Promotion of inclusive tourism by national destination management organizations

TL;DR: The authors analyzed both the explicit and implicit content in text and images in the English brochures published by nine European official destination management organizations and found that the countries' attitudes towards inclusion were aligned with what the countries’ destination management organisations were promoting.

Abstract: Inclusive tourism has the potential to counter balance some of the disadvantages relating to tourism development and effectively exert positive impacts on society at large and specifically on tourist destinations. However, there is a research gap in studies on inclusiveness related to the promotional efforts of national destination management organizations.,Data science-based methods, mainly text mining and image mining, were used to analyze both the explicit and implicit content in text and images in the English brochures published by nine European official destination management organizations.,Results highlighted that the countries' attitudes towards inclusion were aligned with what the countries’ destination management organizations were promoting, especially in the case of highly ranked countries on an inclusiveness index. However, there were differences between their explicit content (what they write in text) and their implicit content (what they show in images).,The combined analysis of text and image content allowed for a complete understanding as to how national’s destination management organizations are promoting inclusion, showing that destination management organizations should make an effort in improving their promotional material and above all the images they use.

Summary

1 Introduction

• This approach has the potential to counterweight disadvantages brought up by tourism development and effectively exerting positive impacts on society at large and specifically in tourist destinations.
• Destination marketing has been addressed by researchers from different perspectives such as collaborative marketing (Garrod & Fyall, 2017), use of technologies (Marasco et al., 2018), local cuisine (Okumus et al., 2018).
• Notwithstanding, there is a research gap in studies on inclusiveness related with the promotional efforts of DMO, notably at the national level.

2 Literature Review

• Inclusion is often used as an opposite concept to discrimination (Collins, 2003).
• Research in inclusive tourism has addressed several dimensions such as race and ethnicity, gender, sexual orientation, age, religion, income inequality, and political representation.
• Another interesting study was conducted by Krymkowski et al. (2014), who took into account that members of racial/ethnic minority groups tend to visit national parks at lower rates than whites, and recommended the design of park and outdoor recreation opportunities in articulation with the values of minority racial/ethnic groups.
• Poria (2006) investigated the experiences of gay men and lesbians in hotels who deemed as important feeling accepted and welcome when their sexual orientation is known as well as desire to be treated in the same fashion as heterosexuals.
• Findings revealed their homogeneity in push travel motivations and destination activity preferences.

3 Data and Methods

• With the goal of studying how national DMOs promoted their respective countries in terms of inclusiveness, their promotion materials were the subject of research analysis .
• Besides the requirement of having brochures written in English, the sample selection criteria took in consideration two other parameters: (1) geographic representation, and (2) each country´s positioning in the 2019 Inclusiveness Index ranking (Menendian et al., 2019).
• As tourism brochures are a distinctive advertisement medium in the tourism industry, where both textual and visual components play an essential part in conveying the sales argument (Brito and Pratas, 2015), both components were analyzed.
• 2017), Sentiment Analysis (Moro et al., 2019), Text Classification, Text Clustering, among other Text Mining techniques (Li et al., 2019; Oliveira et al., 2019), the same is not valid for Image Mining which is a novel approach.
• Effectively, the Scopus database showed that only one publication matched the query ‘“image mining” AND tourism‘, a publication from Lin et al. (2019).

3.1 Text Mining

• As shown in Table 1, 109 brochures were collected from the national DMOs’ websites, covering a wide range of destination information.
• All the brochures were presented in PDF file format.
• The process started by analyzing the textual component of the brochures, using the Python programming language with several additional libraries, namely: the Natural Language Toolkit (NLTK) (Bird et al., 2009), Beautiful soup (Richardson, 2007), PyPDF2 (Phaseit, Inc., n.d.), and other standard Python packages such as Pandas, Numpy, Matplotlib, and Seaborn.
• A preprocessing transformation was applied to each PDF: 1. Extraction of the text by page; 2. Tokenization of the text into sentences, i.e., the splitting of the text into sentences; 3. Per sentence: a.
• The text preprocessing resulted, as shown in Table 1, in the identification of a total of 625,882 words.

