DRIVING FACTORS AFFECTING USERS ACCEPTANCE TOWARDS MOBILE VALUE ADDED SERVICES IN BANGLADESH

Electronic copy available at: http://ssrn.com/abstract=2549902

XIV International Business and Economy Conference

Bangkok, Thailand, January 5–8, 2015

DRIVING FACTORS AFFECTING USERS ACCEPTANCE

TOWARDS MOBILE VALUE ADDED SERVICES IN

BANGLADESH

MOHAMMAD MAJEDUL ISLAM

University of Rajshahi, Bangladesh

[email protected]

Abstract: Mobile technology services are growing very fast in different countries while it is

relatively slow in others. This study tries to understand the factors that contribute to the use

intention of these mobile value added services (MVAS) in Bangladesh. Drawing from the

Technology Acceptance Model, this study develops a model for consumers’ use acceptance

towards mobile values added services. Based on a sample of 230 Bangladeshi consumers’

survey, the main factors of use intention towards MVAS are perceived usefulness, perceived

ease of use, social influence, perceived risk, and perceived enjoyment. This study also finds

that among different MVAS internet browsing, and MMS and SMS services are more popular

use than others with different interest among different gender, age, and occupation. Overall

findings of this study provide some contribution to the researchers in the area of mobile

commerce and some assistance to practitioners in articulating better strategies to retain current

MVAS users as well as potential customers.

Keywords: MOBILE VALUE ADDED SERVICES, DRIVING FACTORS, USER

ACCEPTANCE, BANGLADESH

1 INTRODUCTION

Mobile phone services are the fast growing services in telecommunication industry in

Bangladesh. This sector is showing an inspiring growth in last few years. Along with voice call

service, it has introduced lots of value added services including SMS, MMS, ringtone, games,

E-transaction, mobile banking and internet browsing etc. to vast use of mobile

telecommunication services. Mobile value added services (VAS) are those services that offer

differentiation and the ability for mobile operators to charge a fix or premium price. Value

added services (VAS) refers to advanced and or additional services a content provider (network

operator) offers to possibly increase their revenues, or make their offering more competitive.

Mobile value added services (VAS) include non-voice advanced messaging services such as

SMS, MMS and mobile data services based on mobile data bearer technologies such as GPRS,

WAP, with value added service applications including mobile gamming etc. Not only non-

voice service mobile value added service also includes voice based services such as- PTT, IVR,

and WDA.

Bangladesh has become the 10th highest mobile phone penetrated country in the world having

more than 116 million subscribers base. It is characterized by high levels of awareness and

adoption of mobile phones and services. It has introduced GSM in 1989, GPRS in 2005, UMTS

networks in 2012, and High Speed Downlink Packet Access (HSDPA) has experimented in

2013. Smartphones and Laptops use are growing with 22.86% internet penetration. Almost

twenty-two percent of all Bangladeshi households access the internet via mobile phones.

Compared to other countries, tariffs for mobile services are relatively low. So, mobile phone

operators’ revenue comes highly from call tariffs where Average Revenue Per User (ARPU) is

only around $1.75 per month. Thus mobile value added services (VAS) will become new

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opportunities for telecom service providers to generate more revenues in high competitive

market.

Although new services are being released at all times, whether they are appealing to consumers

and can induce positive purchase intention after consumers have used them so as to effectively

increase revenue and sustainable development will be an important issue for mobile service

providers. However, the conditions for the use of MVAS appear to be favourable, different

market analysis indicate that consumers are reluctant to use their mobile phones to access them.

Accordingly, service providers are looking for ways to show consumers the VAS are offerings.

Practitioners and academics try to predict the conditions for usage of mobile VAS. Technology

acceptance model (Davis, 1989) has been used to predict the attitudes and behavior of users of

mobile services, based on perceived usefulness (PU) and perceived ease of use (PEOU) of

mobile system. Therefore, this study tried to explore the driving forces to use intention towards

mobile values added services in Bangladesh based on Technology Acceptance Model (TAM).

The objectives of this study are to understand the factors affecting consumers use intention

towards mobile value-added services, and to analyse the relationships among these factors.

Results of this study are useful to practitioners in the telecommunications sector for formulating

appropriate marketing strategies to increase mobile value-added services in the future.

