Electronic Word of Mouth(E-WOM) has become a significant factor that that affect tourists’ decision making process in the selection and narrowing down of travel destination choices. With the development of Information Technology infrastructure in Sri Lanka, there is an increasing trend for the adoption of E-WOM among local tourists. Therefore, objective of this research is to identify the effect of E-WOM on local tourists’ travel decisions.
THE IMPACT OF ELECTRONIC WORD OF MOUTH ON TOURISTS’ INTENTION OF DESTINATION SELECTION: A CASE IN SRI LANKAN LOCAL TOURISTS
1. Final Year Defense
2020
Research Project in Information Systems
The Impact of E-WOM (Electronic
Word of Mouth) on Tourists’ Behavioral
Intention to Destination Selection: A
Case in Sri Lankan Local Tourists
R. G. P
. L. M. Weerasinghe
rgplmweerasinghe@std.appsc.sab.ac.lk
3. Introduction
• This study planned to investigate and identify the most affecting E-WOM
factors for select a travel destination through the internet.
• The outcome of this study will contribute for current and future technology-
based developments related to tourism industry in Sri Lanka, in such a way
that can impact positively to the tourists when they select a travel destination.
2
4. Introduction Cont.
Significance
• Tourism industry also has been shaped up by with the growth on internet,
online communities and social media. As a result, Electronic Word of Mouth
(E-WOM) has emerged [1][2].
• Without being familiar with a city, it is not easy to make decisions [3].
Motivation
• Nowadays there is a trend, that more and more Sri Lankan local tourists prefer
to spend their free time for traveling.
• The Internet has a major impact on tourism for tourists [4].
3
5. Introduction Cont.
Research Objectives
• Identifying the main mediums of E-WOM.
• Identifying the most significant factors towards the tourists’ behavioral intention for
selection of travel destinations in tourism industry.
• Finding impact of each of factors identified on the selection of a travel destination.
• Proving recommendations to maintain and manage positive E-WOM within the tourism
sector.
4
6. Introduction Cont.
Research Questions
RQ1: What are the E-WOM mediums that are used to select a destination?
RQ2: What are the E-WOM significant factors that impact on tourists’ behavioral intention
for selection of travel destinations in tourism industry?
RQ3: How does the identified factors impact on selection of travel destinations in tourism
industry?
RQ4: What are the guidelines and recommendations for managing the positive E-WOM in
tourism and technology-based developments?
5
7. Introduction Cont.
Literature Review
6
Searchers’ Intent
Trustworthiness of
Message
Content Creator’s
Expertise
Source Similarity
Effects of E-WOM
Tourists’ Behavioral
Intention to
Destination Selection
Conceptual Framework
9. Methodology Cont.
Proposed Research Model
8
Searchers’ Intent
Trustworthiness of
Message
Content Creator’s
Expertise
Source Similarity
Tourists’ Behavioral
Intention to Destination
Selection
10. Observations and Results
Demographic Analysis
9
Demographic Variables Frequency Percent
Gender Male 146 73.0
Female 54 27.0
Age 20 - 30 165 82.5
31 - 40 27 27.0
41 - 50 8 4.0
Level of Education Certification 29 14.5
Diploma 58 29.0
Graduate 80 40.0
Post Graduate or above 10 5.0
Work Status Employed 89 44.5
Self-employed 29 14.5
Unemployed 2 1.0
Studying 77 38.5
Hours on Internet Less than 2 hours 28 14.0
2 - 5 hours 87 43.5
5 - 8 hours 29 14.5
More than 8 hours 46 23.0
Not regularly 10 5.0
11. Observations and Results Cont.
Reliability Analysis
10
Variable No of Items Mean Standard
Deviation
Cronbach’s
Alpha Value
Reliability
Independent Variables
SI 4 4.3 0.55 0.737 High
TM 5 3.9 0.61 0.810 Very High
CCE 4 3.7 0.72 0.757 High
SS 4 3.5 0.78 0.814 Very High
Dependent Variables
TDS 3 4.1 0.59 0.717 High
• All variables are in acceptable range for Cronbach’s Alpha Coefficient in range of 0.71 to 0.81.
12. Observations and Results Cont.
Validity Analysis
11
Kaiser-Meyer-Olkin Measure of Sampling Adequacy 0.738
Bartlett's Test of Sphericity Approx. Chi-Square 161.558
df 10
Sig. 0.000
• Analysis produced 0.74 for the KMO value, and BTS alongside ensures the
soundness of the strength of association.
