Some Antecedents and Effects of using Mobile Apps in Tourism

Marketing

Vita Briliana and Arton Briyan Prasetio

Trisakti School of Management, JL. Kyai Tapa No.20 Grogol, West Jakarta, Indonesia

Keywords: Perceived Ubiquity, Perceived Informativeness, Perceived Personalization, Perceived Enjoyment, Mobile

App Usefulness.

Abstract: The purpose of this paper is to provide an improved understanding of the effect of Perceived Ubiquity,

Perceived Informativeness, Perceived Personalization, and Perceived Enjoyment towards Mobile App

Usefulness, as well as Mobile App Usefulness towards Revisit Intention. A quantitative approach has been

employed. The gathered data is obtained using questionnaire with itemized rating scale resulting in 100

respondents. For the purpose of data analysis, Structured Equation Model (SEM) method has been adopted.

The causal model was validated using Smart-PLS 2.0. The results indicate that Mobile Application is an

important antecedent of Revisit Intention and mediates the influence of Perceived Ubiquity, Perceived

Informativeness, Perceived Personalization, and Perceived Enjoyment. The study provides a comprehensive

framework of the antecedents and outcome of a mobile application’s usefulness for tourism marketing. The

findings provide insight for marketing managers and governments in developing a successful mobile

application for tourism marketing.

1 INTRODUCTION

Indonesia’s wide range of natural and cultural

attractions is famous throughout the world and has

drawn in throngs of foreign tourists. As an invisible

export, tourism is playing an increasingly important

role in Indonesia’s economy. In developing local

and international tourism, it is necessary to create

appropriate programs that can increase the flow of

foreign tourists. These programs can be

implemented by increasing the marketing activities

and the improvement of various facilities are needed

by visitors such as customs services, as well as

transportation facilities, banks, hostelries,

restaurants, travel bureaus, etc.

During the last five years the number of

international visits to Indonesia has soared. In 2017,

Indonesia had 14.04 million visitors or an increase

of 21.88 percent over the previous year’s number of

11.52 million (BPS, 2017). These increasing

numbers of tourists require ever-greater information

about destinations, available attractions,

transportation, souvenirs, and so on. However,

getting all this information takes time. Tourists often

experience frustration because they do not know

where to go and who to ask for information.

Information for tourists needs to be presented neatly

and structured for easy access. Tourist maps and

brochures have been a mainstay in disseminating

information on tourist destinations, but these tools

have their weakness. A tourist map can indeed help

tourists find attractions easily, but not all the desired

information can be displayed on a single sheet.

Additionally, a brochure typically describes only a

single destination attraction. However, these

limitations have been overcome by digital

technology, which has already transformed the

tourism industry in developed markets and is now

sweeping through emerging markets.

A survey published by Hootsuite in February

2018 indicates that the number of Internet users in

Indonesia in January 2018 reached 132.7 million,

with a penetration rate of 50%. From these data,

there were 130 million active social media users.

Meanwhile, the population of mobile device users is

even higher, reaching 177.9 million users, with a

penetration rate of 67%. Of these mobile device

users, 120 million are active social media users.

Therefore, if the popularity of digital technology is

high enough, then its benefits will be increasingly

realized, especially in the business world.

A mobile app, short for mobile application is

270

Briliana, V. and Prasetio, A.

Some Antecedents and Effects of using Mobile Apps in Tourism Marketing.

DOI: 10.5220/0008491702700275

In Proceedings of the 7th International Conference on Entrepreneurship and Business Management (ICEBM Untar 2018), pages 270-275

ISBN: 978-989-758-363-6

application software designed to run on

smartphones, tablet computers and other mobile

devices. Originally, mobile apps were offered for

informational and productivity purposes that

included email, calendar, contacts, calculator and

weather information. With the rapid magnification in

the technology and users' prospects, the developer

implements expanded into other categories such as

GPS, ticket purchases, social media, etc.

Most recently, Loureiro (2017) found that low-

cost airlines could not have become such a success

without the Internet and easy options for selecting,

booking, and paying for flights online. Yet digital

technology should not be regarded as a quick and

all-inclusive ﬁx for engaging online consumers.

