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CHAPTER 2
REVIEW OF LITERATURE
In the previous chapter, elaborate attempts were made to describe broad concepts related
to Mobile banking. In this chapter, the literature review is done and it started with the
introduction of M-banking which has been reduced to M-banking in India. The market for
M-banking and the various modes of M-banking procedures were also reviewed. The
researcher has also studied the different technologies utilized by the banks in providing M-
banking services. The transmission ofthis innovation, its adoption and further development
of innovative technological advancement i.e. M-banking was also surveyed. This chapter
also helps in describing the adoption and acceptance phase ofM-banking, which has pulled
attention in the past studies of Roger’s Diffusion of Innovation Theory and other models
and theories related to the research carried out in the historical and recent years. This
chapter serves as a framework for this thesis.
2.1 Introduction
Today, the number of mobile phone subscribers is more than 7 billion, up from 748 million in
the year 2000. According to ITU reports, (2016), globally, 3.2 billion individuals are using the
Internet, of which 2 billion belongs to the developing countries. This advancement in the
technology has opened a new domain of prospects for business houses and retailers to sell and
advertise their range of goods and services for clients anywhere and everywhere. In today’s
world, users are “on-the-go” and they value those objects which are easily accessible to the
users.
Banking is one instance of such services. Those days were gone when users used to stand in a
queue to fulfill their financial and non- financial banking needs. In today’s world of advanced
technology, by using electronic banking (e-banking), users can easily transfer funds between
their accounts on click of a button. According to the report of Deloitte (2011), there are few
users of M-banking instead of so much advancement in the mobile technology and banking
sector.

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2.2 Mobile Banking
M-banking services give many services to the financial institutions, like,generating an additional
income, expanding the consumer base, reduce costs, and improve operations. M-banking
services applications are accessed via smartphones, cell phones, and tablets for performing
financial transactions like transfer of funds and other non-financial transactions, like inquiry of
balance (Shaikh, 2015).
Ritu Narwal (2014) stated that developments in telecommunications have facilitated the banks
to introduce innovative procedures for the access of banking services, out of all, one is mobile
banking;inwhicha user interacts with the bank via cellular phone. Inservice use, cellularphones
are used not only for talking and sending text messaging (SMS), but its usage is likely to increase
with the advancement in the technology. The prospects of these innovative technologies in
provision have generated new challenges to the originators of financial banking services; it has
helped to attain the competitive advantage by saving the costs or increasing the user
satisfaction. In order to meet these challenges, M-banking service providing firms seems to be
more interested in enhancing their understanding of an individual’s behavior. This research
work attempted to study the mobile banking overview and its issues and challenges. Mobile
banking has provided all users with day to day banking operations to the users with just one
click of his mobile handset with the supported application.
In the recent mobile technological advancements; one is M-banking. Although ATM, Internet
banking, and telephone also offer the provision of conventional banking products, retail banking
sector and microfinance banks in many developing and developed countries has established as
the latest delivery channels; one is M-banking that has an important impact on the market
(Safeena, Date, Kammani, and Hundewale, 2012).
According to Shaikh (2013), use of smartphones has increased and this has become the main
reason for the increase in demand of M-banking services, this is forcing many banks to offer
these services with innovative applications, specially designed for their clients to improve
customer retention, to increase financial inclusion, enhance market share and offer
employment opportunities. In spite of these benefits of using M-banking services for various
financial transactions and non-financial transactions, it is not very popular as it was expected
(e.g., Dineshwar, 2013; Shih, 2010; and Luarn, 2005), as verified by widespread media reports
(Accenture, 2013).

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Juniper Research report of 2013 has revealed that by 2017, there will be more than 1 billion
users of M-banking, but this is only the 15% of the global phone subscribers. This base accounts
for 95% of the population of the world as per ITU Reports of 2016.
In addition to this, almost half of the mobile phone subscribers are without the bank accounts,
with having only restricted access to customary financial banking services, depicted in Table 2.1.
These developments suggested that noteworthy growth opportunities still remain which is
leading to estimates of substantial surge in the number of users using mobile banking services.
All these data and numbers have authorized the researcher to conduct further examinations of
any remaining issues and factors related to M-banking services adoption, particularly in the case
of mobile phone subscribers.
Table 2.1: M-banking users
Total Global Population 7.100 billion 100%
Mobile phone Subscription 6.835 billion 96%
Mobile Banking accounts or users 0.590 billion 8.6%
Source: International Telecommunication Union, 2010
Despite extensive investigation on the acceptance and adoption of mobile banking that has
existed in many national and international journals across various disciplines, an extensive
literature review on the acceptance and adoption of mobile banking remains lacking. Such type
of in-depth review of literature epitomizes an imperative breakthrough in the advancement of
this field of research. This type of review generally provides a chance to reconsider and
reexamine the collected data that had been gathered from the past researches that have used
several theories, methods, and samples. This kind of effort is predominantly vital when the
results and findings of inaccessible researches have contradicted one another (Hanafizadeh,
Behboudi, Koshksaray, and Tabar, 2014). This research work, therefore, strives to enhance the
knowledge regarding mobile technological advancements by carrying out a comprehensive
reevaluation of the individual’s attitude towards adopting of mobile banking services.
Bearing inmind the intricacy of advancementin the mobile technology and the range of services
and facilities offered, the present research work seeks to enhance the review of literature on
mobile banking services by utilizing exploratory methods of study and investigating the present-

