Department of Policy and Planning Sciences
Discussion Paper Series

No.1330

Behavioral Intention to Use Mobile Entertainment
Services among Bangladeshi Studentsby Qazi M. GHYAS, and Fumiyo N. KONDO

Jul 2015

UNIVERSITY OF TSUKUBA
Tsukuba, Ibaraki 305-8573
JAPAN

Behavioral Intention to Use Mobile Entertainment Services among
Bangladeshi Students
Qazi Mahdia Ghyas1) and Fumiyo N. Kondo2)!
Abstract!

This study aims to understand why mobile usage in Bangladesh access mobile entertainment
services (MES) among young users. We proposed a modified technology acceptance model(TAM) and the theory of planned behavior (TPB) model with some original and additional
factors. Questionnaire surveys were conducted in Bangladesh among young adult mobile
users. We analyzed the data of 251 effective respondents by four TAM-TPB models. We
have chosen the best model with good fits. The three factors of perceived behavior control,
perceived value and attitude are important determinants for intention to use mobile
entertainment services. Our result is potentially helpful for mobile operators to adopt themobile entertainment service (MES) market in Bangladesh.
!
Keywords: Mobile entertainment services; Young users; TAM-TPB model; Perceived value;
Perceived Behavioral Control; Attitude.
!
1. Introduction
Mobile technologies and services worldwide are heralded to create a tremendous
spectrum of business opportunities. There are nearly 7 billion mobile subscriptions
worldwide according to the estimates by the International Telecommunication Union (May2014). This is equivalent to 95.5 percent of the world population. Nowadays, mobile Phones
are not used for voice services only, but also for mobile services such as texts messaging,
gaming, download music, payment services, etc. (Carlsson et al., 2006). According to Kondo
and Ishida (2014), the demand of mobile service market in developing countries such as
China, India and Bangladesh is growing and researchers and practitioners are giving keen
attention to the market.
Most mobile operators in Bangladesh are concentrated in the entertainment category.
Mobile services in Bangladesh have categorized in two categories: Entertainment anddevelopment services. Among them, general entertainment services (news, religion, games,
music, etc.) are the largest used services in Bangladesh, followed by social media, ringtone
and the others (services to recharge prepaid, receiver pays for calls/ SMS, missed called alerts,etc.) in a sequential order (GSMA Intelligence, 2014). It seems that operators have a large
footprint in the mobile entertainment services (MES) space and the market is rapidly
expanding. With the growing importance of Mobile entertainment services (MES), this isessential for service operators to identify the factors relating to customer adoption or
intention to obtain MES for current and future service development.
Several researches have been conducted for Bangladesh mobile service market. Most of
the recent researches are such as 3G Mobile Service Acceptance in Bangladesh have been
researched by Tajmary and latif (2013). Consumer choice behavior towards mobile phone
operators in Bangladesh have been measured by Hasan et al., (2013). Islam et al. (2011)
found that the factors influencing the adoption of M-commerce for Bangladesh are awarenessand knowledge, convenience of mobile devices and handsets, pricing and cost, security and1) Department of Social Systems and Management, Graduate School of Systems & Information
Engineering, University of Tsukuba, Japan
2) Division of Policy and Planning Sciences, Faculty of Engineering, Information and Systems
University of Tsukuba, Japanprivacy, rich and fast information, and perceived usefulness
There is no research that has been conducted covering the mobile entertainment services
for Bangladesh market. The present study is an ample step in covering this gap. Here we
consider Game, music and ringtone as MES.
User’s perception regarding the use of MES has been identified by exploring their
behavioral intention in past researches. Okazaki et al., (2008) examined user “intention to use”
mobile game application for USA, Spain and Czech Republic customers by using TAM(explained in section 3) model among young users. Quan et. al., (2010) researched a categoryof mobile transaction services in China using a TAM-TPB (explained in section 3) approach.
They found that a combined TAM-TPB model is suitable for evaluating the potential“intention to use” specific mobile commerce services. Nysveen et al., (2005) developed andtested a modified TAM-TPB in order to explain consumers’ “intention to use” four types ofmobile services. Kondo and Ishida (2014) has examined the “intention to use” most frequent
used MES (game, music, ringtone) for Japan and USA by using TAM-TPB model. Even
though research in mobile service behavioral intention has used the TAM-TPB extensively,
the literature contains little regarding its applicability to MES in developing countries.
Therefore, we examine the factors of student’s “intention to use” for Bangladesh which
has an expanding mobile market. To understand MES acceptance among Bangladeshi youngusers, the TAM-TPB is suitable as it is suggested by Kondo and Ishida, 2014. We ground our
research framework in two theoretical models. First one is the TAM-TPB model of Kondo
and Ishida (2014) with their factors of perceived value, perceived behavioral control, attitude
and subjective norm on MES intention behavior of young people. The latter added factors
perceived fun, perceived convenience and perceived ease of use were from Okazaki et al.,(2008). More details of the model will be provided later.
The rest of the article is organized as follows. The next sections will describe theoverview of mobile services in Bangladesh, the basic TAM-TPB model, modified TAM-TPB
and then introduces the proposed conceptual model and the hypotheses. These are followed
by sections on methodology and statistical results. The last sections present a summary of thefindings, conclusions, and directions for future research.
2.

