Research on tablet pc adoption model

UNDERSTANDING NEW TECHNOLOGY BY ENGINEERING STUDENTS: APPLICATION OF TECHNOLOGY READINESS AND ACCEPTING

TECHNOLOGY (TRAT)1. Introduction of Consumer behaviour

The study of consumer behavior focuses on how individuals make decisions to spend

their available resources (time, money, effort) on consumption-related items (Schiffman

and Kanuk, 1997). The field of consumer behavior covers a lot of ground. According

to Solomon (1996), consumer behavior is a study of the processes involved when

individuals or groups select, purchase, use, or dispose of products, services, ideas, or

experiences to satisfy needs and desires.

“A customer is the most important visitor on our premises. He is not dependent on us.

We are dependent on him. He is not an interruption on our work. He is the purpose of

it and not an outsider on our premises. He is a part of it. We are not doing him a favour

by serving him. He is doing us a favour by giving us the opportunity to do so.”

Mahatma Gandhi

Customer Vs Consumer

The term ‘customer’ and ‘consumer’ have been used synonymously most of the

time. The term customer refers to the purchaser of a product or service whereas the term

consumer refers to the end user of a product or service. The customer may or may not

be a consumer. Similarly the consumer may or may not be the customer.

Definitions

“Consumer behaviour is defined as activities people undertake when obtaining,

consuming, and disposing of products and services.”

- Roger D. Blackwell, Paul W. Miniard and James F. Engel

“Simply it can be stated that consumer behaviour is the study of “why people buy.”

“Consumer behaviour has been referred to as the psychological, social and physical

behaviour of all potential consumers as they become aware of, evaluate, purchase and

consume and tell others about products and services.”

- Suja R. Nair

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TECHNOLOGY (TRAT)Obtaining: refers to the activities involved in purchase of a product. The activities

include searching for information regarding product features, evaluating the

alternatives, and purchasing. It also includes the place of purchase (shopping

malls/nearest grocery stores), the mode of purchase (cash/credit card), etc.

Consuming: refers to how, where, when and under what circumstances consumers use

products. How – as side dish or main dish; Where – place (home, office or restaurant),

When – time (morning or afternoon or evening) and under what circumstances (happiest

moments or with friends or when alone).

Disposing: refers to how they get rid of products and packaging. Whether they resell it

or give it to children or use it for different purpose.

“Consumer behaviour can be said to be the study of how individuals make decisions on

how to spend their available resources (time, money, effort) on various consumption-

related items.”

- Suja R. Nair

The above definition talks about various activities surrounding the ultimate

consumer and helps the marketer to gauge the consumer behaviour specifically focusing

on:

Who buys the products or services?

How do they buy products or services?

Where do they buy them?

How often do they buy them?

When do they buy them?

Why do they buy them? And

How often do they use them?

These questions will help in understanding better what factors influence the

decision making process of the consumers.



TECHNOLOGY (TRAT)

1.1. Consumer Behaviour – for Whom?

It has been said that the field of consumer behaviour holds for various categories

of people such as consumers, marketers and students of marketing.

Consumers: All the firms have started considering ‘customer’ as the ‘king’ or ‘queen’.

Interestingly, after liberalization of India’s economy, the market place is flooded with

many new players including the MNCs’ resulting in the availability of more number of

brands in every segment of the market. On account of this, the customer has started

being choicy about what to buy. Thus all firms are becoming not only customer

focused but are also trying to build relationship with them. This is done by

continuously updating knowledge, information and understanding of the customer needs

and expectations.

Awareness of such devotion from the firm has made consumers to take more interest

into their own consumption related decisions. They are keen to gain more knowledge

about taking various decisions related to products and the promotional influences that

persuade them to buy. Thus the study of consumer behaviour will enable them to

become better and wiser consumers.

Marketers: have woken up to the reality that exist in a competitive environment and

hence they have to be more focused. The marketers have observed that the choice

empowered customer cannot be taken for granted. This is particularly true because of

the rapidly rising consumer earnings, sharp drop in the savings rate and increase in

earnings resulting in a huge amount of disposable income that are spent lavishly.

Simultaneously, there are changes occurring in the personal, social and influences

making consumer more individualistic, conscious (about the products or services to

fulfill their needs). So, the study of consumer behaviour will help marketers to assess

the consumers’ needs and wants, and make better strategic marketing decisions.

Students: As students of marketing, one will be more concerned with the study of

consumer behaviour. Such a study will help to gauge into the consumer’s mind and

underst and the various consumption related aspects of individuals (consumers). As

students of marketing, understanding of consumer behaviour will make the study of

‘marketing management’ more interesting, understandable and increase awareness of its

practical implications.



TECHNOLOGY (TRAT)

1.2. Development of Consumer Behaviour as a Field of Study

Consumer behaviour as a separate field of study gained attention from the

1960s. In the absence of a history or a separate research of its own, this new discipline

drew/or borrowed concepts from other scientific disciplines such as –

Psychology (the study of individuals)

Sociology (the study of groups)

Socio-psychology (the study of how persons are influenced by groups)

Cultural anthropology (the influence of the culture and society on the individual)

Economics (the relationship between demand and supply in the flow of

marketing activity)

Positivism: Initially, the study of consumer research was emphasizing from a

managerial perspective. In that, if the marketing manager could obtain consumption

related behaviour i.e., if they are able to predict consumer behaviour, then they could

influence it. This type of consumer behaviour approach came to be known as

‘positivism’.

Interpretism: A group of academicians who are interested in the study of consumer

behaviour and are more interested in knowing consumption behaviour going by the

influence of the various disciplines on the consumer behaviour. This approach of

studying the consumer behaviour with a view on understanding consumption behaviour

and the interpretations of such behaviour is known as ‘interpretivism or post-

modernism.’

These interpretivists have included many subjective aspects of consumer

behaviour such as the effect of moods, emotions, type of situations etc. These

interpretivists have also treated each purchase experience as unique because of the many

variables which influence the behaviour at that particular moment of time. On account

of its focus on the consumption experience, the interpretive approach is also referred to

as ‘experientalism’.



TECHNOLOGY (TRAT)

1.3. Consumer Behaviour and Marketing

Broadly, buyers can be classified into two major categories:

Consumers (in the household sector, who buy goods or services for personal

consumption) Industrial buyers (who purchase goods and services for carrying out

activities in the various industrial units).

In this age of information explosion, and internet marketing becoming a reality,

it is all the more necessary that they (marketers) go for the creation of appropriate

database which can help them to go for ‘tailor made’ products to suit individual tastes,

preferences and buying behaviour.

The industrial or organizational markets consist of buyers who buy goods and

services needed in the process of furthering their industrial and institutionlal activities.

The behavioural differences between the domestic consumers and industrial buyers can

be done on the basis of the ultimate objective sought by them. While the domestic

consumers seek need satisfaction and value added by the purchase of the product, the

industrial buyers seek profit or measurement of improved operational efficiency. The

latter’s behaviour, thus, will be influenced by the objectives of the organization they

serve. Accordingly there is also a difference in the buying process adopted by both the

domestic consumer and industrial buyer.

A major implication of the differences in the consumer and industrial behaviour

for marketers is the relative emphasis to be placed on the various marketing mixes to be

adopted by the concerned marketer. Understanding of the consumer behaviour will

enable marketers to design effective marketing strategy and programmes.



TECHNOLOGY (TRAT)

1.4. Consumer Modeling

Model: “A physical, visual or mathematical ….. Simplified representation of a complex system.”

A model is very often referred to as an abstract representation of a process or

relationship. We (human beings) hold various models in our minds which allow us to

make sense of the world and also help to predict the likely course of events. Simply

stated models help us in the following way:

They help in the development of theories

They help to understand complex relationships

They provide the framework for discussions and research work

The primary concern is to use the models to understand consumer behaviour.

Consumer behaviourists as well as marketers are interested in understanding how and

why certain decisions are made. The discussions have been about some of the

important models of consumer behaviour, which attempts to give a comprehensive view

of all those aspects of the buying situations which are deemed to be significant by their

creators.

Andreason (1965) proposed one of the earliest models of consumer behavior. This

model is shown in Figure 2.1.The model recognizes the importance of information in

the consumer decision-making process. It also emphasizes the importance of consumer

attitudes although it fails to consider attitudes in relation to repeat purchase behavior.


Perceived beliefs, Norms,

Values of significant others.

