Factors affecting intentions to use mobile content services in Ho Chi Minh city

ABSTRACT The main purpose of this study is to examine the factors that affect customers’ behavioral intention to use mobile content services, which enhance the understanding of Vietnames

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

HUYNH TRAC SIEU

FACTORS AFFECTING INTENTIONS TO USE

MOBILE CONTENT SERVICES

IN HO CHI MINH CITY

MASTER OF BUSINESS (Honours)

Ho Chi Minh City – Year 2014

UNIVERSITY OF ECONOMICS HO CHI MINH CITY

International School of Business

HUYNH TRAC SIEU

FACTORS AFFECTING INTENTIONS TO USE

MOBILE CONTENT SERVICES

IN HO CHI MINH CITY

ID: 22120137

MASTER OF BUSINESS (Honours)

SUPERVISOR: DINH CONG KHAI, PhD

Ho Chi Minh City – Year 2014

ACKNOWLEDGEMENT

First and foremost, I respectfully express my gratefulness to my research instructor,

Dr Đinh Công Khải for his warmly supports, taking the time from the beginning of the research to shape my research design and during every step of the thesis process

To my ISB Research Committee (IRC), I would like to thank for your recommending and putting me back on track of research Besides, I would be grateful to Professor Nguyễn Đình Thọ for his encouragement, insightful recommendations, and value requirements during my process

My sincere thanks also come to my teachers at International Business School - University of Economic Ho Chi Minh City who provide a lot of knowledge for me during my MBA course

I would also like to thank many different individuals who help me in my developing research, especially the professional mobile development department in UFS International Inc Moreover, I owe thanks to my close friend – Hồ Quang Chi Bảo; your assistances and contributed comments made my research measurement scales more accurate and fit

Furthermore, I would like to specially send my thanks to my classmates, my friends who are working in banks, schools, industrial zones, software development companies, and mobile application development companies for their support during

ABSTRACT

The main purpose of this study is to examine the factors that affect customers’ behavioral intention to use mobile content services, which enhance the understanding of Vietnamese mobile consumers as client of technology services The proposed research model base on Technology Acceptance Model (TAM) and the consideration of Yang and Yoo (2004), whereas both affective and cognitive attitudes as two parts of attitude construct in TAM

In this study, perceived convenience and perceived mobility are also introduced as external factors that reflect the behavioral intention to use mobile content services,

in addition, the mediating role of affective attitude between cognitive attitude and behavior intention is investigated

The study analyzed a sample of 505 consumer responses in Ho Chi Minh City, the results showed that all the cognitive and affective attitudes, perceived mobility, perceived convenience, perceived usefulness and perceived ease of use - have impact on the behavioral to use mobile content services via direct-effect, indirect-effect or both

The finding of this research most focused on providing a guideline for future direction of mobile content services, especially most focus on the attitude change toward using the mobile services

Keywords: Mobile content services, behavioral intention, cognitive attitude, affective attitude, perceived mobility, perceived convenience

TABLE OF CONTENTS

ACKNOWLEDGEMENT ii

ABSTRACT iii

LIST OF FIGURES vi

LIST OF TABLES vii

LIST OF ABBREVIATIONS viii

CHAPTER 1 INTRODUCTION 9

1.1 Research Background 9

1.2 Research Motivation 11

1.3 Research Objectives 12

1.4 Research Scopes 12

1.5 Significance of the Research 13

1.6 Research Methodology 13

1.7 Structure of Research 13

1.8 Summary 14

CHAPTER 2 LITERATURE REVIEW AND RESEARCH MODEL 15

2.1 Mobile Content Services 15

2.2 Theory of Reasoned Action 17

2.3 Theory of Planned Behavior 18

2.4 Technology Acceptance Model 18

2.4.1 Revised Original TAM with Separate Affective and Cognitive Attitude 20 2.4.2 Perceived Convenience – An External Variable of TAM 22

