How Russian Travellers Use Social Media and Other Internet Resources to Make Hotel-Choice Decisions
Transcript of How Russian Travellers Use Social Media and Other Internet Resources to Make Hotel-Choice Decisions
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How Russian Travellers Use Social Media and Other Internet Resources to Make Hotel-Choice Decisions !!
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Dr. Sergey P. Kazakov
Associate Professor
Chair of Enterprise Marketing
Faculty of Management
National Research University – Higher School of Economics
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Moscow
Russian Federation
July 2014
Abstract
The term ‘Social media’ describes web-based and mobile technologies that are
used to turn electronic communication into an interactive dialogue and let users to
exchange user-created content. Social media resources are widely used by travelers as
channels for destinations’ and hotels’ information. Russian tourists are not an exception
to this respect. In this study, the impact of social media on customer choice and booking
decisions in hospitality industry is examined based on the case of the Russian Federation.
The research is aimed at identification of the specifics of the Russian consumers
perception towards the use of social media in comparison with other Internet resources
and traditional off-line sources for decision making for planning their travel. The results
of the study may be utilized by hotel management to rethink and renovate their on-line
strategies targeted at their respective customer audiences.
Keywords
Hospitality and Tourism, hotel management, social media, consumer behavior,
Information and Communication technologies, Russia.
!Introduction
The development of information and communications technologies (ICT) have
had a tremendous impact on the hospitality and tourism industry in recent years. Such
recognizable technology and innovation transfer activity has made this research issue an
appeal for many scholars worldwide. We can witness an emerge of a wide range of
publications dedicated to a transformation of hospitality and tourism industry under the
influence of Information and Communication Technologies or simply ICT (Law &
Jogaratnam (2005), Cho & Olsen (1998), Frew (2000a), Frew (2000b), Ho & Lee (2007),
Buhalis (2003), Buhalis and Lob (2008), Fotis, Buhalis and Rossides (2011)).
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In the second decade of the XXI century ICT continues to drive a momentum on
changes in service products development, processes, structure of an industry, basic nature
of the competition in hospitality as well as interaction process between hotels, travel
agents, airlines and customers (Buhalis, 2003). As D.Buhalis pointed out «The Internet is
one of the most influential technologies that have changed travellers’ behavior» (Buhalis,
2008). The new term, eTourism, which explains the synthesis of ICT and Tourism became
apparent (Buhalis, 2008). However, as ICT and Social Media is a still a newly emerged
phenomena on the global scale. This area of research may require further development
and mastering although recently more papers tend to appear in specialized journals.
Another distinctive peculiarity relevant for Social Media lays in its unique ability to amend
constantly in adjusting itself to new realities, technologies and challenges faced by the
society in common and by consumers and businesses in particular. Hence, such process of
the constant changes in ICT and Social Media requires more attention to be received from
scholars as this evolution needs to be recorded and analyzed to reveal the implications and
supply industry insiders with an up-to-date information for managerial decisions in their
activities. We contribute this study to a stream of publications array to build a knowledge
base for industry congregation and community for such decisions with an emphasis on
studying one particular case of one of the world’s top growing traveling nations - the
Russians.
Background of the study
As a result of the 20-year changes in the country, the Russian hospitality and
tourism industry has undergone dramatic evolution recently. By the beginning of XXI
century the market-oriented model of Russian hospitality and tourism industry had been
formed. Since that time domestic and outbound tourism both have demonstrated the
tendency for a sharp upsurge. The total number of leisure trips traveling abroad out of the
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CIS countries has increased from 4 252 to 12 231 thousand between 2000 and 2010 while
the number of business trips abroad has grown from 11 611 thousand in 2000 to 37 750
thousand in 2013 (GosComStat of Russia, 2014). The number of hotels and similar
accommodation establishments like resorts, B&B and other lodging facilities have
increased in domestic market from 4 182 to 7 410 thousand. The number of travel
agencies operating in Russia has multiplied by 2,3 times in a time period between 2000
and 2009 and accounted 6 897 units in 2009 (GosComStat of Russia, 2010). A wide range
of macroeconomic and microeconomic factors currently influence the development of the
Russian hospitality and tourism industry.
