Adoption of the

2008:063

M A S T E R ' S T H E S I S

Adoption of the

Multimedia Message Service (MMS) in Iran

Amirhossein Shantiayi

Luleå University of Technology Master Thesis, Continuation Courses

Marketing and e-commerce

Department of Business Administration and Social Sciences Division of Industrial marketing and e-commerce

Adoption of the Multimedia Message Service (MMS) in Iran

Supervisors:

Dr. Kazemzadeh Dr. Deon Nel

Referees:

Dr. Engstrom Dr. Chaharsoughi

Prepared by:

AmirHossein Shantiayi

Tarbiat Modares University Faculty of Engineering Department of Industrial Engineering

Lulea University of Technology

Division of Industrial Marketing and E-Commerce

MSc PROGRAM IN MARKETING AND ELECTRONIC COMMERCE Joint

Abstract

This thesis tries to analyze the factors that affect the intention to adopt Multimedia message service (MMS) with the help of a user perspective in Iran. Innovation diffusion theory was chosen as the basis of framework to better explain customer’s acceptance of this new mobile service. MMS provides more multimedia communication with entertainment effects than current text base short message service (SMS). Our main purpose in this thesis is to investigate the occurrence of MMS from a user’s perspective, to present a definition of this new message service and provide a deeper understanding of the phenomenon. The main objective is to present a theoretical framework regarding MMS usage and to empirically investigate which user related factors to consider, when developing services adapted for mobile message use. Survey was chosen to gather the data. The measures and hypotheses were analyzed using SPSS and Lisrel. Results show that Relative advantage and Result demonstrability significantly influence passenger’s intention towards adopting MMS in Iran. At last, the implications of the findings are discussed.

Keywords: Adoption, MMS, Mobile, Innovation Diffusion Theory

Acknowledgements

I would like to express my special thanks to my family for their support and encouragement throughout my life. Also, I am deeply grateful to my supervisors, Dr.

Kazemzadeh and Dr. Deon Nel for their encouragement, guidance and valuable comments on this thesis.

May, 2008

Amirhossein Shantiayi

Table of Contents

Abstract... 1

Chapter One ... 7

Introduction... 7

1 Introduction... 7

1.1 The importance of mobile technology and services ... 7

1.1.1 Importance for providers... 8

1.1.2 Importance for customers ... 8

1.1.3 Importance due to increased use of mobile technology... 9

2.1 Mobile Generations... 9

3.1 Mobile services ... 9

3.1.1 Mobile Services adoption ... 10

4.1 The Research Question ... 11

5.1 Our contribution... 11

6.1 Organization of the Thesis ... 12

Chapter Two... 14

Literature Review ... 14

2 Literature Review... 14

2.1 Overview of mobile technology... 15

2.2 Mobile messaging services ... 16

2.2.1 Short message service ... 16

2.2.2 Multimedia message service ... 17

2.2.3 Alert ... 17

2.2.4 Email and Internet... 17

2.2.5 Faxing ... 18

2.2.6 Other mobile services: ... 18

2.3 Growth of mobile usage and SMS in Iran ... 19

2.4 Theory on adoption of technology and mobile services ... 19

2.4.1 Theory of Reasoned Action ... 21

2.4.2 Theory of Planned Behavior ... 23

2.4.3 Technology Acceptance Model ... 26

2.4.4 Innovation Diffusion Theory ... 28

2.5 The research Model... 31

2.5.1 Hypotheses... 34

Chapter Three ... 36

Research Methodology ... 36

3 Research Methodology ... 36

3.1 Research Purpose ... 36

3.2 Research Approach ... 38

3.3 Sample Selection... 40

3.4 Data Collection ... 41

3.5 Pilot test ... 43

3.5.1 Validity ... 43

3.5.2 Reliability... 44

3.6 Statistical Analysis... 44

Chapter Four... 47

Data analysis and results... 47

4 Data analysis and results... 47

4.1 Demographics and Descriptive Statistics... 47

4.1.1 Reliability of the questions ... 55

4.2 Factor analysis ... 56

4.3 Hypotheses test results... 60

4.3.1 First hypothesis test... 60

4.3.2 Other hypotheses test results by SEM ... 62

4.3.3 Goodness of fit... 66

Chapter Five... 69

Conclusions and implications ... 69

5 Conclusions and implications ... 69

5.1 Conclusions... 70

5.2 Managerial implications... 70

5.3 Limitations and Future research... 72

References:... 74

APPENDIX ... 78

A. Original Questionnaires ... 78

B. Questions in English... 82

List of Tables

Table 2.1 ... 19

Table 3.1 ... 42

Table 3.2 ... 46

Table 4.1 ... 48

Table 4.2 ... 48

Table 4.3 ... 51

Table 4.4 ... 52

Table 4.5 ... 53

Table 4.6 ... 54

Table 4.7 ... 55

Table 4.8 ... 56

Table 4.9 ... 57

Table 4.10 ... 58

Table 4.12 ... 59

Table 4.13 ... 60

Table 4.14 ... 61

Table 4.15 ... 61

Table 4.16 ... 61

Table 4.17 ... 62

Table 4.18 ... 66

Table 4.19 ... 68

List of Figures

Figure 1.1 ... 12

Figure 2.1 ... 20

Figure 2.2 ... 23

Figure 2.3 ... 25

Figure 2.4 ... 27

Figure 2.5 ... 31

Figure 2.6 ... 33

Figure 4.1 ... 49

Figure 4.2 ... 50

Figure 4.3 ... 50

Figure 4.4 ... 51

Figure 4.5 ... 52

Figure 4.6 ... 54

Figure 4.7 ... 55

Figure 4.8 ... 63

Figure 4.9 ... 64

Figure 4.10 ... 65

Figure 4.11 ... 67

Chapter One Introduction

1 Introduction

1.1 The importance of mobile technology and services

The mobile phone has become an integral part of many people’s everyday life all over the world. Until recently, it has been mostly used for phone calls and messaging, but this is now changing. Services, in particular, challenge established ways of using phones.

The study of how and why consumers adopt (new) technology and mobile services and

specially messaging services may be relevant and important for both providers and customers. Increased usage of mobile technology is also an important reason for studying its adoption.

1.1.1 Importance for providers

Understanding the drivers of adoption can give an idea to the mobile service providers or decision makers on how to tailor particular services so that they will be used by the customers. It can also contribute to better and deeper understanding of consumers’

needs and expectations. In this way, vendors will be able to differentiate themselves from the competitors in form of how mobile services are designed for customers’ particular needs. In addition, more customized, specific or better tailored services that meet customers’ needs and expectations will enable providers to deliver superior customer experience. This in turn can have a positive effect on customer satisfaction and loyalty (Sendecka, 2006).

If a mobile service provider manages to achieve all this, the competitive advantage can increase together with positive effect on market share and increased revenues as a result of deeper understanding of how customers adopt the technology or services.