2.5 Perceived Mobility 23

2.6 Research Model and Hypothesis Development 23

2.6.1 Theoretical Model 23

2.6.2 The Competitive Model 27

2.7 Summary 28

CHAPTER 3 RESEARCH METHODOLOGY 29

3.1 Research Process 29

3.2 Construct Measurement 31

3.3 Measurement Refinement 33

3.3.1 Qualitative Pilot Study 33

3.3.2 Quantitative Pilot Study 34

3.4 Main Study 38

3.5 Data Analysis 40

3.5.1 Confirmatory Factor Analysis 40

3.5.2 Structural Equation Modeling 40

3.6 Summary 41

CHAPTER 4 DATA ANALYSIS AND RESULTS 43

4.1 Sample Specification 43

4.2 Confirmatory Factor Analysis 44

4.3 SEM Approach for Theoretical Model 48

4.4 Optimized the Theoretical Model 50

4.5 Competitive Model Test 52

4.6 Applying Bootstrap Procedure 55

4.7 Hypotheses Testing 57

4.8 Construct Effects 59

4.9 Models’ Generalized Squared Multiple Correlation 60

4.10 Summary 61

CHAPTER 5 CONCLUSIONS, IMPLICATIONS AND LIMITATIONS 62

5.1 Conclusions 62

5.2 Managerial Implications 64

5.3 Limitation and Further Research 65

REFERENCES 68

Appendix A 77

Appendix B 83

Appendix C 86

Appendix D 89

Appendix E 90

Appendix F 93

LIST OF FIGURES

Figure 2.1 The Theory of Reasoned Action model……… 17

Figure 2.2 Theory of Planned Behavioral 18

Figure 2.3 First modified version of TAM 19

Figure 2.4 Final version of TAM 19

Figure 2.5 TAM with Affective and Cognitive Attitude 21

Figure 2.6 Revised TAM with Intention, Affective and Cognitive Attitude 21

Figure 2.7 The proposed theoretical model 24

Figure 2.8 The competitive model 28

Figure 3.1 Research process 30

Figure 4.1 Saturated model of the theoretical model 46

Figure 4.2 Standardized SEM results for theoretical model 49

Figure 4.3 The optimized theoretical model 51

Figure 4.4 The Standardized SEM results of Competitive Model 53

Figure 4.5 The final research model 56

LIST OF TABLES

Table 2.1 Summary of Supporting Works for Research Proposition 27

Table 3.1 Cronbach’s Alpha 36

Table 3.2 EFA Results 38

Table 3.3 Summary of the Data Collection Process 40

Table 4.1 Respondent Demographic 44

Table 4.2 Correlations between Constructs 47

Table 4.3 Measurement Validation 48

Table 4.4 Construct Relations 48

Table 4.5 Relations of Constructs (Standardized) 52

Table 4.6 Competing Measurement Modeling 54

Table 4.7 Summary of Models 54

Table 4.8 Competitive Model-Relations of Constructs (Standardized) 55

Table 4.9 Bootstrap Results (Final Model) 55

Table 4.10 Hypotheses Test – Results (Standardized) 57

Table 4.11 The Direct, Indirect and Overall Effects 59

Table 4.12 The Squared Multiple Correlations (R-squared Values) 60

Table A1 Original Measurement Scales 77

Table A2 Measurement Scale (Draft Questionnaire) 78

Table A3 Final Measurement Scales (Final Draft Questionnaire) 80

Table D1 KMO and Bartlett's Test 89

Table E1 Assessment of Normality 90

Table E2 Estimates of Saturated Model (Unstandardized) 91

Table E3 Standardized Regression Weight(Saturated Model) 92

Table F1 Covariances – MI for Theoretical Model 93

Table F2 SEM – Estimates Optimized Model (Unstandardized) 93

Table F3 SEM – Estimates Optimized Model(Standardized) 94

Table F4 SEM – Estimates Competitive Model (Unstandardized) 95

Table F5 SEM – Estimates Competition Model(Standardized) 96

Table F6 Bootstrap – Final Selected Model (Standardized) 97

Table F7 SEM – Variances of Residuals, Independent Constructs 98

Table F8 Bootstrap – Bootstrap Distributions (Final Model) 99

Table F9 Squared Multiple Correlations 101

Table F10 Standardized Residuals for Theoretical Model 102

Table F11 Standardized Residuals for Optimized Model 103

LIST OF ABBREVIATIONS

CHAPTER 1 INTRODUCTION

This chapter introduces the background of mobile content services in general and a basic description of mobile content services in particular Subsequently, the research motivation, research objectives, research scopes and methodology are mentioned

1.1 Research Background

This research focuses on main factors affecting the behavioral intention to use mobile content services (MCS) among Vietnamese consumers The relevance of the topic relates to important themes: the theme of continuous information technology (IT) development and the theme of information technology acceptance and use These themes are extremely meaningful to the business sector because business process under information technology revolution is transforming the way we do business (Mahabir & Geeta, 2013)

Over the last few years, the developments of IT have pushed strong motivation forces on mobile technology Therefore, mobile technology has grown up rapidly and brought a key impact on human life, as the number of mobile devices has reached 4.6 billion in the world (CBSnews, 2010) Gartner (2011) has reported that mobile applications would not only generate $15.9 billion in expected end-user spending in 2012, but also drive other smartphone segments such as advertising spending, phone device sales and mobile technology innovation By offering context-aware features that provide various function services to a user’s mobile environment, mobile content services have redefined the user experiences and shaped a highly competitive marketplace, which enchants the interest of a number

of stakeholders including device vendors, merchants, mobile application developers and marketing firms

According to IDC’s Vietnam Quarterly Mobile Phone Tracker, a total 5.8 million mobile phones have been shipped to Vietnam in the second quarter of 2013 In

addition to the huge smartphone devices used, the internet users and mobile subscriber penetration of Vietnam are rated highly compared to others in Southeast Asia The proportion of mobile subscribers sways the sceptre with 174% and internet usages are just lower than Singapore and Thailand (IMF, 2010) Compared

to other countries in ASEAN, the Vietnamese market is at the maturity state of laptop product life cycle with the highest demand when it has reached a state of equilibrium, while smartphones and tablets are potential with low start Regarding the data usage, there are 2.1 billion advertisements served to mobile devices in Vietnam every month; that is more than 805 advertisements every second passing through mobile devices (ITU, 2012), 62% of Vietnam’s internet users accessed via mobile devices and mobile internet user in Vietnam reached 19 million – according

to Mobile Day Vietnam (2012) Ernst and Young’s Advisory Services (2013) state regarding the mobile money, a part of mobile content services, as follows:

We are convinced that the growth of mobile money services will be one of the most significant trends of the coming years It promises many new benefits for users around the world and is undoubtedly going to shape the telecommunications, technology and financial services industries (p 5)

The increasing roles of mobile devices and mobile content services in Vietnam based on the facts presented above have explained the reason why it is significant to investigate mobile content services

Technology is one of the important factors profoundly changing the nature of services and the way in which firms interact with their customers (Bitner, 2001) Customers with their complex behaviors involve the use and disposal of products and services However, “how to know” the consumer behaviors is difficult and complex to research, especially in technology market segment Accordingly, explaining consumer acceptance of new technology such as mobile data content services has been a longstanding research Since the financial cost for mobile technology infrastructure has often been invested at high budget, it is wasted for

companies if they do not get enough mobile clients for their profit Currently, there are dramatically successful Vietnamese mobile content services providers such as Mobifone, VinaPhone, Viettel, nhacuatui.com, and Zing However, many other companies got failure and withdrew their businesses such as Beeline and Hanoi Mobile Over the past two years, the mobile market in Vietnam has taken major steps forward but mobile content services have not matched potential Despite the rapid growth in the mobile content services, research towards consumers’ intention behavior is scarce

Hence, this study focuses on the factors affecting the behavioral intention of mobile content services and tries to clarify the factors influence the consumers’ behavioral intention in the context of Vietnam mobile market’s development

