Investigating Factors which Influence M-payment Services Adoption

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2010:019

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

Investigating Factors which Influence M-payment Services Adoption

by Iranian Customers

Rose Taeb

Luleå University of Technology Master Thesis, Continuation Courses

Marketing and e-commerce

Department of Business Administration and Social Sciences

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Investigating Factors which Influence M-payment Services Adoption by Iranian Customers

Supervisors: Dr. Keramati & Dr. Chelbi

Rose Taeb

Subject: Electronic Commerce

2009

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Acknowledgements

First of all, I would like to pay my sincere regards to my father, my mother and my husband who have taken an utmost concern and intense care for my project, and my academic achievements in general. I pay them my deepest regards for all their inspiration and love, which has always remained invaluable to me, in each and every step of my life.

I wish to pay my deepest respect and thanks to my supervisor, Dr. Abbas Keramati, for spending extended periods of his time during the crucial points of the project, and Dr. Anis Chelbi for his helpful recommendation.

I would like to thank the number of peoples provided information, which was used in the preparation of this report. In particular, I want to thank those who made time available for interviews and also acknowledge the work of M-payment services in Iran, especially those employees who work in central bank, and those citizens who spend time for filling the questionnaire of this report.

At the end I would be thankful from all of my lecturers and my best friends who helped me in all steps of my college life from entering to the university up to the finishing my project.

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List of Tables:

Table 2-1: Summary of Adoption Models Factors ... 21

Table 2-2: Summary of recent research on IT Adoption (from year 2000) ... 24

Table 4-1: Reliability of each factor in the questionnaire (Pilot test) ... 36

Table 4-2: Sections and characteristic of questionnaire ... 37

Table 4-3: Reliability of each factor in the questionnaire (all 623 data) ... 41

Table 4-4: Factor Analysis ... 42

Table 4-5: Factor Analysis for Culture ... 45

Table 4-6: Factor Analysis for culture after eliminating factor ... 45

Table 5-1: Frequency and Percentage of Gender ... 48

Table 5-2: Frequency and Percentage of Age ... 49

Table 5-3: Frequency and Percentage of Occupation ... 50

Table 5-4: Frequency and Percentage of Education ... 51

Table 5-5: Frequency and Percentage of Income ... 52

Table 5-6: Frequency and Percentage of Married Statues ... 52

Table 5-7: Frequency and percentage of demographic characteristic ... 53

Table 5-8: One-sample T-test on Demographic and Cultural characteristics ... 55

Table 5-9: One-sample T-test regarding Gender ... 56

Table 5-10: MANOVA test for Age ... 57

Table 5-11: One-way ANOVA Test result for groups of Age ... 58

Table 5-12: Post Hoc analysis of the difference between respondent views in Age categories ... 59

Table 5-13: Multiple Comparisons for Computer Knowledge, Usefulness, and Trust factors according to Age ... 60

Table 5-14: MANOVA test for Occupation ... 61

Table 5-15: One-way ANOVA Test result for groups of Occupation ... 62

Table 5-16: Post Hoc analysis of the difference between respondent views in Occupation categories 63 Table 5-17: Multiple Convenience factor according to Occupation ... 63

Table 5-18: MANOVA test for Education ... 64

Table 5-19: One-way ANOVA Test result for groups of Education ... 65

Table 5-20: Post Hoc analysis of the difference between respondent views in Education categories . 66 Table 5-21: Multiple Comparisons for Cost factor according to Education ... 66

Table 5-22: MANOVA test for Income ... 67

Table 5-23: One-way ANOVA Test result for groups of Income ... 68

Table 5-24: Post Hoc analysis of the difference between respondent views in Income categories ... 68

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Table 5-25: One-sample T-test regarding Married Status ... 69

Table 5-26: Independent sample T-Test for Active and Potential Adopters ... 71

Table 5-27: One-Sample Statistics of Variable conditions ... 73

Table 5-28: Confirmatory Factor Analysis result ... 77

Table 5-29: Result of first stage of Logistic regression Model ... 78

Table 5-30: Classification Table ... 79

Table 5-31: Result of stepwise backward of Logistic regression Model ... 80

Table 6-1: Empirical Implication Result ... 89

List of Figures:

Figure 3-1: Proposed Framework ... 29

Figure 5-1: Analysis Structure ... 47

Figure 5-2: Standard Estimate condition, Confirmatory Factor Analysis... 75

Figure 5-3: T-value measurement, Confirmatory Factor Analysis ... 76

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Abstract

The advent of Information and Communication technology (ICT) has changed the daily routines of businesses as well as the lives of private citizens. For some citizens, the use of information technology tools is a natural part of their daily lives, while others prefer more traditional channels. This motivates to investigate customers’ adoption of M- payments by examining the adoption determinants that are specific for the M-payment context. For this aim, I am going to review some adoption theories and previous studies which have been done in adoption of M-payment area and extract the most significant factors and finally develop appropriate model for Iranian customers. The proposed conceptual model combines technological Factors of Mallat and behavioral factors of Dahlberg and Öömi models about M-payment adoption. As a result, 623 filled questionnaires are gathered and analyzed. At first descriptive analysis will perform on the demographic characteristics. After that, to find out the impact of demographic and cultural characteristics on other related research factors use ANOVA and MANOVA analysis. At the end, overall fitness of model and affect of survival outcomes will test by Confirmatory Factor Analysis and logistic regression. At the end it concluded this model has a suitable fitness and both technical and behavioral factors affecting on M- payment adoption; although this was different in different demographic and cultural characteristics.