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day status of M-banking and its acceptance and adoption within many levels of populations
residing in developing and developed countries. While reviewing the literature, it can help in
integrating the incongruent courses of investigation for understanding and review the various
frameworks, methodologies, and models that has been used in this study. Finally, this research
work synopsized the major results and findings and identified numerous gaps that need further
investigation in this field.
2.2.1 Electronic Banking
Regarding e-banking, it is imperative to note that it is a much wider term than just considering
it as conducting all types of banking transactions via internet. Though, the most common type
of e-banking is conducting all the banking transactions financial or non- financial based through
the Internet, also known as Internet banking. E-banking has been defined by many researchers
in various ways and in a very simple manner; it may be defined as “the provision of information
or services by a bank to its customers, via a telephone, television, computer, or mobile phone
(Daniel, 1999)”.
Banking on Personal computers allows users to conducttheir banking transactions only onthose
computers, in which the specific software has been installed such as Microsoft Corp.’s Money
and Intuit, Inc.’s Quicken. Karjaluoto, Mattila, and Pento, (2002) suggested that in banking, the
key electronic delivery channel is the Internet, that can be accessed through computers.
In today’s era of digitization, the traditional ways of banking such as banking on television,
telephone banking. However, many researchers have found out that in the future, the delivery
channel will modify itself from wire based internet networks to advanced wireless mobile
internet technologies. According to Wah (1999) for e-banking computer screen is not the basic
necessity, but users can use it on their own mobile phone’s screen as well. With the updated
technology,users cangetaccess to their bank accounts on their small screen ofmobile handsets.
They can check their account statements, account balance, send emails to the banks and also
instruct to buy or sell securities online or to initiate the payments etc.
As stated by Daniel, 1999; Jayawardhena,(2000), in many of the developed countries,e-banking
has begun as a new channel of delivery for conducting banking transactions and it has a great
impact onmany of the developed country’s banking sector. Itis alsoargued by Nehmzow (1997),
Internet banking is an advanced form of banking which is helping the old players in the financial

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67
sector of banking toreduce their cost by offering services atlow distributioncost. The researcher
also stated that internet banking will give competition to the old branch-based system of
banking and will reduce their market share.
Some researchers have alsoshown concern over the disappearance of the branch based banking
system as the prospects of internet banking is gaining importance. Researchers are also keen to
notice the future of old branch based banking after the advancement of technology in the
banking sector and over increasing demand for internet banking. (Wah, 1999) stated that due
to this technological advancement, branch-based banking will not be negatively impacted, but
it will help these banks to reach the top level. The researcher also stated that with this new
advanced technology, banks will be able to manage their customers in a better manner than
before.
2.2.2 Internet Banking
Internet Banking implies to those services of the banks when provided to the users via the
internet, like services introduction, the inquiry of balance in the account, loan application, and
transfer of funds and so on. I-banking has developed as a “one step service and information
unit” this assures the major assistances to the users as well as to the banks.
As per, Michael Karlin, the President and (COO) Chief Operation Officer of “Security First
Network Bank” (the world’s first such banks), Internet Banking requires:
1. As all the type of banking transaction takes place on the bank’s server or website, so users
need not to buy or install any kind of software or store any data on their personal
computers.
2. For conducting the financial banking transactions easily and be able to conduct their
banking transactions from anywhere users need a personal computer and a modem.
3. The Customer can use the banking services 24 * 7 a year. They no longer have to stand in
a long queue.
2.2.3 Mobile Banking in India
In the past decade, I-banking has proved to be the most useful and successful type of e-
commerce application. Due to technological advancement, banks are facing difficulties in the