3.2 Image Mining

• As previously done when addressing the textual component, in the analysis of the image component of brochures the Python programming language was also used.
• These images were then classified using the “Computer vision” service from Microsoft’s Cognitive Services API (Application Programming Interface).
• When people are present in the image and faces are visible, gender and age are also estimated.
• Since computer vision algorithms have a high number of false positives, after comparing a sample of images classification results with the actual images, a decision was made to only analyze images with a confidence level of the caption being superior to 90%.

4 Results and Discussion

• In the 2019 Inclusiveness Index ranking (Menendian et al., 2019), northern European countries tended to occupy higher positions.
• This finding led us to consider the hypothesis that brochures with longer texts and a higher number of images could reflect the country’s attitude towards inclusion.
• In March, thousands of professionals and amateurs participate in an international RACE called Bieg Piastów” . “’s biggest obstacle course RACE is coming to Kalmar for the first time” Similar examples were found for the terms “alternative”, “accessible”, “visa”, “handicap”, among others.
• From the 233 images with the tag “children”, only two had a non-Caucasian child.
• Also, disabled people were only present in two images.

5 Conclusion

• This study´s findings answer positively to the initially proposed research question.
• In fact, results show that countries' attitudes towards inclusion, as revealed in the 2019 Inclusiveness ranking were aligned with what the countries’.
• DMOs were promoting, especially in the case of those highly-ranked but there was a difference between their textual (explicit content) and visual (implicit content) components, since image mining showed a different perspective from the text component of the brochures.
• Therefore, although an inspection in a random sample has not shown any missing texts, there is the possibility of that occurring.
• Of course, a human can also fail or disagree with other humans in some classifications but today the error in the classifications done by these algorithms tends to be bigger than the error achieved by humans.

Figures

Figure 1. Top 20 Frequent Unigrams

Figure 2. Top 20 Frequent Bigrams

Table 1. Summary Statistics of Collected Data

Figure 4. Average Words per Brochure vs. Average Images per Brochure

Table 3. Inclusion related Tags identified in Images per Country

Figure 3. Top 20 Frequent Nouns

Table 2. Words and Sentences Frequencies Analysis

Full text

Promotion of Inclusive Tourism by National Destination
Management Organizations
Paulo Rita
NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Portugal
(corresponding author: prita@novaims.unl.pt)
Nuno António
NOVA Information Management School (NOVA IMS), Universidade NOVA de Lisboa, Portugal
This is the author accepted manuscript version of the article published by Elsevier
as:
Rita, P., & António, N. (2020). Promotion of inclusive tourism by national
destination management organizations. Worldwide Hospitality and Tourism
Themes. [Advanced online publication on 3 december 2020].
https://doi.org/10.1108/WHATT-07-2020-0068
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International
License.

Promotion of Inclusive Touri sm by
National Destination Management Organizations
Paulo Rita - NOVA Information Management School (NOVA IMS), Universidade NOVA de
Lisboa, Portugal (corresponding author: prita@novaims.unl.pt)
Nuno António - NOVA Information Management School (NOVA IMS), Universidade NOVA de
Lisboa, Portugal
Abstract
• Purpose: Inclusive tourism has the potential to counterweight disadvantages brought up
by tourism development and effectively exerting positive impacts on society at large and
specifically in tourist destinations. However, there is a research gap in studies on
inclusiveness related to the promotional efforts of national Destination Management
Organizations.
• Design: Data Science-based methods, mainly Text Mining and Image Mining, were
employed to analyze both the explicit and implicit content in text and images in the
English brochures published by nine European official Destination Management
Organizations.
• Findings: Results highlighted that the countries' attitudes towards inclusion were aligned
with what the countries’ Destination Management Organizations were promoting,
especially in the case of highly ranked countries in inclusiveness index. However, there
were differences between their explicit content (what they write in text) and their implicit
content (what they show in images).
• Originality: The combined analysis of text and image content allowed for a complete
understanding on how national’s Destination Management Organizations are promoting
inclusion, showing that Destination Management Organizations should make an effort in
improving their promotional material, above all in the images.
Keywords: Inclusive Tourism; Destination Management Organizations; Marketing; Promotion;
Data Science; Text Mining; Image Mining.