Overview of Mobile Services in Bangladesh:In recent years, the uses of mobile phones have witnessed tremendous growth in
Bangladesh. The country is the ninth-largest market worldwide in terms of mobile
subscribers in Q1 2013 with 70 million ‘unique’ subscribers actively using 112 million
mobile connections, i.e. SIM cards (GSMA intelligence, 2014). The total number of Mobile
Phone subscriptions has reached 118.493 million at the end of September 2014. Mobile
phone penetration rate was 69.5% at August, 2014 (BTRC, 2014). Mobile service users
among adults are actually above 50% in Bangladesh (GSMA intelligence, 2014).
There are six mobile phone operators offering their services to customers in Bangladesh.
Grameen Phone Ltd. (GP) owned by Telenor (62%) and Grameen Telecom (38%) is thelargest and the fastest growing cellular service provider in Bangladesh. It has 50 million
subscribers of total. Orascom Telecom Bangladesh Limited (Banglalink), the second largest
cellular service provider, has 30 million subscribers in total. It is a wholly owned subsidiaryof Orascom Telecom. Robi Axiata Limited (Robi), the 3rd largest cellular service provider in
Bangladesh, has 24.966 million subscribers of total. The fourth largest cellular service
provider in Bangladesh is Airtel Bangladesh Limited (Airtel) which has 7.901 million
subscribers of total. The other two mobile phone operators in Bangladesh are PacificBangladesh Telecom Limited (Citycell) with 1.349 million total subscribers and Teletalk

Bangladesh Ltd. (Teletalk) with 3.768 million total subscribers. Robi and Bangalink cellular
service providers are most active in MES.
Nowadays, the following new services are in the great use in Bangladesh: Interactive
Voice Response (IVR), Unstructured Supplementary Service Data (USSD), and Application
Protocol Interface (API), reported by Bangladesh Telecommunication Regulatory
Commission. Approved value added services are listed in the below:
Mobile Financial Services: Web/international recharge, e-ticketing, inward remittances,utility bill payment, mobile banking and others are the various services provided under this.
Call Center based Information Services: Information services like health line, agriculture
info, education line, legal line, blood bank info, travel line etc. are provided by call center
based information service organizations.
Tracking Service: Mobile customers can determine the position of their vehicles and canmanage them by using this service. Basing on the customer demand, this service is also used
for tracking human/materials/vehicles/water vehicles etc.
Directory / Recharge / Live Information Service: Mobile operators in co-operation withcompanies having data based facilities, provide yellow page, directory services, dictionary
services, public examination results, stock exchange info, entertainment services etc.
News Service: In order to keep the people updated with the latest news of home and abroadnews services have been introduced through SMS based news/alert service.
3.