The rapid development and spread of new technologies spear headed by ICT is
one of the main factors significantly contributing to the intensity and increase of business
or leisure domestic and international number of trips completed by Russian citizens. The
number of Internet users in Russia currently overtops 40% of the national population. It is
the matter of fact that the ICT transforms tourism and hospitality industry business
models as well as it stimulates changes in customers’ decision making and their entire
behavior. While a considerable share of business and leisure travelers choose
accommodation and make payment via on-line travel booking systems, obtain information
with a help of travel sites containing hotel reviews and other social media, the traditional
off-line travel agencies are supposed to shift to on-line services selling travel package tours
to chase the mass market tourists or to dig into a niche and to serve VIP sector on so called
concierge type of service, as VIPs commonly are known not to be technologically savvy .
Social media and other internet resources are widely used by travelers as
channels and sources for information on hotels and destinations. The Social Media that
are relevant to hospitality and tourism industry in Russian Federation include common
and special niche electronic media and may be distinguished in three types: public user
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generated and public user supported, business generated and public user supported and
public user generated and business supported (Balaeva, Kazakov, Predvoditeleva, 2012).
In this country, the following global meta-search and on-line booking agencies
are operated in Russian language and are widely known and used: www.Tripadvisor.com,
www.Booking.com, and www.Virtualtourist.com. Indeed, there are several Russian decent
web-sites dedicated to travel and hotel reviews such as www.travel.ru, wwww.otdih.ru,
www.otziv.ru and many others. Some local businesses created the localized web resources,
for instance, www.hotels.ru and www.ostrovok.ru that are quite similar to top global meta-
search and online booking sites and mirror their technologies and business profile. The
top social media networks in this country are Vkontakte (www.vkontakte.ru),
Odnoklassniki (www.odnoklassniki.ru), and Facebook (www.facebook.ru). Vkontakte, or
‘In Touch’ is the biggest Russian social network and is reminiscent in its interface and
functions to Facebook. Since its launch in 2007 the number of Vkontakte user base has
reached 52 million in 2014 and accounts 26 million user connections daily. Odnoklassniki
is another big social media network which is similar to the one in US known as
www.classmates.com. It is organized according to users’ particular school/college/
university background and aimed to classmates and green years friends search. It was
found in 2006 and accounts about for 42 million users now, nearly 10 million of them log
in into their personal pages every day. Facebook have emerged in the Russian internet
zone 5 years ago and currently enjoys a position of #3 among the Russian top social media
sites. It is the ‘junior’ but rapidly growing Social Media network here with 25 million users
registered in Russia as of July of 2014. Twitter accounts currently 12 million users in this
country and is not that big as in the USA.
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Methodology of the research
Based on the relevancy of the research area which is dedicated to the impact of
social media and other internet resources on customer decisions for booking a hotel or
travel package purchase that are likely for Russian tourists and best describe their on-line
consumer behavior, we formulate the key research objective as ‘to reveal the specifics of
internet resources and Social Media utilization in hotel choice and booking decisions that
are distinctive to Russian consumers’. Such objective provided a basis to elaborate the
following set of hypothesis:
H1: Social Media and other internet resources have an impact on consumer
behavior and influence the choice for a purchase of services provided by businesses in
hospitality and tourism;
H2: Customers make their hotel-choice decisions based on recommendations by
their friends colleagues and by availability of negative or/and positive feedback reviews left
by previous guests of the same hotel;
H3: There are vivid differences in the decision making process between business
travelers and leisure tourists;
H4: Russian consumers actively and vastly use the Internet resources for their
travel planning;
H5: There are no tangible gender differences in a consumer behavior and in a
way where men and women utilize Social Media and Internet resources for planning the
trip.