1 Introduction
For the last few decades tourism has grown significantly across the world showing rates
outpacing the economy; for example, 2019 brought another year of strong growth in international
arrivals (+4% to reach 1.5 billion), although slower when compared to the achieved rates of 2017
and 2018 (+6% in each year) (WNTO, 2020). However, tourism influence has not been only
positive on economic and social dimensions; indeed, this sector has also been the subject of
criticism for causing negative impacts on the environment and contributing to both and economic
and social inequality (e.g., Garau-Vadell et al., 2018; Muler Gonzalez et al., 2018).
Following the Sustainable Development Goals (SDG) set by the United Nations Development
Program (UNDP, 2015), inclusive tourism has been recently defined as “transformative tourism
in which marginalized groups are engaged in ethical production or consumption of tourism and
the sharing of its benefits” (Scheyvens & Biddulph, 2018). This approach has the potential to
counterweight disadvantages brought up by tourism development and effectively exerting
positive impacts on society at large and specifically in tourist destinations.
In travel, destinations are represented by Destination Management Organizations (DMOs) which
have the responsibility to be engaged in the development of their respective long-term tourism
marketing strategy. These are generally non-for-profit organizations in charge of promoting
destination attractions, accommodation, restaurants, events, transportation, tourism services to
generating markets. Destination marketing has been addressed by researchers from different
perspectives such as collaborative marketing (Garrod & Fyall, 2017), use of technologies
(Marasco et al., 2018), local cuisine (Okumus et al., 2018). Notwithstanding, there is a research
gap in studies on inclusiveness related with the promotional efforts of DMO, notably at the
national level. Thus, the following research question was formulated to guide the current study:
RQ: Does the promotion material from the National Destination Management
Organizations reflect the country’s level of inclusion?
This paper continues with the review of the relevant scientific literature, providing information
on the data and methods used, namely emphasizing both text and image mining, reporting on the

achieved results as well as bringing them to discussion vis-à-vis other studies, and concluding
with main research contributions, managerial implications, study limitations and
recommendations for future research.
2 Literature Review
Inclusion is often used as an opposite concept to discrimination (Collins, 2003). Whereas
inclusion gives everyone the opportunity to be full members of society, discrimination is based
on unfair judgement and treatment of minorities, excluding people from social and economic
activities due to some defining features like ethnicity, religion or gender. Hence, fighting for
inclusion is the way to undermine the chances for discrimination to occur since it pulls
everybody together in respecting values, beliefs and preferences of others.
Bakker (2019) developed a conceptual framework for identifying and prioritizing the constraints
to tourism-driven inclusive growth by means of linking the discussion on inclusive growth to the
specific features of the tourism industry. This study identified three elements contributing to the
tourism sector’s capability to contribute to an inclusive growth strategy: growth of tourism
opportunities; equal access to tourism opportunities; and equal outcome of tourism opportunities.
Fostering inclusive tourism enables to bring into this sector those who are more frequently
marginalized or sometimes even excluded from tourism. The implementation of this perspective
drives direct benefits to those involved (Biddulph & Scheyvens, 2018). Research in inclusive
tourism has addressed several dimensions such as race and ethnicity, gender, sexual orientation,
age, religion, income inequality, and political representation.
Previous tourism studies identified differences in race as one of the leading explanations for
inequality of access to tourism opportunities (Scheyvens, 2002). Many aspects of tourism are
permeated by ethnicity which in many cases is involved with a complex interrelation with the
social structure. Not only tourist destinations have been using strategies to cope with
stereotyping, but tourism has also contributed to identity formation in countries, and majority
populations have been encouraged to re-evaluate their perceptions about minorities (Hitchcock,