1.1.2 Importance for customers

As for a customer himself, understanding of motives for adoption of technology or services can increase the customer’s awareness of his own motives for the use of mobile services. Being aware of own motives, customer can choose better and more deliberately technology or services that fits to his individual needs. It will also enable

money, which were wasted on bad choices before, by choosing appropriate service right away (Sendecka, 2006).

1.1.3 Importance due to increased use of mobile technology

These facts increase the significance of understanding how consumers accept and use the technology, because for new technologies to improve productivity they must first be accepted and used. Davis says himself that it is important to understand what lies behind the intentions to use technology, because it helps vendors to assess user demand for new ideas and for organization managers to evaluate these vendors’ offerings (Davis, 1989). Another reason for studying technology adoption is due to constant development of new and more sophisticated information technology devices (Nysveen, Pedersen &

Thorbjornsen, 2005).

2.1 Mobile Generations

Major stages in the development of mobile telecommunications are commonly described as generations. First generation networks were analogue cellular systems.

Second generation networks are digital cellular systems such as GSM (Global System for Mobile Communication) (ITU, 2002). Second generation networks are able to serve some data services although the network speed limits the amount of data that can be transferred. First and second generation networks were largely developed under a number of proprietary, regional and national standards (ITU, 2002). The development of 3G systems has been characterized by the aim to develop an interoperable, global standard (ITU, 2002).

3.1 Mobile services

With the increasing number of mobile phone subscribers, usage of mobile Internet services has increased in recent years. The mobile Internet refers to mobile commerce

activities, including mobile telecommunication, mobile content, entertainment service and e-commerce relying on a mobile platform (Chin-Lung Hsu, 2007).

Among mobile telecommunications, the messaging service markets which include short message service (SMS), multimedia message service (MMS), and mobile e-mail, are growing rapidly. According to the (Datamonitor, 2003), the value of the messaging market will increase from US$ 17.4 billion in 2002 to more than US$ 29 billion in 2006.

In mobile services, the message services have become the main revenues for telecommunication companies, especially in Iran. In 1386 (2007), mobile service usage on SMS was approximately 20,000,000, per day in Iran. It was projected that 80% of mobile expenditures was also on messaging service in the whole world by 2007, (Ovum, 2003; Chin-Lung Hsu, 2007).

The proliferation of mobile Internet applications has caused telecommunication organizations to extend their service scopes. With the arrival of the third generation (3G) gear, MMS may become a ‘killer’ application for messaging services. Unlike text-based SMS, MMS allows mobile phone users to exchange pictures with sound clips on their handsets or digital cameras. MMS users send text messages as well as multimedia messages incorporating pictures, voice recordings, animated characters, and video clips to others. Users can enjoy more multimedia effects via colorful graphics and crisp sounds of MMS than text-based SMS. MMS users can also send multimedia messages to other users through Internet content providers (ICP). MMS has reshaped the landscape of mobile communication, making it more personal, more versatile, and more expressive than ever before (Chin-Lung Hsu, 2007).

3.1.1 Mobile Services adoption

The commercialization of mobile services is approaching a critical stage in Iran

of mobile services but even there, rather basic services such as messaging and ring tones have been most successful (Funk, 2005; Srivastava, 2004; Kim et al., 2004). Such services have during recent years been popular also in Europe (Carlsson et al., 2005;

Mylonopoulos & Doukidis, 2003), but more advanced services have not yet found their ways into the everyday lives of consumers.

Recently Iran is gaining much attention due to third generation mobile telephony (3G), which is expected to take off commercially in 1386-1387 (2007-2008). Initially 3G was limited mostly to Hutchison's networks in various countries but this is changing rapidly as more conventional mobile operators are launching their networks. From the perspective of service development, this is a significant step as 3G has been planned to be the basis of new business growth and to generate new revenues from services, specially messaging services (ITC, 2007).

4.1 The Research Question

The emerged research question is:

What are the main factors that influence the Iranian mobile customer’s intention to adopt MMS service?

We propose hypothesis testing in trying to find answers to our research question.

Through literature review we will try to make and propose a proper model to identify factors affecting the intention to use MMS service. Identification of such factors will shed light to the online consumer behavior in our country, Iran.

5.1 Our contribution

First, this study aims to apply IDT to examine the determining factors of MMS adoption within different categories of adopters over innovation diffusion stages.

Understanding the perceptions of different categories of adopters can help mobile and MMS providers plan appropriate strategies. Second, this study aims to find the factors that influence MMS adoption for potential users and experienced users in Iran. Since

Chapter One – Introduction

Chapter Two – Literature Review

Chapter Three – Methodology

Chapter Five – Conclusion Chapter Four – Data analysis

different group may have different preference and behavior in MMS, the results can provide further insights for MMS marketing strategies.

6.1 Organization of the Thesis

This thesis is consisting of five chapters. Chapter one provides a preview of this thesis, including an introduction to the mobile services and the research question .Chapter two, is theoretical review. In this chapter a theoretical background of adoption technologies and the proposed research frame work used in this thesis will be proposed.

In chapter three is assigned to the research methodology. Chapter four provides the data descriptions, analysis and results. Finally the last chapter delivers the conclusion.

Figure 1.1, illustrates the outline of the thesis.

Figure 1.1: Organization of the Thesis

Chapter Two

Literature Review

2 Literature Review

In this chapter the literature review related to this thesis is delivered. First part is

assigned to the mobile technology and services background, and second part is dedicated to the introduction of different adoption theories.

2.1 Overview of mobile technology

The technical development within mobile industry has progressed more rapidly the last decades. Although mobile was introduced a bit later in Iran, in comparison with the western countries, but it showed a very rapid growth after its introduction.

In 1982 the Conference of European Posts and Telecommunications (CEPT) was founded to establish a standardized system for the second generation of mobile communications (2G). GSM which was the result of the work is an abbreviation for Global System of Mobile communications and is the largest standard for mobile communication worldwide. The system is digital based, which enables for possibilities for data based mobile services. GSM has a bandwidth of 9,6 kbit/s which is quite slow for users that would like to use the GSM network for data transfers and other services than making phone calls (Edström, 2003).

To compensate for the low bandwidth in the GSM networks, different upgrades have been done to this standard. One of the most known upgrades is Global Packet Radio Service (GPRS). GPRS has a theoretical bandwidth of 115 kbit/s, and has the ability to be online all time, which enables fast access to mobile services. Since GPRS is a complement to ordinary GSM and is developed for data transfer only; the GSM is still used to handle the talk. GPRS, also known as 2,5G is of many considered to be the technological basis of what we today describe as Mobile Internet since GPRS allows users to be online at all time (Edström, 2003).

