipality to help make better
decisions.
Hence, on the one hand, we propose a theoretical framework to develop the methodology
and, on the other, we implement it in a real way in a destination with more than 70 years of
history, Puerto de la Cruz (Tenerife, Canary Islands, Spain). There are other theoretical
frameworks, but they have not been implemented as in our approach. In addition, we compare
our product with other existing STS, which are not underpinned by the same scientific study
as the tool proposed by us.
This paper is organized into the following sections (Figure 1):
(1) Literature, where we discuss the importance of implementing new technological
trends in smart destination environments in order to improve the industry. We
discuss smart tourism, big data, artificial intelligence and smart tourism system
(STS) concepts.
(2) Methodology, which provides an explanation of the conceptual framework
implemented. It is divided into the selection of key performance indicators (KPI) in
collaboration with industry experts that will determine the tourist image and
behavior of a smart city destination (STD); the definitions of the technologies needed
to automate the extraction, transformation, and loading (ETL) of data from the
existing pool of big data; and the generation of an index to measure business
confidence through multiple criteria decision-making methods (MCDM), and
specifically, the analytic hierarchy process (AHP).
IMDS
122,10
2300
(3) Case study, where we adapt the methodology implemented for a tourist destination,
Puerto de la Cruz (Tenerife, Canary Islands, Spain), for which we define the specific
variables and provide a comparison with other STS.
2. Literature review
2.1 Smart tourism
Tourism is defined as “a social, cultural and economic phenomenon which entails the
movement of people to countries or places outside their usual environment for personal or
business/professional purposes”by United Nations World Tourism Organization (UNWTO)
(2022). With this definition, it is logical to think about how the new technologies that shape
our daily lives affect and can improve the industry. According to Gretzel (2015), it is normal
for the “smart”concept to be applied to the tourism industry due to the availability of big data
on tourism and to the great dependence on the information and communication industry
(ICT). Since, as the author says, the term “smartness”is often used to describe the social,
economic and technological development driven by technologies that handle and transport
data. In relation to the author’s argument, smart tourism involves multiples components and
three layers; smart destination (or smart tourism destination), smart business (or business
intelligence) and smart experience.
The concepts of STDs and smart cities are highly correlated. Specifically, we can say that
STDs apply the principles of smart cities but also consider tourists as part of the urban
environment, the goal being to improve mobility, sustainability and, in general, the quality of
life (Gretzel et al., 2015). Consequently, according Buhalis and Amaranggana (2013,2014),to
achieve an STD, planners need to dynamically interconnect the different industry
Figure 1.
The design logic for the
system
Quality of the
destination
2301
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