1999).
Moreover, tourism influences the re-interpretation of identity among members of local
communities who depend on or are affected by this sector and its many businesses. According to
Jamison (1999), tourism development mitigated the inter-ethnic relationships within a
community in Kenya. Another interesting study was conducted by Krymkowski et al. (2014),
who took into account that members of racial/ethnic minority groups tend to visit national parks
at lower rates than whites, and recommended the design of park and outdoor recreation
opportunities in articulation with the values of minority racial/ethnic groups.
A bibliometric analysis of 466 journal papers published during 1985–2012 on tourism gender
research was presented by Figueroa-Domecq et al. (2015) in a thorough critical analysis of this
sub-field of tourism. After categorizing prevailing themes and methodologies as well as
identifying the most productive researchers and popular scientific journal, these authors
concluded that tourism gender research remains marginal to tourism enquiry, lacking the critical
mass of research leaders, publications, citations and multi-institutional networks characterizing
other tourism sub-fields. An interesting study was developed by Duffy et al. (2015) who
explored the ways in which employing women in the tourism sector challenged or reinforced the
traditional gender ideology in the Dominican Republic. Results showed that tourism employment
constituted an opportunity source for women to gain both economic and social independence and
generated tension between women and men in the negotiation of new gender roles and identities.
Within the tourism context, sexual orientation has also been the subject of research. For instance,
Poria (2006) investigated the experiences of gay men and lesbians in hotels who deemed as
important feeling accepted and welcome when their sexual orientation is known as well as desire
to be treated in the same fashion as heterosexuals. Hotel staff behavior, hotel attributes, and its
environment were considered critical elements of hotel experience. Hughes & Deutsch (2010)
examined holidays of older gay men finding holiday requirements as similar to those of other
older people but with the extra dimension of gay-friendliness as well as identifying opportunities
for tour operators and destinations to develop products positioned more adequately for this
market segment.
Tourism with the purpose of leisure and visiting friends and relatives was found to be related

Frequently asked questions

Q1. What contributions have the authors mentioned in the paper "Promotion of inclusive tourism by national destination management organizations" ?

In this paper, text mining and image mining techniques were employed to analyze both the explicit and implicit content in text and images in the English brochures published by nine European official destination management organizations. 

Q2. What are the future works in "Promotion of inclusive tourism by national destination management organizations" ?

Therefore, although an inspection in a random sample has not shown any missing texts, there is the possibility of that occurring. 

Q3. What is the impact of tourism on income inequality in developing economies?

The long-run elasticities on squared tourism revenue confirmed that if the current level of tourism becomes double then it will significantly reduce the income inequality in developing economies. 

Q4. What is the definition of the term “computer vision”?

For each image processed, the “Computer vision” service returns a JSON object with, among other data: image metadata (e.g., height and width), list of objects with an associated confidence level inpercentage, a list of tags (based on the objects present in the image), a caption (constructed based on the tags found in the image), and a confidence level of the caption. 

Q5. What did Fleischer & Pizam (2002) find in their research?

Fleischer & Pizam (2002) surveyed senior citizens in Israel to identify factors that influence their decision to take holidays for differing time lengths and found that their tourism motivation was a function of income and health, but their trip duration changed with age. 

Q6. What is the role of tourism in reducing income inequality in China?

The important role to be played by tourism development also in reducing regional income inequality was studied by Li et al. (2016) with empirical findings indicating that tourism development contributed significantly to the reduction of regional inequality in China, with domestic tourism making a greater contribution when compared to international tourism. 

Q7. What countries used images with people from different races to attract foreign students?

The Czech Republic had a photo of a wedding with an Asian couple (man and woman) which seems to be related to attract Asians for wedding tourism, and Spain that used photos with people from different races to attract foreign Spanish students and meeting/conference events. 

Q8. What was the first step in the analysis of the brochures?

With the help of the Python package Fitz (Kastman, n.d.), PNG image files were extracted from all images included in the brochures. 

Q9. What are the main factors that influence the motivation of older people to travel?

Hughes & Deutsch (2010) examined holidays of older gay men finding holiday requirements as similar to those of other older people but with the extra dimension of gay-friendliness as well as identifying opportunities for tour operators and destinations to develop products positioned more adequately for this market segment. 

Q10. What are the main limitations of text mining and image mining?

Text Mining and Image Mining are highly effective methods in the analysis of large volumes of textual and image data, but both have limitations related to the probabilistic nature of some of the Artificial Intelligence algorithms. 

Q11. What was the common term used in the search list?

the reading of these sentences revealed, as expected, that the use of the search terms was, in most cases, not related to inclusion, nor even diversity.