Recently, the third generation of mobile communications, 3G, is under development, and is available in Iran too. 3G is to greater extent adapted to mobile data services and also facilitates higher bandwidth. In Europe the standard for 3G is UMTS, Universal Mobile Telecommunications System. The theoretical bandwidth of this technology is 2 Mbit/s.

Even further into the future 4G systems will emerge including standards like HiperLan2, which offers even higher bandwidth, up to 54 Mbit/s. Important to understand though, is that the major technology shift, from a Mobile Internet perspective, takes place when we

start using GPRS. Some people even refer to GPRS as the revolution and UMTS as an evolution (Edström, 2003).

An important part of the mobile revolution is the mobile devices used for communication. Today there exist several different types of mobile devices, and mobile phones are still the most common device but PDA’s and combined smart phones are getting more common. An example of these new smart phones is the latest combination of mobile phone and PDA. These new mobile devices are becoming more sophisticated and offer its users a wider range of application, which helps the providers to offer more services on them (Edström, 2003).

2.2 Mobile messaging services

There are many mobile services available today. In this section I will give a rough overview over available mobile services on today’s market, all over the world. First service and the most popular one is messaging. Generally, mobile messaging involves the following services:

2.2.1 Short message service

Traditional text messaging, so called SMS (Short Message Service) involves sending and receiving messages to and from wireless phone number. However, it is also possible to send and receive messages from anyone with an e-mail address to the mobile phone, but this feature needs to be offered by the service provides. The second service is instant messaging, or chatting, is primarily just like text messaging but faster. It allows people to talk to their friends online anytime, even without a computer, simply by using their mobile phones. Service provider must support instant messaging providers (for example Real time, Aol instant messenger, MSN messenger or Yahoo messenger). A

2.2.2 Multimedia message service

Picture or video messaging, so called MMS (Multi-Media Messaging Service), which we will discuss on its adoption process in Iran, in this thesis as a second generation of mobile messaging service, allows pictures, sound and video clips to be attached to the traditional SMS messages. Pictures or movies taken by mobile phone can then be sent to other mobile phones or e-mail addresses. In order to use these services, both sender and receiver must posses a mobile phone with a camera (Sendecka, 2006 ; Chin-Lung Hsu, 2007 ).

In addition to messaging service, there are variety of other available services like alerts, email and internet, faxing, payment and etc. In following section some of these services will be briefly discussed.

2.2.3 Alert

Alerts can be also classified as a subtitle of messaging services. It allows news headlines, scores, horoscopes, sport results etc. to be sent to a mobile phone. We can distinguish between two types of alerts: Scheduled Alerts and Alerts on Demand. With scheduled alerts, user can decide on what alerts he wants to receive and the times and days he receives them. Alerts on Demand are the instant addition to the present alerts. A person just sends an appropriate code for the alert and gets the information he is wondering about at the moment, like for example a game score (Sendecka, 2006).

2.2.4 Email and Internet

E-mail and internet on a mobile phone allows sending, receiving, and reading personal and business e-mails when necessary. However, this service requires special

mobile phone or handset and a GPRS function available. User can easily brows and surf in internet, as well as checking emails (Sendecka, 2006).

2.2.5 Faxing

Faxing is the last service in the group of messaging services. Some providers like Vodafone, Norwegian and etc. offer the customers to receive faxes to the mobile phone anytime and anywhere. A person receives a SMS message announcing the arrival of new fax once somebody sends a fax to the person’s mobile phone fax number. Then, the person can just print out the fax on the nearest printer (Sendecka, 2006).

2.2.6 Other mobile services:

The above mentioned services were services within messaging, also called communication services. Further down, following section introduces other types of services available through mobile phone deferred from messaging services or used by messaging services help. One of these available services is Payment service, which involve paying for product and services with a mobile device. So, mobile payments can be define as, any payment where a mobile device is used in order to initiate, activate, and/or confirm any payment (Karnouskos & Fokus, 2004). There are several ways of pursuing payment with mobile phone. One way is payment via SMS. Second is via electronic purse on mobile device the third way of payment is through charging telephone bill (Sendecka, 2006).

The other available service, which is offered widely by providers in the world, is gaming. The popularity of gaming services increases, but it is not available in Iran yet.

There are other mobile services available today, like Voicemail, and is usually included in the mobile subscription. If the owner of the mobile phone is not available, the person calling can leave a voice message or telephone number. The owner gets an SMS message when somebody has left the message. This service is available in Iran, and is offered by

2.3 Growth of mobile usage and SMS in Iran

Even though all mobile services have not yet been widely adopted in Iran, but some of them gain importance for mobile service providers recently. However, the immense increase in growth in mobile technology, as illustrated above, has also led to increase in the services provided on mobile phones.

As mentioned earlier mobile was introduced on 1994 in Iran, with only 9200 users in capital, Tehran. According to the statistics the mobile usage in the Iran’s market has been dramatically increased from the beginning of its birth, and it reached 60,000 users in 1996. By this rapid growth, the number of mobile users was 3.5 million in 2003, which was the year of SMS introduction as well. This number is now, 20 million for year 2007 and according to the statistics published by Ministry of communication; each Iranian mobile user exchanges approximately two SMS per day. In continues, the following part is consist of some adoption theories, and finally the research framework chosen for our research (ITC, 2007).

Year Mobile users SMS users 1994 9200 0 1996 60,000 0

2003 3.5 Million 15,000

2007 20 Million 20 million

Table 2.1: Statistics of Iran mobile industry

2.4 Theory on adoption of technology and mobile services

In order to understand the processes behind the factors affecting consumers’

intention to use and adopt mobile services, it is necessary to get a thorough understanding of the theory behind it. The theory on this topic is based on several models that have been developed gradually and built up on each another (Sendecka, 2006). In this chapter I will

present such models and show how they can be used in the search for adoption of MMS in Iran.

Theoretical models on user acceptance of information technology (e.g. mobile services) employ “intention to use” and “actual use” as the main dependant variables (Venkatesh et al 2003). Intention to use information technology as a predictor of behaviour (e.g. usage, adoption) has been well established in the literature (e.g. Ajzen 1991; Sheppard et al.,1988; Sendecka, 2006). Following figure 2.1 shows the basic concept:

(Source: Sendecka, 2006)

Figure 2.1: Theoretical model on user acceptance of information technology

Since intention to use information technology is a valid predictor of behavior (use, adoption of technology), it is necessary to have a look at the theories that will explain more about behavior and intention to use. There is a big variety of models that explains consumers’ behavioral intentions and intentions to use technology (Sendecka, 2006). As, for this paper, I will use the following theories:

ƒ Theory of Reasoned Action (TRA; Fishbein & Ajzen 1975)

ƒ Theory of Planned Behavior (TPB; Ajzen 1991)

ƒ Technology Acceptance Model (TAM; Davis 1989)

ƒ Innovation diffusion theory (Rogers 1983)

2.4.1 Theory of Reasoned Action

Theory of reasoned action (Fishbein & Ajzen, 1975) is an extension of Fishbein’s multi attribute model to account for the relationship between attitudes and behaviour.