We used an updated and localized questionnaire of the similar study that was
conducted in 2010 by the Center of Hospitality Research at Cornell University and kindly
contributed to our research project by our colleagues from this institution (McCarthy,
Stock, Verma, 2010).
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In order to test the above list of assumptions we have arranged for the online
survey using the OMI panel in 15 cities of Russian Federation that account one million
residents or more. OMI, or Online Marketing Intelligence is a company originated in the
USA and facilitates on-line consumer panels in many countries where Russian Federation
is not an exception. Customer experience in hospitality tourism services purchased and
consumed over the last year served as a key selection criterion for the sample recruitment.
As a result, n=536 surveyed in April of 2014. The analysis of modes demonstrated the
most frequent descriptives for Russian tourists that include Muscovites, 29 years old
males, who have bachelor education in live in a family of 3 people and their household
income is considered as Russian average or approximately €1 200 per month. We used a
Crombach alpha to test the data reliability and α=0.892 which shows a good fit of the
collected data.
Results
The influence of Social Media and internet resources on consumer
behavior in hotel choice or travel package purchase decision making
We used the analysis of means related to the hotel choice factors that are
considered by the tourists in Russia during the buying decision making process in the
hospitality industry. The analysis of means allowed to distinguish 4 factor groups that can
be tied one to another and ranked according to their importance for the consumers (Table
1).
Table 1. Hotel choice importance factors clumping
Factor Groups according to Likert’s scale of the least important (1) to the most important (5)
Mode Mean
1. Least important factors (mode=1, mean=1~2.5)
1.1. Preferred hotel brand 1 2.24
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The factors 3.5, 3.6, 3.7 that have a direct relationship with internet resources
and Social Media on-line networking bear the level of mid-to-high importance for the
consumers. Yet it should be revealed here that, according to the study, the top five
decision support sources for the consumer to select a right hotel included hotel reviews
1.2. Loyalty programs offered by a hotel 1 2.4
2. Medium important factors (mode≈2~3, mean=2.5~3.5)
2.1. Travel agent recommendations 3 2.94
2.2. Information on promotions offered by a hotel 3 3.01
2.3. Recreation (fitness, park, spa) facilities near the hotel 3 3.16
2.4. Attractions and landmarks near the hotel 3 3.47
2.5. Shopping area near the hotel 3 3.1
2.6. Entertainment facilities near the hotel 3 3.16
3. Important factors (mode≈4, mean=3~4)
3.1. Hotel category or ‘star’ rating 4 3.52
3.2. Own previous travel experience 4 3.42
3.3. Recommendations by friends and relatives 4 3.41
3.4. Recommendations by colleagues 4 3.16
3.5. On-line hotel reviews and feedback 4 3.63
3.6. Hotel video and photo materials exposed in internet 4 3.64
3.7. Hotel interior and design 4 3.62
4. The most important factors (mode≈5, mean=4~5)
4.1. Location 5 4.21
4.2. Room rate 5 4.15
4.3. Perceived value for money 5 4.36
4.4. Hotel reputation and general impression 5 3.84
Factor Groups according to Likert’s scale of the least important (1) to the most important (5)
Mode Mean
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Fig.1. Logistic behavioral model of the consumer in a process for
the hotel information evaluation and buying decision
!and consumer general feedback sites e.g. otziv.ru (47%), on-line booking agencies e.g.
booking.com and tripadvisor.com (39%), phone call to the travel agent (28%), hotel brand
web sites (26%) and direct phone call to the hotel (16%).
Such result demonstrates the high share of internet resources and Social Media
sites in the sources for hotel booking decision making. The ratio between on-line and off-
line or traditional resources that support hotel purchase decision making is 73%/27$. On-
line hotel booking within the last year was highlighted by 51% of the surveyed sample
participants. Hence, internet and social media produce some tangible influence on
consumer buying behavior in hospitality industry and tourism. Using the data for H1
testing also encouraged us to build a logistic consumer behavioral model which visualizes a
process of hotel information search and evaluation, further buying decision and also the
final actual spot where hotel booking is made (Fig.1).