Other customer Decision-makers

UNDERSTANDING NEW TECHNOLOGY BY ENGINEERING STUDENTS: APPLICATION OF TECHNOLOGY READINESS AND ACCEPTING TECHNOLOGY (TRAT)

Information

Intrinsic attributes

Extrinsic attributes

Price availability

Advocate impersonal

sources

Independent impersonal

sources

Advocate personal sources

Independent personal sources

Information storage

Attitudes towards sources

Filtration

Personality

Direct experience

Beliefs

Wants Want strength

Feelings

Disposition

Search

Select

No action

Attitudes towards product, substitutes,

complement

Income, budget piorities, physical capacity,

household capacity

Ownership Other

purchase decisions

Hold

Key

Direct Flows

Feedbacks

Yes

No

Figure 1 Andreason, A.R (1965 Attitudes and Consumer Behavior: A Decision Model in New Research in Marketing (ed. l. Preston). Institute of Business and Economic Research, University of California, Berkeley, pp.1-61

Constraints

7


TECHNOLOGY (TRAT)second model, which concentrates on the buying decision for a new product, was

proposed by Nicosia (1976). This model is shown in Figure 2.2. The model

concentrates on the firm's attempts to communicate with the consumer, and the

consumers' predisposition to act in a certain way. These two features are referred to as

Field One. The second stage involves the consumer in a search evaluation process,

which is influenced by attitudes. This stage is referred to as Field Two. The actual

purchase process is referred to as Field Three, and the post-purchase feedback process

is referred to as Field Four. This model was criticized by commentators because it

was not empirically tested (Zaltman, Pinson and Angelman, 1973), and because of the

fact that many of the variables were not defined (Lunn, 1974).

Perhaps, the most frequently quoted of all consumer behavior models is the Howard-

Sheth model of buyer behavior, which was developed in 1969. This model is shown in

Figure 1. The model is important because it highlights the importance of inputs to the

consumer buying process and suggests ways in which the consumer orders these

inputs before making a final decision. The Howard-Sheth model is not perfect as it

does not explain all buyer behavior. It is however, a comprehensive theory of buyer

behavior that has been developed as a result of empirical research (Horton, 1984).

Schiffman and Kanuk (1997) mentioned that many early theories concerning

consumer behavior were based on economic theory, on the notion that individuals act

rationally to maximize their benefits (satisfactions) in the purchase of goods and

services. A consumer is generally thought of as a person who identifies a need or

desire, makes a purchase, and then disposes of the product during the three stages in

the consumption process in Figure2.2 (Solomon, 1996)

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TECHNOLOGY (TRAT)

1.5. CONCEPTS AND DIMENSIONS OF CONSUMER BEHAVIOUR

Consumer behaviour is an interdisciplinary science and relatively

emerged as a new field of study in the mid to late 1060s. This new discipline is

borrowed heavily from concepts developed in other scientific disciplines such as

applied psychology, social psychology, cultural anthropology, economics and

econometrics. Therefore, it is crucial to discuss various dimensions of consumer

behaviour in the context of Indian consumer.

(a) Consumer Needs and Motivation: Consumer needs are the basis of all

modern marketing. The key to a company‟s survival, profitability and growth in a

highly competitive environment is its ability to identify and satisfy unfulfilled

consumer needs Marketers do not create needs though in some instances they

may make consumer more keenly aware of unfelt need. Motivation can be

described as the deriving force within individuals that impels them to action.

The deriving force is produced by a state of tension exists as the result of an

unfilled need. Motivation is a need-induced tension which exerts a “push” on the

individual to engage in behaviour that he expects, will gratify needs and thus

reduce tension. Individuals strive both consciously and subconsciously to reduce

this tension through behaviour that they anticipate will fulfill their needs.

Consumer motivation is dynamic in nature because their wants are frequently

changing.

(b) Consumer Psychographics: Marketing practitioner and consumer researchers

refer Psychographics as lifestyle analysis or AIO (activity, interest and

opinions) research. Consumer specific psychographics researches are related to

consumer personality, buying motives, interests, attitudes, beliefs and values.

Services specific psychographics researches are related to product attributes

such as consumer responses about products, brands or a specific consumption

situation.

Consumer perception: Perception is defined as the process by which an

individual selects, organises and interprets stimuli into a meaningful and

coherent manner. Stimuli are sensory inputs include services, packages, brand names,



TECHNOLOGY (TRAT)advertisements and commercials. Sensory receptors are the human organs that

receive sensory inputs. Sensation is the immediate and direct response of the

sensory organs to simple stimuli.

Learning and consumer involvement: Consumer learning is the process of

acquiring the knowledge related to purchase and consumption information.

Consumer attitudes: Attitudes are expression of inner feelings that reflects

whether a person is favorably or unfavorably predisposed to some object,

person or event. As an outcome of psychological process attitudes are not

directly observable but must be inferred from what people say or do.

(c) Demographic Factors: Demographics describe a population in terms of its

size, distribution and structure. Demographics influence buying behaviour both

directly and indirectly by affecting other attributes of individuals such as their

personal values and decision styles. There are contradictory conclusions about the

effect of age, income and gender for a particular service. Age, age-groups, education

level, income, occupation etc. serves as various dimensions of demographics. In

India additional factors such as religion, social denominations, caste, age,

family background, regional disparities instates, linguistic difference, regional

perception of class factor and the degree of impact of these factors in affecting the

social status, all play crucial role in determining the social status of an individual.

(d) Economic Factors: Wealth, home ownership, number of earning members in a

family, household income, expenditure, rate of interest, inflation, economic

conditions and investment pattern are some of the economic factors have

strong influence on consumer purchase decision.

(e) Communication and Consumer Behaviour: Communication is the

transmission of messages from a sender to a receiver by means of signals of

some sort sent through a channel. There are four basic components of all

communications: a source, a destination, a medium and a message. There are two

types of communication to which a consumer is exposed interpersonal

communication and impersonal (or mass) communication.



TECHNOLOGY (TRAT)(f) Socio-cultural Factors: Consumer in a group and consumer reference

groups: A group may be defined as two or more people who interact to

accomplish similar goals. Consumer relevant groups are family, friends, formal

social groups, shopping groups, consumer action groups, work groups, references

groups etc. Four basic functions provided by the family are relevant to consumer

behaviour these include; economic well-being, emotional-support, suitable family

lifestyles and family-member socialization. Sociologists and researchers have

strongly favoured the concept of Family Life Cycle (FLC) - a way to classify

family units into significant groups. FLC is a strategic tool for marketers to

segment families in terms of a series of stages spanning the life course of a

family unit. Traditional family life cycle stages are bachelorhood,

honeymooners, parenthood, post parenthood and dissolution.

Consumer and their social classes: Social class is defined as the division of members

of a society into a hierarchy of distinct status classes so that members of each

class have relatively the same status and members of all other classes have

either more or less status. Social class is measured in terms of social status of its

members and comparison of members of each social class with other social

classes. Some of the variables of the social class are occupation, income,

educational level and property ownership etc. Culture and consumer behaviour:

Culture is a sum total of learned beliefs, values and customs that serves to direct

the consumer behaviour of a particular society. Subculture can be thought as a

distinct cultural group that exists as an identifiable segment within a larger and more

complex society.

(g) Consumer and Consumerism: The word consumerism has many expressions

depending on who is using the term government, business, consumer groups,

academicians and researchers. Consumerism is defined as a social movement of

citizens and government to enhance the rights and powers of buyers in relation

to seller.



TECHNOLOGY (TRAT)

2. BUYING PROCESS OR CONSUMER DECISION MAKING

A decision is the selection of an action from two or more alternatives. In other words,

in order to make a decision, there must be a choice of alternatives available.

If a person has a choice between making a purchase and not making a

purchase, or a choice between brands, we can say that this person is in a position to

make a decision. A “no-choice” decision is commonly referred to as a “Hobson‟s

choice.”

Buyer decision making is an attempt to solve consumer problems. A problem refers to

a discrepancy between a desired state and an ideal state which is sufficient to

arouse and activate a decision process. Thus problem can be major or minor and the

broader and more ambiguous a problem is, the more potential solutions are

generally available.

The study of buyer behaviour is the most dynamic marketing activities as the

buyer rapidly change their preferences and are affected by multiple factors at a

given point of time, are difficult to analyze. Therefore, it is necessary that

continuous study of buying behaviour must be conducted and extended. This

monitoring will make an understanding of marketing management to take effective

decisions regarding service price, distribution and promotion. A marketer

understands how buyer will respond to different service features, prices, advertising

appeals and so on will have an enormous advantage over his adversaries. When a

buyer takes a decision to buy there is no rigid rule to bind them. Sometimes the

decisions are taken on spot or after evaluating various alternatives available

and reassuring himself with the opinion of those who have already purchased

the service.

Four views of buyer decision making: Before presenting a simple model how

consumers make decisions. For depicting consumer decision making it‟s important to

consider several models of man. The term model of man refers to a general

perspective held by a significant number of people concerning how (and why)

individuals behave as they do. Following are the consumer-related models of man:-



TECHNOLOGY (TRAT)

(1) Economic man (Traditional view): Economics reflects a world of perfect

competition and the consumer is often characterised as an economic man. The

economic theory of consumer behaviour was synthesized by Alfred Marshall

from the ideas of Classical Economists and the proponents of theory of

„Marginal Utility.‟ Economic view explains the consumer as an economic man

who buys rationally to maximize the utility (benefits) derived from a service.