TRA is intended to predict behaviour in situations where the customer controls his own behaviour and he is thoughtful about it. TRA states that the most important determinant of consumer actual behaviour is the intention to behave. The behavioural intention is affected by attitude towards behaviour and subjective norms, which are two new contributions to Fisbein’s previous model (Sendecka, 2006). For graphical representation of TRA, please, refer to figure 2.2.

Attitude to behave is defined as “an individual’s positive or negative feelings about performing the target behaviour” (Fishbein & Ajzen 1975). Adding attitude towards behaviour as a new component means that in order to predict a specific behavior it is necessary to measure person’s attitude toward performing that behaviour, and not just general attitude toward the object at which the behaviour is directed (Kassarjian &

Robertson 1991).

Subjective norms are defined as “the person’s perception that most people who are important to him think he should or should not perform the behaviour in question”

(Fishbein & Ajzen 1975). Subjective norms are intended to account for social influences that the person’s behaviour is exposed to. Thus, performing a particular behaviour is also influenced by other’s opinions about the behaviour. And hence the intention to behave or to use technology would not be only determined by personal attitude towards the behaviour but will also be influenced by other’s opinions about the behaviour (Sendecka, 2006). The rationale for direct effect of subjective norms on intention is that “people may choose to perform a behaviour, even if they are not themselves favourable toward the behaviour or its consequences, if they believe one or more important referents think they should, and they are sufficiently motivated to comply with the referents” (Venkates &

Davis 2000)

Subjective norms are further composed of two factors, namely normative beliefs and motivation to comply. Normative beliefs are beliefs of a specific referent about what a person should or should not perform. Normative beliefs are in other words beliefs about what others expect. Motivation to comply is a person’s motivation to comply with normative beliefs, i.e. with the beliefs that other specific referents have. Similarly to Fishbein’s multiattribute model, in TRA the change in attitude can result in changing either evaluative aspect associated with consequence of the behaviour or changing the strength of belief associated with consequence of the behaviour. However, in TRA it can also be change in normative components (i.e. change in normative beliefs or in motivation to comply) that can be derived from this model (Sendecka, 2006).

Ryan & Bonfield (1980)support behavioural intentions as the determinants of the behaviour as they demonstrate predictive validity and external validity of the TRA model in a real- world marketing applications. In addition, TRA has been used to predict different behaviours (Sheppard et al 1988). Consequently, theory of reasoned action is one of the most influential theories of wide range of human behaviour (Vekantesh et al 2003). It suggests that attitude toward behaviour and subjective norms will determine intention to perform behaviour. And thus, it will be behavioural intention, rather than attitudes, that will determine actual behaviour (Sendecka, 2006).

(Source: Kassarjian et al., 1991)

Figure 2.2: Theory of reasoned action

2.4.2 Theory of Planned Behavior

Ajzen revises Theory of Reasoned Action in 1991 and proposes an extension in form of perceived behavioural control in his Theory of Planned Behaviour (TPB) (figure 2.3). Perceived behavioural control is defined as “the perceived ease or difficulty of performing the behaviour” (Ajzen, 1991). Taylor and Todd modify the definition of perceived behavioural control in context of Information Systems research (IS) in 1995 as

“perceptions of internal and external constrains on behaviour” (Taylor et al., 1995).

Perceived behavioural control is included as an additional determinant of intentions and behaviour. It accounts for situations where people do not have a complete control over their behaviour. It says that the behaviour can be influenced by other factors

than just the personal intention to perform the behaviour and other people’s opinion about the behaviour (subjective norms) as it was in TRA. Such other factors refer to the amount of requisite opportunities and resources, such as time, money, skills and cooperation of others (Harrison et al 1997; Sendecka, 2006). The extent to which one possesses time, skills and money will determine intention to perform a particular behaviour (in this case to use and adopt a service) Thus, it is intention and the availability of resources and opportunities that jointly determine whether or not behaviour is performed (Sendecka, 2006).

Perceived behavioural control is further decomposed into control belief and perceived power. Control beliefs are beliefs about resources and opportunities that can be either part of a person’s previous experience with the behaviour or can be influenced by second- hand information that increases or decreases the perceived difficulty of performing that particular behaviour (Ajzen, 1988; Sendecka, 2006). Perceived power is the power of the particular control factor to make it easy or obstruct the performance of the behavior.

As with the other models, perceived control can be either weighted or non- weighted. If not weighted, perceived power component of perceived control is not stressed. In empirical work, it is very common to consider the perceived control as non- weighted.

(Source: Ajzen, 1991)

Figure 2.3: Theory of planned behavior

Ajzen (1991), shows that attitudes, subjective norms, and perceived behavioural control are all positively related to the intentions about the behaviour. Intention about the behaviour will thus predict the actual behaviour of a consumer. Theory of planned behaviour has been used to predict intention and behaviour in variety of settings (Ajzen 1991; Sendecka, 2006). It has been also successfully applied to acceptance and usage of many different technologies. For example Harrison et al (1997) summarise the wide range of settings (Sendecka, 2006): Schifter (1984) used TPB to predict weight loss

behaviour. Ajzen & Madden (1986) used it to predict college students’ intentions to attend class and earn a good grade. Mathieson (1991)predicted a person’s intention to use a specific information system.

2.4.3 Technology Acceptance Model

Several studies focusing on adoption of mobile technology and services have their roots in Technology Acceptance Model (Davis 1989), that was completely designed to predict user’s acceptance of information technology and usage on the job. TAM model has become the most widely applied model of user acceptance and usage (Ma & Liu 2004; Sendecka, 2006). Venkatesh & Davis indicate that TAM has become well established as a strong, powerful and parsimonious model for predicting user acceptance (Venkatesh et al., 2000).

This model is an adaptation of TRA specifically tailored for modeling user acceptance of information systems. It provides a basis for tracing the impact of external factors on internal beliefs, attitude and intention. (Davis et al, 1989) Also, according to Ajzen, TAM is grounded in the Theory of Reasoned Action (Fishbein & Ajzen 1975) and Theory of Planned Behaviour (Ajzen 1991). The core of TAM lies in the hypothesis that intention to use a system is determined 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” (Davis 1989; Sendecka, 2006). Perceived ease of use is defined as “the degree to which a person believes that using a particular system would be free of effort” (Davis 1989).

TAM theorizes that perceived usefulness and ease of use mediate the relationship between external variables, such as system characteristics, development process, training, and intention to use a system (Venkatesh & Davis 2000; Sendecka, 2006). Perceived usefulness and ease of use are therefore user’s beliefs on information technology and so, form user’s attitude toward technology which will, in turn, predict acceptance (intention

(Source: Davis, 1989)

Figure 2.4: Technology acceptance model

The rationale behind these relationships is that technology that is easy to use, and is found to be particularly useful will have a positive influence on the intended user’s attitude and intention towards using the technology. Consequently, the usage of the technology will increase (Taylor & Todd 1995).