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Information request
Off-line resoures
On-line resources
Information evaluation Final decision
Off-line resources
On-line resources
Booking and purchase
Offline
On-line
84%
16%
73%
27%
51%
49%
k=0.85 k=0.67
Search engines (google) = 83%On-line booking (booking.com etc.) = 32%Hotel sites = 38%Facebook = 7%Twitter = 3%Blogs = 8%Youtube = 11%On-line feedback sites (otziv.ru) = 10%Odnoklassniki = 8%Vkontakte = 24%Other SM= 2,6%
Call to the agency = 33%Call to the hotel = 14%
On-line booking (booking.com etc.) = 39%Meta-search engines (kayak.com etc.) = 7%Hotel site = 26%On-line feedback sites (otziv.ru) = 47%Mobile App = 4%
Call to the agency = 28%Call to the hotel = 16%
The model demonstrates some decline in internet resources and Social Media
usage across the stages of the buying process unfold as conversion rates are 0.85 and 0.67
with a general conversion rate of 0.6 throughout the entire consumer activity. However,
on-line booking as a logical process end has a bit more than equal share (51%) in
comparison with traditional off-line points of hospitality services sale (49%).
Influence of negative or/and positive off-line recommendations and
on-line feedback and reviews left by previous guests on consumer intent to
book a particular hotel
Initially we had assumed that WOM recommendations usually given by a
traditional social networking environment e.g. relatives, friends and colleagues and on-line
hotel reviews, comments or rankings found in Social Media sites have strong and solid
impact on consumer decision if given both together or separately. That meant that, if
consumer sees any negative hotel review, he to she immediately drops the idea of
considering this particular hotel further and go somewhere else in a search for a better and
more positive solution. The results of the study however showed a different picture (Table
2).
Table 2. Positive and negative Social Media on-line feedback impact
on hotel booking decision
The influence of off-line recommendations was tested with the assistance of hotel
choice importance factors (Table 1) and also provided the medium values of ‘Friend
Likert's Scale: 1(very unlikely)~5(very likely) Mode Median Mean
Q: If you see positive comments about a hotel on social media sites how likely are you to book this hotel?
4 4 3.72
Q: If you see negative comments about a hotel on social media sites how likely are you to book this hotel?
2 2 2.37
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recommendation’= 3.41, ‘Colleague recommendation’=3.16 and ‘Travel agent
recommendation’ = 2.41. In the data analysis, there was an attempt to find a covariance
between off-line and on-line hotel feedback but Pearson’s test revealed a small level of
dependency in all cases whereas the factor value did not exceed 0.156 (p=0.000-0.005 in
all cases). ANOVA test also proved no relationships between off-line and on-line hotel
recommendations and reviews so far. Hence, traditional or off-line recommendations and
modern type of consumer feedback which spreads via internet both can shape the
customer choice as they influence on this behavior although the level of such influence
tend to be quite medium.
Decision making patterns for business and leisure tourists
According to Levene’s t-test business and leisure tourists have much in common
when it comes to the search for the relevant information and making their final decision to
book a selected hotel. Still there are some differences there though in hotel choice factors
of importance for these two consumer groups as room rate (p=0.002), perceived value for
money (0.000) and off-line hotel recommendations difference (p=0.003). Type of travel,
business or leisure, also affects the specific internet resources or sites where tourists insert
the initial query for the information and make their final stop for hotel booking. Leisure
tourists are inclined to consider hotel reviews and feedback sites accompanied by Social
Media for the initial information search as more important than other internet venues
(p=0.000). Business tourists more likely will browse through on-line meta-search or
agencies (p=0.000), use mobile app like Kayak or TripIt (p=0.000); or would rather call
the hotel directly when planing their trip (p=0.000). On-line hotel reviews and feedback
provide the same level of influence on both leisure and business tourists in their final
decision as Levene’s test for this group of variables uncovered p>0.05, and Pearson’s χ2>0
whilst p>0.05 also that demonstrates no multi collinearity between analyzed variables.