To behave rationally in the economic sense a consumer would have to be aware of all

available service alternatives. The consumer would have to be capable of correctly

ranking each alternative in terms of its benefits and disadvantages. According

to leading social scientists this view is unrealistic because of three reasons (a)

people are limited by their existing skills, habits and reflexes (b) people are

limited by their existing values and goals (c) people are limited by the extent

of their knowledge. However, consumers rarely have enough information,

sufficient or sufficiently information, or even an adequate degree of involvement or

motivation to make perfect decision. Consumers are living in an imperfect world

where they do not maximise their decisions in terms of economic considerations

such as price- quantity relationships, marginal utility or indifference curves. Indeed

the consumers are often unwilling to engage in extensive decision making

activities and will instead settle for a “satisfactory” decision, one that is “good

enough.” For this reason, the economic model is often rejected as too idealistic

and simplistic. The economists described man as a rational buyer and viewed the

market as a collection of homogenous buyers.

(2) Passive man: This model is quite opposite to the economic model of man. The

passive view depicts the consumer basically submissive to the self-serving

interest and promotional efforts of marketers. Consumers are perceived as

impulsive and irrational purchasers, ready to yield to the arms and aims of

marketers. At least to some degree the passive model of the consumer was

subscribed by the hard deriving salesman who is trained to manipulate

customer. The passive man view fails to recognize that the consumer plays an equal

(if not dominant) role in many buying situations by seeking information about

service alternatives and selecting the service that appears to offer greatest

satisfaction.



TECHNOLOGY (TRAT)

(3) Cognitive man: According to this view consumer is defined as a thinking

problem solver. Within this framework consumers are frequently depicted as

either receptive to or actively seeking services that fulfill their needs and

enrich their lives. The cognitive man focuses on the process by which

consumers seek and evaluate information about the services. There are six

types of consumer perceived risks (functional risk, economic risk, physical risk,

social risk, psychological risk and time risk) which a consumer use to handle

such as collecting information about alternatives, patronizing specific agents,

brand loyalty etc. These risks are key components of cognitive view and

consumers are viewed as information-processing systems. Consumer may use a

preference formation strategy that is “other-based” in which they allow another

person probably a trusted person or an expert to establish preferences to them.

(4) Emotional man: Marketers prefer to think of customer in terms of either

economic or passive models. Emotional man is also a reality of each of us

because of deeply rooted feeling and emotions: joy, fear, love, hope, fantasy,

sadness etc. These emotions have an impact on purchases and possessions.

Such feelings or emotions are likely to be highly involved for making a

purchase decisions. When a consumer makes any emotional purchase.



TECHNOLOGY (TRAT)

2.1 Models of consumer behaviour

The Economic Model

Learning Model

Psychological Model

The Sociological Model

Howard-Sheth Model (1969)

McNeals’ Basic Model of Consumer Behavior(1973)

The Engel-Kollat-Blackwell (EKB) Model (1960)

Nicosia Model(1976)

Solomon Model of comparison process (1996)

Theory of Innovation Diffusion Rogers Model (1995)

Diffusion of Innovation Theory in Information System

Theory of Reasoned Action (TRA) (1975)

The Theory of Planned Behaviour (TPB)

Unified Theory of Use and Acceptance of Technology

Technology Acceptance Model (TAM)(1989)

Technology Acceptance Model 2

Bettman’s Information Processing Model of Consumer Choice

Sheth-Newman Gross Model of Consumption Values

Model of Travel-Buying Behavior Mathieson and Wall

Stimulus-Response Model of Buyer Behavior

Model of Consumer Decision-Making Framework



TECHNOLOGY (TRAT)

2.2. VARIOUS MODELS OF CONSUMER BEHAVIOUR

2.2.1 Nicosia Model

This model focuses on the relationship between the firm and its potential consumers.

The firm communicates with consumers through its marketing messages (advertising),

and the consumers react to these messages by purchasing response. Looking to the

model we will find that the firm and the consumer are connected with each other, the

firm tries to influence the consumer and the consumer is influencing the firm by his

decision.

Field 1

Attitude

Field 2: Search And evaluation Of mean/end(s)

Experience relation(s) (Pre action field)

Motivation Field 4: Feedback

Field 3: Act of Purchase

Purchasing Behavior

Figure2. Nicosia Model of Consumer Decision Processes Source: Nicosia, (1976).

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Message Exposure

Subfield 1

FirmsAttribute

Subfield 2

ConsumersAttributes

(EspeciallyPredisposition

Searchand evaluation

Decision(Action)

Consumption

16 16


TECHNOLOGY (TRAT)

The Nicosia model is divided into four major fields:

Field 1: The consumer attitude based on the firms’ messages.

The first field is divided into two subfields.

The first subfield deals with the firm’s marketing environment and communication

efforts that affect consumer attitudes, the competitive environment, and characteristics

of target market. Subfield two specifies the consumer characteristics e.g., experience,

personality, and how he perceives the promotional idea toward the product in this

stage the consumer forms his attitude toward the firm’s product based on his

interpretation of the message.

Field 2: search and evaluation The consumer will start to search for other firm’s brand and evaluate the firm’s brand

in comparison with alternate brands. In this case the firm motivates the consumer to

purchase its brands.

Field 3: The act of the purchaseThe result of motivation will arise by convincing the consumer to purchase the firm

products from a specific retailer.

Field 4: Feed backThis model analyses the feedback of both the firm and the consumer after purchasing

the product. The firm will benefit from its sales data as a feedback, and the consumer

will use his experience with the product affects the individuals attitude and

predisposition’s concerning future messages from the firm.

The Nicosia model offers no detail explanation of the internal factors, which may

affect the personality of the consumer, and how the consumer develops his attitude

toward the product. For example, the consumer may find the firm’s message very

interesting, but virtually he cannot buy the firm’s brand because it contains something

prohibited according to his beliefs. Apparently it is very essential to include such

factors in the model, which give more interpretation about the attributes affecting the

decision process.



TECHNOLOGY (TRAT)

2.2.2 Howard – Sheth model

This model suggests three levels of decision making:

1. The first level describes the extensive problem solving. At this level the consumer

does not have any basic information or knowledge about the brand and he does not

have any preferences for any product. In this situation, the consumer will seek

information about all the different brands in the market before purchasing.

2. The second level is limited problem solving. This situation exists for consumers

who have little knowledge about the market, or partial knowledge about what they

want to purchase. In order to arrive at a brand preference some comparative brand

information is sought.

3. The third level is a habitual response behavior. In this level the consumer knows

very well about the different brands and he can differentiate between the different

characteristics of each product, and he already decides to purchase a particular

product. According to the Howard-Sheth model there are four major sets of variables;

namely:

Inputs.

These input variables consist of three distinct types of stimuli (information sources) in

the consumer’s environment. The marketer in the form of product or brand

information furnishes physical brand characteristics (significative stimuli) and verbal

or visual product characteristics (symbolic stimuli). The third type is provided by the

consumer’s social environment (family, reference group, and social class). All three

types of stimuli provide inputs concerning the product class or specific brands to the

specific consumer.



TECHNOLOGY (TRAT)

Inputs Perceptual Constructs Learning Constructs Outputs

Stimuli display

Figure 3 A Simplified Description of the Theory of Buyer Behavior Source: Howard, and Sheth,Pp32 (1969)

Perceptual and Learning Constructs,

The central part of the model deals with the psychological variables involved when

the consumer is contemplating a decision. Some of the variables are perceptual in

nature, and are concerned with how the consumer receives and understands the

information from the input stimuli and other parts of the model. For example,

stimulus ambiguity happened when the consumer does not understand the message

from the environment. Perceptual bias occurs if the consumer distorts the information

received so that it fits his or her established needs or experience.


Significativea. Qualityb. Pricec. Distinctived. Servicee. Availability

Symbolic a. Qualityb. Pricec. Distinctived. Servicee. Availability

Sociala. Familyb. Reference groupsc. Social class

Purchase

Intention

Attitude

BrandComprehen- sion

Attention

Overtsearch

Stimulusambiguity

Attention

Percept-ual bias

Confidence

Attitude

Motives

ChoiceCriteria

BrandCompre-hension

Intention

19 19


TECHNOLOGY (TRAT)

Learning constructs category, consumers’ goals, information about brands, criteria for

evaluation alternatives, preferences and buying intentions are all included. The

proposed interaction In between the different variables in the perceptual and learning

constructs and other sets give the model its distinctive advantage.

OutputsThe outputs are the results of the perceptual and learning variables and how the

consumers will response to these variables (attention, brand comprehension, attitudes,

and intention).

Exogenous(External) variables

Exogenous variables are not directly part of the decision-making process. However,

some relevant exogenous variables include the importance of the purchase, consumer

personality traits, religion, and time pressure.