In addition to this, after conduction of numerous experiments, Davis (1989) found out that overall, perceived usefulness was more correlated with the system usage than did perceived ease of use. He also suggested, after conducting a regression analysis, that perceived ease of use influences technology acceptance (usage of the system) via perceived usefulness, rather than directly. The reason for this is that the easier the system is to use the more useful it can be (Sendecka, 2006).

Venkates & Davis (2000) have extended the original TAM to TAM2 by including subjective norms as an additional predictor of intention to use technology. Reason for not including subjective norms in the original TAM in the first place was that Davis, Bagozzi

& Warshaw (1989) found no significant effect on intentions over and above perceived usefulness and ease of use (Sendecka, 2006). However, they acknowledged that it was necessary to research further on “the impact of social influences on usage behaviour”

(Davis et al 1989).

The result of the study carried out by Venkatesh & Davis (2000) shows that subjective norms have significant direct effect on usage intentions. They hence confirmed

that TAM2 provides a detailed evidence of the key forces behind perceived usefulness, while explaining 60 percent of variance in it. It thus shows that perceived usefulness, ease of use and subjective norms are important drivers of usage intentions (Sendecka, 2006).

Ma & Liu (2004), claim that there have been about 100 studies done related to TAM between 1989 and 2001 (Sendecka, 2006). TAM has been tested with different sample sizes, user groups, using different statistical tools, applied to many different user technologies and compared with different competing models (Gefen 2000). This had led to many divergent findings with many different explanations. Ma & Liu (2004) therefore carried out Meta- analysis of TAM in order to integrate all the findings and to generate a quantitative and objective synthesis. The result of their study confirmed Davis’ original findings: Relationships between perceived usefulness and ease of use, and perceived usefulness and technology acceptance are strong, while relationship between perceived ease of use and technology acceptance is weak. Thus, the relationship between usefulness and perceived ease of use cannot be ignored (Sendecka, 2006).

2.4.4 Innovation Diffusion Theory

Innovation diffusion theory is one of the other theories that explains acceptance of technology (Teo & Pok 2003). In his book Diffusion of innovations, Rogers (1983) defines innovation diffusion theory as “the process by which innovation is communicated through certain channels over time among the members of social system”. It conceptualizes the sequence of events where individual passes through initial point of basic knowledge of innovation, through forming a favorable or unfavorable attitude toward it, through a decision to either adopt or reject it, and through utilization of innovation to finally seeking reinforcement of the adoption decision made (Rogers 1983;

Sendecka, 2006). The key elements of this process are innovation, communication channels, time and social systems or innovation’s perceived characteristics, the individual’s attitude and belief, and communication received by the individual from his social environment (Karahanna, Straub & Chervany 1999; Sendecka, 2006).

used for many years. He claims that the five attributes are somewhat empirically interrelated with each other, but at the same time, they are conceptually distinct. The selection of particularly these five attributes is based on past research. The five attributes are following: relative advantage, compatibility, complexity, trialability and observability (Sendecka, 2006).

Relative advantage is “the degree to which innovation is perceived as being better than the idea it supersedes” (Rogers 1983). The degree of relative advantage can be expressed in, for example, economic profitability or in status giving. Research scholars have found out that relative advantage is one of the best predictors of an innovation’s rate of adoption and that it is positively related to it. The reason for this is that when individuals or organizations pass through innovation process, they are motivated to seek information in order to decrease uncertainty about the relative advantage of an innovation. Potential adopters want to know the degree to which a new idea is better than an existing one (Rogers 1983; Sendecka, 2006).

Compatibility is “the degree to which an innovation is perceived as consistent with the existing values, past experiences and needs of potential adopters” (Rogers 1983).

The more compatible idea will be less uncertain to the potential adopter. Hence, compatibility has a positive direct effect on rate o adoption of innovations. Some analyses show compatibility to be of relatively less importance in predicting rate of adoption than other attributes. Innovation can be compatible or incompatible with socio cultural values and beliefs, with previously introduced ideas, or with clients needs for innovation (Sendecka, 2006).

Complexity is “the degree to which an innovation is perceived as relatively difficult to understand and use” (Rogers 1983). Rogers has suggested that the complexity of an innovation is negatively related to its rate of adoption. The reason for this is that the less difficult the innovation will be to understand and use, the less complex it will be perceived. Therefore, the rate of adoption will be higher.

Trialability is “the degree to which an innovation may be experimented with on a limited basis” (Rogers 1983). The ideas that can be tried will be, according to Rogers, adopted more rapidly than innovations that have not been tried. Roger and other researchers (Singh 1966, Fliegel & Kivlin 1966) support the fact that trialability is positively and directly related to the rate of adoption of innovations (Sendecka, 2006).

Observable is “the degree to which the results of an innovation are visible to others” (Rogers 1983). The more visible the innovation is to others, the faster the adoption of the innovation will be. This is the reason why Rogers suggest the positive relation between observability and adoption rate (Sendecka, 2006).

Rogers claims (1983) that these five attributes explain 49 to 87 percent of the variance in the rate of adoption. Figure 2.5, below summarizes Rogers’ findings.

According to Rogers (1983), all five factors underlying the rate of adoption of innovation, except complexity, will have positive and direct effect on the rate of adoption of innovations. Complexity is, according to Rogers, negatively related to it. However, Tornatzky & Klein (1982)found out that, of all of them, it was only relative advantage, compatibility and complexity that were consistently related to adoption decisions (Sendecka, 2006).

(Source: Rogers, 1983)

Figure 2.5: Drivers of adoption of innovations

2.5 The research Model

Moore and Benbasat (Moore, 1991) developed and measured framework that identified perceived attributes which may influence the adoption of IT innovation. The main attributes were derived by Rogers (Rogers, 1983) from the literature on diffusion of innovations; these include relative advantage, ease of use, compatibility, observability, and trialability. Considering the diffusion of new end-user IT, Moore and Benbasat (Moore, 1991) proposed some extended constructs such as image, visibility, result demonstrability, and voluntariness of use. Image emerged as a separate factor from relative advantage and was seen as social approval. Visibility and result demonstrability were developed from observability. Voluntariness of use was a new construct beyond Rogers’ classification (Chin-Lung Hsu, 2007).