Keywords:

M-commerce, M-payment, Adoption Theory, Technical and Behavioral Factor, Confirmatory Factor Analysis

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Chapter 1. Introduction

1.1 Introduction

In first chapter, explain problem statement of the research about M- payment adoption, after that M-payment in Iran will be described. At next step, Justification, research objective and research problem of this study will be presented. Finally the structure of this Thesis will introduce.

1.2 Problem Statement

With the emergence of information and communication technologies, it is possible to locate services closer to the users through different channels, which help them in managing their transactions. While the E-commerce is mostly about buying and selling, the mobile commerce, widely referred to as M-commerce, is expected to be largely data-driven. Of course, the ever-growing number of mobile phone users as target group, the tendency to reduce costs of transactions and the concern of market players to improve relations with customers represent an enormous potential for mobile commerce (M-commerce) as a new level of electronic commerce. In Addition, for using wireless-based applications effectively in an M-commerce environment, need a better understanding of factors that influence a successful adoption (Wang and Liao, 2007). An example of necessary mobile support services is mobile payment (M-payment) services, which would provide common payment solutions to mobile services. It has already been predicted that M-payment will become a successful mobile service for the reason that in addition to the necessity support services, the growth of M-commerce relies vitally on effective payment solutions provided by M-payment services and vice versa (Constance, 2001; Lee and Benbasat, 2004). The M-payment services have different stakeholders, which are Banks and credit card companies, Mobile operators, Handset suppliers, Merchants and Mobile phone users. As mobile phone users are one of the important stakeholders, it is important to try to investigate on them. This is because of the insufficient user acceptance, which has long been an impediment to the successful adoption of any new system. It is a fact that, at present there is an uncertainty as to whether the adoption and use of M-payment technologies will prevail as expected. Therefore, it is important to consider what factors drive users to adopt new M-payment system or habit them

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Although IT adoption has been researched by academics for more than decades and many theories attempt to explain IT adoption in different domains, there are still several critical components related to IT adoption that have not yet been thoroughly investigated. First, among studies that focus on technology adoption, only a small percentage is devoted to the adoption and use of M-payment as a system but they usually study the adoption of special organization. Second, there is a need to validate existing theories in different contexts. The majority of IT adoption research focuses on the technologically developed world, mostly because the majority of research and academic institutions are located in developed countries and not developing countries as Iran.

Hence, the objective of this work is to provide useful guidelines for researchers and developers of E-commerce applications to better understand the important factors of M- payment, which could be influential on its adoption by users in Iran as a developing country that happen for the first time in Iran.

1.3 M-payment in Iran

Considering the double-digit inflation rate and relative stability in the currency denomination, the recent trend of the payment instrument has gradually moved from notes to various kinds of cheques, particularly traveler’s cheques. The introduction of modern payment instruments in Iran can be traced back to the early 1990s when the commercial bank of Sepah launched its Aber Bank, Debit Card and ATM services. Since then, almost all Iranian banks have provided their customers with the card payment services focusing on cards with debit function and ATM services to tackle the problem of heavy branch traffics. The inter-bank card switch (SHETAB) was introduced in 2002 and now all card issuing banks in Iran are connected to the central bank; building up a uniform card payment network where all issued cards are accepted in all acquiring terminals. (Central Bank of Islamic Republic of Iran Website: www.cbi.ir)

M-payment in Iran is a new way of payment system, which commenced about a year ago.

Despite its recent start, M-payment is used with eight banks from the seventeen Iranian banks (about 50% of them). According to banks in order to use M-payment, special software (pecmp.jar) should be used. It is available in their websites. Thus, in order to activate the M- payment system in the mobile phone, one should install the software, and then send the

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information of inter-bank card to the bank by SMS. According to M. Hakimi, the Vice President of Research Department of Central Bank of Islamic Republic of Iran, there is not any appropriate software with complete security and support of Central Bank for M-payment, and banks created software packages individually, with a complete absence of integration with each other. As a result, inter-banks transactions are not possible, and only some intra- banks transactions happen. While, as said before, since 2002 all banks card (banks cards are as an instrument for doing M-payment) have good potential to provide this services.

As mentioned above, because of the lack of appropriate software, there are not correct statistics about the number of M-payment users. However, according to Mr. Hakimi, there are some unofficial statistics which show that Eghtesad Novin Bank, as the most active bank in M-banking, has registered only about 350 thousand M-payment transactions among the total of 1200 million transactions trough the last year. This small number of transactions is only related to the intra-bank and not inter-bank transaction. The inter-bank activities that can be performed trough Mobile phones are as shown below. Only the two first ones can be considered as M-payment and the others are part of M-banking.

• Electronic payment to other persons’ account in the same bank up to 2000 $

• Payment of bills

• Receiving three last turnovers of the account

• Announcement of a certain turnover

• Announcement of a bounced Cheque

• Changing the Password

• Charging Mobile account

1.4 Justification

Statistics about M-payment and the speeches of Mr. Hakimi increase motivation to perform research on this subject in order to understand why despite all the potentials, which are available for the M-payment in Iran, the number of users is still too small, whereas the number of Card banks and mobile phones users (Card banks and mobile phones are instruments for doing M-payment) are respectively about 58 million and 35 million (Central Bank of Islamic Republic of Iran Website; FABA Center website). Note however that some

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card banks to be greater than the number of mobile phones. These statistics show that most of the above 18 years old of Iranians who can have bank accounts have mobile phones.