Theoretical Framework

Emerging information technology cannot deliver improved organizational effectiveness if
it is not accepted and used by potential users. Technology Acceptance Model (TAM) andTheory of Planned Behavior (TPB) are the most successful and effective models formeasurements of digital device based usage among practitioners and academics.
3.1 TAMTAM provides a basis for discovering the impact of external variables on internal
perceptions (beliefs), attitudes, and intentions (Davis et al., 1992). According to TAM, aperson’s performance of a specific behavior is determined by his/her behavioral intention(BI) to perform the behavior and BI is jointly determined by the person’s attitude (A) andsubjective norm (SN) concerning the behavior in question. (Ajzen and Fishbein, 1980).
3.2

TPB
TPB includes an additional construct, perceived behavioral control (PBC). PBC is definedas one’s perception of the difficulty of performing a behavior. The TPB views that the people
have control over their own behavior lies on a continuum from behaviors that are easily
performed to those requiring considerable effort and resources.
3.3

The TAM-TPB Model
In order to form a behavioral intention, customers concern to know what kind of benefit
or values them can obtain from the services, this is perceived value. Perceived value defines
as “the consumer’s overall assessment of the usefulness of a product/service based on
perceptions on what is received and what is given (Heinonen, 2004). The consumer’s overall
assessment of the usefulness of a service depends on the quality and price information forusing the services. Perceived value defines the utility derived from the perceived quality andperceived cost when users accept a mobile commerce (Sweeney et al., 1999). The more users
will be beneficial, the more they will intend to use the services. Use intention measures thepossibility that a consumer will use the service. The more the user intention, the more their
willingness will be to use the service (Dodds et al., 1991). The willingness to use is affectedby the perceived value as suggested by (Groth (1995); Heskett et. al., (1997). Perceived value
have positive association with decision making which has also indicated by (Zeithaml, 1988;
Schiffman & Kanuk, 2000). Therefore, we will observe whether perceived value has any
influence on intention to use MES.
Several researches have done by using different theoretical model for mobile service
market. TAM model was investigated for mobile application use by Seok Kang, 2014. TPB
Model was studied for customers in India on MES (games, music, videos, camera, andinternet access) (Kumar and Janaki, 2011). There are very few studies which used TAM-TPB
model for MES.
The TAM-TPB is an effective predictive model in field that leads to a certain degree of
behavioral change by individuals have summarized by Kondo and Ishida (2014). They
proposed to use the concept of perceived value. Our TAM-TPB model will be constructed byusing the following five concepts to deal with entertainments services in the Bangladesh
mobile market: Behavioral control, perceived value, attitude towards mobile services,behavioral intention to use, and subjective norm. Therefore, we examine user behavioral
intentions based on the model shown in Figure 1. Thus, we postulate the following
hypotheses:
H1. Perceived behavioral control positively influences perceived value in Bangladesh.
H2. Perceived value positively influences attitude in Bangladesh.
H3. Perceived behavioral control positively influences attitude in Bangladesh.
H4. Attitude positively influences behavioral intention of overall entertainment services in
Bangladesh.
H5. Perceived value positively influences behavioral intention of overall entertainment
services in Bangladesh.
H6. Perceived behavioral control positively influences behavioral intention of overall
entertainment services in Bangladesh.
H7. Subjective norm positively influences behavioral intention of overall entertainment
services in Bangladesh.