The decision-making process, which Howard-Sheth Model tries to explain, takes

place at three Inputs stages: Significance, Symbolic and Social stimuli. In both

significative and symbolic stimuli, the model emphasizes on material aspects such as

price and quality. These stimuli are not applicable in every society. While in social

stimuli the model does not mention the basis of decision-making in this stimulus, such

as what influence the family decision? This may differ from one society to another.

Finally, no direct relation was drawn on the role of religion in influencing the

consumer’s decision-making processes. Religion was considered as external factor

with no real influence on consumer, which give the model obvious weakness in

anticipation the consumer decision.



TECHNOLOGY (TRAT)2.2.3 Engel – kollat- Model

This model was created to describe the increasing, fast-growing body of knowledge

concerning consumer behavior. This model, like in other models, has gone through

many revisions to improve its descriptive ability of the basic relationships between

components and sub-components, this model consists also of four stages;

First stage: decision-process stages

The central focus of the model is on five basic decision-process stages: Problem

recognition, search for alternatives, alternate evaluation (during which beliefs may

lead to the formation of attitudes, which in turn may result in a purchase intention)

purchase, and outcomes. But it is not necessary for every consumer to go through all

these stages; it depends on whether it is an extended or a routine problem-solving

behavior.

Second stage: Information input

At this stage the consumer gets information from marketing and non-marketing

sources, which also influence the problem recognition stage of the decision-making

process. If the consumer still does not arrive to a specific decision, the search for

external information will be activated in order to arrive to a choice or in some cases if

the consumer experience dissonance because the selected alternative is less

satisfactory than expected.


Stimuli:Marketer-

Dominated,other

Exposure

External search

Attention

ComprehensionPerception

Yielding/ Acceptance

Retention

Dissatisfaction Satisfaction

M E M O R Y

ProblemRecognition

SearchInternalsearch

Outcomes

Purchase

Alternative evaluation

IndividualCharacteristics

:

MotivesValues

LifestylePersonality

Beliefs

Attitude

Intention

SocialInfluences

:

CultureReference

group

Family

SituationalInfluences

Input Information Processing

Decision Process Variables Influencing Precision Process


TECHNOLOGY (TRAT)

Figure 4 .The Engel-Kollat-Blackwell Model of Consumer Behavior.Source: Engel , Blackwell, and Miniard,(1995) page No 95

Third stage: information processing

This stage consists of the consumer’s exposure, attention, perception, acceptance, and

retention of incoming information. The consumer must first be exposed to the

message, allocate space for this information, interpret the stimuli, and retain the

message by transferring the input to long-term memory.



TECHNOLOGY (TRAT)Fourth stage: variables influencing the decision process

This stage consists of individual and environmental influences that affect all five

stages of the decision process. Individual characteristics include motives, values,

lifestyle, and personality; the social influences are culture, reference groups, and

family. Situational influences, such as a consumer’s financial condition, also

influence the decision process.

This model incorporates many items, which influence consumer decision-making

such as values, lifestyle, personality and culture. The model did not show what factors

shape these items, and why different types of personality can produce different

decision-making? How will we apply these values to cope with different

personalities? Religion can explain some behavioral characteristics of the consumer,

and this will lead to better understanding of the model and will give more

comprehensive view on decision-making.



TECHNOLOGY (TRAT)2.2.4 Bettman’s Information Processing Model of Consumer Choice

Bettman (1979) in his model describes the consumer as possessing a limited capacity

for processing information. He implicate that the consumers rarely analyze the

complex alternatives in decision making and apply very simple strategy.

In this model there are seven major stages.

Stage No. 1: Processing capacity

In this step he assumes that the consumer has limited capacity for processing

information, consumers are not interested in complex computations and extensive

information processing. To deal with this problem, consumers are likely to select

choice strategies that make product selection an easy process.

Stage No. 2: Motivation

Motivation is located in the center of Bettman model, which influence both the

direction and the intensity of consumer choice for more information in deciding


Motivation Goal hierarchy

Processingcapacity

Attention

Informationacquisition

andevaluation

Decision Processes

Consumptionand

learningprocesses

Perceptualencoding

Perceptual

Scannerand

interruptmechanisms

interruptinterpretation

andresponse

Memorysearch

Externalsearch

Scannerand

interruptmechanisms

Interrupt interpretation and response

Scannerand

interruptmechanisms

Interruptinterpretation

andresponse

Scanner and interrupt mechanisms

Interrupt interpretation and response


TECHNOLOGY (TRAT)

Figure 5. the Bettman Information-Processing Model of Consumer ChoiceSource: Bettman. (1979). Pp 402

Between the alternatives Motivation is provided with hierarchy of goals’ mechanism

that provides a series of different sub-goals to simplify the choice selection. This

mechanism suggests that the consumers own experience in a specific area of market

and he doesn’t need to go through the same hierarchy every time to arrive at a

decision, which make this mechanism serves as an organizer for consumer efforts in

making a choice. No concern was given on religious motives, and how religion may

motivate the consumer in his decision. Most of the general theories of motivation such

as Maslow’s hierarchy of needs (1970) emphasizes self-achievement, the need for

power, and the need for affiliation.



TECHNOLOGY (TRAT)

Stage No. 3: Attention and perceptual encoding.

The component of this step is quite related to the consumer's goal hierarchy. There are

two types of attention; the first type is voluntary attention, which is a conscious

allocation of processing capacity to current goals. The second is involuntary attention,

which is automatic response to disruptive events (e.g., newly acquired complex

information). Both different types of attention influence how individuals proceed in

reaching goals and making choices. The perceptual encoding accounts for the

different steps that the consumer needs to perceive the stimuli and whether he needs

more information.

Stage No. 4: Information acquisition and evaluation

If the consumer feels that the present information is inadequate, he will start to look

for more information from external sources. Newly acquired information is evaluated

and its suitability or usefulness is assessed. The consumer continues to acquire

additional information until all relevant information has been secured, or until he

finds that acquiring additional information is more costly in terms of time and money.

Stage No. 5: Memory

In this component the consumer keeps all the information he collects, and it will be

the first place to search when he need to make a choice. If this informations is not

sufficient, no doubt he will start looking again for external sources.

Stage No. 6: Decision Process

This step in Bettman’s model indicates that different types of choices are normally

made associated with other factors, which may occur during the decision process.

Specifically, this component deals with the application of heuristics or rules of thumb,

which are applied in the selection and evaluation of specific brand. These specific

heuristics a consumer uses are influenced by both individual factors (e.g., personality

differences) and situational factors (e.g., urgency of the decision); thus it is unlikely

that the same decision by the same consumer will apply in different situation or other

consumer in the same situation.



TECHNOLOGY (TRAT)

Stage No. 7: Consumption and Learning Process

In this stage, the model discusses the future results after the purchase is done. The

consumer in this step will gain experience after evaluating the alternative. This

experience provides the consumer with information to be applied to future choice

situation. Bettman in his model emphasize on the information processing and the

capacity of the consumer to analyze this information for decision making, but no

explanation was given about the criteria by which the consumer accepts or refuses to

process some specific information.


Consumer Choice Behavior

Functional Value Conditional Value SocialValue

Emotional Value EpistemicValue


TECHNOLOGY (TRAT)

2.2.5 Sheth-Newman Gross Model of Consumption Values

According to this model, there are five consumption values influencing consumer

choice behavior. These are functional, social, conditional, emotional, and epistemic

values. Any or all of the five consumption values may influence the decision. Various

disciplines (including economics, sociology, several branches of psychology,

marketing and consumer behavior) have contributed theories and research findings

relevant to these values, (Sheth et al. 1991). Each consumption value in the theory is

consistent with various components of models advanced by Maslow (1970), Katona

(1971), Katz (1960), and Hanna (1980). Five consumption values form the core of the

model:

Figure 6. The five values influencing Consumer Choice BehaviorSource: Sheth, Newman, and Gross (1991) Pp159-170

The first value: Functional value

To Sheth et al. (1991) the functional value of an alternative is defined as:

"The perceived utility acquired from an alternative for functional, utilitarian, or

physical performance. An alternative acquires functional value through the possession

of salient functional, utilitarian, or physical attributes. Functional value is measured

on a profile of choice attributes."



TECHNOLOGY (TRAT)

Traditionally, functional value is presumed to be the primary driver of consumer

choice. This assumption underlies economic utility theory advanced by Marshall

(1890) and Stigler (1950) and popularly expressed in terms of "rational economic

man." An alternative’s functional value may be derived from its characteristics or

attributes, (Ferber, 1973) such as reliability, durability, and price. For example, the

decision to purchase a particular automobile may be based on fuel economy and

maintenance record.

By identifying the dominant function of a product (i.e., what benefits it provides),

marketers can emphasize these benefits in their communication and packaging.

Advertisements relevant to the function prompt more favorable thoughts about what is

being marketed and can result in a heightened preferences for both the ads and the

product, (Solomon 1996;160).