In the past decade, researchers have applied the IDT to examine IT usage. For example, Agarwal and Prasad (Agarwal R, 1997) found that relative advantage and result

demonstrability were relevant in explaining acceptance of the WWW. The two variables together explained 46% of the variance in future-use intentions. Similarly, perceived innovative characteristics with specific contexts have been examined. Slyke et al., (2002) used IDT to investigate factors that may influence intentions to use groupware applications. He found that relative advantage, complexity, compatibility, and result demonstrability were significantly related to intention. Chen et al. (2002) applied a technology acceptance model (TAM) and IDT to examine consumer behavior in the virtual-store context. Their findings indicated that compatibility, perceived usefulness, and perceived ease of use were the primary determinants of consumer attitudes towards using virtual stores. Factors identified as influences on cell-phone banking adoption included relative advantage, trialability, and consumer banking needs (Brwon I, 2003).

These studies confirmed that characteristics identified by Rogers and his successors do explain acceptance behavior in specific contexts (Chin-Lung Hsu, 2007).

Although IDT has been successfully used to explain intention to use IT, as mentioned earlier there are some established theories such as theory of reasoned action (TRA), TAM, and theory of planned behavior (TPB) that can also be used to predict users’ behavior. Nevertheless, it is unknown how readily they can be applied to investigate the adoption of new innovations like MMS. Moreover, as use in MMS continues to rise, understanding how and why people decide to use has become more and more important to MMS service providers and diffusion researchers. The main contribution of IDT has also allowed researchers to study how new innovations spread among groups of people. Therefore this study intends to examine MMS adoption by using the IDT framework as the basis, as shown in Figure 2.6 For the purposes of this study, these eight constructs seem to be the most appropriate: relative advantage, perceived ease of use, compatibility, trialability, image, visibility, result demonstrability, and voluntariness (Chin-Lung Hsu, 2007).

IDT further proposes that there will be different adopter groups over innovation

respectively. However, a reduced model should be considered when IDT is applied to specific industry (Fell DR, 2003). Therefore in this study the entire innovation diffusion stages have been reduced to four groups. Innovators and early adopters are combined into a single category because of their small number of users in each group. As a result, the adopters were classified into four categories: innovators/early adopters, early majority, late majority, and laggards. It is worth mentioning the reasons for making different decisions for IT adopters and nonadopters in the context of MMS use. Karahanna et al.

(1999) indicated that there were different beliefs about IT use between pre-adoption and post-adoption. In his study, the sample was merely categorized into potential adopters and users to investigate the behavioral differences between them (Chin-Lung Hsu, 2007).

The main selected model for this research, based on innovation diffusion theory which is also empirically validated by Chin-Lung Hsu, in 2007, has been shown in figure 2.6.

(Source: Chin-Lung Hsu, 2007)

Figure 2.6: Main Research Model

2.5.1 Hypotheses

Rogers proposed that each adopter category has different characteristics (Roger, 2003). In the past decade, empirical studies have shown that IT adoption behaviors differed among Rogers’ adopter categories (Agarwal R, 1998 ; Beatty RC, 2001).

Accordingly, and by considering that a same study has been done by (Chin-Lung Hsu, 2007) with our selected research model, so our hypotheses will be as follow:

H1. The innovators/early adopters, early majority, late majority, and laggard groups will show differences in their judged perceptions of:

H1a: relative advantage, H1b: perceived ease of use, H1c: compatibility,

H1d: trialability, H1e: image, H1f: visibility,

H1g: relative result demonstrability, H1h: voluntariness,

H1i: Intention to use.

Because IDT is used as the baseline model, the following IDT hypothesized relationships will also tested in the context of MMS for all the respondents.

H2. Relative advantage will positively affect intention to use.

H3. Perceived ease of use will positively affect intention to use.

H4. Compatibility will positively affect intention to use.

H5. Trialablity will positively affect intention to use.

H9. Voluntariness will positively affect intention to use.

Chapter Three

Research Methodology

3 Research Methodology

This chapter includes some discussion and introductions on different research methods y and also explains the chosen method for this research. It will further describe the research purpose, data collection methods and analysis approach. Furthermore, this chapter describes the chosen way for data collection, and the techniques used to analyze the collected data.

3.1 Research Purpose

All research purpose formulations can be categorized as being exploratory,

The purpose of academic research can be exploratory, descriptive, and explanatory. Exploratory studies are valuable means of finding out what is happening, seeking new insights, asking questions and assessing phenomena in a new light.

According to Eriksson and Wiedersheim-Paul An exploratory research is useful when the problem area is difficult to limit, the perception of which model to use is diffuse and it is unclear what characteristics and relations that are important (Eriksson et al., 2001).

In an exploratory study it is common to use many different sources to gather as much information about a specific subject as possible. Wallen states that an exploratory research is a suitable approach when the researcher is uncertain of the theories that are relevant, and when important characteristics and relations are difficult to determine (Wallen, 1996). So, as mentioned earlier, the purpose of an exploratory research is to gather as much information as possible about a specific subject, so it is ordinary to use many different sources to gather this information. Finally, an exploratory study should be designed by stating a purpose and stating the criteria to judge the exploration successful (Yin,1994).

In contrast to exploratory research, when a problem is clearly structured and when the intention of the study is not to conduct research about factors’ related causes and symptoms it is appropriate to conduct descriptive research (Eriksson et al., 2001). The researcher conducting the descriptive study possesses good knowledge of a market problem or market situation but lacks an updated, clear picture of its status (Christensen et al., 1998). Thus, instead of describing new phenomena that affect a certain area, the descriptive research focuses on describing it. Descriptive studies’ object is to portrait an accurate profile of persons, events or situations. Some experts believe that, these kinds of studies can be an extension of, or a forerunner to, a piece of exploratory research.

An explanatory approach is used when it’s necessary to show that one variable causes or determines the value of other variable. This research is good to use when there is no clear apprehension about what model that should be used and what qualities and relations that is important (Zikmund, 1994). Most explanatory researches seek casual relationships between independent and dependent variables. By changing the value of the independent variable it is possible to study fluctuations in the value of the dependent

variable. Thus, in order to conduct an explanatory research one must in advance know which independent variables assert influence on the dependent variable (Christensen et al., 1998).

In this study, I will explain, describe and possibly start to find factors affecting the MMS adoption in Iran. So, my research is primarily explanatory, but as I will then describe the discovered patterns of the explanatory stage, my research will secondary be descriptive.

3.2 Research Approach

The approach of any type of research is basically a result of how the researcher chooses to manage two dimensions; the analytical- and time dimension. The analytical dimension is concerned with the width and depth of the research and affects the number of studied variables, the size of the sample, and the extent to which the result can be generalized. The correlation between the research’s width and depth is not in any way fixed, but merely describes two underlying dimensions: wide-narrow and deep-shallow.