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3.4

Proposed Conceptual Model
We extend our model by adding some factors on behavioral intention to use from related
model. We are trying to use the hedonic and utilitarian concept on TAM-TPB model. The
hedonic (intrinsic) and utilitarian (extrinsic) value components frame the behavioral intention
to use (Holbrook, 1994). Attitude to be ‘‘an overall evaluation, encompassing both utilitarianand hedonic components’’ and find that it completely mediated the effects of two antecedents,
fun and usefulness (Bruner and Kumar, 2005). Perceived ease of use, perceived enjoyment
and perceived attractiveness are antecedents of attitudes for online gaming adoption which
has hedonic and utilitarian instincts (Ha et al., 2007 and Hsu and Lu, 2004). Few previous
researches on MES have focus on this concept. Therefore, we will study these three
additional factors perceived fun, perceived convenience and perceived ease of use which may
have influence on attitude.
Perceived fun:
We add to our model, perceived fun which represents the level of the hedonic component of
handheld MES. Enjoyment can be defined as the degree to which performing an activity isperceived as providing pleasure and joy in its own right (Venkatesh, 2000). Compared to
information system uses, enjoying mobile service is more experience-oriented. Enjoyment
affects the use of experiential mobile services (i.e., contact and gaming) more strongly thanthe use of goal-oriented mobile services for Norwegian users. (i.e., SMS and payment)(Nysveen et al., 2005). In other study, Khalid and Noor (2011) for Jordan and Dai and Palvia(2009) for China obtained no significant relationship between enjoyment and mobile phoneservices. There is a conflict between the two results. So, here we will observe whether
perceived fun influence the attitude that consumers experience in MES. So, our hypothesis is:
H8: Perceived fun will directly and positively affect attitude toward MES in Bangladesh.
Perceived ease of use:
Perceived ease of use, refers to the extent to which an individual believes that the use of amobile entertainment will be free of effort (Venkatesh, 2000). Previous literature provides
inconsistent results that show how perceived ease of use influences attitude significantly(Bruner and Kumar, 2005). They found perceived ease of use has only an indirect effect on
attitude. Perceived ease of use has a direct effect on the perceived fun and perceived
convenience dimensions, but not on attitude. By the same token, our study proposes
perceived ease of use posited by Okazaki et Al., (2008). Thus, the hypothesis is:
H9: Perceived ease of use will directly and positively affect perceived fun and perceived
convenience in MES in Bangladesh.
Perceived convenience:
Our model includes perceived convenience as an antecedent of attitude, but not perceived
usefulness used in the TAM. This dimension crystallizes the core utilitarian values of MES:
simplicity in design, functionality in technology, and practicality in use. Dabholkar andBagozzi (2002) argue that the dimension of usefulness is appropriate for products such as
computer software but not relevant for technology-based self-service, in which the consumer
participates but which he or she does not own. By the same token, our study proposes
perceived convenience (Okazaki et al., 2008). Our study postulates attitude is theconsequence of the perceived convenience that consumers experience in MES. Thus, thehypothesis is:
H10: Perceived convenience will directly and positively affect attitude toward MES in
Bangladesh.
Usage patterns of MES may have differences or similarities among countries. We focus

on entertainment services (game, music and ringtones) for Bangladesh analysis. Four factorsof mobile services have identified by Ghyas et al., (2011): Information intensiveness (Factor1), entertainment (Factor 2), low penetration service (Factor 3), and communication service(Factor 4) on Japan data. Factor 2 represents services with entertainment characteristics. In
our study, we focus on Factor 2. Specifically, the following entertainment services are
examined: Games, music, and ring tones. Kondo and Ishida (2014) also researched these
services for USA and Japan.
4.

Methodology

4.1

Data Collection

Five surveys were conducted in faculty of Business Administration from five universities
in Dhaka, Bangladesh in the period of June-August, 2014. One hundred thirty five mobile
phone users at a private university, 40 users at another reputed private university and 50 users
at another private university were invited to participate. The rest of two surveys wereconducted in two reputed public universities of 68 mobile phone users at a public university
and 33 users at another public university. In total, 326 subjects received the questionnaires,
resulting in 276 completed responses.
We used responses from young users who were 18- 30 years for this research. We also
used responses from experienced mobile device users, following the approach of Kondo and
Ishida (2014) that experience is required to form opinions. (2014) eliminated non-mature cell
phone users in order to eliminate the strong influence of IT dexterity in their research. We
also eliminated non-user and non-mature cell phone users. Therefore, after the elimination,
there were 251 respondents for our analysis.
Table 1 shows the descriptive statistics of the respondents based on the questions asfollows: Q1. How many years have passed since you started to use the first cell phone? Q2.
How much do you spend for cell phone services on monthly average basis, including device
price and service charge? Q3. What category (or type) of program are you using?
Table 1

Demographics of Respondents to questions, Q1 – Q3

Category

ValuesBangladesh
N=251

Age

under 20
20-25
25-30
Male
Female
Yes
No

35
203
13
163
88
251
N/A

13.9
80.9
5.2
65
35
100
N/A

less than 6 months

N/A

N/A

6 months - less than 1 year
1 year - less than 2 years
2 years - less than 3 years