Katz (1960) developed the functional theory of attitudes. He identifies four attitudes based on the functional values:

1) Utilitarian function. The utilitarian function is related to the basic principles of

reward and punishment. We develop some of our attitude toward products simply

based on whether these products provide pleasure or pain.

2) Value-expressive function. Attitude that performs a value-expressive function

expresses the consumers’ central values or self-concept. A person forms a product

attitude not because of its objective benefits, but because of what the product says

about him or her as a person.

3) Ego-defensive function. Attitude formed to protect the person, either from external

threats or internal feelings, perform an ego-defensive function. Example of this

function is deodorant campaigns that stress the dire, embarrassing consequences of

being caught with underarm odor in public.

4) Knowledge function. Some attitude is formed as a result of a need for order,

structure, or meaning. This need is often present when a person is in an ambiguous

situation or is confronted with a new product.



TECHNOLOGY (TRAT)

The second value: Social value

Sheth et al. (1991;161) defined social value of an alternative as:

"The perceived utility acquired from an alternative association with one or more

specific social groups. An alternative acquires social value through association with

positively or negatively stereotyped demographic, socioeconomic, and cultural-ethnic

groups. Social value is measured on a profile choice imagery."

Social imagery refers to all relevant primary and secondary reference groups likely to

be supportive of the product consumption. Consumers acquire positive or negative

stereotypes based on their association with varied demographic (age, sex, religion),

socioeconomic (income, occupation), cultural/ethnic (race, lifestyle), or political,

ideological segments of society.

Choices involving highly visible products (e.g., clothing, jewelry) and good service to

be shared with others (e.g., gifts, products used in entertaining) are often driven by

social values. For example, a particular make of automobile is being chosen more for

the social image evoked than for its functional performance. Even products generally

thought to be functional or utilitarian, are frequently selected based on their social

values.

The third value: Emotional value

Sheth et al. (1991; 161) defined emotional value of an alternative as:

"The perceived utility acquired from an alternative’s capacity to arouse feelings or

affective states. An alternative acquires emotional value when associated with specific

feelings or when precipitating those feelings. Emotional values are measured on a

profile of feelings associated with the alternative."



TECHNOLOGY (TRAT)

Consumption emotion refers to the set of emotional responses elicited specifically

during product usage or consumption experience, as described either by the distinctive

categories of emotional experience and expression (e.g., joy, anger, and fear) or by the

structural dimensions underlying emotional categories such as pleasantness/

unpleasantness, relaxation/action, or calmness/excitement. Goods and services are

frequently associated with emotional responses (e.g. the fear aroused while viewing

horror movie). Emotional value is often associated with aesthetic alternatives (e.g.

religion, causes). However, more tangible and seemingly utilitarian products also

have emotional values. For example, some foods arouse feeling of comfort through

their association with childhood experiences, and consumers are sometimes said to

have "love affairs" with their cars.

A number of different attempts have been made to identify the various emotions that

people experience. Izard (1977) develops the taxonomy of affective experience

approach that describes the basic emotion that people feel. He measures emotions

using ten fundamental categories: interest, joy, surprise, sadness, anger, disgust,

contempt, fear, shame, and guilt. This approach has been used extensively by

consumer researchers, for example, Westbrook and Oliver (1991).

The fourth value: Epistemic value

Sheth et al. (1991 ;162) defined epistemic value as:

"The perceived utility acquired from an alternatives capacity to arouse curiosity,

provide novelty, and/or satisfy a desire for knowledge. An alternative acquires

epistemic value by items referring to curiosity, novelty, and knowledge."

Epistemic issues refer to reasons that would justify the perceived satisfaction of

curiosity, knowledge, and exploratory needs offered by the product as a change of

pace (something new, different). Entirely new experience certainly provides epistemic

value. However, an alternative that provides a simple change of pace can also be

imbued with epistemic value. The alternative may be chosen because the consumer is

bored or satiated with his or her current brand (as in trying a new type of food), is

curious (as in visiting a new shopping complex), or has a desire to learn (as in

experiencing another culture).



TECHNOLOGY (TRAT)

The concept of epistemic values has been influenced by theory and by several

important areas of research. Exploratory, novelty seeking, and variety seeking

motives have been suggested to active product search, trial, and switching behavior,

(Howard and Sheth 1969). One of the most significant contributors to the study of the

optimal stimulation and arousal has been Berlyne (1970), who contends that

individuals are driven to maintain an optimal or intermediate level of stimulation.

Finally, Hirschman (1980) has advanced innovativeness, or a consumer’ propensity to

adopt new products.

The Fifth value: Conditional value

Sheth et al. (1991;162) defined the conditional value as:

"The perceived utility acquired by an alternative is the result of the specific situation

or set of circumstances facing the choice maker. An alternative acquires conditional

value in the presence of antecedent physical or social contingencies that enhance its

functional or social value. Conditional value is measured on a profile of choice

contingencies."

An alternative’s utility will often depend on the situation. For example, some products

only have seasonal value (e.g., greeting cards), some are associated with once in a life

events (e.g., wedding dress), and some are used only in emergencies (e.g., hospital

services). Several areas of inquiry have also influenced conditional value. Based on

the concept of stimulus dynamism advanced by Hall (1963), Howard (1969)

recognized the importance of learning that takes place as a result of experience with a

given situation. Howard and Sheth (1969) then extended Howard’s earlier work by

defining the construct inhibitors as noninternalized forces that impede buyers’

preferences. The concept of inhibitors was more formally developed by Sheth (1974)

in his model of attitude-behavior relationship as anticipated situations and unexpected

events. Recognizing that behavior cannot be accurately predicted based on attitude or

intention alone, a number of researchers during the 1970s investigated the predictive

ability of situational factors (e.g., Sheth 1974).



TECHNOLOGY (TRAT)

The five consumption values identified by the theory make differential contributions

in specific choice contexts. For example, a consumer may decide to purchase coins as

an inflation hedge (functional value), and also realize a sense of security (emotional

value) from the investment. Social, epistemic, and conditional values have little

influence. Of course, a choice may be influenced positively by all five consumption

values For example, to a first-time home buyer, the purchase of a home might provide

functional value (the home contains more space than the present apartment), social

values (friends are also buying homes), emotional values (the consumer feels secure

in owning a home), epistemic value (the novelty of purchasing a home is enjoyable),

and conditional value (starting a family).


How does a consumer decide that he/she needs a product? What are the best sources of information to learn more about alternative choices?How are consumer attitudes toward products formed and/or changed?What cues do consumers use to infer which products are superior to others?

CONSUMER'S PERSPECTIVE MARKETER'S PERSPECTIVE

Is acquiring a product a stressful or pleasant experience? What does the purchase say about the consumer?How do situational factors, such as time pressure or store displays, affect the consumer’s purchase decision?

Does the product provide pleasure or perform its intended function?How is the product eventually disposed of, and what are the environmental consequences of this act?

What determines whether a consumer will be satisfied with a product and whether he/she will buy it again?Does this person tell others about his/her experiences with the product and affect their purchase decisions?

PREPURCHASE ISSUES

PURCHASE ISSUES

POSTPURCHASE ISSUES


TECHNOLOGY (TRAT)

2.2.6 Solomon Model of comparison process

Figure 7. Model of comparison process Source: Solomon (1996) Pp33Figure 2.2.7 explains some of the issus that are addressed during each stage of the

consumption process. The ‘exchange’, in which two or more organizations or people

give and receive something of value, is an integral part of marketing. He also

suggested that consumer behavior involves many different actors. The purchaser and

user of a product might not be the same person. People may also act as influences on

the buying processes. Organizations can also be involved in the buying process.

Much of marketing activity, they suggest, concentrates on adapting product offerings

to particular circumstances of target segment needs and wants. It is also common to

stimulate an already existing want through advertising and sales promotion, rather

than creating wants. The definitions and models, which have been presented so far,

have been from general marketing theory. Tourism is, by its very nature, a service

rather than a product, which may have a considerable effect on consumer behavior.



TECHNOLOGY (TRAT)

3. TECHNOLOGY ADOPTION MODEL

3.2.1 Theory of Innovation Diffusion Rogers Model (1995)

Innovation Diffusion:

Implementation Success or Technology Adoption is depends the Compatibility of

Technology, Complexity of Technology, Relative Advantage (Perceived Need for

Technology) system (Rogers, 1995). Individuals are seen as possessing different

degrees of willingness to adopt innovations and thus it is generally observed that the

portion of the population adopting an innovation is approximately normally

distributed over time (Rogers, 1995). Breaking this normal distribution into segments

leads to the segregation of individuals into the following five categories of individual

innovativeness (from earliest to latest adopters): innovators (Figure 3), early adopters,

early majority, late majority, laggards (Rogers, 1995). Members of each category

typically possess certain distinguishing characteristics as shown below:

1.Innovators - venturesome, educated, multiple info sources

2.Early adopters - social leaders, popular, educated

3.Early majority - deliberate, many informal social contacts

4.Late majority - sceptical, traditional, lower socio-economic status

5.Laggards - neighbours and friends are main info sources, fear of debt

Figure 8. : Diffusion of Innovation Source: Roger 1995



TECHNOLOGY (TRAT)Diffusion of Innovation Theory in Information System

Diffusion model

The model developed by Frank Bass (1969) and describes the process of how the new

product gets adopted as an interaction between users and prospects. It has been

described as one of the most famous empirical generalizations in marketing, along

with the Dirichlet Model of repeat buying and brand choice (Mark et al 1995). The

model is widely used in forecasting especially product forecasting and technology

forecasting. Mathematically, the basic Bass diffusion is a Riccati with constant

coefficients.