Companies still need to recognize and fulfill the

demands for a personalised, self-service, end-to-end

journey experience.

A research gap was identified within the

literature on mobile application features in tourism

marketing. Much research has focused on Perceived

Ubiquity, Perceived Informativeness, and Perceived

Personalization (Okazaki & Mendez, 2013; Kim et

al., 2016), but has overlooked how perceived

enjoyment could influence perceived benefit for

travelers.

However, none of these studies reached

conclusions which can be applied to all countries—

such as in Indonesia. Indonesia has a cultural and

economic environment that is markedly different

from those countries where research has been

previously conducted.

This research was conducted in the province of

Banten, which is a popular tourist destination. At

one time an exotic and little-known corner of the

world, Banten has since become famous for its

natural beauty, as well as its rich local history and

religious wisdom. Ujung Kulon National Park in

Banten has been designated as one of the Seven

Wonders of Indonesia.

The main objective of this research is to examine

the impact of Perceived Ubiquity, Perceived

Informativeness, Perceived Personalization, and

Perceived Enjoyment towards Mobile App

Usefulness, as well as Mobile App Usefulness

towards Revisit Intention.

2 LITERATURE REVIEW

2.1 Perceived Ubiquity

Perceived Ubiquity is a person’s perception of a

product or service being available for use (Okazaki

and Mendez,2013; Kim et al., 2016). “Ubiquity”

simply means being everywhere (Subhadip Roy,

2017). The existence of “anywhere, anytime”

benefits enhances the usefulness of mobile features,

leading to positive attitudes towards them (Okazaki

and Molina, 2012).

H1. Perceived Ubiquity influences Mobile App

Usefulness.

2.2 Perceived Informativeness

Kim et al., (2013) point out that apps with

informative features are more likely to be used.

Studies have investigated how the informative

features of mobile apps increase consumer attitudes

toward brands and purchase intention (Bellman et

al., 2011).

H2. Perceived informativeness influences Mobile

App

Usefulness.

2.3 Perceived Personalization

Personalized services based on location directly

influence task performance and enhance perceived

usefulness (Ho, 2012). Previous studies indicate that

the informativeness of mobile apps provides

enjoyable experiences to consumers. According to

Yang and Jun (2002), personalization is an

important determinant of service quality for internet

buyers. It is also of high perceived value for users of

mobile shopping applications.

H3. Perceived personalization influences Mobile

App

Usefulness.

2.4 Perceived Enjoyment

Wen et al., (2011) stated that enjoyment is a holistic

sensation as people are totally involved in a certain

activity. Online shopping enjoyment is just as

important as enjoyment in a physical shop and can

influence a customer’s intentions and behavior.

Perceived enjoyment is the extent to which a person

can feel happy about something they get (Indah and

Briliana, 2017). An earlier study by Rajalie and

Briliana (2014) showed that the higher the perceived

pleasure, the greater the intention to repurchase.

H4. Perceived enjoyment influences Mobile App

Usefulness.

2.5 Mobile App Usefulness

Mobile applications now allow transactions from

any location in real time. Because of this

convenience, sellers must provide interfaces that

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271

allow buyers to conduct their transactions anytime

and anywhere, thereby providing opportunities for

consumers to enjoy the services offered without

restrictions on time or place (Mallat et al., 2009).

H5. Mobile App

Usefulness influences revisit

intention.

2.6 Revisit Intention

According to a study by Moez Ltifi (2018), more

and more cell phone users have a good experience

when using a mobile application. By doing so, their

use of m-service operations is increased. Meskaran

et al., (2013) note that online purchase intention

refers to a situation where a consumer is willing to

make an online transaction. In this context,

customers are willing to find, select, and purchase

products via mobile apps. Revisit intention relates to

consumers’ behavior and their intentions to use

information technologies after their initial adoption

(Chang, 2013). However, research on the

determinants of the Revisit Intention of mobile

applications in the tourism context remains limited.

3 RESEARCH METHODOLOGY

PLS analysis was selected because it can assess all

paths simultaneously for model prediction. The

SmartPLS 2.0 software package was used to assess

the model in two stages, which fulfilled the criteria

suggested by Anderson and Gerbing (1988).