2 LITERATURE REVIEW

Though there are large numbers of innovation adoption models exist, this study focuses on

Technology acceptance model as theoretical perspectives. This theory is considered the most

relevant and applicable for explaining use behavior in the context of mobile value added

services. The following paragraphs are briefly explains the technology acceptance model and

review on relevant literatures on mobile value added services researches.

2.1 Technology acceptance model

Technology acceptance model (Davis, 1989) has been used to predict the attitudes and behavior

of users of mobile services. Derived from the Theory of Reasoned Action (Fishbein and Ajzen,

1975) the TAM includes five constructs: perceived usefulness, perceived ease of use, attitude

towards use, intention to use, and actual use. The model of this theory proposes that (1)

perceived usefulness and perceived ease of use have a direct impact on attitude towards using

an innovation, while perceived ease of use has a direct influence on perceived usefulness; (2)

perceived usefulness alone directly affects intention to use an innovation; (3) attitude towards

innovation has a direct impact on intention to use such an innovation; and (4) intention to use

has a direct influence on actual system use. This model has gone through extensive validation

and extension from many replication studies. Several recent empirical studies have validated

adoption theory in relation to a wide range of products (Holak & Lehman, 1990; Labay &

Kinnear, 1981; Ostlund, 1974; Rogers, 1995) and technology (Beatty, Shim, & Jones, 2001;

Plouffe et al., 2001). Some researchers have extended the original model by adding additional

constructs that they felt were more relevant to their studies (Bhatti, 2007; Pagani, 2004;

Klopping and McKinney, 2004; McCoy et al., 2005; Nysveen et al., 2005; Sendecka, 2006;

Teo et al., 1999; Venkatesh and Davis, 2000). While others have dropped the link between

perceived usefulness and perceived ease of use as this relationship has proven to be the least

significant (Chen et al., 2004). This research goal is to explore different driving factors those

affect user acceptance of MVAS in the context of Bangladesh applying TAM model.




2.2 Driving factor affecting user acceptance

Different studies have been explored, confirmed, and made some modelling to measure the

acceptance and intention of mobile services in different countries. People are low willing to

use mobile services in general, but an exceptionally high willing to use certain applications

(Anckar and D’Incau, 2002). Different factors like perceived usefulness, perceived ease of use,

perceived enjoyment positively affect satisfaction with m-services while perceived cost has a

negative effect (Revels, Toib, and Tsarenko, 2010). Usefulness describes the generic efficiency

increase due to new technology use and mobility, includes time and place independent service

access, reduced queuing, and substituting for other services (Mallat, 2009). This study has

added view that use context was a new concept in this study. The most important factor in

increasing consumer’s behavioural intention to use 3G mobile value added services is attitude,

followed by perceived ease of use, perceived cost and perceived usefulness (Kuo and Yen,

2009). Entertainment value as well as information value as the strongest drivers of the

acceptance of the mobile phone as an innovative medium of advertising content

communication (Bauer, et al., 2005).The most important factor in increasing consumer’s

behavioral intention to use 3G mobile value-added services is attitude, followed by perceived

ease of use, perceived cost and perceived usefulness (Kuo and Yen, 2008).

The effect of perceived enjoyment was very important but usefulness did not influence an

individual’s attitude where age can be key moderator of mobile VAS acceptance (Ha and Choi,

2007). Compatibility of the mobile service is a major determinant of adoption and others like

budget constraints, availability of alternatives, and time pressure were also have a strong effect

(Mallat, et al., 2008). The key factors explaining success of mobile value added service

business model are advanced in-house technology, technological advancement of mobile

devices, positive network externalities, service targeting, and advertising knowledge

(Sirasoontorn, 2010). Service quality and fair price have indirect influence on customer

satisfaction through perceive value. Again, perceived value has mediating role between quality,

charge fairness and satisfaction. Whereas, there is no significant impact of service quality found

on customer satisfaction (Uddin and Akhter, 2012). The mobile service attributes of

personalization, identifiability, and perceived enjoyment have significant positive influences

on the key brand loyalty, perceived quality, brand awareness, and brand association (Wang and

Li, 2012). Building an adoption network that involves organizations with high brand awareness

in the eyes of prospective customers positively impacts the early market survival of services

relying on mature technologies (Dell’Era and Ghezzi, 2013).