1
12
20

0.4
4.8
7.9

3 years - less than 5 years
5 years - less than 10 years

48
142

19.1
56.6

10 years or more

28

11.2

GenderMobile user
Q1

(%)

Q2

Q3

less than 200tk

42

16.8

200 - less than 400tk
400 - less than 600tk

52
54

20.8
21.5

600 - less than 800tk
800 - less than 1000tk

33
31

13.2
12.4

More than 1000tk
Pre-paid (you purchase calling cards)
Monthly billing (based on contract with your provider)

39
237
14

15.6
94.5
5.5

Note: 200tk=US$2.57
Our demographic values are compatible to Kondo and Ishida (2014). They had 66.1%(Japan) and 73.7% (USA) respondents of age group 20-25. We have 80.9% for Bangladesh.
For male group, they had 66.9% for Japan and 70.1% for USA. We have 65% for Bangladesh.
About mature users of more than 5 years, they had 71.9% for Japan and 76.4% for USA. We
have 67.9% for Bangladesh.
Our initial survey items were adapted from previous studies, Kondo and Ishida (2014);
Mathwick et al., (2001); Dholakia and Baggozi (2002) and Boontaring et al., (2012). We used
the following sets of 5 and 10 point likert scales: Strongly disagree/strongly agree; unfair/fair;very low/ very high; definitely won`t/ definitely will. We used the items of Kondo and Ishida(2014) and improved by adding one more questions with their original two questions ofperceived value and Attitude. We added one question with perceived value from Boontaring
et al., (2012) as follows “MES (game, music, ringtone) have an acceptable standard of
quality”. We also added one question with attitude from Celik and Yilmaz (2011) as follows:“Using MES (game, music, ringtone) services are beneficial to me”.
4.2

Measurement Scales

In order to assess the reliability and validity of the constructs, several measures werecomputed. The reliability coefficient, composite reliability (CR), average variance extracted(AVE) and the squared inter-correlations (SIC) are reported for Bangladesh in table 2. The
Cronbach ! Coefficient is the measured value of questionnaire items for each construct fromthe point of view of internal consistency. If the value of this coefficient was 0.7 or more, theinternal consistency of the measurement scale is considered as being high and the reliabilities
are adequate. The coefficients for each factor are shown in table 2. Since all values exceeded
0.7, it was concluded that the items of these constructs had common parts. The threshold for
CR is 0.70 or higher (Bagozzi & Yi, 2011).
All AVE values were above 0.5 indicating convergent validity. For discriminant validity,
the AVE of each construct should exceed the SIC of the construct with other constructs. As
shown in the table 3, this holds true for all constructs except subjective norm and perceived
convenience. There exists multicollinearity between perceived convenience and perceived
fun (0.942). Previous two studies on online gaming adoption (Ha et al., 2007; Hsu and Lu,
2004) found that perceived usefulness has little or no impact on attitude. Nasveen et al.,(2005) also found that there are stronger direct effects of perceived usefulness on intention touse goal directed mobile services (test messaging and payment) than on intention to use
experiential mobile services (gaming and contact). So, here we will omit perceived
convenience with our proposed hypothesis H10. For the correlation between PBC and SN(0.756), we will use the both in the most complex model because they were used in theprevious TAM-TPB model by Kondo and Ishida (2014), in which SN were removed later intheir best model.

Table 2

CR, AVE, and SIC for Each Construct for Bangladesh

Constructs

1

ATT

No. ofItems
3

Cronbach's Alpha
0.825

PV

3

0.808

PF

3

0.871

PEOU

3

PC

2

3

4

5

6

7

8

CR

AVE

AVE and SIC

0.805

0.580

0.613

0.721

0.600

0.310

0.600

0.870

0.700

0.422

0.355

0.700

0.863

0.865

0.684

0.536

0.265

0.451

0.684

3

0.831

0.834

0.628

0.399

0.390

0.942

0.502

0.628

BI

3

0.817

0.810

0.588

0.329

0.317

0.618

0.441

0.584

0.588

PBC

3

0.760

0.770

0.533

0.502

0.22

0.252

0.264

0.261

0.105

0.533

SN

3

0.819

0.758

0.626

0.612

0.247

0.326

0.34

0.342

0.222

0.756

0.626

Note: The values of AVE are on the diagonal and those of SIC on the off-diagonal.