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survival in this digitized era of the banking sector by ignoring the essence of electronic
commerce. According to Graumann and Koehne (2003), the M-banking users has increased to
40.5% in 2007 from 14.9% in 2001.
According to Kreyer, Pousttchi, and Turowski (2002), Pousttchi and Schurig (2004) the capacity
and ability of internet banking is much more than what has been attained in term of M-banking.
It allows using the mobile phone for conducting banking transactions via wireless networks
anywhere and anytime. The ever increasing demand of mobile phone for conducting banking
transactionsis taking electronic commerce toits nextupperlevel. Itis noticeable thatM-banking
is not in competition with internet banking, but they will exist as allies.
2.3 Adoption of Mobile Banking
The authors (Lamb, Hair, and McDaniel, 2004) characterized consumer behavior as “the acts of
decision-making which directly involve the obtaining and utilizing need-satisfying products and
services, which incorporates the decision-making process”. Rice (1997) defined consumers as
“individuals who use products and services and make payment for those the things they have
bought”. According to (Schiffman and Kanuk, 2000), there are two kinds of consumers: personal
and business (organizational consumers). “The buying of products,services, equipment, etc. just
to expedite their business” are business consumers, whereas “individuals who buy goods and
services for their own use” are Personal consumers. As per Block and Roering, (1979) the “act
of procuring and using economic goods and services is denoted to as consumer”. Users are
involved in decision making when they are purchasing the product or service either online or in
offline mode i.e. through stores and banks will be able to study the profile of all those users to
gain deep insight of characteristics of their target users and it will also help the researcher or
the banks to understand the constructs which influence the purchasing behavior of the
consumer and the challenges or difficulties faced by them during online purchase.
There are numerous predetermining variables that has an impact on the user’s attitude towards
M-banking services and many researchers have also found out that motivational factors,
demographic factors and user’s acceptance of advanced and innovative technology are a few of
them. Researchers have also studied that the attitude of the individuals in the developed
countries is generally influenced by their past experience in the relevant technology and it has

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actually helped the researchers to enhance the rate of adoption due to past experience but this
is not the case in the developing countries where the advancement in the technology is at the
nascent stage only. According to Benamati and Serva (2007), while using e-banking users are
more concerned about the integrity of the password, hacking, protection of personal
information shared during the process etc. There are many other challenges that have been
faced by the user of e-banking services that can either affect their decision positively or
negatively.
2.4 Theoretical Framework
2.4.1 Social Psychology
There are a few conceptual models projectedinmobile banking adoption studies thathave been
reviewed (Kim, Chan and Gupta, 2007; Cheon et al., 2012), and a complete list of models and
theories supporting the studies reviewed is presented in Table 2.2.
2.4.1.1 Theory of Reasoned Action (TRA)
This TRA theory was propounded by Ajzen and Fishbein in the year 1975. This model is very
widely studied and proved beneficial in the field of social psychology. It is related to various
consciously intended behavior variables such as Social Influence, Attitudinal, and Intention to
use to envisage the behavior of individuals. The relationships among concepts in TRA are
represented in Figure 2.1. Itis also postulated by this theory that the user’s Behavioral Intention
(BI) to act upon is mutually influenced by the Attitude of the user towards performing a
particular Behavior i.e. Subjective Norm (SN) and ATB; SN is defined as “the general perception
of what significant others think the individual should or should not do.” The importance of
Attitude of the individual towards enacting the Behavior and Subjective Norm to predict
Behavioral Intention will differ from behavioral domain.
This theory also postulates that AB i.e. Actual Behavioral is the direct precursor of Behavioral
Intention (BI). As stated by Fishbein and Ajzen (1975), Behavioral Intention will predict AB precisely
only if it holds the below mentioned three conditions: “(a) the degree to which the extent of
intentionandthe behavioral conditioncorrespondwithrespecttotheir levels of specificity of target,
action,context,andtimeframe;(b)thereliabilityofintentionsbetweenperformanceofthebehavior
andtimeofmeasurement;and(c)theleveltowhichbringingouttheintentionisunderthevolitional
control of the individual.”

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Furthermore, TRA has not included beliefs that are important and operative for a specific type
of behavior. Academicians and Researchers using this theory must foremost distinguish the
beliefs that are noticeable for all the subjects with respect to the behavior under study.
Source: Fishbein and Ajzen, 1975
Figure 2.1: Theory of Reasoned Action
To investigate the performance of anindividual’s behavior and their intention, this model of TRA
has been widely used and applied to various situations. Such as, TRA prophesied education
(Fredricks and Dossett, 1983); examination of breast cancer (Timko, 1987) and turnover
(Prestholdt, 1987). Sheppard (1988) deduced that in a meta-analysis of research on TRA, it was
predicted that the utility of this model was resilient across many situations and conditions.
2.4.1.2 Theory of Planned Behavior
In spite of the obviousness of the Theory of Reasoned Action is persuasive across studies, it will
become challenging if the individual’s behavior under examination is not under full volitional
constraint.
As pointed out by Sheppard (1988), there are two problems with this theory. Primarily, the
researcher must be able to distinguish between the individual’s intentions with behaviors. This
kind of differentiation could be challenging for the researchers as here are many other features
in addition to the individual’s intentions to use that will be able to determine as of how the AB
is executed. Secondly, it is very difficult to judge, whether the chance of failing to execute an
action is merely due to individuals’ own intentions or due to individuals’ own behavior, there is
no scope of the model for considering this problem. To deal with these stated problems, Ajzen
(1985) included one more factor in the TRA model that is Perceived Behavioral Control (PBC),
which prophesies Behavioral Intentions (BI) and Behavior. This new extended model is known