Mobile services can be used to organise everyday lives and there are risks which can discipline

discourses (Berg and Jansson, 2005). Perceived usefulness, ease of use, price, and speed of use

are the most important determinants of adoption of mobile value added services (Pagani, 2004).

In adoption of technology, traditional antecedents of behavioural intention, ease of use and

perceived usefulness can be linked to diffusion-related variables, such as social influence and

perceived benefits (Lo’pez-Nicola’s et al., 2008). Mobile services quality attributes that are

important to Generation Y-eras and baby boomers has significant differences between the two

groups in terms of the effect of perceived value on satisfaction (Kumar and Lim, 2008). It is

confirmed that mobile browsing and social media are the most frequently used by mobile

subscribers. In addition, it was also discovered that the trust did not significantly affect the

loyalty and where social value does not affect satisfaction significantly (Oktavianto and

Hudrasyah, 2013).



3 OBJECTIVES

The foremost objective of this research is to understand the existing and potential users’

acceptance of mobile value added services in Bangladesh. This objective focuses to study on

below specific objectives

3.1 To explore the mobile value added services present status in Bangladesh

3.2 To understand the driving factors those affect users’ acceptance of mobile values

added services in Bangladesh

4 RESEARCH METHODOLOGY

4.1 Questionnaire design

The questions in the questionnaire were developed considering on review of literatures and the

specific characteristics of Bangladeshi people & market context. The specific characteristics

represented different services and facilities provided by the mobile network operators (MNOs)

and expected by the consumers of Bangladesh. The questionnaire was translated into Bengali

language to make clear and simple to understand by every respondent. The items in the

questionnaire were constructed based on the consumer intention and acceptance of mobile

value added services. After the draft was designed, a pre-test was performed on users and

experts familiar with mobile value added services to modify ambiguous expressions. Based on

the respondents’ feedback, the questionnaire was adjusted to improve its readability and ensure

its accuracy and appropriateness. The questionnaire was then adopted in a pilot test involving

30 undergraduate and graduate students from one public university in Bangladesh. It was

consisted of 24 questionnaire items on six factors including “use intention,” “usefulness”, “ease

of use”, “social influence”, “perceived risks”, and “speed of use.” The items were measured on

a 6-point Likert scale to avoid the tendency of answering neutral comment of Bangladeshi

respondents. The questionnaire also includes six demographic items including gender, age,

occupation, income, residence, and mobile operator use.

4.2 Sample

The sample of this study included 230 respondents from different regions of Bangladesh those

are representative of the country’s population. The respondents comprise of 60% male and 40%

female mostly (74.8%) are in the 18-30 years age range. Among the respondents, most them

(50%) were students and others business (15.2%), service (27.8%), and agriculture (7%).

4.3 Data collection

Subjects of this study were recruited from either in front or beside of the mobile phone shops

in different public places in Bangladesh. The researcher approached potential respondents and

asked for their willingness to participate in the study. Participants were selected on a

convenience basis. At the time of intercepts, the researchers asked whether the participant had

prior experience with using mobile value added services.

4.4 Data ANALYSIS

As far as scale-based variables were concerned, principal factor analysis was performed. In this

study, the correlation matrix was used to obtain Eigen values. To facilitate the interpretation of



factor loading, VARIMAX rotation was performed. In addition, Pearson correlation analyses

were also conducted to examine the relationships among the constructs. SPSS software version

18 was used for analyzing the data.

5 ANALYSIS AND RESULTS

5.1 Sample characteristics

Among 230 valid respondents, highest uses are mobile internet service (35.7%) followed by

messing (25.2%), music & ring tone download (22.6%), utility payment (13.5%), and games

(3%). In terms of occupation, mostly students are using mobile value added services (50%). In

this study found most of the services users getting mobile value added services were provided

by Grameen Phone (56.1%). Among the different income group, 83% of the respondents’

earnings are less than 21,000 taka ($1=78 Taka).