Fig. 2. Proposed TAM-TPB Model
4.3

Analytical Method

The research models were analyzed for Bangladesh via structural equation modeling(SEM) by using the statistical software AMOS version 22.0. The SEM is a statistical
approach to understanding social and natural phenomena by identifying a causal relationshipbetween the observed variables and the latent variables that cannot be observed directly. A
useful and powerful aspect of SEM is the test of hypotheses across samples (Bagozzi & Yi,
2011).
Based on fit indices, the best was obtained. the classification of these model fit indices asroughly two types, absolute fit indices and comparative fit indices summarized by Hooper etal. (2008). The absolute fit indices include goodness-of-fit (GFI), adjusted goodness-of-fit(AGFI) and root mean square error of approximation (RMSEA). The comparative fit indicesinclude Akaike Information Criterion (AIC), Browne-Cudeck Criterion (BCC), Normed Fit
Index (NFI) and Tucker-Lewis Index (TLI). Threshold guidelines exist for these indices. The

overall fit indices of the revised models were examined. A t-value was used as a criterion totest the significance of the parameters at the .05 level. A t-value was defined as the ratio
between the parameter estimate and its standard error (Joreskog & Sorbom 1989).
5.

Results

We have conducted four TAM-TPB models in order to establish the best-fit index. The
four TAM-TPB models are as follows: The research model in Figure 2 was Model 1. Model 2,
3 and 4 were created by using a step-by-step approach. Model 2 was created by deleting
perceived fun and perceived ease of use in model 1 to make better fit measures. Model 3 wascreated by deleting the non-significant path from subjective norm to behavioral intention in
Model 2. Model 4 was created by deleting the non-significant path from PBC to behavioral
intention in Model 3. Table 3 shows the fit measures for the four models for Bangladesh data.
All fit indices are in the acceptable range for model 4. These results indicate that Model 4 has
the smallest AIC value (132.18) and has the information criterion with the most significant
estimated coefficients. Therefore, it was selected as the best model. The values for GFI(0 .947) and AGFI (0.914) exceeded 0.9 and are thus in the acceptable range. The RMSEA is
0.049, which is less than 0.05 and thus considered to be a good fit (Tsang et al. 2004). Table
3 shows that the goodness of fit of generated or re-specified models are better compared tothe hypothesized model. In summary, generated values for model 4 are superior to those forthe other models.
Table 3

Values of Model Selection Criteria on Each Model for Bangladesh

Model 1 (hypothesized model)
Model 2 (without PF->ATT
and PEOU->PF)
Model 3 (without SN->BI)
Model 4 ( without PBC->BI)

GFI
0.804

AGFI
0.749

RMSEA
0.109

CFI
0.798

AIC
737.8

BCC
749.6

0.877

0.825

0.107

0.853

357.8

363.8

0.947
0.947

0.913
0.914

0.050
0.049

0.973
0.973

133.1
132.1

137.0
135.9

Since the hypothesized model (Figure 2) did not achieve model fit, the explanation of
hypotheses result is based on generated or re-specified model 4. Model 4 shows the highest
applicability and well fitting for Bangladesh among all models in this research. The final
model for Bangladesh is shown in Figure 3. The coefficients of the measurement variables
that explain the latent variables are all significant at the level of 0.1% or less. Therefore, themeasurement variables generally appear to explain the latent variables well. Hypotheses from
H1 to H5 in model 4 were supported in our analysis for Bangladesh.
H1: Mobile users’ perceived behavioral control towards MES has a direct positive impact on
their perceived value to use MES with standardized estimate of 0.221 and the hypothesis is
accepted.
H2: Mobile users’ perceived behavior control towards MES has high positive impact on theirattitude to use MES with standardized estimate of 0.452 and the hypothesis is accepted.
H3: Mobile users’ perceived value towards MES has positive impact on their attitude to use
MES with standardized estimate of 0.214 and the hypothesis is accepted.
H4: Mobile users’ attitude towards MES has a direct positive impact on their intention to use
MES with standardized estimate of 0.250 and the hypothesis is accepted.
H5: Mobile users’ perceived value towards MES has positive impact on their behavior
intention to use MES with standardized estimate of 0.243 and the hypothesis is accepted.