Therefore, understanding the factors which influence the M-payment adoption by users is important and useful for both Banks and Users. In fact, considering such factors, banks can provide more attractive services to users, and users can use these services more and more.

1.5 Research Objective

This study aims at investigating the framework of M-payment adoption to find out what are the factors that affect Iranian users’ adoption of this new way of payment system, which allows payments with the mobile phone.

1.6 Research Problem

The main research problem tackled in this work consists in trying to answer the following question:

Research Problem: What are the importance factors that influence the adoption of M-payment services by Iranian customers?

This research problem, will divided to the sub questions according to the framework which will proposed in the chapter three after the reviewing of the adoption theories.

In order to answer this question, we will need to have a close look to theories about the adoption of new information technologies. We will specially focus on adoption factors proposed by Mallat (2007) and Dahlberg and Öörni (2007). Hence, we will be dividing the question into the two following sub-questions:

RQ1: What is the impact of behavioral factors (Mallat characteristics) on the adoption of M- payment services by Iranian customers?

RQ2: What is the impact of technical factors (Dahlberg and Öörni characteristics) on the adoption of M-payment services by Iranian customers?

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1.7 Structure

Chapter two of this thesis will be dedicated to a literature review on E-commerce, M- commerce, M-payment and Adoption theories. In chapter 3, the frame of reference will be discussed the factors which may influence on the adoption of Iranian customers from M- payment services. Chapter 4 will be discussed the methodology which will be used in this study. Chapter 5 presents analysis of collecting data, and study will be ended with conclusion and finding in Chapter 6.

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Chapter 2. Literature Review

This chapter begins with some definitions related to E-commerce and M-commerce. After that, different ways of payment will be reviewed. After that some example of M-payment adoption in different countries will mentioned. Next, the different stakeholders of M-payment will be presented and finally a brief review of adoption literature closes the chapter.

2.2 E-commerce

Electronic commerce (E-commerce) emerged with the development and growth of Internet and the related communication technologies. Some defined electronic commerce as “the buying and selling of goods and services on the Internet” (The Australian Taxation Office (ATO), 1997). On the other hand, some believe that E-commerce involves much more than electronically mediated financial transactions between organizations and customers.

Therefore, many people refer to E-commerce as all electronically mediated transactions (such as facsimile, telex, electronic data interchange (EDI), the Internet, digital television such as cable and satellite, digital media such as wireless and mobile, and the telephone) between an organization and any third party it deals with (Chaffey, 2007). As a result, non-functional transactions such as customer request for extra information would be also considered as a part of E-commerce. Kalakota and Whinstone (1997) defined different perspectives of E- commerce as follows:

• A communication perspective: the delivery of information, products/services or payment by electronic means.

• A business process perspective: the application of technology towards the automation of business transactions and workflow.

• A service perspective: enabling cost cutting at the same time as increasing the speed and quality of service delivery.

• An online perspective: the buying and selling of products and information online.

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Electronic commerce activity can be classified as either business-to-business (B2B) or business-to-consumer (B2C) electronic commerce. In B2B electronic commerce, businesses commonly use the Internet to integrate the value-added chain that can extend from the supplier of raw materials to the final consumer. Although B2B electronic commerce represents the bulk of all electronic commerce, most attention has been directed on the B2C segment, which refers to commercial transactions between organizations and customers.

As it obviously comes out from these definitions, users’ acceptance is one of the important concepts in E-commerce. Nevertheless, insufficient user acceptance has long been an obstacle to the successful adoption of new information systems (IS) and information technologies (IT).

2.3 M-commerce

In regard to the definition of mobile commerce, due to the fact that its development is still at an initial stage, there is not a unified definition. Lee, et al. (2003) defined Mobile commerce as the exchanges or buying and selling of commodities, services, or information on the Internet by using mobile handheld devices. With M-commerce, people can be reached at any time via a mobile device. It not only expands the transaction amount in the electronic transaction market, but at the same time amplifies the entire market of electronic commerce.

In this study, M-commerce refers to the conduct of commerce via wireless devices.

Mylonopoulos and Doukidis (2003) proposed a systematic definition, which views mobile commerce as an interactive ecology system of individuals and corporations, and this ecology system is built upon the social economic background and various succeeding technologies.

Based on the aforementioned, mobile commerce can be generally defined as follows:

Through any highly mobile device and wireless communication network, activities related to commerce transaction, data access, network service, and so on, processed without any boundaries of time and space; or intended to promote business operations and the efficiency of commercial procedures are within the coverage of mobile commerce (Kuo and Yu, 2006).

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These days many E-commerce transactions are conducted through mobile devices (e.g., cellular phones, hand-held or palm-sized computers, and even vehicle-mounted interfaces) using wireless telecommunications networks and other wired E-commerce technologies.

They are referred to as mobile commerce (M-commerce). The potential of these M- commerce applications has increased rapidly in the last little while, leading many organizations to spend enormous amounts of money on these technologies.

While the E-commerce is mostly about buying and selling, the mobile commerce, widely referred to as M-commerce, is expected to be largely data-driven. Of course, the ever- growing number of mobile phone users as target group, the tendency to reduce costs of transactions and the concern of market players to improve relations with customers represent an enormous potential for mobile commerce (M-commerce) as a new level of electronic commerce. In addition, in order for wireless-based applications to be used effectively in an M-commerce environment, we need a better understanding of which factors influence a successful adoption (Wang and Liao, 2007). An example of necessary mobile support services is mobile payment (M-payment) services, which would provide common payment solutions to mobile services.