1.2 Research Motivation

As numerous mobile devices are used for multi purposes, mobile content services provide many convenient ways for mobile clients to easily access information by mobile devices Huge new mobile services are provided but the acceptance of these services has always been the big question and needs to be answered Regarding the acceptance of mobile technology research, many studies have been conducted (Suoranta, 2003; Cheong & Park, 2005; Kaasinen, 2005; Lu, Yao & Yu, 2005) Since a lot of studies focused on mobile banking such as research done by Sripalawat, Thongmak, and Ngramyarn (2011), Suoranta and Mattila (2004), Yang (2009) or on mobile internet (Ying & Shieh, 2009), “Mobile Content Services” is the new concept that covers a set of “mobile communication services”, “mobile commercial services”, “mobile entertainment services”, and “mobile information services” However, there are limited studies pertaining to what are the factors that affect customers’ behavior intention to use mobile content services, especially in Vietnam market

According to the reviews above, this study tries to figure out how to pinpoint the significant factors that affect the behavioral intention to use mobile content services among Vietnamese consumers This also provides solutions or implications to enhance opportunities for mobile services providers so that they can sustainably develop mobile content services market in Vietnam

1.3 Research Objectives

The main objective of this study is to examine the factors that affect customers’ behavioral intention to use mobile content services, enhance our understanding of Vietnamese mobile consumers as clients of technology services In specific the objectives are:

(1) To examine the causal factors that affect consumers’ behavioral intention to

use mobile content services;

(2) To examine the important effects of cognitive and affective attitude on

behavioral intention to use mobile content services

1.4 Research Scopes

According to the research objectives, this study focuses on Vietnamese mobile users Moreover, this research is conducted in Ho Chi Minh City (HCMC) – the biggest city located in the South of Vietnam Currently, HCMC is the economic, technology and financial hub of Vietnam, which attracts migrants from other provinces As a result of this, the city’s official population was 7,990,100 in 2013 (General Statistics Office, 2013) Therefore, this place has more mobile users than other places or areas

Again, customers in this study are limited to individual mobile clients and not institutions or groups who are also customers of many mobile content services providers in Vietnam Finally, the research only focuses on the factors affecting behavioral intentions to use mobile content services, hence, the other dependent

factors such as “use behavior” and “actual use” are out of the contents of this research

1.5 Significance of the Research

This study contributes to the application of the attitude change process It is a meaningful outcome for researchers in analysis the process of attitude change It also embosses the important roles of other factors affect on behavioral intention to use mobile content services in Vietnam market Regarding the managerial implications, these finding help managers to control the attitudes change and next, improving the user’s acceptance of technology It brings valuable practical implications for mobile operators so that they can improve the usage of mobile content services

1.6 Research Methodology

This study utilizes two forms of qualitative and quantitative research The research includes pilot study and main study Firstly, the pilot study is undertaken by qualitative and quantitative methods while the main study is used quantitative method Secondly, in the pilot study, a draft of questionnaires is created; after that,

it still needs a refining for the final questionnaire Next, in the main study, the final questionnaires are distributed via email, social network and in hardcopy to respondents In order to reduce time during sampling process, the convenience sampling is used Finally, the analysis tools such as IBM SPSS 22, IBM AMOS 22 and Microsoft Excel 2012 are used for data analysis process Chapter 3 provides more details of research methodology

1.7 Structure of Research

The structure of research consists of five chapters:

Chapter 1: Introduction

This chapter introduces the readers to the background of mobile content services in general, as well as, research motivation and research objectives Subsequently, research scope, research methodology and research structure are outlined

Chapter 2: Literature Review and Research Model

In this chapter, the author provides the literature reviews that concern the mobile content services, theoretical models and competitive model Finally, the research model is presented

Chapter 3: Research Methodology

This part presents brief description of the research methodology, which includes the research process, construct measurements, measurement refinement, main study and data analysis methods

Chapter 4: Data Analysis and Results

Chapter 4 presents the sample specification and data analysis Based on the results, the author draws conclusions for the proposed hypotheses

Chapter 5: Conclusions, Implications and Limitations

This chapter presents the main conclusions, implications and limitations Moreover, the recommendations for future research are also provided

1.8 Summary

The research begins with the introduction, which discusses the research background

of mobile content services in general Then the research motivation explains why there is a need for this research It summaries the status and gaps of mobile content services, since a lot of study focused on mobile application; however, there are limited studies pertaining to what the factors affect consumer’s behavioral intention

to use mobile content services, especially in Vietnam Based on the research objectives and resources, the scope of research is the examination of the individual mobile clients who use the mobile devices and data content services in Ho Chi Minh City Finally, the overviews of research methodology and research structure are presented The next chapter presents the literature review, research model and hypothesis development

CHAPTER 2 LITERATURE REVIEW AND RESEARCH MODEL

This chapter focuses on five important contents: (1) Mobile content services definitions; (2) the major theories built from belief, attitude, intention and technology acceptance model (TAM); (3) Attitude with separated cognitive and affective constructs; (4) Perceived convenience and (5) Perceived mobility characteristics reviews After theoretical reviews, the research model and hypotheses are proposed accordingly

2.1 Mobile Content Services

Mobile Content Services are services process in which customers participate with their mobile devices to get multifarious contents These contents are provided by the service providers as an outcome and delivered to the customer’s mobile device or to the customer in any other forms (Niemela, 2006) Mobile content services are delivered to or used with mobile phone via public telecommunications network Payment for these services may occur immediately by card or other ways such as post payment through user’s phone bill, deducing mobile prepaid account

Mobile content services are results of technological innovations as outcome of information technology revolution Mobile content services and mobile applications

do not exist separately; they merged and quickly emerged together due to the convergence of Internet, Media, Social Media, Information technology and telecommunications technology Mobile content services consist of digital services which are added to mobile networks or integrated into mobile devices other than traditional voice services; hence, it is postulated that the benefit offered by these services are highly diverse (Bouwman, López-Nicolás, Molina-Castillo & Van Hattum, 2012)