13. Observations and Results Cont.
Pearson’s Correlation Analysis
12
Variable SI TM CCE SS TDS
SI 1
TM .296** 1
CCE .180* .330** 1
SS .223** .201** .345** 1
TDS .415** .432** .424** .303** 1
**. Correlation is significant at the 0.01 level (2-tailed).
* Correlation is significant at the 0.05 level (2-tailed).
• Relationships between all the dependent and independant variables are shown as significant and
positive.
14. Observations and Results Cont.
Structural model Analysis
Model Summary
Coefficients of Model Variables
13
Model R R Square Adjusted R
Square
Std. Error of the
Estimate
1 0.592𝑐 .351 .341 1.432
a. Predictors:(Constant), TM, SI, CCE
Model Unstandardized Coefficients Standardized
Coefficients
t Sig.
B Std. Error Beta
(Constant) 2.656 0.960 2.768 .006
SI .230 .048 .288 4.755 .000
TM .145 .036 .251 3.986 .000
CCE .178 .038 .289 4.725 .000
a. Dependent Variable: TDS
15. Observations and Results Cont.
RQ1: What are the E-WOM mediums that are used to select a destination?
14
16. Observations and Results Cont.
RQ2: What are the E-WOM significant factors that impact on tourists’ behavioral
intention for selection of travel destinations in tourism industry?
15
Searchers’ Intent
Trustworthiness of
Message
Content Creator’s
Expertise
Tourists’ Behavioral
Intention to
Destination Selection
Refined Research Model
17. Observations and Results Cont.
RQ3: How does the identified factors impact on selection of travel destinations
in tourism industry?
Searchers’ Intent
• Regularly consumers are more likely to follow and read about travelling
through travelling websites, videos, review, travelling blogs and travel related
groups and things in social media.
• Consumers have intended to use those mediums of internet before they travel
a particular destination.
• Therefore, every IT based developments which are related to tourism should
be developed to gain the user attraction.
16
18. Observations and Results Cont.
Trustworthiness of Message
• Consumers always tend to get know about experiences of other travelers
about a particular travel destination where they planned to travel.
• Travellers do not depend just on the content of a website. They read those
customer testimonials in a website, blog or in social media before travelling.
17
19. Observations and Results Cont.
Content Creator’s Expertise
• Content creator’s expertise have a more power to influence travellers decisions.
• Research study’s results show there is a trend among travelers to believe
contents which more liked and agreed by lot of other travelers.
• Travellers have more confident about contents if content have updated
constantly.
18
20. Observations and Results Cont.
RQ4: What are the guidelines and recommendations for managing the
positive E-WOM in tourism and technology-based developments?
• Online brand reputation
• Handling online complaints
• Do more investment on E-WOM
• Consumers believe user generated content
19
21. Future Works
• Evaluate mobile application impact
• Examine for foreign tourists
• Specialized the medium
• Examine impact of demographic factors
20
22. References
[1] K. Ishida, L. Slevitch, and K. Siamionava, “The Effects of Traditional and Electronic
Word-of-Mouth on Destination Image: A Case of Vacation Tourists Visiting Branson,
Missouri,” Adm. Sci., vol. 6, no. 4, p. 12, 2016, doi: 10.3390/admsci6040012.
[2] A. M. Abubakar, M. Ilkan, R. Meshall Al-Tal, and K. K. Eluwole, “eWOM, revisit
intention, destination trust and gender,” J. Hosp. Tour. Manag., vol. 31, pp. 220–227, 2017,
doi: 10.1016/j.jhtm.2016.12.005.
[3] M. R. Jalilvand, A. Ebrahimi, and N. Samiei, “Electronic Word of Mouth Effects on
Tourists’ Attitudes Toward Islamic Destinations and Travel Intention: An Empirical Study in
Iran,” Procedia - Soc. Behav. Sci., vol. 81, no. 2006, pp. 484–489, 2013, doi:
10.1016/j.sbspro.2013.06.465.
[4] M. Reza Jalilvand, N. Samiei, B. Dini, and P. Yaghoubi Manzari, “Examining the
structural relationships of electronic word of mouth, destination image, tourist attitude
toward destination and travel intention: An integrated approach,” J. Destin. Mark. Manag.,
vol. 1, no. 1–2, pp. 134–143, 2012, doi: 10.1016/j.jdmm.2012.10.001.
22