It has already been predicted that M-payment will become a successful mobile service for the reason that in addition to the necessity support services, the growth of M-commerce relies vitally on effective payment solutions provided by M-payment services and vice versa (Constance, 2001; Lee and Benbasat, 2004). It is a fact that, at present there is an uncertainty as to whether the adoption and use of M-payment technologies will prevail as expected.

2.4 Payment System

Buying and selling goods implies payment, this is what always was happening. In the past, this activity was done using money (notes) but with growing technology people started to use different technologies for payment. At first, people used Internet but they experienced some limitations. One of the important limitations was related to the fact that a connection to Internet is needed to fulfill the transaction. This problem can now be resolved by introducing wireless connectivity, thus introduce M-commerce (Jonker, 2003). Therefore, there are different ways for payment:

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• Paying exact money

• Using Credit card online

• Using Debit card

• Using cell phone (M-payment)

M-payment is shorthand for using a cell phone to pay for goods and services. For consumers, mobile payments mean no more fishing for credit cards or cash, and, with prepaid services, no more monthly bills to worry about. M-payment can be done anywhere and anytime. It is caused by the increasing pace of modern life, the tendency to reduce costs of transactions and the concern of market players to improve relations with customers.

M-payments are catching fire in Japan and Korea, but have so far failed to spark much interest in the U.S. and Europe. In 2003, 94.4% of the number of global mobile payment users was Japanese. This country started developing mobile communication when the rest of the world focused on the Internet. Nevertheless, in Japan because the Internet was not widespread, mobile communication became the way of communication. Telecoms are driving the M-payment revolution in Japan and Korea, but it will be a lot harder for them to follow the same path in the U.S. and parts of Europe where payment cards are already a deeply embedded fixture of consumer behavior, accounting for 70 percent of retail transactions. In these places, any telecom wishing to establish an M-payment system is up against a population that is not eager to move away from its familiar payment systems and might never have thought of cell phones as payment devices. (Jonker, 2003)

The single most important step in building a successful M-payment system is to set the incentives for all stakeholders. Without this, there will be no progress. Each of the participants, furthermore, should accept certain fundamentals and step up as needed for the good of the entire enterprise: (Friedrich, R. et al., 2005)

• Banks and credit card companies (and incumbent stakeholders like acquirers, which bring new merchants into the network and process transactions, and network operators, which equip merchants with POS technology) should leverage existing value chains, rather than build new competitive solutions. They should also evaluate ways to let mobile telecoms participate in collaborative value generation.

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• Mobile operators should consider new mobile payment systems in the context of new ways to open up revenue streams, especially from monthly M-payment subscription charges or per transaction fees. Operators should also take full advantage of the positive side effect of embedding the mobile phone even deeper into the life of the subscribers (a significant motivator in the Japanese model).

• Handset suppliers should embrace new approaches and start to consider active integration of mobile payment capabilities into product road maps and line-ups.

Mobile payment capabilities are seen by some as the next big thing to drive handset replacement, making standardization and compatibility across operators and platforms critical to preserve user attractiveness and scale benefits.

• Merchants should use their vast experience with cashless payments to drive further cost decreases that accrue from giving up cash, and to offset POS technology upgrade costs.

• Mobile phone users are more attractive to mobile payment than other more familiar payment schemes. The bundle of convenience aspects (safe, secure, available, fast, transparent, etc.) needs to be packaged and sold to target groups individually.

However, since insufficient user acceptance has long been an impediment to the successful adoption of any new payment system (Wu and Wang, 2005), it is imperative to consider what factors drive users to adopt new M-payment system or inhibit them from doing so. The three principal forces that would determine the user uptake are Habit (Saji, 2007), Cost Proposition (Wu and Wang, 2005) and Convenience (Saji, 2007).

2.5 Adoption

Information technology (IT) adoption is critical to the growth of an economy (Kendall et al., 2006). According to the papers and articles, Davis (Davis, 1989) proposed the first and common theory of adoption in 1983. His theory was “Technology Acceptance Model (TAM)”. In his theory, he proposed that Perceived Ease of Use and Perceived Usefulness affect the acceptance and use of information systems technology. This theory modified several times. Ahmad Al Sukkar & Helen Hasan did one of the modifications in 2005. They

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clarified that Culture, Trust and Technical Quality are the external factors that affect on Perceived Usefulness and Perceived Ease of Use factors in TAM model (Sukkar and Hasan, 2005).

Another important theory of adoption is the Innovation Diffusion Technology (IDT), which was defined by Rogers. According to Rogres (1995), potential of adopters evaluate an innovation based on innovation attributes such as Relative Advantages, Compatibility, Complexity, Observability, and Trialability. He clarified that characteristics of Relative Advantage can be stated as Usefulness and Complexity as opposite to Ease of Use (Rogers, 1995). Diffusion research has been criticized for its deterministic character and for its ex post approach to diffusion (De Marez and Verleye, 2004; McMaster and Wastell, 2005). To overcome the limitations of diffusion research, De Marez and Verleye (2004) make it clear that insight into customer needs and Adoption Potential is important (De Marez and Verleye, 2004). In De Marez and Verleve’s defense Rogers clearly draws a distinction between the knowledge of an innovation. Furthermore, he is aware that the adoption of an innovation is not a straightforward process and that innovations often fail to pass the tipping point, i.e. the point at which critical mass is reached and the diffusion process takes off, reaching not only the innovators and early adopters but the early majority as well. According to Rogers (2003), attitudes towards a specific innovation intervene between the knowledge of an innovation and the decision to adopt. There are a number of related concepts, like the more general novelty seeking (Hirschman, 1980) and need for innovativeness (Lin, 1998), and the more specific Product Specific Adoption Potential (De Marez and Verleye, 2004). In the separate analysis, Tornatzky and Klein identified 10 characteristics, which included 5 characteristics indentified by Rogers plus Cost, Communicability, Divisibility, Profitability and Social Approval. In their discussion, they noted that Communicability is closely related to Observability and Divisibility to Trrialability (Tornatzky and Klein, 1982).