This model has been widely influential in marketing and management science. In

2004 it was selected as one of the ten most frequently cited papers in the 50-year

history of Management Science. It was ranked number five, and the only marketing

paper in the list. It was subsequently reprinted in the December 2004 issue of

Management Science.

(Moore and Benbasat, 1991), working in an Information System context, expanded

upon the five factors impacting the adoption of innovations presented by Rogers,

generating eight factors (voluntariness, relative advantage, compatibility, image, ease

of use, result demonstrability, visibility, and trialability) that impact the adoption of

Information Technology. Scales used to operationalize these factors were also

validated in the study.



TECHNOLOGY (TRAT)

Figure 9: Bass diffusion model of new adopters

Since the early applications of DOI to IS research the theory has been applied and

adapted in numerous ways. Research has, however, consistently found that technical

compatibility, technical complexity, and relative advantage (perceived need) are

important antecedents to the adoption of innovations see figure no. 4 (Bradford and

Florin, 2003; Crum et. al., 1996) leading to the generalized model.

Diffusion models only try to predict the type of customers only. But does not deal

with detailed the process of adoption. Hence does not focus more on the Consumer

Behaviour part of technology adoption.



TECHNOLOGY (TRAT)3.2.3 Theory of Reasoned Action (TRA) (1975)

The Theory of Reasoned Action (TRA) which was formulated in 1975 by Fishbein

and Ajzen has been used extensively in marketing research. Figure no.5presents a

diagrammatic model of the theory. TRA has been applied to explain the behaviour

beyond the acceptance of technology and includes four general concepts: behavioural

attitudes, subjective norms, intention to use and actual use. It argues that individuals

evaluate the consequences of a particular behaviour and create intentions to act that

are consistent with their evaluations. More specifically, TRA states that individuals'

behaviour can be predicted from their intentions, which can be predicted from their

attitudes and subjective norms. Following the chain of prediction further back,

attitudes can be predicted from an individual's beliefs about the consequences of the

behaviour. Subjective norms can be predicted by knowing how significant other

individuals think the behaviour should or should not be done.

Figure 10 :Theory of Reasoned Action (TRA)

A particularly helpful aspect of TRA from a technology perspective is its assertion

that any other factors that influence behavior do so only indirectly by influencing

attitude and subjective norms. Such variables would include, amongst others things,

the system design characteristics, user characteristics (including cognitive styles and

other personality variables) and task characteristics. Hence, TRA is quite appropriate

in the context of predicting the behavior of using multimedia technology. Although

TRA, is a very general theory and as such does not specify what specific beliefs

would be pertinent in particular situations.



TECHNOLOGY (TRAT)3.2.4 The Theory of Planned Behavior (TPB)

In exploring consumer's usage behavior, researchers adopt behaviour theories from

psychology and marketing. It is in this context that the TPB was constructed. The

TPB was proposed as an extension to the TRA mentioned earlier, by Ajzen in 1991.

The TPB sought to account for conditions where individuals do not have a complete

control over their behavior. When applied to the acceptance of information

technology systems or services, the model contains five concepts. As in TRA, it

includes behavioral attitudes, subjective norms, intention to use and actual use.

However, this theory interprets behavioral control as a perceived construct. Perceived

behavioral control covers both the intention to use and the actual usage. Actual usage

is in turn a weighted function of intention to use and perceived behavioral control.

Under this arrangement control aspects of the observation is introduced into the

model. This makes the TPB more functional in its application. Researchers have used

the TPB widely to model the acceptance of a variety of new information technologies

in businesses as well as to predict levels of usage.

Figure 11 :The Theory Planned Behaviour



TECHNOLOGY (TRAT)3.2.5 Unified Theory of Use and Acceptance of Technology

A recent adoption theory formulated (Venkatesh et al. 2003) Unified Theory of

Acceptance and Use of Technology (UTUAT). UTUAT includes four core elements:

performance expectancy, effort expectancy, social influence and facilitating

conditions. These elements are direct determinants of information systems usage

intention and behaviour. In addition the model proposed that gender, age, experience,

and voluntariness of use mediate the impact of the four core elements on usage

intention and behaviour.

Figure 12 :Unified Theory of Use and Acceptance of Technology



TECHNOLOGY (TRAT)

The model has excellent explanatory power, and is able to explain up to 69 percent of

the variance in usage intention (Venkatesh et al., 2003). UTUAT has been widely

employed in studies of various IT innovations. Zhou et al. (2010) used UTUAT to

study Tablet Pc adoption, and found that performance expectancy, social influence

and facilitating conditions are direct predictors of user adoption, along with the extra

dimension of task technology fit. (Gupta,et. al., 2008) found that performance

expectancy, effort expectancy, social influence and facilitating conditions all

positively influence the use of the ICT. In addition UTUAT has been used in studying

users’ adoption of mobile wallets (Shin, 2009), health information technology

(Kijsanayotin et al., 2009) and intentions to continue using web-based learning (Chiu

and Wang, 2008).



TECHNOLOGY (TRAT)3.3.1 Technology Acceptance Model (TAM)(1989)

The Technology Acceptance Model (TAM) (Davis, 1989; Davis,et. al., 1989)

examines the adoption of technology based on the perceived usefulness and ease of

use of the technology by the consumer. TAM theory applies its fundamentals to the

adoptions of technology, introducing variables like Perceived Usefulness (PU) and

Perceived Ease Of Use (PEOU) and removing Subjective Norms. The objective of

TAM is to provide an “explanation of the determinants of computer acceptance that is

general, capable of explaining usage behaviour across a broad range of systems or

end-user computing technologies and user populations, while at the same time being

both parsimonious and theoretically justified” (David, et. al.,1989,). Through TAM,

(Davis,1989) posits that an individual’s behavioural intention to adopt and use a

particular technology is determined by the individual’s attitude toward it. Two factors

contribute to the development of the Attitude (A): Perceived Usefulness (PU) and

Perceived Ease of Use (PEOU).

Will this technology enhance the individual’s performance professionally or socially?

Will the use of this technology be effortless? Each of these questions is a descriptor

for the factors. The two perceptions around usefulness (utility) and use are cognitions

around the innovation of technology. Usefulness is the cognitive evaluation of the

individual regarding the utility provided by the innovation.

Use is an indicator of the cognitive effort necessary to properly deploy the

technology. The usefulness variable is heavily influenced by the ease of use.

Figure 13 :The Technology Accptance Model



TECHNOLOGY (TRAT)All other variables being equal, the easier the technology is perceived to be to use, the

useful it is perceived to be. A key strength of Technology Acceptance Model (TAM)

is its predictive power. It has been empirically verified as a tool for predicting

technology use (Szajna, 1996) and emerged as the dominant model in the literature

(Venkatesh, 2000; VenkateshandDavis, 1996; Szajna, 1994; Davis, 1989). Its

capability has been demonstrated to explain between 17% to 33% of the variance in

attitude and usage intentions (Thompson, et. al., 1991; Davis, et. al., 1989). The

variables introduced in this model, perceived ease of use and perceived usefulness,

continue to collect empirical support and momentum in predicted technology

acceptance behavior (Venkatesh, 2000: Venkatesh and Davis, 1996). As its popularity

is growing, Technology Acceptance Model (TAM) is being used outside of the

Information System research within the marketing discipline within consumer

research around online retail shopping (O’Cass and French, 2003;Childers, et. al.,

2001), buying intentions on the web (Gentry and Calantone, 2002) and understanding

technology-based self-service usage (Dabholkar and Bagozzi, 2002). Size as well as

the enterprise’s type of activity has an influenced on the adoption of technology

(Filiatrault and Huy 2006) Technology Acceptance Model (TAM) is a fairly efficient

model with a potential to help in understanding technology acceptance pre-service

teachers (Teo, 2010). All the independent variables (perceived usefulness, subjective

norm, and perceived ease of use) predict the attitude technology Acceptance (Shittu,

et. al, 2011).



TECHNOLOGY (TRAT)3.3.2 Technology Acceptance Model 2

The original TAM model extended to explain perceived usefulness and usage

intentions in terms of social influence and cognitive instrumental processes

(Venkatesh and Davis 2000). As mentioned earlier, the original TAM model was

based on Aizen’s TRA model but did not include the subjective norms construct.