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Overall, leisure and business tourists show the similar consumer behavior patterns with
some vivid specific signs of ambiguity as described above.
The level of internet usage by tourists in Russia for travel planning
Russian tourists actively use internet in their travel planning as 51% of surveyed
sample indicated reference to internet resources at various stages of the hotel and package
buying process. With respect to computing and communications devices, Russians mostly
use notebook computers (42,7%), tablet computers e.g. Apple iPad or Samsung Galaxy
(29%), desk top computer (21%) or smartphones (7%). Mobile devices including tablet
computers and smartphones together account 36% share in devices used by consumers for
hotel search and booking. This fact may be good reason to give momentum for further
mobile applications development, their active promotion and vast distribution. The
Technology Readiness Level Index (TRLI)(Bennett and Maton, 2010) mean for Russian
hospitality industry and tourism consumers was calculated as good as 3.4 out of 5 as a
maximum TRLI possible value. Almost everyone, or 99.3% of surveyed sample
participants use the computer and internet at least once in an every day routine.
As standard question set that is used to identify the TRLI value has a capability to
provide scale variables and there is a possibility to split all the sample into homogeneous
groups that can be clumped due to similarity in their responses. The factor analysis
discovered three distinctive groups of hospitality industry and tourism consumers with
respect to their internet usage level and attitude towards the latest advances in technology.
The first group may be named as ‘Advanced and confident users’ and accounts 25% of the
dispersion. ‘Mistrustful users’ (18%) who also utilize internet resources very heavily for
the life needs but prefer to refrain from the on-line transactions in a belief that this activity
is not secure. ‘Non experienced and non accepting users’ (12%) badly tend to accept new
technologies and rather prefer to use the traditional off-line methods, especially travel
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agents, for information search and evaluation. The remaining 44% of the dispersion
accounts 7 other groups that have a big scale of ambiguity in factor values and thus can be
interpreted.
Gender differences in on-line consumer behavior for hotel choice and
booking
In majority of the cases men and women demonstrate different behavioral
patterns in a decision making and hotel booking as well as in a ways of information search
and evaluation. We again have exploited the Levene’s t-test for most of the consequent
variables to test the commons and differences between two genders. First the gender pair
was tested for the hotel choice importance factors to determine the differences (Table 3).
Table 3. Levene’s t-test results for gender similarities and differences
in hotel choice importance factors
Hotel choice factors of importance Similarity/ Difference
Which gender more
important to
p value
Location difference female 0.008
Hotel category and ‘star’ rating similarity - 0.658
Preferred hotel brand difference male 0.008
Hotel customer loyalty programme participation difference male 0.027
Room rate difference female 0.032
Value for money perception difference female 0.004
Hotel reputation and general impression difference female 0.000
Previous experience similarity - 0.062
Hotel recommendations by friends difference female 0.023
Hotel recommendations by colleagues similarity - 0.815
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Hotel reviews and other forms of on-line feedback produce the same level of
influence on both men and women. Both genders yet equally consider hotel ‘star’ rating,
own previous experience, colleagues’ recommendations, hotel promotions and some
facilities availability as hotel choice importance factors for themselves. Other factors
demonstrate differences in a way men and women evaluate the hotels and tour packages.
There’s no tangible differences in the impact of the on-line positive or negative
hotel reviews and rankings on men and women when they make their decision for the hotel
booking. Yet both gender representatives are equally inclined to leave their own hotel
reviews after experiencing hotel services and upon return back home from the travel
(Table 4).