After Rogers, different modifications were done on the Rogers’s Innovation Diffusion Theory; one of the most popular and common modification was done by Moore and Benbast on 1991 (Moore and Benbast, 1991). They proposed Perceived Characteristics of Innovating (PCI) theory and added several constructs to Rogers’s theory. These constructs are (1) Image (the degree to which use of an innovation is perceived to enhance one’s image or status in one’s social system), (2) Voluntariness of Use (the degree to which use of innovation is perceived as being voluntary or free will), (3) Visibility (the extent to which an innovation is

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perceived to be widely diffused), (4) Result Demonstrability (the degree to which the unique features and benefits of an innovation are readily discerned by the potential adopter).

Whereas, behavior of users influence on the acceptance of them on the new technology, Ajzen and Fishbein proposed Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB). In their theories, they clarified that Attitude toward Behavior, Subjective Norm, and Perceived Behavioral Control affect on Intention to Use and Usage Behavior (Ajzen and Fishben, 1991). Furthermore, one has to be careful with the extrapolation of adoption behavior based on limited knowledge of user behavior (Bouwman and Van der Duin, in press). Extensive research into know-how of and attitudes towards innovations is important if understanding future behavior. Many variables correlate with the knowledge of an innovation (the knowledge of various types of mobile devices and services). Education and Socio-Economic Status, as well as Personality Variables and Communication Behavior, explain the differences in knowledge of an innovation.

Lockett & Littler examined the behavioral characteristics of the adopters. They noted that, although there are many behavioral characteristics, which can be considered, but “Social Interactions” are mentioned because they have a good potential in terms of useful findings on the categories of adopters. According to Lockett and Litter (1997), Social Character and Opinion Leadership can measure Social Interaction and Communication. In addition, the factor used for measuring “Attitude and Personality” include Attitude towards Change and Venturesomeness. (Lockett and Littler, 1997)

In addition to above factors, which affect on the adoption of new technology, Demography factors affect on the adoption. Age, Income and Education all are directly related to the adoption of technology (Donnelly, 1970; Lee and Lee, 2000). Gender has not been found to have a direct effect on adoption of technology in general (Taylor and Todd, 1995; Gefen and Straub, 1997), but men are more likely to adopt specific computer technologies (Gefen and Straub, 1997). Kolodinsky et. al. (2004) mentioned to the Marriage status of persons and noted that, Marriage status will affect on the adoption of new technology, especially e- banking. They noted that, when married couples come to bank accounts, they may have jointly held account; thus at the household level, adoption maybe related to marriage status.

(Kolodinsky, 2004)

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(Mallat, 2007) examined consumer adoption of new electronic payment service, mobile payments. The theoretical background of his study was drawn from the diffusion of innovations theory of Rogers (1995), which has been widely established as a powerful tool to explain the adoption of a variety of financial and mobile technologies including electronic payment, mobile commerce and mobile banking. He added Network Externalities, Costs, and Payment System Security and Trust factors to Relative Advantages, Compatibility and Complexity of Innovation Diffusion theory, which Tornatzky and Klein (1982) Suggested as most relevant constructs to adoption research.

(Dahlberg and Öörni, 2007) examined Changes in Consumer Payment Habits especially in context of Mobile Payment. In their study, they examined Time Benefit, Payment Habit, Trust, Security, Compatibility, Availability of Payment transaction Information, Ease of Use, Convenience, Social Norm, Age, Education, and Mobile Phone Skill. They found that consumers regard five specific beliefs important for new payment instruments: Social Norm, Compatibility based on Skills, Trustworthiness, Compatibility (large applicability) and Ease of Use. They claimed that compare to previous diffusion and acceptance studies (TAM especially) the role of compatibility and trust come out strongly. In the analysis of use intentions they discovered that factors impacting the use intentions of these payment habits fall into facilitating (e.g. trust) and differentiating factors (e.g. ease of use). They also discovered that current use of these technologies, age, and profession are differentiating factors. In addition to mentioned factors, the basic demographic characteristics of respondents used to evaluate their Mobile phone skills.

Both tables shown below, present summaries of the adoption models. Table 1 is the summary of adoption factors, by model developers’ persons. Table 2 is the summary of recent research on IT adoption made after year 2000.