Because of the convergence of technology as discussed above, the terms Mobile Content Services, Mobile Data Services and Mobile Applications have often been

used interchangeably by various studies Fang and colleagues (2006) categorize the type of mobile services based on their objectives into three types:

(1) General tasks: These tasks do not involve transaction and gamming such as mobile email, mobile SMS, browse website, map and search location services

(2) Transaction tasks: These tasks include mobile banking, mobile money and online purchase via internet-store

(3) Entertainment tasks: These tasks include gaming and entertainment data services such as mobile game, vote/contest via value added public number, polyphonic ring tones, downloading logo, wallpapers, listening music via mobile network and standby background music

These three types of tasks differ in their objectives The objective of general tasks is

to search information or communicate with other parties whereas the goal of transaction tasks is to commit financial transactions The purpose of entertainment tasks is to entertain their performers All of the three tasks above can be found in Vietnam

Besides, the International Telecommunication Union (ITU) classifies mobile data services into four categories: communication services, information content services, entertainment services and commercial services (ITU, 2002; Sadeh, 2002) Mobile communication services, which are the most widely used form of mobile content services, include short message service (SMS), multimedia message service (MMS), e-mails and mobile chatting (ITU, 2002) Mobile entertainment services include ring-tones, digital characters, horoscope, mobile gamming, mobile video, and mobile music Information content services deliver information contents such as weather news, maps, sport news, traffic information, location based information and news headlines Finally, commercial services enable consumer to purchase financial transactions, booking online, shopping and payment online All of four categories can be found in Vietnam

2.2 Theory of Reasoned Action

Figure 2.1 shows a model of the Theory of Reasoned Action (TRA), which is proposed by Fishbein and Ajzen (1975)

Figure 2.1 The Theory of Reasoned Action model (Ajzen & Fishbein, 1980)

The ultimate objective of TRA is to predict and discover an individual’s behavior (Ajzen & Fishbein, 1980) Ajezen and Fishbein recommend that individual’s actual behavior can be determined by considering his or her prior intention along with the beliefs that a person have for the given behavior According to TRA, individual’s intention consists of two basic determinants: attitude that a person has toward the actual behavior and subjective norm associates with the behavior in question Suggesting that attitude of a person toward behavior (A) can be measured by calculating the sum of the product of all salient beliefs ( : consequences of performing that behavior) and an evaluation ( ) of those consequences, we have the formula as below:

A = ∑ The subjective norm (SN) can be determined by considering the sum of the product

of a person’s normative beliefs (n ) which is the perceived expectation of other individuals or groups and his or her motivation to comply ( ) The formula for measuring the subjective norm along with an actual behavior:

SN = ∑ Hence, the individual behavior intention (BI) can be determined by one formula as below:

BI = A + SN

TRA provides a useful model that can explains and predicts the actual behavior of

an individual fairy well

2.3 Theory of Planned Behavior

Ajzen (1985) has extended TRA model by proposing the Theory of Planned Behavior (TPB) Actually, the TPB model is not different from TRA model In addition, it takes into account one new construct: perceived behavioral control (PBC) PBC refers to the perception of control over performance of a given behavior PBC is predicted by the effect of two beliefs: control belief and perceived facilitation Control beliefs include perceived availability of skills, resources and opportunities, whereas perceived facilitation is the personal assessment of available resources to the achievement of a given set of outcomes (Mathieson, 1991) Figure 2.2 shows the model for the TPB

Figure 2.2 Theory of Planned Behavioral (Matheison, 1991)

2.4 Technology Acceptance Model

The Technology Acceptance Model (TAM) applies Fishbein and Ajen’s Theory of Reasoned Action (TRA) as theoretical basic to explain causal relationship between the variables in the model (Davis, Bagozzi & Warshaw, 1989) See Figure 2.3 for the first modified version of TAM

Figure 2.3 First modified version of TAM (Davis et al, 1989)

This version posits that technology acceptance can be explicated by two variables:

“perceived usefulness” and “perceived ease of use” Perceived usefulness is defined

as “the degree to which a person believes that using a particular system would enhance his or her job performance” Perceived ease of use is defined as “the degree

to which a person believes that using a particular system would be free of effort” Although perceived usefulness and perceived ease of use are not only variables affecting acceptance, they seem to hold a central role (Davis, 1989) This model also shows that there is case when given system, perceived usefulness and one person may have a strong behavior intention to use the system without pass through any attitude That means there is a direct link between perceived usefulness and behavioral intention bypass the attitude variable

Davis et al (1989) use above model to deploy a study with 107 users to measure their intention to use system after one-hour introduction about the system and repeat

14 weeks later Their results show that both “perceived usefulness” and “perceived ease of use” influence directly on behavior intention to use, thus they eliminate the role of attitude construct from the model See Figure 2.4 for the final version of TAM

Figure 2.4 Final version of TAM (Venkatesh & Davis, 1996)

2.4.1 Revised Original TAM with Separate Affective and Cognitive Attitude

As previous review, attitude is one construct of first version of TAM It uses Fishbein and Ajen’s Theory of Reasoned Action (TRA) as theoretical basic to explain the causal relationship between the variables in model (Davis et al., 1989) However, in the last version, Davis and his colleagues eliminate attitude construct out of model (Figure 2.4) Although Davis and his colleagues omit attitude from TAM, many other studies have used the original TAM (included attitude), for instance, Agarwal and Prasad (1999); Lu, Yao, and Yu (2005); Curran and Meuter (2005) Thus, it is extremely difficult to compare these studies with contradictory findings about attitude since consistent measures of attitudes are not used across studies

Based on TRA, TAM conceptualizes attitude as an affective unidimensional construct Contrary to TAM, Cacioppo, Petty, and Crites (1994) have argued: “the most common classification for the basis of attitude is affect and cognition” The affective dimension of attitude focuses on how much the person likes the object of thought and measures the degree of emotional attraction toward the object On the other hand, the cognitive dimension of attitude refers to an individual’s specific beliefs related to the object and consists of the evaluation, judgment, reception or perception of the object of thought based on values