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as TPB i.e. Theory of Planned Behavior.
These two models, i.e. TRA and TPB have many likenesses for example, in the prediction of AB,
BI is still the principal factor. Both the theories assume that individuals are fundamentally
rational and while making any decision they use information in a systematic manner.
This extended model has added PBC as the chief determining factor of BI as well as Control
Beliefs (CB) that influence PBC; this is the main difference between these two theories.
However, it might be very challenging for the researcher to evaluate actual control of individual
afore executing a behavior, Theory of Planned Behavior emphasizes that it is viable to compute
Perceived Behavioral Control - “people’s perception of the ease or difficulty in performing the
behavior of interest” (Ajzen, 1991). According to the researcher, PBC is a function of Perceived
facilitation and CB. Perceived facilitation is “one’s judgment about the significance of those
resources to the accomplishment of the outcomes”. Control belief is “the perception of the
existence or absenteeism of essential resources and prospects needed to carry out the
behavior”. (Ajzen and Madden, 1986).
As discussed by Bandura (1977), there is an empirical support which states that individual’s
confidence in their own capability to carry out behavior influences the individual’s behavior.
There exists a fundamental link from PBC to BI that indicates the motivational influence of
control on AB via individual’s intentions.
To foretell the execution of an individual’s behavior and intentions, TPB model has been widely
used by many researchers, for example, predicting the individual’s user intentions to avoid
caffeine (Madden, 1992), performance of unethical behavior (Man, 1998), intention to use an
innovative software (Mathieson, 1991), performing the self-examination of breast (Young,
1991), and to understand wastepaper recycling (Cheung, 1999). Madden (1992), Man (1998),
and Cheung (1999) found that the Theory of Planned Behavior has a better explanatory and
predictive power of individual’s behavior than TRA.

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Source: Pavlou, 2001
Figure 2.2: Theory of Planned Behavior
2.4.1.3 Decomposed Model of Theory of Planned Behavior
As stated by Taylor and Todd (1995), attitudinal beliefs need further decomposition into
variables to get a better understanding of the association between two important variables of
this model i.e. belief structures and precursors of intention. The researcher also stated that,
based on the Roger’s (1983) theory i.e. IDT (diffusion of innovation theory), there are three
attitudinal belief’s characteristics of aninnovation that has animpact onthe individual’s attitude
towards adoptionof any innovative technology; these are relative advantage, compatibility, and
complexity. Shimp and Kavas (1984) claimed that it is very difficult to systematize all the
cognitive elements of belief into one unit. Taylor and Todd (1995) confirmed that this model i.e.
decomposed model of TPB has better explicatory potential as compared to original models and
theories of TPB and TRA models. In this way, the contention of this research work is that M-
banking is a high-tech invention and hence this model of TPB gives a more reasonable
clarification of intention of the user towards adopting M-banking services.
According to Rogers (1983), the innovation’s rate of adoption is supportively associated with
Relative Advantage. Innovative and advanced technologies that user perceives as easy to use
(opposite of complexity) have a greater prospect of adoption and intention to use by the
prospective consumers. Therefore, Davis (1989), stated that complexity is anticipated to have a
negative association with user’s attitude towards the innovation. In the decision of acceptance

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and adoption of any innovative technology, this element i.e. Complexity is found to be the
significant factor.
Tornatzkey and Klein (1982) also claimed that the compatibility is supportively related to the
adoption of innovation by the individual, as any innovation in the technology is more likely to
be accepted and adopted by the individual only when it is in line with the value system and job
responsibilities of the user.
Likewise, Ajzen (1985, 1991) also argued that PBC reveals a belief that involves access to the
opportunities and resources that are expected to impact individual’s behavior. Bandura (1977),
stated that PBC seems to incorporate two main constituents i.e. facilitating conditions and self-
efficacy. The first element, i.e. “Facilitating conditions” as explained by Triandis (1979),is “which
reflectthe availability of resources expected toperform a specificbehavior.”This includes access
to money, time and other resources. In reality, internet commerce banking applications i.e.
banking services on mobile phones are becoming easily and readily available to the users, this is
all possible due to the supporting high-tech infrastructures which are readily available.
According to this,toincrease the adoptionrate of thisinnovationinmobile telecommunications,
government can play a leadership and major role. The second constituent, i.e. self-efficacy as
described by Ajzen, (1991) is, “being assured of the capability to behave successfully in the
situation.”
All the individuals who have the skills and expertise to use to use a computer and the Internet
are the ones who are likely to adopt this technological advancement of M-banking.