Fig. 3. Path Analysis of Model 4 for Bangladesh at significance level
Note: ***p <0.001; **p <0.05; *p <0.1.
Table 4Standardized Estimates on Model 4 for Bangladesh
Hypotheses

Paths

Standardized
Estimate

S.E.

t- value

H1

Perceived behavioral control !Perceived
value

0.221**

0.227

2.619

H2

Perceived behavioral control !Attitude

0.452***

0.088

5.105

H3

Perceived value !Attitude

0.214**

0.029

2.714

H4

Attitude !Behavioral intention

0.250**

0.136

2.904

H5

Perceived value ! Behavioral intention

0.243**

0.050

2.820

Note: ***p <0.001; **p <0.05; *p <0.1.
Our hypothesized model 1 with additional constructs: perceived fun, and perceived easeof use did not show a good model fit. There are some previous researches that also suggestingthat perceived enjoyment does not positively influenced the using behavior to use atechnology system (Fagan et al., 2008; Shin & Kim, 2008; Venkatesh et al., 2002). So, itappears to have happened for model 1.
We observed from our result that perceived behavioral control, perceived value andattitude are positively significant determinants on intention to use. We got positive significant
values of standardized estimate for the dependent and independent variables. The resultshows that behavioral control concerning mobile information services is a very importantdriver of attitude. Then Attitude has strong positive indicator for behavioral intention. We canstate that attitude and perceived value is important indicator for behavioral intention. Also,
Perceived behavioral control is a good determinant of perceived value and perceived value
has moderate influence on attitude.
Our results of selected model 4 are generally compatible with the results on MES reported
in Kondo and Ishida (2014). Our result also an agreement on gaming services reported in
Nysveen et al., (2005) concerning Norwegian customers. Perhaps, our data was for 2014 and,
Kondo and Ishida (2014) was for Japan and USA data in 2009. There had time difference but
the results seem similar because Bangladesh in 2014 is at the same stage of provided 3G
mobile services where USA and JAPAN were in 2009. The result provided an interesting
implication that the TAM-TPB model could be applied in both developed countries and adeveloping country after the adjustment of technology diffusion timing.
6.