Yang and Yoo (2004) believe that attitude might have important effects on information system use so that it needs to be reconsidered in the TAM They also

propose that instead of eliminating the attitude construct as Davis et al (1989)

worked, two cognitive and affective attitude dimensions are considered (Figure 2.5)

In there, “the cognitive dimension of attitude directly influences individual information system use, while the affective dimension needs to be treated as an overcome variable of its own” Consistent with this perspective, the cognitive attitude describes the expected performance of the system and the affective attitude

is closely related to the appeal and usability of the system (Zaad & Allouch, 2008)

Figure 2.5 TAM with Affective and Cognitive Attitude (Yang & Yoo, 2004)

Based on the TAM from Davis et al (1989), Yang and You’s (2004) research, with the addition of behavioral intention back as mediator between attitude and usage, Wang and Liu (2009) develop a conceptual model of cognitive and affective attitude toward behavioral intentions to use Railway’s Internet Ticket System in Taiwan The results of their case studies show that both affective and cognitive attitudes positively influence behavioral intention (Figure 2.6)

Figure 2.6 Revised TAM with Behavioral Intention, Affective and Cognitive

Attitude (Wang & Liu, 2009)

According to Yang and Yoo (2004), the affective dimension of attitude is influenced by beliefs and the beliefs can be evaluative or non-evaluative (true or false) The cognitive attitude can be assigned as an evaluative belief and developed from non-evaluative beliefs and values, whereas, evaluative beliefs in turn develop into affective attitude (like or hate) Therefore, Yang and Yoo (2004) point out that

“there is a hierarchical relationship among these four constructs: affective attitude is influence by cognitive attitude, which is affected by non-evaluative beliefs, which is

in turn developed by values” The empirical test of Yang and Yoo (2004) found a positive influence of cognitive attitude on affective attitude

Again, “attitude” might also have an effect beyond a direct impact on intention Several studies have investigated the positively effect of attitude on behavioral intention, such as, the original TAM (Davis, 1986), the models of Taylor and Todd (1995a), Morris and Dillon (1997)

2.4.2 Perceived Convenience – An External Variable of TAM

To consumers who use products or services, convenience depends on effort and time (Berry, Seiders & Grewal, 2002) Therefore, when a product or service saves time and effort for a user, it is considered convenient Some researchers posit that product or service is convenient when it lowers the emotional, cognitive and physical burdens for a user (Chang, Yan & Tsen, 2012) Another researcher defines the convenience of product or service by five elements: time, acquisition, use, execution and place (Brown, 1990) According to the definition of Brown (1990), the perceived convenience of the wireless network is measured in set of three elements: time, place and execution (Yoo & Kim, 2007) Yoo and Kim (2007) have defined perceived convenience as a level of convenience toward time, place and execution that user perceives when using the wireless network to complete a task Moreover, when examining the extended TAM with perceived convenience, they found that perceived convenience do not affect intention to use directly while perceived ease of use positively affects perceived convenience and perceived convenience positively affects perceived usefulness

In Cheolho and Sanghoon’s (2007) study, a set of four constructs (perceived usefulness, perceived ease of use, behavioral intention and perceived convenience) are used to examine a ubiquitous wireless LAN environment The results have showed that perceived ease of use positively affects perceived convenience; perceived convenience positively affects perceived usefulness

More recent research on investigating English learning through “personal digital assistant (PDA)” (Chang et al., 2012), which indicates a significantly positive effect

of perceived ease of use on perceived convenience, perceived convenience on perceived usefulness and perceived convenience on attitude toward using PDAs

Mobility may not be satisfied if there are not enough network signal coverage areas, the device battery is so weak or there is not enough mobile operators offering the mobile data services Hence, Krueger (2001) has predicted a demand for “payment roaming” and the pressure from users for co-operative solutions Such payment roaming includes both the mobile users wanting to process payments while travelling outside of network coverage or to make payments to other networks Buhan, Cheong, and Tan (2002) forecast that the good solutions would be able to interact with other solutions to create a global payment network

2.6 Research Model and Hypothesis Development

2.6.1 Theoretical Model

Taking into consideration the combined models of revised TAM with separate cognitive and affective attitudes , perceived convenience and perceived mobility, the specific relationships among the TAM constructs and identified variables - the theoretical model for this research are proposed (See Figure 2.7)

Figure 2.7 The proposed theoretical model

TAM explains the relationships between perceived ease of use, perceived usefulness, attitude toward using technology and behavioral intention as the followings: (1) perceived ease of use positively affects perceived usefulness; (2) perceived ease of use and perceived usefulness positively affect attitude toward using technology; (3) attitude toward using technology positively affects behavioral intention (Davis, 1986)

Regarding perceived ease of use positively affects perceived usefulness; there are many empirical tests, such as Davis (1986), Yang and Yoo (2004), Wang and Liu (2009), which prove that users perform well in tasks when they do not need to pay much effort Therefore, hypothesis H1 is proposed as follows:

H1: Perceived ease of use positively affects perceived usefulness

Back to research of Yang and Yoo (2004), the attitude toward using technology is developed to affective and cognitive attitude In there, attitude has both affective and cognitive components Zaad and Allouch (2008), Petty et al (1994) have argued: “the most common classification for the basic of attitude is affective and cognitive” As attitude has already been explained in the literature review of this chapter, many studies point out the different mediating role of two attitudes between

perceived usefulness, perceived ease of use and behavioral intention, such as Yang and Yoo (2004), Wang and Liu (2009), Alhabahba and colleagues (2012) As a result, this study attempts to answer the question “what is the causal relationship between two belief constructs in TAM (perceived usefulness and perceived ease of use) and two attitude constructs (affective and cognitive attitude) leading to behavioral intention?” (Yang & Yoo, 2004) Therefore, based on the changes in the attitudes and the original TAM framework, these following hypotheses are proposed

to reflect the relationships between the addition of the two construct of attitudes and other variables:

H2: Perceived usefulness positively influences cognitive attitude

H3: Perceived usefulness positively influences affective attitude

H4: Perceived ease of use positively influences cognitive attitude

H5: Perceived ease of use positively influences affective attitude

In addition, there are many studies confirmed attitudes have a positively influences behavioral intention, such as Taylor and Todd (1995a), Morris and Dillon (1997), and Davis (1986) According to Yang and You (2004), “The dyadic view presumes the affective and cognitive to be independent variables that affect behavioral intention” Other recent research on the Railway’s Internet Ticket System (Wang & Liu, 2009), which demonstrates that both cognitive and affective attitudes positively influence behavioral intention In their research, the beta coefficient from cognitive attitude to behavioral intention is stronger than the beta coefficient from affective attitude to behavioral intention Thus, using cognitive and affective attitude constructs instead of single attitude leads to the following hypotheses:

H6: Cognitive attitude positively influences behavioral intention to use mobile content services

H7: Affective attitude positively influences behavioral intention to use mobile content services

Reviewed the literature, cognitive attitude also positively influences affective attitude (Yang & You, 2004) The empirical study of Wang and Liu (2009) shows a positive influence of cognitive attitude on affective attitude Thus, there is likely such evaluative beliefs (cognitive attitude) in turn develop into clients’ affective attitude Hence, it hypothesizes that:

H8: Cognitive attitude positively influences affective attitude

The literature in this chapter shows that perceived convenience is an external variable of TAM Yoon and Kim (2007), Chang et al (2012) found that the perceived ease of use positively affects perceived convenience and perceived convenience positively affects perceived usefulness Namely, the easier the use of mobile system, the more convenient a user perceives it and the more convenient the user feels the mobile system is, the more useful one perceives it to be Based on these empirical results, this research defines three dimensions of perceived conveniences are place, time, execution, and then proposes the hypotheses:

H9: Perceived ease of use positively affects on perceived convenience

H10: Perceived convenience positively affects on perceived usefulness

Finally, back to the review of perceived mobility, perceived mobility is an addition variable to TAM, since the perceived mobility has been assigned as important factor that makes user accept the system (Hong et al., 2008; Amberg et al., 2003; Ajzen, 2002) Therefore, this study hypothesizes that perceived mobility might have a positive relationship with user’s behavioral intention to use mobile content services

H11: Perceived mobility has a positive influence on consumers’ behavioral intention to use mobile content services

The summary of supporting works for research proposition and theoretical model are presented on Table 2.1 and Figure 2.7, respectively

Table 2.1

Summary of Supporting Works for Research Proposition

Perceived

Usefulness

The degree to which a person believes that using a particular system would enhance his or her job performance

Davis et al (1989)

Attitude

The degree of attitude that an individual’s specific beliefs related to the object and consists of the evaluation, judgment, reception or perception of the object of thought based on value

Yang and Yoo (2004)

Affective

Attitude

The extent to which an individual likes the object of thought and measures the degree of emotional attraction toward the object

Yang and Yoo (2004) Perceived

Convenience

The level of convenience toward time, place and execution that one perceives when using the wireless network to complete a task

Yoon, C and Kim, S (2007) Perceived

Mobility

The extent to which "mobile services" are perceived as being able to provide pervasive and timely connections

Hong et al (2008) Behavioral

Intention

Behavioral intention toward system usage Venkatesh et al

(2012)

2.6.2 The Competitive Model

Beside the theoretical model, the competitive model takes an important role in creating scientific theory (Nguyen Dinh Tho & Nguyen Thi Mai Trang, 2011b) Zaltman, Lemasters, and Heffering (1982) (as cited in Nguyen Dinh Tho & Nguyen Thi Mai Trang, 2011b) recommend that the researcher should check for both the theoretical model and the competitive model instead of only focusing on theoretical model Bagozzi (1984) (as cited in Nguyen Dinh Tho & Nguyen Thi Mai Trang, 2011b) also suggests that the researcher must compare competitive and theoretical models in their current research rather than they do this in another research Bollen and Long (1993) (as cited in Nguyen Dinh Tho & Nguyen Thi Mai Trang, 2011b) claim the important role of checking the competitive model instead of testing only one theoretical model

According to previous researches regarding the necessary of building competitive model beside the existing theoretical model, this study suggests one competitive

model for the theoretical model Based on many researches relate to perceived convenience directly effect on behavioral intention to use services, for instance, Liao, Tsu, and Huang (2007) found that convenience value affects shopping motivation, which is a determinant of consumers’ intention to shop on the Internet Studies on Radio Frequency Identification (RFID) (Hossain & Prybutok, 2008) and online shopping (Gupta & Kim, 2007) reveal that perceived convenience is an antecedent factor that affects intention to use a mobile technology or system Gupta and Kim (2006) found that convenience has a positive impact on online shopping intention as well Therefore, the competitive hypothesis is proposed:

Hc: Perceived convenience positively effect on behavioral intention to use mobile content services

Based on the competitive hypothesis, the competitive model is formed (Figure 2.8) This competitive model is used to compare with the theoretical model to select the final research model

Figure 2.8 The competitive model

2.7 Summary

This chapter focuses on definitions and theoretical background of each concept within model The research model is formed by applying original TAM (Davis, 1986) and the revised attitude by Yang and Yoo (2004) In this study, the theoretical model and competitive model are proposed and then tested There are eleven hypotheses for the theoretical model and one addition competitive hypothesis for competitive model The next chapter discusses about the research methodology

CHAPTER 3 RESEARCH METHODOLOGY

The previous chapter reviewed the literature and proposed the theoretical model as well as hypotheses Chapter 3 briefly presents a description of the research method and clarifies how to develop the research measurement Both qualitative and quantitative approaches are employed in the study This chapter includes five parts: (1) the research process; (2) construct measurement; (3) measurement refinement; (4) main study and (5) data analysis methods for main study