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Source: Shih and Fang, 2004
Figure 2.3: Decomposed Model of Theory of Planned Behavior
2.4.1.4 Technology Acceptance Model (TAM)
Davis (1989), introduced this model, which is a variation in the previous theory i.e. TRA (Theory
of Reasoned Action), it is specially customized for demonstrating an individual’s attitude
towards adopting information systems i.e ISs. The mainobjective of TAMis togive a justification
of the elements of computer acceptance which can explain the individual. The main objective
of this model is to present the foundation for drawing the influence of the external factors of
internal beliefs, intentions, and a user’s attitude. This model was framed in an attempt to
accomplish these objectives by categorizing a few fundamental factors recommended by prior
studies dealing with cognitive and affective components of computer acceptance, and utilizing
TRA as an imaginary background for demonstrating the theoretic relations amongst these
factors.
Figure 2.4 demonstrates that, for computer acceptance behavior, there exists basically two
specific beliefs i.e. Perceived Ease of Use (EOU) and Perceived Usefulness (PU), as postulated in
TAM. PU refers to “the extent to which a prospective user believes that by using a specific

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system would improve his or her job performance. Within a managerial context, individuals are
usually boosted by good performances by raises, bonuses, promotions, and other rewards”
(Pfeffer, 1982).
EOU is clearly described as “the extent to which a potential user believes that using a specific
kind of system would be free from any effort.” For predicting the users’ acceptance, this model
has gained recognition as a vigorous, parsimonious and influential model.
Source: Davis, 1989
Figure 2.4: Technology Acceptance Model
2.4.1.4.1 Extension of Technology Acceptance Model (ETAM)
Hu (1999) has found that TAM has a comparatively low explanatory power of an individual’s
Attitude and Intention in the research work of the individual’s adoption of telemedicine
technology by the physician. The researchers also proposed that to develop the better
explanatory efficacy ina specificarea by incorporating Technology Acceptance Model with other
Information Technology acceptance models.
Many researchers have started to use the Technology Acceptance Model to assess the
prospective precursors of PU and EOU, concerning the usage of microcomputers (Iivari, Igbaria
and Maragahh, 1995; Igbaria, Guimaraes, and Davis, 1995). Still, as stated by Gefen and Keil
(1998), there is one disparagement of the present TAM researches is that, there are few types
of research that focus on the investigation of the external factors that affect both PU and EOU.
Venkatesh and Davis (1996) used three experimentations to deal this issue and to examine the
elements of the EOU and the outcomes revealed that general EOU is significantly affected by
“Computer Self-Efficacy”, whereas “Objective Usability” in the technological system influences
individual’s opinion after they encounter the system directly.

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Moreover, by including a few elements in Perceived Usefulness in the new model, Venkatesh and
Davis (2000) established and confirmed a new model i.e. TAM 2 (Figure 2.5). This model is a
hypothetical extension of the basic TAM that explicates PU and Usage Intentions of the individual
in terms of “cognitive instrumental processes” (Result Demonstrability, Job Relevance, Output
Quality and EOU) and “social influence processes” (Voluntariness, Subjective Norm, and Image).
2.4.1.5 Diffusion of Innovation Theory
This theory is propounded by Roger in the year 1962, in this model researcher has described the
method by which technological innovations are adopted by the individuals. Rogers (1995) has
defined innovation as, “an idea, practice, or object that is perceived as new by an individual or
other unit of adoption.” The researcher has also described diffusion as, “the process by which
aninnovationis connected through certain channels over time amongst the members of a social
system.” So, this theory basically explained that how innovative concepts and ideas gain
extensive adoption.
This theory reflects a set of characteristics related to innovations in the technology that
influence their rate of pervasive adoption. Roger has defined these characteristics as:
Relative Advantage – “The extent to which aninnovation is perceived to be better than the idea
it supersedes.”
Compatibility – “The extent to which an innovation is perceived as consistent with the existing
values, needs of potential adopters and past experiences.”
Complexity – “The extent to which an innovation is perceived as relatively difficult to
understand and use.”
Trialability – “The extent to which an innovation may be tested with on a limited basis.”
Observability – “The extent to which the outcomes of aninnovation are visible to others.”
According to Chen (2000), among all the characteristics, only Compatibility, Complexity and
Relative Advantage are constantly associated with the individual’s attitude towards adoption of
any technological innovation.
Roger has studied nearly 1500 studies in which diversities of IDT have been used to examine the
technological innovation’s adoption in a range of fields, including city planning, healthcare,
agriculture, and economic development. Few studies have emphasized on, how these
characteristics can influence the individual’s behavioral intention and use of these innovations.
Rogers has formed his own Innovation Diffusion Theory factors by categorizing the

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characteristics of the product are most critically influenced by the adoption intention of
innovation.
Source: Venkatesh and Davis, 2000
Figure 2.5: Technology Acceptance Model 2 (TAM2)
2.5 Comparison of Theories
Though the TAM, TAM2, TRA, TPB and IDT models focused on dissimilar elements that describe
the individual behavior in terms of technological adoption, all these theories and models also
reveal some kind of similarities among themselves. Firstly, TRA, TPB, TAM presumes an
individual’s Attitude-Intention-Behavior association, that is, cognitive and normative beliefs
form Attitude, which, in return, has an impact on individuals’ Behavioral Intention and their
actual usage behavior.
Furthermore, the variable Perceived Usefulness in TAM is like Relative Advantage in the Roger’s
theory of innovation to some level. These factors are the cognitive element of user’s Attitude.
The variables of Relative Advantage, PU and perceived consequences in numerous models
further defend the rationale in TRA that the beliefs about the consequences of the behavior are
bases for the construction of user’s Attitude about the individual user’s behavior. Finally, the
Variable of EOU in TAM is having similarity with complexity variable in Roger’s IDT Model.
Table 2.2: Comparison of Models
Models and Theories Constructs
From the field of Social Psychology, Fishbein and Ajzen (1975)
propounded a Theory of Reasoned Action (TRA) to determine the
behavioral intention and performance.
Attitude
Subjective norm