TABLE 1

Sample characteristics Item Sample Characters Frequency Percent Valid Percent Cumulative Percent

Ag

e (i

n

Yea

r)

<18 23 10 10 10

18-25 109 47.4 47.4 57.4

26-30 63 27.4 27.4 84.8

>30 35 15.2 15.2 100

Occ

up

atio

n Student 115 50 50 50

Business 35 15.2 15.2 65.2

Service 64 27.8 27.8 93

Agriculture 16 7 7 100

Inco

me

(in B

DT

)

<10000 139 60.4 60.4 60.4

10000-20000 52 22.6 22.6 83

21000-30000 33 14.3 14.3 97.4

>30000 6 2.6 2.6 100

Mobil

e N

etw

ork

Op

erat

or

GP 129 56.1 56.1 56.1

BL 43 18.7 18.7 74.8

T&T 21 9.1 9.1 83.9

Robi 19 8.3 8.3 92.2

Citycell 6 2.6 2.6 94.8

Airtel 12 5.2 5.2 100

Mobil

e V

AS

Use

Mobile Internet 82 35.7 35.7 35.7

Ringtone & Music 52 22.6 22.6 58.3

MMS & SMS 58 25.2 25.2 83.5

Games & Application 7 3 3 86.5

Utility Payment Service 31 13.5 13.5 100

5.2 Reliability and validity

There are twenty four items have been considered for the study. Multi-item scales (Six Point

Likert Scale) response format has been used to operationalize each individual item of the



questionnaire. The overall measurement for contextually formatted items is described in Table

2 result shows that scales used for the data collection are mostly reliable with highly

recommended alpha scores which is within the range of good scale reliability (O’Leary-Kelly

& Vokurka, 1998). As the respondents are new in experiencing mobile value added services in

Bangladesh, some of the scores are less than acceptable level (perceived risk 0.469 and speed

of use 0.596). The study identifies 24 items based on Eigenvalue - 1 or above includes into the

list of items. Statistically 24 items construct six factors which can explain 60.85% of the field.

So, this study considers these factors are important for the study. Factor-1 explains 22.533%

having Eigenvalue of 5.408 and Factor-6 explains 4.377% with Eigenvalue 1.051 as lowest

(Table 2). Hence, factor-1 is the most important in the current study which is related to the use

intention of mobile VAS consumers in Bangladesh.

TABLE 2

Reliability and validity

Factor Mean SD # Items

remain

Cronbach's

alpha

Eigenvalue

Total

% of

Variance

Use intention 4.188 0.695 6 0.799 5.408 22.533

Perceived usefulness 4.902 0.744 5 0.814 2.790 11.623

Perceived ease of use 4.215 0.813 4 0.809 2.278 9.49

Social influence 4.550 0.920 4 0.754 1.667 6.946

Perceived risks 3.006 0.737 3 0.469 1.411 5.881

Speed of use 3.302 0.913 2 0.596 1.051 4.377

5.3 Pearson correlation coefficients

The factor correlation matrix depicted in Table 3 below, indicated that the largest correlation

between any pair of constructs was 0.494 (perceived ease of use and perceived usefulness)

while the smallest score was 0.006 (perceived risk and perceived usefulness). Hence,

considerable numbers of correlation coefficients among variables are significant (p ≤ 0.01).

TABLE 3

Pearson correlation coefficients among all factors FACTORS UI PU PEoU II PR SOU

UI 1

PU 0.327** 1

PEoU 0.229** 0.494** 1

II 0.388** 0.191** 0.204** 1

PR 0.107 -0.006 0.046 -0.036 1

EJ 0.128 0.100 0.282** -0.203** 0.294** 1

5.4 Factor Analysis

The data was first studied with a factor analysis to validate the proposed mobile value added

service characteristics. As the measurement scales were modified to suit the current research

topic, exploratory factor analytic technique to identify the observed underlying structure in the

data matrix of variables affecting respondents’ acceptance towards mobile value added

services. The data was first screened for inter-variable correlations to deem if the data justified

application of factor analysis. It has observed a relatively very good number of strong inter-

variable correlations. The study also ran Bartlett’s test for sphericity and Kaiser-Meyer-Olkin

(KMO) measure of sampling adequacy (Table 5) that was 0.788 indicates very good measure.