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Table 2-1: Summary of Adoption Models Factors

A d o p ti on f a ct o rs

Davis, 1989 Sukkar and Hasan, 2005 Rogers, 1995 De Marez and Verleye, 2004 Tornatzky, and Klein, 1982 Moore and Benbast, 1991 Ajzen and Fishben, 1991 Lockett and Littler, 1997 Mallat , 2007 Dahlberg and Öörni, 2007

N u m b er

Perceived Ease of

Use / Complexity 7

Perceived Usefulness/

Relative Advantage

6

Attitude toward

Using 2

Behavioral

Intention to Use 3

Culture 1

Trust 3

Technical Quality 1

Compatibility 5

Observability 3

Trialability 3

Needs 1

Wants 1

Adoption

Potential 1

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A d op ti o n f ac tor s

N u m b er

Cost 2

Profitability 1

Divisibility 1

Communicability 2

Social Approval 2

Image 1

Voluntariness of

Use 1

Visibility 1

Result

Demonstrability 1

Attitude toward

Behavior 1

Norm 2

Perceived Behavioral

Control 1

Attitude towards

Change 1

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A d op ti o n f ac tor s

N u m b er

Venturesomeness 1

Demography 1

Network

Externalities 1

Security 2

Time Benefit 1

Payment Habit 1

Convenience 1

Payment transaction

Information 1

Availability Mobile Phone

Skill 1

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Table 2-2: Summary of recent research on IT Adoption (from year 2000)

Researchers Context Adoption

Factors

Instrument Findings

Plouffe, et al , (2001) The phenomenon of multi-group adoption with a particular focus on applications within the new smart card-based electronic payment system

Using PCI and TAM model:

Relative advantage, Compatibility, Trialability, Ease of use, Visibility, Result

Demonstrability, Image, and Voluntariness

Data were collected via mail survey from consumers and merchants who chosen by random samples

They found that a detailed analysis of adoption antecedents can lead to marketing mix strategies that improve the

likelihood of adoption of a technological innovation among target segments and groups

Eastin (2002) The adoption of four e-commerce activities currently available to Internet users: (1) online shopping, (2) online banking, (3) online

investing, and (4) electronic payment for an Internet service

the diffusion model factors:

perceived convenience and financial benefits, risk, previous use of the telephone for a similar purpose, self- efficacy, and Internet use

Data were collected from a large USENET organization (i.e., nntp.msu.edu). 50 news groups were randomly selected from 127 target population and send email to them.

Results indicate that six attributes common to the diffusion model (i.e., perceived convenience and financial benefits, risk, previous use of the telephone for a similar purpose, self- efficacy, and Internet use) all play a significant role in the adoption processes.

Results also indicate that when users decide to adopt one of these activities they tend to adopt another.

Lee, et al., (2003) compared smart card adoption in Singapore and Australian universities

Based on Rogers(1995), Moore and Benbasat(1991) and Davis(1989) models: Relative advantage, Compatibility, Trialability, Ease of use, Visibility, Result

Demonstrability, Image,

Information, and Perceived usefulness

Use pilot study for determining the sample size. Using Questionnaire for collecting data form MU and MTU students

The compatibility and relative advantage constructs were identified by both of these studies as the major factors that influence the adoption process of smart cards. In addition, local students would most probably be willing to adopt.

University environment does offer one of the best opportunities for the adoption

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Researchers Context Adoption Factors

and Helen Hasan (2005)

the penetration of Internet banking in Jordan (a strategic developing country of the Middle East)

modification:

Perceived Usefulness, Attitude toward using, Behavioral Intention to Use, Perceived Ease of Use, Culture, Trust and Technical Quality

exploratory interviews of major banks in Jordan and their customers

acceptance model may be more useful if it is extended to include specific issues of culture and trust on the customer side and more basic elements of quality in technology usability and service on the side of the banks.

Mallat, N. (2007) Examined consumer adoption of new electronic payment service, mobile payments

IDT modification:

Relative Advantages, Compatibility, Complexity, Network Externalities, Costs, and Payment System Security, and Trust

Using focus group interviews: Teens, Students, Young adults I, Young adult II, parents, and middle-aged

The results suggest that the relative advantages of mobile payments include time and place independence, availability, possibilities for remote purchases, and queue avoidance. The interviewees found mobile payments to be mostly compatible with digital content and service purchases and to complement small value cash payments.

Interestingly, the findings suggest that the relative

advantages of mobile payments depend on certain situational factors such as lack of other payment methods or urgency.

Dahlberg and Öörni (2007)

examined Changes in Consumer Payment Habits especially in context of Mobile Payment

Time Benefit, Payment Habit, Trust, Security, Compatibility, Availability of Payment transaction Information, Ease of Use,

Convenience, Social Norm, Age, Education, and Mobile Phone

Survey

questionnaire mail to 2000 randomly selected Finnish consumers aged between 18 and 65 years

They found that consumers regard five specific beliefs important for new payment instruments:

social norm, compatibility based on skills,

trustworthiness, compatibility and ease of use. Compared to many previous diffusion and

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Researchers Context Adoption Factors

Skill acceptance Studies,

the role of compatibility and trust comes out strongly

Nan, et al (2008) Survey was done in two empirical studies: among the freshmen of undergraduate students in a business school and the users of a newly

implemented e- Government system

Perceived Usefulness, Attitude toward using, Behavioral Intention to Use, Personal

innovativeness of IT, Job relevance, Substitutability, Impression of training, Compatibility, Resource facilitating conditions, Technology facilitating conditions, and Perceived enjoyment

Survey was done in Two rounds:

First, 134 questionnaires were distributed and 121 valid responses were collected, with a responding rate of 90 percent.

Second, Questionnaires were handed out to the 121 students who participated in the first round and 93 valid responses were collected, with a responding rate of 77 percent

The decline of usage could both be attributed to the problems hidden in compatibility and facilitating conditions

After literature review and adoption theories, which explained in this chapter, the proposed framework for this research will be explained in next chapter.