Since TAM’s introduction, consequent studies have built on TAM’s promising

robustness, trying to compare TAM to its origins and with other models used in

explaining technology acceptance such as diffusion of innovation which is discussed

in section 13. Previous studies agreed upon the need for adding other variables to

serve as determinants of the major construct since the original model lacked such

determinants for Perceived Usefulness (PU) & Perceived Ease of Use (PEOU).

TAM2, an extension of TAM, includes additional key determinants of perceived

usefulness and usage intention constructs which are meant to explain the changes in

technology acceptance over time as individuals gain experience in using the targeted

technology. Figure 9 shows the proposed model referred to as TAM2. The new model

incorporates additional theoretical constructs covering social influence processes

(subjective norm, voluntariness, and image) and cognitive instrumental processes (job

relevance, output quality, result demonstrability, and perceived ease of use).



TECHNOLOGY (TRAT)Figure 14:

Figure 14:Technology Acceptance Model 2 (TAM2)

Venkateshand Davis explained the role of social influences in computer usage

contexts. According to them, TAM2 theorizes that the subjective norms direct effect

on intention over Perceived Usefulness (PU) & Perceived Ease Of Use (PEOU) will

occur in mandatory system usage settings. The model posits voluntariness as a

moderating variable to distinguish between mandatory versus voluntary compliance

with organizational settings. Nevertheless, subjective norms can influence intention

through Perceived Usefulness (PU) or what is called internalization.



TECHNOLOGY (TRAT)3.3.3 Technology Readiness Index(TRI)

Technology readiness (TR) refers to "people's propensity to embrace and use new

technologies to accomplish goals in home life and at work" (Parasuraman, 2000, p.

308). It combines the positive and negative technology-related beliefs. These beliefs

are assumed to vary among individuals. Collectively, these coexisting beliefs

determine a person's predisposition to interact with new technology (Parasuramanand

Colby 2001). Further, the findings show that these beliefs can be categorized into four

dimensions: optimism, innovativeness, discomfort, and insecurity (Parasuraman,

2000).

Optimism is defined as "a positive view of technology and a belief that it

[technology] offers people increased control, flexibility, and efficiency in their

lives" (Parasuramanand Colby, 2001, p. 34). It generally captures positive

feelings about technology.

Innovativeness is defined as "a tendency to be a technology pioneer and

thought leader" (Parasuramanand Colby 2001, p. 36). This dimension

generally measures to what degree individuals perceive themselves as being at

the forefront of technology adoption.

Discomfort is defined as "a perceived lack of control over technology and a

feeling of being overwhelmed by it" (Parasuraman and Colby 2001, p. 41).

This dimension generally measures the fear and concerns people experience

when confronted with technology.

Insecurity is defined as a "distrust of technology and scepticism about its

ability to work properly" (Parasuraman and Colby, 2001, p. 44). This

dimension focuses on concerns people may have in face of technology-based

transactions.



TECHNOLOGY (TRAT)Optimism and innovativeness are the drivers of technology readiness. High

score of these dimensions will increase overall technology

readiness.Discomfort and insecurity, on the other hand side, are inhibitors of

technology readiness. Thus, a high score of these dimensions will reduce

overall technology readiness (Parasuraman, 2000). Results show that the four

dimensions are fairly independent, each of them making a unique contribution

to an individual's technology readiness (Parasuraman and Colby, 2001).

Source: Parasuraman (2000, p. 34),Figure 15: Technology readiness Index

TRI emerged through an extensive multiphase research program in the United States.

In the final 36-item scale the four dimensions demonstrated, for purposes of group

analysis, a sound reliability with Cronbach's alpha ranging from .74 to .81. Further,

Parasuraman (2000) found a positive relationship between TR scores and technology-

related behaviours (i.e., ownership of new technology, use, and desirability to use in

the future). A replication in Great Britain has further strengthened the soundness of

the TRI. (Tsikriktsis 2004) extracted the same four-factor structure with Cronbach's

alpha ranging from .74 to .88. Both studies obtained large national cross sectional

samples by conducting random based telephone interviews: A total of 1000 adults

(over 18 years) participated in the United States, and 400 adults (over 16 years)

participated in Great Britain (Parasuraman, 2000; Tsikriktsis, 2004).



TECHNOLOGY (TRAT)3.3.4 Technology Acceptance Model 3

A third iteration of the TAM model (TAM 3) was created, combining TAM 2 and the

determinants based on perceived ease of use by incorporating the findings of previous

research in order to improve acceptance rates of new technologies. The TAM 3 model

contains both factors influencing perceived ease of use (computer self-efficacy,

computer anxiety, computer playfulness, perceptions of external control, perceived

enjoyment and objective usability) and perceived usefulness (perceived ease of use,

subjective norm, image, and result demonstrability). The goal of the revised model is

to produce practical guidance and suggestions to practitioners (Venkatesh and Bala,

2008). TAM 3 longitudinal testing by Venkatesh and Bala (2008)identifies many new

relationships between variables. Specifically, perceived ease of use, subjective norm,

image, and result demonstrability are significant predictors of perceived usefulness at

all time periods. When participants experience increasing output quality, job

relevance has a strong positive effect on perceived usefulness. Additionally, with

increasing experience, the subjective norm has less effect than perceived usefulness.

The anchors (computer self-efficacy, computer anxiety, computer playfulness, and

perceptions of external control) are significant predictors of perceived ease of use at

all points in time and adjustments of perceived enjoyment and objective usability

become significant at later times to perceived ease of use. Finally, perceived

usefulness is the strongest predictor of technology acceptance and use at all times

(Venkatesh and Bala, 2008). While research efforts to develop TAM and TAM 2 were

interested in identifying relationships between variables, TAM 3 focuses on

producing actionable points for practioners. Researchers divide their advice into two

stages: pre-implementation interventions and post-implementation (Venkatesh and

Bala, 2008). The pre-implementation stage occurs during the development and

deployment of a technology. Venkatesh and Bala (2008) suggest that

managers/administrators encourage user participation by allowing the employees to

help pick out new technology. Also, good managerial support of the new system is

needed. Lastly, they suggest managers/administrators implement an incentive

alignment, which entails matching the individual’s perception of the new technology

with his/her job requirements and value system (Venkatesh and Bala, 2008). The

TAM 3 Model is shown in figure no.10.



TECHNOLOGY (TRAT)

Figure 16: Technology Acceptance Model 3



TECHNOLOGY (TRAT)As per the TAM 3 model, it is suggested that the determinants of perceived ease of

use will not influence perceived usefulness. The determinants of perceived ease of use

suggested by Venkatesh (2000) are primarily individual differences variables and

general beliefs about computers and computer use. These variables are grouped into

three categories: control beliefs, intrinsic motivation, and emotion. Perceived

usefulness is an instrumental belief that is conceptually similar to extrinsic motivation

and is cognition (as opposed to emotion) regarding the benefits of using a system. The

perceptions of control (over a system), enjoyment or playfulness related to a system,

and anxiety regarding the ability to use a system do not provide a basis for forming

perceptions of instrumental benefits of using a system. For example, control over

using a system does not guarantee that the system will enhance one’s job

performance. Similarly, higher levels of computer playfulness or enjoyment from

using a system do not mean that the system will help an individual to become more

effective (e.g., Van der Heijden, 2004). Therefore, it is expect that the determinants

of perceived ease of use will not influence perceived usefulness.

The summary of the various constructs used for in various adoption models are

summarised and listed in the table 2.



TECHNOLOGY (TRAT)Table 1:Models and Theories of Individual Acceptance


Models and Theories Constructs

Theory of Reasoned Action (TRA) by Fishbein and Ajzen (1975) derives from psychology to measure behavioral intention and performance.

Attitude Subjective norm

Technology Acceptance Model (TAM) by Davis (1989) develops new scale with two specific variables to determine user acceptance of technology.

Technology Acceptance Model 2 (TAM2) by Venkatesh and Davis (2000) is adapted from TAM and includes more variables.

Perceived UsefulnessPerceived Ease of UseSubjective Norm*Experience*Voluntariness*Image*Job Relevance*Output Quality*Result Demonstrability** indicates TAM2 only

Theory of Planned Behavior (TPB) by Ajzen (1991) extends TRA by including one more variable to determine intention and behavior.

Attitude Subjective normPerceived Behavioral Control

Combined TAM and TPB (C-TAM-TPB) by Taylor and Todd (1995).

Perceived UsefulnessPerceived Ease of Use Attitude Subjective normPerceived Behavioral Control

Innovation Diffusion Theory (IDT) by Rogers (1962) is adapted to information systems innovations by Moore and Benbasat (1991). Five attributes from Rogers’ model and two additional constructs are identified.

Relative Advantage*Compatibility*Complexity*Observability*Trialability*ImageVoluntariness of Use* indicates Roger’s constructs.