TABLE 4

Measurement items and factor loadings Factor Item(s) Item loading(s) Mean Std. Deviation

Use Intention

Daily Requirement 0.774 4.25 1.000

Self-Phone Use 0.705 4.19 0.874

Huge Advertisement 0.687 4.40 0.937

FNF Use 0.672 4.23 1.122

Less Expensive 0.625 4.07 0.980

Regular Use 0.516 4.00 0.971

Perceived

Usefulness

Internet 0.824 4.94 0.872

Games 0.735 4.69 0.909

MMS &SMS 0.731 5.04 0.988

Mobile banking service 0.726 4.87 0.983

Ring Tone Download 0.522 4.96 1.140

Perceived Ease

of Use

Anywhere Use 0.799 4.13 0.998

Secured 0.754 4.14 1.070

Anytime Use 0.750 4.22 0.937

Easy to Use 0.693 4.37 1.069

Social

Influences

Different people Uses 0.789 4.53 1.170

FNF Forces 0.748 4.36 1.238

Bank agents influence 0.674 4.86 1.121

Utility service providers force 0.583 4.45 1.313

Perceived Risks

Error Solution 0.675 3.45 1.013

Network connection 0.640 2.80 0.995

Safety of M-Wallet 0.477 2.77 1.280

Speed of Use Quick Access 0.695 3.09 1.062

Speed of Internet 0.644 3.52 1.101

To clarify the structure of mobile VAS attitudes, the principle component analysis was utilized

as the extraction method, with the rotation method of varimax with Kasier normalization. The

results of factor analyses revealed that consumers’ responses in the mobile VAS attitudes

survey were grouped into six factors. In Table 4 six factors were initially formed considering

24 measures to influence users’ acceptance towards mobile VAS in Bangladesh. These factors

have been used in different literatures of previous study on users’ acceptance towards mobile

value added services. Factor analysis was conducted to know the underlying factor associated

with all 24 measures.

The interpretation of the factors has been facilitating through applying VARIMAX rotation

with Kaiser normalization. The factor analysis suggests that there are six dimensions in the

evaluation space of users’ acceptance towards mobile VAS in Bangladesh. These dimensions

are (1) use intention, (2) perceived usefulness, (3) perceived ease of use, (4) social influence,

5) perceived risk, and (6) speed of use respectively.

TABLE 5

KMO and Bartlett’s test Kaiser-Meyer-Olkin Measure of Sampling Adequacy

Bartlett's Test of Sphericity

0.788

Approx. Chi-Square 1935.376

df 276

Sig. 0



6 DISCUSSIONS AND CONCLUSION

The primary theoretical contribution of this study is the identification of factors that can be

used to enlighten and foretell consumers’ acceptance towards mobile value added service,

particularly within the Bangladesh context. This research also creates a research interest on

mobile VAS for the business researchers. Finally, by investigating consumers’ acceptance

towards mobile VAS within the Bangladesh context, this study answers the call for additional

research to different fields of mobile commerce.

The factor use intention (UI) scores highest (22.533) acceptance value than other factors where

speed of use (SOU) scores lowest (4.377). Consumers are thinking that perceived risk (PR) is

less important to accept mobile value added service. Perceived usefulness (PU), perceived ease

of use (EoU), and interpersonal influence (II) are highly important to accept mobile VAS. In

case of perceived usefulness, the mobile financial service institutions should improve the

services of ringtone & music download. Consumers in Bangladesh are price sensitive and

highly accept the mobile value added service when purchase facility will be under self-control.

Service providers should give special focus in reducing network problem, internet speed, and

utility payment services system. People are very much expressive and want to do many things

like others. So, proper communication and hands-on support in remote areas is required for

prompt adoption and penetration.

7 LIMITATIONS AND FUTURE RESEARCH

The sample size of this study was not necessarily representative of the Bangladeshi population

as a whole as it ignored large rural population. Secondly, the generalizability of this research

may be impacted by fact that the sample’s is skewed towards males. This may be due to general

tendency of Bangladesh culture. In addition, this research only explores the factors to influence

motivators and inhibitors on behavioral intentions. In terms of future research, a large scale

study with more representative sample could be conducted to validate the factors of this study

and to enhance the generalizability of the research conclusions.

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DRIVING FACTORS AFFECTING USERS ACCEPTANCE TOWARDS MOBILE VALUE ADDED SERVICES IN BANGLADESH

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