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Chapter 3. Frame of Reference

So far, the literature related to M-payment and customer adoption has been reviewed, and different adoption models have been introduced. In this chapter, research questions are indicated and the selected theoretical framework is described.

3.2 Theoretical Framework

The aim of this section is to provide an appropriate frame of reference for investigating the adoption of M-payment services by Iranian Customers.

According to the previous chapter, there are different kinds of theories and models, which have been proposed for the adoption of new technologies. However, few studies investigate about the isolated system of new technology such as M-payment services. The current study will be based on the two last adoption models which have been proposed by Mallat (2007), and Dahlberg and Öörni (2007).

In his study, Mallat used a qualitative approach. As mobile payments are a relatively new research area with little previous empirical work on the subject, a qualitative approach using focus group interviews was proposed to explore consumer adoption of mobile payments. For doing this study, he examined some factors, which are affecting users’ adoption of M- payment. These factors are: Relative Advantages, Compatibility, Complexity, Network Externalities, Costs, Payment System Security, and Trust. These factors come from the Modification of IDT model (Rogers, 2003). The focus groups that were interviewed were teenagers (14-15 years of age), university students, young adults who had already entered working life, parents of small children, and middle-aged persons. The discussions followed a semi-structured guide, which was tested with a pilot group of young adults. His group sizes varied between 6 and 9 Helsinki (capital of Finland) subjects and the total number of subjects was 46. His further selection criterion for participants was previous experience on mobile phone use. Experience on mobile phone use was estimated to be necessary in order for the participants to be able to discuss the use of mobile payments.

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After the interview, points are assigned to each factor considered in his model. The relative advantages of mobile payments mentioned by interviewees included the possibility to make purchases ubiquitously, independence of time and place, and possibility to avoid queues.

Factors inhibiting mobile payment adoption reflect the immature state of mobile payment market, and include complex solutions, premium pricing, low adoption rates, perceived risks and perceived incompatibility with large value purchases. These findings suggest that in order to create volume, mobile payment systems need to be better integrated with existing financial and telecommunication infrastructures. Proprietary systems with exclusive service providers and infrastructures are not likely to succeed in the long term. Instead, compatibility with users’ existing services and common standards between different service providers could facilitate adoption and advance the emerging market. (Mallat, 2007)

Dahlberg and Öörni in their paper seek to find out if the generic technology adoption models are sufficient to explain factors consumers consider when they decide whether or not to adopt new payment services. In particular, they develop two models in the payment context. One of them models the determinants of the mobile payments services adoption while the other models the determinants of electronic invoicing adoption. They combined some factors of various adoption models and developed their research models. In their research model, they considered the following adoption factors: Time Benefit, Payment Habit, Trust, Security, Compatibility, Availability of Payment transaction Information, Ease of Use, Convenience, Social Norm, Age, Education, and Mobile Phone Skill. The empirical part of their research consisted of three phases. They augmented the research model with individual and focus group interviews. Then, they developed the final survey questionnaire with an expert panel and tested it with a pre-study. Finally, they collected data with a self-administered mail survey sent to 2000 randomly selected Finnish consumers aged between 18 and 65 years. The aim of the mail survey was to collect a sufficiently large set of data for statistical analyses.

They found that consumers regard five specific beliefs important for new payment instruments: social norm, compatibility based on skills, trustworthiness, compatibility (large applicability) and ease of use. In addition, in the analysis of use intentions they discovered that factors impacting the use intentions of these payment habits fall into facilitating (e.g.

trust) and differentiating factors (e.g. ease of use). They also discovered that current use of these technologies, age, and profession are differentiating factors. (Dahlberg and Öörni, 2007)

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As both technological factors and behavioral characteristics are important in adoption of new technologies, choosing these two studies is because, Mallat focused more on the technological factors that affect on the adoption of new technology, whereas Dahlberg and Öörni focused more on the behavioral characteristics (although they use some of the technical factors such as time benefit and convenience).

As a result, in this study the factors of Mallat (2007) and those of Dahlberg and Öörni (2007) will be used to identify the most influential factors on the adoption of the M-payment services by Iranian customers. Hence, the proposed framework will be as follows:

Source: Dahlberg T. and A. Öörni (2007) Mallat N. Factors

______________________

Ease of use/ Complexity Usefulness/ Relative Advantage

Trust Compatibility

Cost

Network Externalities Security

Dahlberg T. & A. Öörni Factors ______________________

Demography Norm Payment Habit

Payment Transaction Information Availability Mobile Phone Skill

Culture Convenience Adoption Factors

Source: Mallat, N. (2007)

Figure 3-1: Proposed Framework

3.3 Research Question(s) or Objectives

According to the previous sub-section, the first question, which should be answered at the end of the study is: “RQ: What are the importance factors that influence on the adoption of M-payment services by Iranian customers?”. Obviously, it is a comprehensive question that

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should be divided into partial questions. These partial questions arise from the factors used by Mallat (2007) and Dahlberg, and Öörni (2007). Therefore, the main research question can be divided into the some sub-research questions, which are:

RQ1: What is the impact of Technological characteristics (Mallat charactrestics) on the adoption of M-payment services by Iranian customers?

RQ1,1: What is the impact of Ease of Use (Complexity) characteristic on the adoption of M-payment services by Iranian customers?

RQ1,2: What is the impact Usefulness (Relative Advantage) characteristic on the adoption of M-payment services by Iranian customers?