The former dimension indicates the number of cases being studied; the wider the study, the more cases are taken into consideration. The concern of the latter dimension is the number of variables being studied. A greater number of variables are scrutinized in a deep research than in a shallow one. Most market researches are either wide and shallow or narrow and deep. (Christensen et al., 1998)

As research that is wide and shallow study, few variables among a large number of cases, it aims to comment on characteristics of the population as a whole. This type of research is often of quantitative nature as the results are based on numbers and statistics and are presented in figures. On the other hand, research that is narrow and deep focuses on a few cases which characteristics are studied thoroughly. The concern of this type of research is to obtain a complete understanding and overview of a problem, or situation,

determined by the analytical dimension but also by the time dimension which can be divided into two anti poles. The research problem can either be studied over time in order to create a dynamic view of reality, or at a certain point in time, which instead provides a picture of how reality appears in that specific moment (Christensen et al., 1998). Also, according to Wallsrom’s idea, two choices of research approach are available, namely the qualitative and quantitative. Qualitative research provides a deeper understanding of the phenomenon under investigation, and the problem can be understood within its context, thus furnishing a holistic view. Quantitative methods are often used within natural science, and the aim is usually explanatory – to explain causal relationships, to permit generalization, and to enable predictions about the future (Wallstrom , 2002).

This thesis method is quantitative, as the data are gathered through questionnaire, and I decide to analysis the data by statistical methods, in order to explain the behavioral intention to a new mobile messaging service.

According to the Yin’s idea, case studies are the preferred strategy when “how” or

“why” questions are being posed, when the investigator has little control over events, and when the focus is on a contemporary phenomenon within some real-life context (Yin,1994).

In addition Christensen claim that there are no definite rules restricting how to conduct a case study or how to collect data (Christensen et al, 1998). It is common that several data collection procedures are used. This lack of structure is a prerequisite for the ability of the case study to thoroughly investigate a problem; however, it is also its biggest drawback. As there are no given rules the researcher must obey, it is easy to make mistakes or jump to false conclusions. Zikmund concurs and explains that researchers must be flexible and attempt to glean information and insights wherever they find them.

This implies that the success of any case study is highly dependent on the alertness, creativity, intelligence, and motivation of the researcher (Zikmund, 2000). As a consequence, the results from case analysis should be seen as tentative.

It is states that a case study can involve a single or a multiple case study. A single case study makes an in depth investigation regarding only one organization or decision. When two or more organizations are investigated, it is called a multiple case study, which gives the opportunity to compare studies in a cross-case analysis, so that a higher level of understanding can be reached (Yin, 1994).

According to Eriksson and Wiedersheim-Paul the risk when conducting a multiple case study is that each case might be less in depth investigated (Eriksson et al.,2001). It is further states that evidence from a multiple case study is often considered as more compelling than evidence from a single case study, and therefore the multiple case study is looked upon as more robust.

It was in the previous part mentioned that the purpose of this study is explanatory with the objective of identifying and investigating factors and motivations that affects adopting a service (MMS) in the Iran’s mobile industry context. This implies that the analytical dimension be wide and general. Therefore, given the nature of the stated research problem, it has been concluded that the most favorable approach would be to perform a survey, to answer questions such as who, what, where, how many and etc.

about the mentioned context.

3.3 Sample Selection

The sample selection could be in various ways. According to Zikmund, the major alternative sampling plans may be grouped into probability techniques and non probability techniques (Zikmund, 2000). Probability sampling is characterized by each member of the population having a known nonzero probability of selection. In non probability sampling, on the other hand, the units of the sample are selected on the basis of personal judgment or convenience. As the selection of elements in this particular study

It is states that there are three non probability sampling techniques; convenience sampling, quota sampling and snowball sampling. As the name suggests, convenience sampling selects the units, or people, that are most conveniently available. The purpose of quota sampling is to ensure that certain characteristics of a population sample will be represented to the exact extent the investigator’s desire. The third technique, snowball sampling, is a procedure in which initial respondents are selected by probability methods, and then additional respondents are obtained from the information given by the initial respondents. The technique that has been used in this study is probability sampling, and all the respondents were selected randomly among mobile users that have experienced SMS service at least once.

3.4 Data Collection

There are two principal methods of obtaining data from respondents, communication and observation. Communication requires the respondent to actively provide data through verbal response, while observation requires the recording of the respondent’s passive behavior. As the observation technique does not comply with the purpose of this research it will not be subject for further discussion (Kinnear et al., 1996).

The data collection methods used in communicating with respondents are personal interviews, telephone interviews, mail questionnaires and questionnaires. The main advantage of the personal interview is its versatility, meaning it has an ability to collect data on a wide range of information needs. On the other hand, the main limitations of the method are the respondent’s unwillingness or inability to provide data, and the risk of the questioning process having a negative influence. For instance, the respondents may bias their responses in order to give a socially acceptable answer or to please the interviewer (Kinnear & Taylor, 1996).

Interviews are ideal when in-depth information is preferred and that it allows flexibility and closeness to the respondents, which is important when conducting qualitative studies (Holme and Solvang, 1997). An interview is a two-way conversation which gives the interviewer the possibility to actively participate in the interview (Yin,

1994). The fastest way to collect data is usually through telephone interviews. The time spent on travelling when conducting personal interviews makes this method slower, and the speed of mail questionnaires is difficult to influence. However, personal interviews have an advantage over telephone interviews in that they give the interviewer the confidence of face-to-face interactions (Eriksson & Wiedersheim-Paul, 2001). Some advantages and disadvantages of personal interviews are listed in table 3.1, below.

Advantages Disadvantages Is fairly easy to accomplish

(time e wise)

High Cost Increased control of the

interview situation Risk that interviewer has an affect

Complicated questions can be

asked Not suitable for delicate question

Suitable for questions that require knowledge

Often a small number of respondents

Material can be shown Requires well-trained interviewers

Resulting questions can be asked Often complicated data analysis

(Source: Christensen et al., 1998)

Table 3.1: Advantages and disadvantages of personal interviews

Although we are going to answer questions such as: how can people understand and discuss MMS technology in Iran that is still in its development stage? And in this way, interview may guide us thought a better perception and opinion of mobile users concerning this case, but by considering disadvantages of interview in this field, such as small number of respondents that could not be a presenter of the whole population, and requirement of well trained interviewers and complicated analysis process, we decided to use paper questionnaire for the data collection phase of this thesis.

Telecommunication company of Iran, responsible person said: “We do not offer MMS service, and do not have any plan to offer it in future”. Irancell was offering this service for some times, but they stopped offering it at the time I was negotiating for this project with them. As I know, now they are going to start offering MMS again. Anyway, after several meetings, finally Irancell agreed to let me use their offices only for distributing the questionnaires and collecting the data. But their staffs would have no cooperation, and I have to do all the tasks myself. In addition I decided to collect some other questionnaires from Telecommunications company of Iran offices in different parts of the city, in order to have a mixed data, consist of both provider customers.

In addition to above, I have sent some of the questionnaires for my colleagues through email, but the response rate was very low, and only 5-6 questionnaires were returned. So, we decide not to consider those questionnaires.