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Technology Acceptance Model (TAM) by Davis (1989) has
developed a new scale comprises of two specific variables to
determine individual’s acceptance of the technology.
Perceived Usefulness
Perceived Ease of Use
Theory of Planned Behavior (TPB) by Ajzen (1991) is an extension
of TRA by including an additional factor in determining intention
and behavior.
Attitude
Subjective norm
Perceived Behavioral Control
Taylor and Todd (1995) proposed combination of two models,i.e.
TAM and TPB
Perceived Usefulness
Perceived Ease of Use
Attitude
Subjective norm
Perceived Behavioral Control
Roger’s Innovation of Diffusion Theory (IDT) is adapted to
innovations in information systems innovations by Moore and
Benbasat (1991). Five characteristics have been taken from the
Rogers’ model and two additional constructs were also identified.
Relative Advantage
Compatibility
Complexity
Observability
Trialability
Image
Voluntariness of Use
Venkatesh (2003) integrated all the above models and theories
and formed UTAUT i.e. Unified Theory of Acceptance and Use of
Technology Model, which is used to measure user’s intention
usage of technology.
Performance Expectancy
Effort Expectancy
Attitude toward Using Technology
Social Influence
Facilitating Conditions
Self-Efficacy
Anxiety
2.6 Trust
According to many researchers, there are various meanings of trust that has existed in several
subjects that imitate the multifaceted nature of trust, Table 2.3, shows the summary of all the
definitions given by many researchers. The widespread review of the literature on trust across
various fields by Rousseau (1998), illustrates that, irrespective of the fundamental subject of
researchers, the willingness of the measure to be vulnerable, confident and expectations are
few essential constituents of all explanations of trust. In the literature of trust Mayer’s (1995)
definition is widely adopted and most cited definitions which is “The willingness of a party to be
vulnerable to the actions of another party based on the expectation that the other will perform
a particular action important to the trustor, irrespective of the ability to monitor or control that
other party”.
Table 2.3: Definitions of Trust
Currall and Judge (1995) “An individual dependence on another party under
conditions of dependence and risk.”
Mayer, Davis, and Schoorman (1995) “The willingness of a party to be susceptible to the actions of
another party based on the belief that the other will perform
a particular action important to the trustor, irrespective of
Source: Self

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the ability to monitor or control that other Party.”
Michalos (1990) “A relatively informed attitude or tendency to allow oneself
and perhaps others to be susceptible to harm in the interests
of some perceived greater good.”
Hosmer (1995) “In the context of economic transactions, of the behavior of
stakeholders of the firm under conditions of organizational
susceptibility and dependence.”
Source: Self
In the context of M-banking, this definition of trust axes upon the trustor forcing him/ herself
susceptible, which suggests that because of involving into a trusting relationship, something of
importance could possibly be lost (Mayer, 1995).
To cite an example of trusting behavior, the user making any kind of banking transaction via
Internet is a good example, since a user makes himself susceptible to the acts of the Internet.
The user is agreeable to be reliant on the Internet, depends on the prospect that it will execute
what the user wants it to do.
2.6.1 Multidimensionality of Trust
According to the relationships, trust can take numerous forms. As classified by Rousseau (1998);
there are three different types of trust: calculus-based trust, relational trust, and institutional
trust. Calculus-based trust is based on rational choice – “attribute of interactions in economic
exchange.” Relational trust “derives from repeated dealings over time, between a trustor and
trustee.” The basis of relational trustis developed from the Information accessible to the trustor
from within the relationship. Institutional trust originates from “the institutional factors which
can act as massive supports for the critical mass of trust that resists further risk taking and
trusting behavior” (Sitkin, 1995).
Nooteboom (1997) has characterized into two distinct sorts: Competence trust and Intentional
Trust. Competence trust “relates a partner’s ability to perform as per the goals and desires of a
while intentional trust relates a partner’s expectation not to defect (Nooteboom, 1997).” In the
case of electronic medium, intentional trust not only shows much relevance as, the individual
to be trusted does nothing by itself and hence competence trust plays the supreme role. As
stated by Schneider (1998), a trustworthy electronic channel does what individuals anticipate
that it will do, notwithstanding the likelihood of ecological disturbance, human client and