RQ1,3: What is the impact of Trust characteristic on the adoption of M-payment services by Iranian customers?

RQ1,4: What is the impact of Compatibility characteristic on the adoption of M- payment services by Iranian customers?

RQ1,5: What is the impact of Cost characteristic on the adoption of M-payment services by Iranian customers?

RQ1,6: What is the impact of Network Externalities characteristic on the adoption of M-payment services by Iranian customers?

RQ1,7: What is the impact of Security characteristic on the adoption of M- payment services by Iranian customers?

RQ2: What is the impact of the Behavioral characteristics (Öörni characteristics) on the adoption of M-payment services by Iranian customers?

RQ2,1: What is the impact of Demography characteristic on the adoption of M- payment services by Iranian customers?

RQ2,2: What is the impact Norm characteristic on the adoption of M-payment services by Iranian customers?

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RQ2,3: What is the impact of Payment Habit characteristic on the adoption of M- payment services by Iranian customers?

RQ2,4: What is the impact of Payment Transaction Information characteristic on the adoption of M-payment services by Iranian customers?

RQ2,5: What is the impact of Availability Nobile Phone Skill characteristic on the adoption of M-payment services by Iranian customers?

RQ2,6: What is the impact of Culture characteristic on the adoption of M-payment services by Iranian customers?

RQ2,7: What is the impact of Time Benefit characteristics on the adoption of M- payment services by Iranian customers?

RQ2,8: What is the impact of Convenience characteristic on the adoption of M- payment services by Iranian customers?

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Chapter 4. Methodology

In this chapter, at first research methodologies are indicated. In methodology subsection, discuss about Research purpose, Research approach, Research Strategy, Sample selection and data collection. At the end, the instrumentation for requirement analysis was mentioned.

4.2 Research Purpose

Research purpose is an important thing, which should be considered. Within this highlighted, how the way in which asked the research question would result in descriptive, explanatory or exploratory. In descriptive study, research will be done for the purposing of producing an accurate representation of person, events or situation (Robson, 2002). Explanatory study focuses on studying a situation or a problem in order to explore and understand the data.

Exploratory study aims to seek new insights into phenomena, to ask questions and to access phenomena in a new light (Robson, 2002).

From the above explanation and the object of this research for finding the answer to the

“what are the important factors that influence on the adoption of Iranian customers of M- payment services”, it will be concluded that the suitable research purpose for this research is Descriptive research purpose.

4.3 Research Approach

The design of any study begins with the selection of a topic and a research methodology.

Two general approaches are widely recognized: quantitative research and qualitative research. Quantitative research is an inquiry into an identified problem, based on testing a theory, measured with numbers, and analyzed using statistical techniques. The goal of quantitative methods is to determine whether the predictive generalizations of a theory hold true. By contrast, a study based upon a qualitative process of inquiry has the goal of understanding a social or human problem from multiple perspectives. Qualitative research is conducted in a natural setting and involves a process of building a complex and holistic

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research, try to use from the existing models and test it in the context of Iran by using from statistical techniques, quantitative research will consider.

Research approach is important for designing the research. It is because of; the research project will involve the use of theory. Research approach can be Deductive or Inductive. In deductive approach develop a theory and hypothesis and design a research strategy to test the hypothesis. However, in inductive approach would collect data and develop theory as a result of data analysis (Saunders et al., 2007). As in this research, use from literature to develop a theorical framework and test these factors in this research situation by selecting some sample from the whole population, the research approach is Deductive.

4.4 Research Strategy

Survey, Case Study, Experiment, Action Research, Grounded Theory, Ethnography, and Archival Research are different types of Research Strategy (Saunders et al., 2007).

According to Yin, there are number of approaches for a researcher to conduct empirical data collection. Depending on the character of research question, the researcher can choose between an Experiment, a Survey, an Archival Analysis, History and a case study (Yin, 1994). Survey is a technique in which information is collected from a sample of people through a questionnaire. According to Yin (1994), a Survey is research strategy which consists of “who”, “what”, “where”, “how many” and “how much” forms of research questions (Alagheband, 2006, Ghezelayagh, 2006). As this study aim to find out the factors that influence adoption of using M-payment services by Iranian customers, the strategy which suit for this study will be survey. This choice is partly determined by one of our research approaches, quantitative nature. In addition, the Survey strategy is usually associated with the deductive approach, descriptive purpose and involves the structured collection of data from a sizeable population, the most suitable research strategy is Survey.

4.5 Sample Selection

Sampling is a survey-based research where researcher needs to analyze the sample about a population to answer the research questions or meet the research objectives (Saunders et al., 2007). As Saunders mentioned the choice of sampling technique depends on the feasibility

Investigating Factors which Influence M-payment Services Adoption

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

Investigating Factors which Influence M-payment Services Adoption

by Iranian Customers

Rose Taeb

Investigating Factors which Influence M-payment Services Adoption by Iranian Customers

Supervisors: Dr. Keramati & Dr. Chelbi

Rose Taeb

Subject: Electronic Commerce

2009

Acknowledgements

Table of Contents

List of Tables:

List of Figures:

Abstract

Keywords:

Chapter 1. Introduction

Chapter 2. Literature Review

A d o p ti on f a ct o rs

N u m b er

A d op ti o n f ac tor s

N u m b er

A d op ti o n f ac tor s

N u m b er

Chapter 3. Frame of Reference

Chapter 4. Methodology