3.5 Pilot test

In this part we had run a pilot test in order to assess the questionnaire’s comprehension and probable problems. The preliminary questionnaire was conducted on 5 Irancell experts and 10 mobile users. The result revealed that some modifications in translation have to be made in to the questionnaire. So, the modifications have been applied, and finally the final version was accepted by my supervisor.

3.5.1 Validity

The validity I also consider to be high. The problem discussion and the questionnaire’s template were revised together with the supervisor at Tarbiat modares University in order to increase the construct validity.

An important factor, regarding the validity is whether the persons were asked by questionnaire were the ones possessing the most accurate and valuable information for this study. Finally, my questionnaire has been seen by my supervisors both English and

Persian version and all its ambiguities and problems were removed and after getting correct and getting validate and being approved by my supervisors they were used.

3.5.2 Reliability

Reliability can be defined as the degree to which measurements are free from error and, therefore, yield consistent results. In the other words, Reliability concerns the extent to which an experiment, test, or any measuring procedure yields the same results on repeated trials (Carmines and Zeller, 1979).

Operationally, reliability is defined as the internal consistency of a scale, which assesses the degree to which the items are homogeneous. The composite reliability measure proposed by Werts et al. (1974) which is an alternate conceptualization of reliability represents the proportion of measure variance attributable to the underlying trait. The composite reliability was used to assess the reliability of the scales for this study.

According to Bagozzi and Yi (1988) a scale considered reliable if the reliability values of each construct are greater than the benchmark of 0.60.

So, for this purpose, the alpha cronbach’s value has been measured for total questions, and it was equal to 0.812, which is acceptable according to the benchmark value.

3.6 Statistical Analysis

For this purpose and for hypotheses test (H2 to H9) I decided to use the Structural Equation Modeling (SEM) approach to evaluate the model (Bagozzi 1988). Also some other statistical analysis plus some descriptive statistics will be describe in detailed in chapter four. A brief introduction of SEM and the reason of its selection are presented in the following section. Advantages of using SEM are also mentioned.

Structural Equation Modeling techniques have become very popular for validating instruments and testing linkages between constructs in Information Systems Research and MIS quarterly journals (Gefen et al., 2000). Structural Equation Modeling (SEM) techniques are second generation data analysis techniques that can be used to test the extent to which IS research meets recognized standards for high quality statistical analysis. In fact the term SEM does not designate a single statistical technique; instead it refers to a family of related procedures (Kline, 1998). SEM enables researchers to answer a set of interrelated research questions in a single, systematic and comprehensive analysis by modeling the relationships among multiple independent and dependent constructs simultaneously (Gefen et al.,2000). This capability for simultaneous analysis differs greatly from most first generation regression models which can analyze one layer of linkages between independent and dependent variables at a time. The results of this test will be presented in the next chapter. Figure 3.1 and table 3.2 shows the hypotheses overview, which we are going to test by Structural equation modeling.

Figure 3.1: Model overview

Hypothesis Effects

H2 RA – IU

H3 PE – IU

H4 C – IU

H5 T – IU

H6 V – IU

H7 RD – IU

H8 IM – IU

H9 VL – IU

Table 3.2: Hypotheses overview

Chapter Four

Data analysis and results

4 Data analysis and results

In this chapter I try to present demographics and descriptive statistics, reliability and validity assessment of the each model’s variable, and then results of hypotheses tests. The software which has been used for this purpose is Lisrel.

4.1 Demographics and Descriptive Statistics

Out of five hundred and fifty questionnaires, two hundred and twenty were completed, and returned (response rate = 40 %). After data reduction, the number of questionnaires was reduced to two hundred and thirteen (38.72%), from which 43 were filled by innovators, 67 by early adopters, 57, early majorities, 34 late majorities and 12 laggards. Table 4.1 lists the sample demographics based on the above classification, and table 4.2 illustrates the total sample demographics.

Item Frequency Percent

Innovator 43 20.2

Early adopter 67 31.5

Early majority 57 26.8

Late majority 34 16

Laggard 12 5.5

Total 213 100

Table 4.1: respondent categories

Measure Item Frequency Percent

Male 129 60.6

Female 84 39.4

Gender

Total 213 100

15-25 56 26.3

26-35 131 61.5

36-45 18 8.45

46-55 6 2.8

55 and over 2 0.95

Age

Total 213 100

No high school degree

34 16

High school degree 45 21.2 Bachelor degree 104 48.8

Post graduate 30 14

Education

Total 213 100

Table 4.2: Sample demographics

between 26-35 years old, 26.5 percent were between 15-25 years old, 8.45 percent were from 36 to 45 years of age and the minorities were over 55 years old.

Most of the mobile users in this survey has bachelor degree (48.8 %) and 21.2 percent had high school degree or high school diploma. Among 213 respondents, 16 percent had education less than high school and 14 percent had continued their education and had more than bachelor degree. In addition to above statistics, the below pie charts show table 4.1 results too.

129; 61%

84; 39%

Male Female

Figure 4.1: Respondent’s gender

56; 26%

131; 62% 18; 8%

6; 3%

2; 1%

15-25 26-35 36-45 46-55 55 and over

Figure 4.2: Respondent’s separated by their age

Table 4.3 classifies the whole respondents by their occupation, and figures 4.4 shows these results in a pie chart for a better perception.

34; 16%

45; 21%

104; 49%

30; 14%

No high school degree High school degree

Item Frequency Percent

Housekeeper 10 4.7

Private 40 18.8

Work in governmental company

12 5.6

Student 43 20.2

Work in private company 84 39.5 Work in manufacturing

industry

16 7.5

No job 0 0

Financial industry 0 0

Other 8 3.7

Total 213 100

Table 4.3: Respondents by their occupation

10; 5%

40; 19%

12; 6%

43; 20%

84; 38%

16; 8% 0; 0%0; 0%8; 4%

Housekeeper Private

Work in governmental company Student

Work in private company Work in manufacturing industry

No job Financial industry

Other

Figure 4.4: Respondents by their occupation

One of the questions in the questionnaire was asking the mobile user, how many SMS does he/she send per day. This question could result to a better understanding of the Iranian mobile user’s attitude toward sending a message by using their mobile phone.

And we could generalize results obtained from this question for multimedia message service (MMS) too. The results of this question are summarized in table 4.4 and figure 4.5.

Item Frequency Percent

1 or less than 1 SMS per day

30 14

Between 2 and 5 SMS per day

98 46

More than 5 SMS per day 85 40

Total 213 100

Table 4.4: Amount of SMS sent per day by the respondents

30; 14%

98; 46%

85; 40%

1 or less than 1 SMS per day Between 2 and 5 SMS per day More than 5 SMS per day

Figure 4.5: Amount of SMS sent per day by the respondents