3.1 Research Process

Two phases of study were conducted in this research: pilot study and main study The pilot study aims to explore certain issues before undertaking the main study The pilot study in this research was undertaken by qualitative and quantitative method while the main study used quantitative method This research focused on the factors affecting on the behavioral intention toward using mobile content services, especially the role of the cognitive and affective bases of attitudes in the behavior of mobile users Therefore, the unit of analysis was an individual mobile user The research site was Ho Chi Minh City, the principal business and technology center in Vietnam Most of respondents of this study were individuals who had experience in using mobile devices

The qualitative pilot phase employed three focus group discussion while the quantitative pilot phase adjusted and refined the final draft measurement The qualitative pilot study involved three focus groups who were skillful in mobile content services and professional in English Its purpose was to investigate the issues regarding the contents, number, structure and meaning of the measurement scales before the quantitative pilot study was conducted Next, in the pilot quantitative phase, the final draft questionnaires were sent to 150 mobile users who lived in District 1 and District 7, Ho Chi Minh City; however, only 130

questionnaires were valid Simultaneously, Cronbach alpha and exploratory factor analysis (EFA) were used to test the final draft measurement scales

The main study was conducted by quantitative method This research selected a sample size at 500 (n = 500) and the sampling was based on convenience sampling That mean all respondents were required to have enough information about the

“mobile content services” before he/she agreed to join the main survey The purpose

of main study was to test the measurement and structural models Hence, the measurement scales had been deeply test by composite reliability and confirmatory factor analysis (CFA) before the theoretical model with its hypotheses were tested

by structural equation modeling (SEM) Figure 3.1 presents the research process for the study

Figure 3.1 Research process

3.2 Construct Measurement

Based on the literature review, this study designed the measurement scales from previous researches (See Table A.1, Appendix A) for the model’s constructs and rephrased them to adapt the context of the current research All of measurement items used a 7-point Likert-type scale, anchored from 1 (completely disagree) to 7 (completely agree) The preliminary scales (Table A.2, Appendix A) were shown as follows:

• Cognitive and affective attitudes were measured by three items for each construct, which were borrowed from the scales of Yang and You (2004):

Cognitive attitude (CA)

- Mobile content services is a wise instrument for work/entertainment over mobile network (CA1)

- Mobile content services is a beneficial instrument for work/entertainment over mobile network (CA2)

- Mobile content services is a valuable instrument for work/entertainment over mobile network (CA3)

Affective attitude (AA)

- Using mobile content services makes me feel happy (AA1)

- Using mobile content services makes me feel positive (AA2)

- Using mobile content services makes me feel good (AA3)

• Perceived usefulness and perceived ease of use were adapted from Davis (1989):

Perceived usefulness (PU)

- I would find mobile content services to be useful in my daily life (PU1)

- Using mobile content services would be enable me to accomplish tasks more quickly (PU2)

- Using mobile content services in my tasks would increase my productivity (PU3)

- Using mobile content services would enhance my effectiveness on my tasks (PU4)

- Using mobile content services would make it easier to do my tasks (PU5)

- Using mobile content services in my task would improve my task performance (PU6)

Perceived ease of use (PEU)

- My interaction with mobile content services would be clear and understandable (PEU1)

- It would be easy for me to become skillful at using mobile content services (PEU2)

- I would find mobile content services easy to use (PEU3)

- Learning how to use mobile content services would be easy for me (PEU4)

- It would find it easy to get mobile content services to do what I want it to do (PEU5)

- It would find mobile content services to be flexible to interact with my tasks (PEU6)

• Perceived convenience (PC) was measured by four items borrowed from the scale of Yoo and Kim (2007):

- I can use mobile content services at anytime via the mobile network by my mobile devices (PC1)

- I can use mobile content services at any place via the mobile network by my mobile devices (PC2)

- Mobile content services provide a lot of convenience methods for me to engage in work/entertainment (PC3)

- In general, I feel that mobile content services is convenient for me to do work/entertainment (PC4)

• Perceived mobility (PM) was measured by five items from scale of Hong at al (2008):

- Mobility is an outstanding advantage of mobile phone with mobile content services (PM1)

- I would find mobile content services to be easily accessible and portable (PM2)

- I expect that mobile content service would be available for use whenever I need it (PM3)

- In general, I expect that I would have control over using mobile content services anytime and anywhere (PM4)

- I am able to use mobile content services anytime and anywhere (PM5)

• The behavioral intention to use mobile content services was measured by three items according to Venkatesh, Thong and Xu (2012):

- I intend to use mobile content services in the future (BI1)

- I will always try to use mobile content services in my daily life (BI2)

- I plan to keep using mobile content services as regularly as I do now (BI3)

3.3 Measurement Refinement

3.3.1 Qualitative Pilot Study

Based on the literature review, the author built the draft measurement scales for the study (See Table A.2, Appendix A) After that, the researcher started up the

“qualitative pilot study”, which involved three focused groups Two “mini groups” (Group A, Group B) were skillful in mobile content services and professional in English In there, five professional mobile application developers were selected for

“Group A”, while “Group B” included five experienced mobile users After “mini group discussion” and “in-depth interview” were conducted (Nguyen Dinh Tho & Nguyen Thi Mai Trang, 2011a), the author received some significant feedbacks and suggestions from the participants Next, the “full group” (Group C, 8 participants) was added to the other group discussion in Vietnamese to deeply investigate the issues regarding the contents, number, structure and meaning of the Vietnamese questionnaire After group discussions, five items were removed out of the preliminary scales:

- Perceived usefulness:

Removed “Using mobile content services would make it easier to do my tasks (PU5)”, due to all of the participants selected “PU5” belong to

“Perceived ease of use”

Removed “Using mobile content services in my tasks would improve my

tasks performance (PU6)”, due to it made confusions among “accomplish tasks more quickly (PU2), “increase my productivity (PU3)” and “enhance

my effectiveness (PU4)” in this study context

- Perceived ease of use:

Removed “I would find it easy to get mobile content services to do what I want to do (PEU5)” due to all of interviewees got confusions with this item Removed “I would find mobile content services to be flexible to interact with

my tasks (PEU6)” due to “flexible characteristic” would be measured in perceived convenience (PC) scale

- Perceived mobility :

Removed “I am able to use mobile content services anytime and anywhere (PM5)”, because “PC1” and “PC2” already measured the “time and place” characteristics

Lastly, the final draft questionnaire was formed and continued to use for quantitative pilot step (Table A3, Appendix A)

3.3.2 Quantitative Pilot Study

In the reliability analysis, high coefficient reliability means high consistency When Cronbach‘s Alpha is less than 35 means low reliability and Cronbach‘s Alpha is

more than 70 means high reliability (Cuieford, 1965) Acceptable reliability is no less than 50 (Nunnally, 1967) According to Connely (2011):

Cronbach’s alpha is used as only one criterion for judging instruments or scales It only indicates if the items “hang together”; it does not determine if they are measuring the attribute they supposed to measure Therefore, scales also should be judged on their content and construct validity (p 45)

According to Leech, Barrett, and Morgan (2005), the acceptable value of Cronbach’s alpha for reliability is greater than 70 However, it can reduce to 60-.69, especially if there is only a handful of an item in the scale However, if the Cronbach’s alpha is considerable high (greater than 90), it probably means that the items are repetitious or there are more items in the scale than are necessary for a reliable measure of the concept

Besides evaluating the value of the Cronbach’s alpha, the “Corrected Item–Total Correlation” needs to be considered Leech et al (2005) suggested that, if the

“corrected item-total correlation” is high (equal 40 or above), the item is probably correlated with most of the other items and make a good component of this summated rating scale If the “corrected item-total correlation” is negative or too low (less than 30), it is necessary to consider the item for wording problems and conceptual fit by modifying or deleting such items

This pilot study applied the acceptable threshold for Cronbach alpha should be equal or above 6 and the “corrected item-total correlation” exceeds 30, according

to Nunnally and Berstein (1994) (as cited in Nguyen Dinh Tho & Nguyen Thi Mai Trang, 2011b) The results showed that all seven scales had Cronbach’s alpha above 60 (the highest was 928 and the lowest was 835) and in addition, the “corrected item-total correlation” of each item exceeded 30 (the highest was 867 and the lowest was 647) The reliability of all scales was in the reasonable range Hence, all

observation variables in the final draft measurement scales were used for the next step (EFA) The results of Cronbach’s alpha test are presented in Table 3.1

Table 3.1

Cronbach’s Alpha

Observation Variable

Scale Mean if Item Deleted

Scale Variance

if Item Deleted

Corrected Item-Total Correlation

Cronbach's Alpha if Item Deleted Cognitive Attitude (CA): Alpha = 837

• Exploratory Factor Analysis (EFA)

The primary objectives of exploratory factor analysis (EFA) are to determine the number of factors affecting the measures and the strength of the relationship between each factor and each observed measure (DeCoster & Claypool, 2004) According to Byrne (2010):

EFA is designed for the situation where links between the observed and latent variables are unknown or uncertain The analysis thus proceeds in an exploratory mode to determine how and to what extent, the observed variables are linked to their underlying factors Typically, the researcher wishes to identify the minimum number of factor that underlie (or account for) covariation among the observed variables (p 5)

In this quantitative pilot study, the procedures of EFA were conducted by the software package IBM SPSS 22.0 This software provided two basic methods for extracting factors during EFA, they are principal component analysis (PCA) and Principal Axis Factoring (PAF) with promax rotation However, PAF with oblique rotation such as promax (Hendrickson & White, 1964) was suggested for process because PAF reflects the underlying data structure more accurately than PCA (Gerbing & Anderson 1988)

The results of EFA showed that seven factors were extracted at eigenvalue equal 1.082 and variance extracted at 70.77% (Table 3.2) Besides, EFA is appropriate to data if the Kaiser-Meyer-Olkin value (KMO) is 60 or greater and the Barlett’s test

of sphericity is statistically significant at p < 5% (Pallant, 2005) In this study, the KMO was 878 and the Barlett’s test indicated significant at p = 000 (See Table D1, Appendix D)

Table 3.2 showed that all factors loading after rotation exceeded 50 that were acceptable as requirements (no item was deleted from scales) Therefore, the final draft questionnaire was accepted as the final questionnaire for the main study

Phase 1: The researcher finalized the main survey for the main study (Appendix B, C)

Phase 2: The researcher determined the sample size for the main study

According to DeCoster and Claypool (2004), Hair, Black, Babin, and Anderson (2010), the minimum sample size (n) used in study analysis should be equal to or greater than five times of the number of observation variables, but not less than 100

to generate reliable results (n ≥ 100 and n ≥ 5*k, where k is the number of observation variables)

This research used “Structural Equation Modeling (SEM)” technique, Raykov and Widaman (1995) (as cited in Nguyen Dinh Tho & Nguyen Thi Mai Trang, 2011b) recommended that this method should require a large sample size However, how large sample size is sufficient, which is not clear on the exact number Hair et al (1998) suggested that the minimum sample size about 100-150 elements in case of Maximum Likelihood (ML) estimation method while Bollen (1989) assumed that the minimum sample size should equal five elements for one estimated parameter Based on previous research recommendations, the sample size of main study was

500

Phase 3: The researcher delivered the survey to public

Researcher issued questionnaires to respondents who live in Ho Chi Minh City by:

- Delivering paper forms (hard copy) directly to respondents

- Public on the Internet using Google survey form, using this link researcher can send the survey via social network (Facebook, Twister, Google Blog), email, instant messenger and over the top (OTP) application

At the beginning of the survey form, the “mobile content services” was clearly defined to ensure all respondents could understand the “mobile content services” concept Data collection was conducted during 45 days The researcher received

160 questionnaires in paper form, 420 forms from Internet survey, especially the online survey spread almost all districts in Ho Chi Minh City The number of