Perceived Ubiquity, Perceived informativeness,

Perceived personalization, and Perceived Enjoyment

were proposed as antecedents of Mobile App

Usefulness in the first stage of the model, covering

H1, H2, H3 and H4. The second stage of the model

was used to study the influence of Mobile App

Usefulness in the proposed Revisit Intention,

covering H5. The figure below shows the conceptual

framework used for this research.

Figure 1: Conceptual framework.

Hair et al., (2017) explain that analysis using PLS-

SEM consists of two sub-models. The first is the

measurement model (or outer models), which shows

how latent variables represent the observed variables

to be measured. The second is the structural model

(or inner models), which shows the estimated

strength between latent variables or constructs. All

constructs were deemed highly reliable and

consistent due to their Cronbach’s α and composite

reliability scores, all of which exceeded 0.8

(Malhotra, 2011). Convergent validity was measured

through an assessment of the average variance

extracted (AVE) values for each construct, with all

clearing the prescribed minimum of 0.5 (Hair et al.,

2017). This study used a self-administrated

questionnaire with closed-ended questions. The

questionnaire was distributed using non-probability

purposive sampling. The object of this study was the

Banten Province tourism app. Respondents in the

study were people who toured Banten with the

following additional criteria: had obtained at least

one reference from the Banten Province tourism

portal; possessed the Banten Province tourism app;

were present at the Banten Province Tourism

Festival held on 17–18 February 2018; were over 17

years of age.

4 RESULTS AND DISCUSSIONS

From the respondents’ given profiles, the majority

(51%) were between 26 and 30 years of age and held

bachelor degrees (53%). Most (58%) stated that they

had previously been to Banten in the last 6 months,

while a significant percentage said they had visited

Banten more than 4 times (15%).

Tabel 1: Summary result of the measurement model and

convergent validity.

Loading AVE α CR

Perceived PP1 .645 .527 .777 .847

Personalization PP2 .792

PP3 .829

PP4

.671

PP5 .678

Perceived PU4

.875

.627 .420 .769

Ubiquity PU6 .699

Perceived PI1 .930 .876 .859 .934

Informativeness PI2 .942

Perceived PE2 .766 .541 .151 .701

Enjoyment PE4 .703

Mobile App MAU1 .844 .721 .807 .886

Usefulness MAU2 .860

MAU3 .844

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272

Tabel 1: Summary result of the measurement model and

convergent validity. (cont.)

Loading AVE α CR

Revisi

RI1 .823 .718 .804 .884

Intention RI2 .858

RI3 .862

Composite Reliability (CR) = (square of the summation of the

factor loadings)/{square of the summation of the factor loadings}

+ (square of the summation of the error variances)}.

Average Variance Extracted (AVE) = (summation of the square

of the factor loadings)/{(summation of the square of the factor

loadings) + (summation of the error variances)}.

To conﬁrm the reliability and validity of the

model, convergent and discriminant validity was

assessed. As Table 1 shows, all measures were

robust in terms of their reliability, as all standardized

loadings were statistically signiﬁcant – that is,

greater than the minimal threshold of 0.50 (Hair et

al., 2017). Cronbach’s α for all constructs exceeded

the minimal threshold of 0.70 (Hair et al., 2017), and

the composite reliabilities ranging from 0.701 to

0.934 also exceeded the recommended threshold

value of 0.70 (Gefen et al.,2003). Finally, AVE for

each construct was greater than 0.5 (Fornell and

Larcker, 1981), in the range of 0.527 - 0.876. These

results indicated that the convergent validity of the

model was adequate.

Table 2: Discriminant Validity.

MAU PE PI PP PU RI

MAU .849

PE .408 .736

PI .417 .199 .936

PP .509 .320 .213 .727

PU .167 .399 .036 .167 .792

RI .982 .434 .429 .511 .162 .847

Diagonal entries (in bold) represent the square root of the average

variance extracted (AVE) while the other entries represent the

squared correlations. Note : AA = Authenticity Atmospherics,

AF= Authenticity Food, SW= Social eWOM, PV= Perceived

Value, BI= Behavioral Intentions

Table 2 represents the correlations between the

constructs along with the AVE on the diagonal.