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administrator mistakes, and assaults by inimical parties.
In other context, trust in the banking firms offering the banking services on the mobile phones,
another important role is played by the intentional trust as the trustor is susceptible to the
probable effects because of the involvement of the banks in offering M-banking services.
Rousseau (1998) contended that it is important to coordinate the varying perspectives of trust
in different subjects and set out that trust may be just a “meso” idea that acclimatizes the two
perspectives of trust i.e. at the individual level and at the institutional level. In this study,
researcher emphasis is on the exchanges led by people utilizing the internet (an electronic
medium) to network with a service ( M-banking) offered by a firm (the banking firms).
2.6.2 Importance of Trust
The vulnerability is because of the way that traders are certainly independent and not completely
at risk, while there is an innate need amongst clients to comprehend the merchants’ activities.
Clients will not be able to carry out business without condensing the instability. Out of all the
techniques which are used to decrease the level of instability, trust is considered to be the most
effective technique (Hart, 1997; Gefen, 2000). As discussed by Crosboy, (1990), Grazioli and
Jarvenpaa (2000),wherever the warranties and contracts are missing,ittends tobe a very risk and
uncertain in this technologically advanced era, where the internet is the medium used to transfer
the files in all the parts of the world. So, from the security perspective, internet banking is risky by
nature and hence trust plays an important role. Besides, M-banking is highly indeterminate
because, parties belong to different places involved in the banking (Clarke, 1997). Many of the
Analysts in the marketing field have believed trust as one of the important and prime variables of
relationship marketing (Crosboy, 1990; Morgan, 1994; Macintosh and Lockshin, 1997; Doney and
Cannon, 1997; Newell, 1998; Gefen, 2000). Macintosh and Lockshin (1997) claimed that to
maintain a long term relationship with a store, client trust has a direct influence on store loyalty,
which has been empirically tested by them. By adding trust with extending TAM with Trust, it can
be examined whether trust influences the adoption decision of users’ of M-banking services or
not.
2.6.3 Trust and Technology Acceptance Model
As suggested by many researchers,the associations amongst Technology Acceptance Model and

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Trust have been widely examined while reviewing the literature. In that, the relations between
Trust, PU and EOU are theorized in different online based business settings (Gefen, 2003;
Pavlou, 2003; Saeed, 2003; and Gefen, 2004). Specifically, in the online shopping, a model of
Trust and TAM was fitted (Gefen, 2003a). This combined model clearly demonstrated the
relationship between Trust, PU, and EOU, as trust is a precursor of PU, EOU is a precursor of
trust, and trust impacts individual’s Behavioral Intention to use. Besides, as discussed by Pavlov
(2003), trust anticipates having a beneficial outcome on PU as, trust consents customers to
become susceptible against e-vendor to check that they get the valuable communication and
administration.
As discussed by Ganesan, (1994) and Gefen, (2003) EOU is supposed to positively impact the
trust on the grounds that EOU can empower users’ favorable influence of online vendors in the
primary stage of adoption of online services and can additionally influence clients to be eager to
make an investment and pledge in buyer-seller relations. While, M-banking is thought to be a
superior kind of online-service, TAM and Trust is not fully incorporated into this on-line mode of
banking.
2.7 Risk
The risk is developed into a potentially important precursor of mobile banking adoption. Some
authors (Lee, 2008; Zhang, Tan, Xu, Tan, and Genlue, 2012) however regarded Perceived risk as
the single construct, but it possibly contains several dimensions like Perceived Quality Risk,
Perceived Health Risk, Perceived Privacy Risk, Perceived Time Risk, Perceived Social Risk,
Perceived Delivery Risk, Perceived Economic Risk and Perceived After-Sale Risk.
2.7.1 Multidimensional Nature of Risk
There are two important and noteworthy variables i.e. trustworthiness and security of a service;
in every focus of client section, when determining banking service delivery channel usage. Many
researchers consented that use of the cell phone for managing an account is reliable. As defined
by Fain and Roberts, 1997; Mattila, 2002, risk is a “perception of the consumer, attributes of a
product”. It was also noted by many researchers that security is the important factor that could
impact users’ attitude towards the use of online banking services (Laforet and Li, 2005).
Additionally, out of all the factors that influence the attitude of the users towards adopting M-