Hotel recommendations by travel agent difference female 0.029
On-line hotel reviews or other forms of feedback similarity - 0.093
Promotions announced by the hotel similarity - 0.694
Video and photo materials demonstrating hotel facilities on-line difference female 0.004
Hotel interiors (lobby, room, sea view, restaurant and hotel territory) difference female 0.039
Recreation and sports facilities in the hotel (SPA, swimming pool, tennis court etc.) similarity - 0.481
Tourists attractions near the hotel difference female 0.000
Shopping ares near the hotel difference female 0.000
Entertainment and dining facilities near the hotel similarity - 0.271
Hotel choice factors of importance Similarity/ Difference
Which gender more
important to
p value
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Table 4. Levene’s t-test results for gender similarities and differences
in positive or negative hotel feedback impact on consumer behavior and
readiness to leave the hotel review on-line after return from the travel
The analysis of frequencies allowed to determine which internet resources and
Social media sites are preferred by men and women at the early stages of the travel
planning and used as initial information search sources (Table 5).
Table 5. Frequency analysis results demonstrating the gender
preferences in internet resources and Social Media sites used at the early
travel planning stages for information search
Questions for variables determination Similarity/Difference
Which gender more
important to
p value
Q:If you see the positive hotel review on-line how likely you will book this particular hotel? difference female 0.000
Q:If you see the negative hotel review on-line how likely you will book this particular hotel? similarity - 0.3
Q:How likely you will leave an on-line review if you receive a positive hotel stay experience? similarity - 0.744
Q:How likely you will leave an on-line review if you receive a negative hotel stay experience? similarity - 0.345
Internet resources and Social Media sites Preferred by a gender of
General search engines (e.g. Google, Yahoo, Yandex) both gendersMeta-search engines and on-line travel agencies (e.g. Kayak, Expedia, Ostrovok) male
Hotel brand web-site ( e.g. marriott.com) femaleFacebook maleTwitter maleBlogs femaleYoutube maleTripadvisor female
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Following the information in Table 5, most internet web sites and Social Media
on-line networks may be distinguished as ‘male’ or ‘female’ resources as both genders have
a different preferences when applying for the information at the initial stages of their travel
planning. These gender differences remain when it comes to a final stop of the entire
buying process and where consumers make their final hotel choice decision and proceed to
booking. The internet resources and traditional off-line points of hotel accommodation
sales according gender preferences is shown in a Table 6.
Table 6. Frequency analysis results demonstrating the gender
preferences in internet resources and off-line purchase options used at the
later stages of consumer decision making process for a hotel booking
Odnoklassniki maleVkontakte maleOther Social Media sites both gendersCalling the travel agent femaleDirect calling the hotel male
Internet resources and Social Media sites Preferred by a gender of
Internet resources or off-line options to book a hotel Preferred by a gender of
On-line travel agencies (e.g., Booking.com, Expedia.com, hotels.ru) male
Meta-search engines (e.g. kayak.com) maleHotel brand web-site ( e.g. marriott.com) maleHotel review sites with booking capabilities (e.g. Tripadvisor.com, otziv.ru) female
Direct hotel booking with a phone call maleOff-line travel agency office femaleMobile applications both genders
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Here we need to emphasize the dominance of men in a usage of the majority of
on-line resources to book a hotel, whilst women would rather go to a local travel agency
office and make their purchase there, and also hotel review sites with a booking
capabilities like tripadvisor.com are more appealing for females than for males at their
final buying stop. Overall, when it comes to the usage of on-line resources for the hotel
booking 53% of those who make on-line transaction were men and 47% were women. Men
also use smartphones more often for on-line booking (65%) as well as desktop computers
(61%) and women showed more preference towards tablet computer devices (58%).
Computer notebooks are equally used by both genders for the same matter.
Summarizing the results of the study we can deduce the following on the
hypothesis testing:
H1 - fully confirmed;
H2 - partly confirmed according to medium correlation between on-line and off-
line hotel choice factors that are important for travelers;
H3 - partly confirmed as similar and different consumer behavioral patterns do
exist depending on the purpose of the travel which can be leisure or business tourism;
H4 - fully confirmed;
H5 - partly confirmed as men and women may act the same and also differently
in entire travel planning process.