Discussion

Our results for Bangladesh mobile service usages by young adults through our proposed
TAM-TPB model have led to similar results to those of Nysveen et al., (2005) concerning
Norwegian customers and Kondo and Ishida (2014) concerning USA and Japan customers.
Our result in the best TAM-TPB model confirmed the significant paths from perceived
behavioral control to perceived value and perceived value to attitude. This means that users’
positive attitude is influenced by the positive value perception of using MES. The perceptionof value is affected by the user’s positive perception of their ability to using entertainment
services. Our analysis also found strong impact of attitude to behavioral intention, perceived
behavioral control to attitude and perceived value to behavioral intention for MES.
Bangladeshi users find that mobile phones are very important device in daily life, apartfrom talking they have perceived many other benefit from mobile phone like hearing music,
playing games, download ringtones, etc. which made this attitude strong for good intention touse mobile phone for entertainment and behavior to adopt it. Their intention to adopt MES
appears to be determined to a greater extent by perceived benefits that they are receiving.
Bangladeshi young users feel that they have skills, ability, money, time and others resources
to use MES such as game, music, ringtone.
Our analysis found that hypothesized model with perceived fun has not fitted well for
Bangladesh. This result is consistent with previous researches by Khalid and Noor (2009) for
Jordan and Dai and Palvia (2009) for China. Students of Jordan use the mobile phone forother purposes such as making and receiving calls, SMS service, discussing studying issues
but not for enjoyment. Chinese young focus on needs, values and expenses rather thanhedonic characteristics of mobile commerce in their intention to use. The plausible reasonsfor Bangladesh can be entertainment system and structure via mobile phone might have notdeveloped enough that young users do not find fun aspects. Bangladeshi students may have
many services to enjoy more than MES, such as, internet music, computer games, sports, etc.
We may be able to summarize that perceived fun is not supported for developing countries
whereas it is supported for developed countries. Providing high enjoyment quality withaffordable price in entertainment services needed to be addressed for future.
Subjective norm was not a good indicator of Behavioral Intention to use in our research.
This follows what were found in previous research of Kondo and Ishida (2014) andOkazaki et al., (2008). They also exclude subjective norm from their model. Since theparticipants in this study are young people who have good education and experience withtechnology, the effect from Social Influence may decline.
Clearly, there are more similarities than differences among the youth “intention to use”
MES on TAM-TPB framework. Mobile entertainment technology appears to be a‘‘nice-to-have’’ accessory among the cross-border youth segments. As yet, however, there
are few empirical studies of the factors connecting youth and adoption of mobile
entertainment technology. Therefore, this pattern can be considered as universalities ofmobile entertainment service use on youth segment.
If the determinants of perceived value, attitude and perceived value have a measurable
effect on usage intention in some countries, then there is an opportunity that it will be
accepted by another country also. Therefore, it can be said that this framework is useful ininternational markets by being able to identify opportunities and threats to consumer
acceptance of mobile services. Our analysis also has providing an expectation of further
expansion of its future market among young generation in a developing country.
Young generations in Bangladesh want to be more entertained by using the newlyintroduced technologies of 3G spectrums and the smart phones. Also, gaming is the second
most used 3G services in Bangladeshi young users (78.9%) (Tajmary et al., 2013). These cansurmise that Bangladesh mobile entertainment service market is a potential market for themobile entertainment business now. Therefore, it demands to adopt the correct marketingstrategy and business model to catch on the potential customers.
7.

Limitations

Our study has some limitations. All of the respondents are young students who have goodeducation and knowledge in technology who had attended business classes of several
universities in a capital city. Also, they are convenience samples. Thus the results cannot be
generalized to the whole population in Bangladesh. Although the limitations exist, the usageof such samples provides useful insights on describing an emerging market of MES among
young adults who are innovative users, which are otherwise not available
8.

Conclusion

This study represents an attempt to explain mobile ringtone, music and gaming adoption
in Bangladesh context. Despite increasing empirical research, there is a serious lack ofstudies that examine specific mobile entertainment service applications in Bangladesh. Our
study serves as one of the good attempts in this area. The study conducted the survey basedon the modified TAM-TPB model captures relevant antecedents of the attitude-intention
chain for Bangladeshi young. The result provides a good fit and significantly positive results
for the model with four constructs: Behavioral control, perceived value, attitude, andbehavioral intention to use mobile services. The estimated coefficients shows that thegenerated model fits generally well with the data for Bangladesh. The outcomes from thisstudy revealed that the TAM-TPB model with attitude, perceived behavioral control andperceived Value could be applied to understand Bangladeshi young behavioral intention touse MES. However, perceived fun was not supported for Bangladesh, possibly in developing
countries. Our result indicates that whenever customers make decision to use mobile ringtone,
music and gaming application, they will think whether these are worth to use or not.
Concerning the impact of perceived value, perceived behavioral control and attitude on
intention to use MES, we found almost similar results in Bangladesh to the previous research
results in Japan and USA. In order to examine the applicability of the TAM-TPB framework,
we recommend researchers to conduct researches on these three factors for intention to use
MES in different countries, especially developing countries.
For the better development of the competitive mobile entertainment service market in
Bangladesh, the developer should note our findings that the three factors are the important
determinants for intention to use MES. It may be possible to assume from our study that ahomogeneous youth segment exists across borders. This segment seeks innovativetechnology that provides enjoyable and efficient pastimes, in which young consumers
perceive these three factors as important determinants of behavioral intention to use MES.
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