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banking services, security was considered as the prime factor. (Luarn and Lin, 2004; Brown,
2003), as people may stress over security issues while conducting banking transactions over
mobile phones like feeding personal data and output mechanisms personal performance
mistakes (Laukkanen and Lauronen, 2005; Kuisma, 2007) and risk due to the network (Kuisma,
2007; Black, 2001). Therefore, many individuals may not opt for M-banking services and
overlook the additional advantages of utilizing M-banking. Nonetheless, some past reviews like
Suoranta 2003; Laukkanen and Lauronen, 2005, have contended that, despite what might be
expected, they found out that the security issues while adopting and using M-banking services
for shopping are not the actual obstructions. After reviewing, the security factor seems to be
the most essential component of M-banking services which is impacting the adoption and
acceptance of M-banking services by the users’, hence, further investigation of this factor is
important.
For instance, Soroor (2006), studied in detail, regarding the security issues while adopting M-
banking services and also proposed some assessment procedures which could be utilized to
enhance the framework:
1) Primarily, the formation of a secured medium togive information secrecy anduprightness
amongst the banking firms service provider and the users.
2) Secondly, the verificationof the user toward the start of the session of M-banking services
(e.g. substance confirmation, exchange validation).
Table 2.4: Definitions of perceived Risk Dimensions in the Literature
Factors Description Research
Performance
Risk
“The possibility of the product malfunctioning
and not performing as it was designed and
advertised and therefore failing to deliver the
desired benefits. (Grewal et al., 1994).”
Cunningham (1967), Peter and
Ryan (1976), Jacoby and Kaplan
(1972), Stone and Gronhaug
(1993)
Time Risk “Consumers may lose time when making a bad
purchasing decision by wasting time researching
and making the purchase, learning how to use a
product or service only to have to replace it if it
does not perform toexpectations.”
Roselius (1971), Cunningham
(1967), Stone and Gronhaug
(1993), Peter and Ryan (1976)
Psychological
Risk
“Potential loss of self-esteem (ego loss) and ego
frustration based on feelings about oneself.
Consumers feel unwise if they experience a non-
performing product and may experience
Stone and Gronhaug (1993),
Cunningham (1967), Roselius
(1971), Jacoby and Kaplan
(1972), Peter and Ryan (1976)

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feelings of harm to their self-image from the
frustration of not achieving their buying goals.”
Social Risk “Potential loss of status in one’s social group as
a result of adopting a product or service, looking
foolish or untrendy.”
Stone and Gronhaug (1993),
Cunningham (1967), Jacoby and
Kaplan (1972)
Privacy Risk “Potential loss of control over personal
information, such as when information about
you is used without your knowledge or
permission. The extreme case is where a
consumer is ‘spoofed’, meaning, a criminal uses
their identity to perform fraudulent
transactions.”
Jarvenpaa and Todd (1996),
Featherman and Pavlov (2003),
Scott (2004), Comegys C. (2009)
Source: Featherman and Pavlov (2003)
Featherman and Pavlou (2002), discussed about various aspects of Perceived Risk like Perceived
Financial Risk, Perceived Psychological Risk, Perceived Performance Risk, Perceived Time Risk,
Perceived Social Risk, Perceived Privacy Risk (discussed in Table 2.4) and they found out that out
of all the facets of risk, only four are important, these are: performance, financial, time, privacy.
They also claimed that the usability of the software is important in defining the expected risk
inherent in service. If the user is unable to easily use the e- services, then Perceived Risk
increases. This indicates the inverse relationship between the two as, the e-services usability
increases, the performance risk decreases, this has ultimately increased the prominence of
perceived ease of use factor which is generally overlooked by many researchers.
2.7.2 Importance of Risk
Perceived Risk is still considered as the foremost important element that influences the user
Behavior Intention towards the adoption of any new technological applications, such as, M-
banking. Sorror (2005), in his research perceived the security issues in M-banking and, also tried
to propose a few methods and techniques to improve this system. According to Bhatnagar,
2000; Vijayasarathy 2002; Jarvenpaa and Todd (1996), Privacy Risk is influenced to the extent
by which a user is ready to provide any personal information on the online platform, users are
ready to sacrifice their privacy. According to Cox and Rich (1964), when conducting any kind of
retail transactions, Performance Risk is one which can cause users’ to feel insecure about “not
getting what they want.”

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2.8 Conclusion
Notwithstanding the limited samples of studies surveyed, the following tentative conclusions
can be drawn for working purpose of the thesis:
1. It is revealed that numerous studies have been conducted in the area of awareness
and adoption of mobile banking all over the world. But, very few studies have been
conducted in India.
2. In India, not much research has been conducted on the Mobile Banking Service,
factors influencing its adoption and Behavioral Intention of users.
3. Many authors have given the suggestion to incorporate risks and trust-related
factors and their influential role on the Behavioral Intention towards the adoption
of technological advancements that have not studied so far.
4. Information Technology dimension of security is much in need to understand the
nature of the transaction, and its effect on the usage intention of consumers.
5. Many researchers have given the future direction of research that, the researchers
should examine different facets of risk and trust to gain insight into these factors.
Hence, based on the current review of researchers in the area of M-banking, which has also
verified that Perceived Risk and Perceived Trust are imperative and, influential elements that
can impact the individual’s adoption and acceptance behavior, this research work has covered
the investigation of all these variables by exploring different measurements of Perceived Trust,
Perceived Risk, and its impact on user’s Attitude and Behavioral Intention towards using M-
banking services. As, there were not many literature available associated with mobile banking
services in India, this research work was an attempt to fulfill this researchgap. Accordingly, after
the in-depth review of the literature, the main aim of this study was to inspect the user’s
Attitude and adoption Intention for using mobile banking services by integrating Trust and Risks
variables with TAM.
This chapter covered the major studies by various researchers and extensive literature based on
books, journals, periodicals, websites, and the internet. Next chapter presents research
methodology employed in this study. It also covers the objectives, hypotheses, sample,
population etc. considered for this study.