Limitation of the research
The resulting sample appeared to bear a clumping type with a predominance of
respondents, that live in Moscow and are males aged of 29. Due to the fact that currently
Other ways to book a hotel female
Internet resources or off-line options to book a hotel Preferred by a gender of
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there is no reliable official statistics available in Russia that reflect the properties of the
population according to the sample selection criteria for the online survey, it was
impossible to re-weigh the sample. In this context, analysis of the collected data was
carried out «as is», and resulting clumping sample type may be attributed to limitations of
the study. This consequently did not allow to accomplish a factor analysis for the hotel
choice factors to fully classify and describe groups that are specific to Russian tourists.
Managerial Implications
Based on the findings of the study, we can propose the following list of activities
that will allow businesses in hospitality industry and tourism to use their innovative
potential and improve their value for customers with a use of ICT:
1) Take into consideration on-line feedback and place an immediate response on-
line, apologizing for customers that somehow are not satisfied with their experience and
thank guests who have placed a positive feedback;
2) Eliminate reasons that impel hotel guests to leave a negative feedback as
quickly as possible, however this is true mainly for the hotel services as some of the hotel
peculiarities like location cannot be changed over night or at all;
3) Offer a compensation for the negative experience in a form of specific
compliment, e.g. give away a free room upgrade and tangible discounts for services
available in the hotel for the next stay;
4) Encourage guests to write their on-line reviews, shoot and upload their video
and photo materials dedicated to the hotel with a help of a variety of marketing activities -
contests, gifts and discounts;
5) Re-think and update hotel web site and ensure its convenient usability and
modern state-of-the-art web design;
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6) Initiate or further strengthen collaborations with Social Media networks,
online travel agencies and meta-search sites using partnership marketing tools or exploit
the advertising opportunities provided by these internet businesses;
7) Establish a presence in various social media by creating corporate pages and
actively manage groups in Social Media with a frequent information update about the hotel
properties, facilities, services and currently undergoing marketing campaigns;
8) Take into account gender differences when developing appropriate messages
targeted to different groups of customers and Social Media networks users;
9) Recognize the growth of mobile applications importance and commence their
development and integration into communications with target customers;
10) Further develop ICT and IT integration with a business processes in
hospitality businesses, including the software capabilities to blend with on-line internet
resources and mobile applications that will increase the processing speed and quality in
interaction with customers.
These activities will help to ensure a more intimate contact with the target
customer audiences. They will also improve the efficiency of business in the hospitality
and tourism by providing a closer link with the market and provide opportunities to
improve the hotel and travel agency business model based on innovations brought by IT
and ICT.
Proposed directions for the future research
Given the fact of tourist-oriented Social Media on-line networks and other
internet resources rapid development which occurred most recently, there is a need for a
series of similar research projects that will make the present and other similar studies
longitudinal, because it is obvious that the results of the subsequent research will vary
from the previous studies. In this regard, it is also relevant to track a longitudinal
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dynamics of relationship and coexistence between traditional off-line and new on-line
sources of information in their impact on consumer choice in the final stage of hotel and
travel package booking
In addition, future studies should also take into account the rapidly growing
sector of mobile applications as the present study depicted that the aggregate share of
mobile devices, e.g. tablet computers and smartphones, was 36% amongst the devices
utilized these days by tourists for going on-line and web-browsing.
Conclusion
The present study certainly can not find all the needed answers to questions
related to the Social Media and online resources research area relevant for the hospitality
industry and tourism. Nevertheless, the results of the present research can be considered
as situational analysis of the current specifics of Russian consumers behavior including
their preferences in the search for hotel information both off-live and on-line; and the
decision to book a hotel room or purchase the whole travel package. The results of the
study demonstrate the importance of Social Media and other internet tools for consumer
choice in the Russian Federation.
As it is impossible to predict the trend of development of online resources and
their impact on the hospitality industry development with a great level of certainty, so it is
necessary to point up once again the call for a series of similar research projects in the
future.
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