Using Shiue et al.’s (2010) recommendation, all of

the diagonal values exceed the inter-construct

correlations—thus indicating adequate discriminant

validity. This also explains how the constructs were

retained for further analysis of data.

Using a bootstrapping technique, path loadings

and t-statistics for hypothesized relationships were

calculated. The PLS analysis results are shown in

Table 3. In marketing, researchers usually assume a

significance level of 5%. Hypotheses with a t-value

above 1.96 will be accepted and a hypothesis will be

rejected when its t-value is found to be less than 1.96

for significance level = 5% (Hair et al., 2017). The

results of which appear in Figure 2.

Figure 2: Structural Model.

Table 3: PLS results of path coefﬁcients and hypothesis

testing.

H Path β SE t-value

Deci

sion

1 PP MAU .371 .027 13.9

***

Yes

2 PU MAU .002 .038 1.97

Yes

3 PI MAU .291 .027 10.7

***

Yes

4 PE MAU .228 .042 5.4

***

Yes

5 MAU RI .982 .003 294.8

***

Yes

Note: significance at **p < 0.05. ***p < 0.01

Mobile App Usefulness was predicted by

Perceived Personalization (β=0.374, p<0.001),

Perceived Ubiquity (β=0.003,p<0.05), Perceived

informativeness (β=0.292,p<0.001), and Perceived

enjoyment (β=0.229, p< 0.001). This includes 40.6%

of Mobile App Usefulness variance. Hence, H1, H2,

H3, and H4 found support.

H5 examines the effects of Mobile App

Usefulness on Revisit Intention. Mobile App

Usefulness is significantly related to Revisit

Intention with a t-value of 294.8 and a path

coefficient of 0.98. Therefore, H5 is accepted at the

one percent significance level, and it may be

concluded that Mobile App

Usefulness influences

Revisit Intention.

The study found Perceived Personalization,

Perceived Ubiquity, Perceived informativeness, and

Perceived enjoyment to be positively related to

Mobile App Usefulness in tourism marketing. These

conclusions are consistent with previous studies,

such as those by Okazaki and Mendez, (2013);

Seeun Kim et al., (2016).

The influence of Mobile App Usefulness is

particularly strong when tourists need as much

information as they can get on destinations they

have not yet seen. For example, if they want

information about Ujung Kulon National Park, they

also want to know the best route to get there, the

Some Antecedents and Effects of using Mobile Apps in Tourism Marketing

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locations of suitable restaurants and lodgings

together with offerings and price information, the

various tour packages, and the real-time conditions

such as weather. The technology must also provide

information that is dependable and which meets the

needs of its users.

Studies have investigated how mobile

technology assists the customization of travel

experience, eases information search activities and

facilitates interaction between the customer and the

company (Buhalis and Amaranggana, 2014;

Seeun

Kim, 2016). Mobile apps that broaden the scale of

the tourism industry with real time information

platforms serve to integrate the roles of tourism

service providers and local communities and social

media, because they are the most useful for

promoting, improving, and managing tourism

services.

5 CONCLUSIONS

For tourists, Perceived Personalization, Perceived

Ubiquity, Perceived Informativeness, and Perceived

Enjoyment were characterized as antecedents of

mobile apps usefulness. In addition, Revisit

Intention was proposed as a consequence of mobile

app usefulness in tourism marketing.

Tourism depends on infrastructure. If the access

is good, then the tour will be good. Indonesia has the

opportunity to grow, but it still faces challenges in

creating the infrastructure for fast internet access.

The challenge is Indonesia’s geography which

consists of thousands of mountainous islands. The

biggest need now is support from the government so

that Indonesia’s digital network can overcome its

historic backwardness. Internet penetration must be

improved. It should not just focus on Java, but must

be available in all parts of the nation.

ACKNOWLEDGEMENTS

The authors would like to express gratitude and

appreciation to Banten Provincial Tourism Office

for supporting data.

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