Unified Theory of Acceptance and Use of Technology Model (UTUAT) by Venkatesh et al. (2003) integrates above theories and models to measure user intention and usage on technology

Performance ExpectancyEffort ExpectancyAttitude toward Using TechnologySocial InfluenceFacilitating ConditionsSelf-EfficacyAnxiety


TECHNOLOGY (TRAT)

Taking this into consideration, the present study focuses on Tablet pc adoption

models that influence the adoption of Tablet pc. For this purpose, Theory Technology

acceptance model (TAM) perceived risk was used to construct a conceptual model to

study the adoption Tablet pc. It is important for Tablet pc service providers to

understand the factors influencing the intention to use or adopt Tablet pc. Further, this

study also validates the model by explaining the behavioral intentions from the user’s

perspective; the findings of this research not only help Tablet manufactures to develop

a more user-accepted Tablet pc adoption, but also provide insight into the best way to

promote new systems to potential users

3.4.1 Application of Adoption Models

The application of adoption models for various technology products are summarized

and presented in table no. 2. The following table i.e. Usage technology Adoption

Model lists the key application studies carried details in the area of technology

adoption. The table gives the details of the technology selected for the study and also

the details of the adoption models used for the validation.



4. Application of Technology Adoption models.

Table No : 02Sl.No Year Name of author Sector/industries About

01 2009 Marie Pierre Healthcare A questionnaire, based on the Technology Acceptance Model (TAM), was developed. A panel of experts in technology assessment evaluated the face and content validity of the instrument. Two hundred and thirty-four questionnaires were distributed among nurses and doctors of the cardiology, pulmonologist, and internal medicine departments of a tertiary hospital. Cronbach alpha was calculated to measure the internal consistency of the questionnaire items. Construct validity was evaluated using interitem correlation analysis. Logistic regression analysis was performed to test the theoretical model. Adjusted odds ratios (ORs) and their 95% confidence intervals (CIs) were computed. Results: A response rate of 39.7% was achieved. With the exception of one theoretical construct (Habit) that corresponds to behaviors that become automatized, Cronbach’s alpha values were acceptably high for the remaining constructs. Theoretical variables were well correlated with each other and with the dependent variable. The original TAM was good at predicting telemonitoring usage intention, Perceived Usefulness being the only significant predictor (OR: 5.28, 95% CI: 2.12–13.11). The model was still significant and more powerful when the other theoretical variables were added. However, the only significant predictor in the modified model was Facilitators (OR: 4.96, 95% CI: 1.59–15.55).

02 2009 Vincent S. Lai internet banking The technology acceptance model (TAM) has been applied in different contexts to investigate a wide range of information technologies (IT), and a cumulative tradition has already been developed in this stream of research. Most TAM studies have been empirical investigations, using the survey approach with great success.



TAM is a mature model and has been validated in different contexts. However, it still needs to be empirically investigated for its invariance across different respondent subgroups in order to make sure that different sample profiles would not have a negative effect on the findings. Unfortunately, this has not happened in most TAM research. Here, we applied different levels of invariance analysis on the TAM construct in the context of Internet banking acceptance.

03 2012 Versha Mehta Self-Service

Technologies in

Banks

Self-service technologies have found an immense use in our daily activities owing to

the rapid advancement in technology, paradigm shift in the taste and changing life-style

of consumers as well. To provide maximum benefit to their consumers, the firms have

been continuously finding alternatives to services which are in consonance with

consumer's needs, expectation and life-style besides providing them the satisfaction.

Hence, present study is an understanding of factors that lead to the formation of

consumer's attitude towards using self-service technology and finally its acceptance.

04 2011 Hala Al-Khatib

& Habin Lee

E-Government This paper proposes a conceptual model to explain user acceptance of E-Government systems considering the diverse layers of user groups. Due to digital division developing countries are providing e-Government services to heterogeneous user groups including non-educated and less skilful citizens for using computer based systems. Therefore this paper considers support quality of E-Government systems is one of critical success factors and integrates the factor in a widely adopted user



acceptance and success model of information systems.

05 2012 Abdulaziz

Alrashidi

E-Government The study has been focused on the integration of motivation into the technology acceptance model (TAM) and theory of planned behavior (TPB) towards using e Government. An online survey was created to measure the user opinion about the e Government ease of use, usefulness, and motivation.

06 2013 Hari Mohan &

Norani Ahmad

internet banking The objective of this study is to determine factors that influence individual intention towards online banking In Malaysia. Specifically, the study examines the influence of Self Efficacy (6 item), Trust (6 item), Perceived Ease of Use (5 item) and Media reference (4 item) on the intention towards Online banking. Each variable is measured using 7-point interval scale. To achieve a more balance findings among the internet banking users in Malaysia, a total of 250 questionnaires to online bank customers at 4 major banks in Klang Valley, Selangor, and across the major cities in Penang, Ipoh & Johor. 210 usable questionnaires were returned with a response rate of 84%. The data was analysed using SPSS. It was found that Self Efficiency; Trust; Perceived Ease of Use are significantly related to the intention to adopt internet banking among the users in Malaysia. Perceived Ease of Use was the main determinant towards the intention for online banking as compared to Self-Efficacy and Trust.

07 2013 Nurudeen

Abdulkadir &

Shehu Inuwa

Galoji

Mobile Banking This study extends the applicability of Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) constructs to investigate the significant factors influencing users’ adoption of mobile banking services in one of the Malaysian public universities. The research model was empirically tested through a survey. Data collected from 125 respondents were analyzed by means of multiple regression. Findings showed that perceived usefulness and social influence have significant impact on mobile banking adoption.



08 2011 Yi-Hsuan Lee &

Yi-Chuan Hsieh

E-Learning This study intends to investigate factors affecting business employees’ behavioral intentions to use the E- Learning system. Combining the innovation diffusion theory (IDT) with the technology acceptance model (TAM), the present study proposes an extended technology acceptance model. The proposed model was tested with data collected from 552 business employees using the e-learning system in Taiwan. The results show that five perceptions of innovation characteristics significantly influenced employees’ e-learning system behavioral intention. The effects of the compatibility, complexity, relative advantage, and trial ability on the perceived usefulness are significant. In addition, the effective of the complexity, relative advantage, trial ability, and complexity on the perceived ease of use have a significant influence. Empirical results also provide strong support for the integrative approach.

09 2011 Henny

Medyawati

Marieta

Christiyanti &

Muhammad

Yunanto

E- Banking The object of this research is customers on the five major banks in the city of Bekasi namely Bank Mandiri, BCA, BRI, Bank Danamon, and BNI. This study aimed to analyze the implementation of E-Banking with the approach of Technology Acceptance Model (TAM). The research method is a survey method with a descriptive analysis and statistical analysis. The data is processed and analyzed by multiple linear regression statistical models using statistical software. The results of this study indicate that the person's ability to use computers, and interface design does not significantly influence perceived ease of use. Experience of computer use, relevance, security and privacy significantly influence the perceived ease of use.



10 2013 L. Hartmann, F.

Kerssenfischer

T. Fritsch, and T.

Nguyen

Customer Self-

Service Portals

The attitude of users towards an online customer self-service portal, which is newly introduced by one of the biggest finance companies worldwide, is the focus of this article. The Technology Acceptance Model (TAM), proposed by Davis in 1986, is applied to evaluate 521 customer responses to a questionnaire consisting of 22 questions.The authors choose partial least squares (PLS) as statistical instrument and define “attitude of customers towards the online self-service portal” as the dependent variable. Apart from this, six factors are specified to directly or indirectly correlate with attitude.

11 2013 Mohamed Gamal

Aboelmaged

and Tarek R.

Gebba

Mobile Banking This study aims at extending our understanding regarding the adoption of mobile banking through integrating Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB). Analyzing survey data from 119 respondents yielded important findings that partially support research hypotheses. The results indicated a significant positive impact of attitude toward mobile banking and subjective norm on mobile banking adoption. Surprisingly, the effects of behavioral control and usefulness on mobile banking adoption were insignificant.

12 2011 Basheer A. Al-

alak

&

E-Learning The aim of the study was to investigate Jordanian lecturers' attitudes towards the adoption of e-learning system. A number of hypotheses were formulated for this purpose. The findings of the study show that there existed positive relationship between perceived usefulness, perceived ease of use, computer knowledge, management support and intention to adopt. Whereas there existed negative relationship between normative pressure, computer anxiety and intention to adopt.



Ibrahim A.M.

Alnawas

Based on the results a number of recommendations were proposed, and suggestions for future studies were made.

13 2013 Shallone K.

Chitungo

&

Simon Munongo

Mobile Banking Improvements in wireless technologies and increased uptake of advanced mobile handsets have led to a growing trend in mobile banking activities on a global scale. This empirical study sought to investigate the applicability of the extension of the renowned framework of Technology Acceptance Model (TAM) in determining factors that influence unbanked rural communities Zimbabwe‟s intention to adopt mobile banking services. A self-administered questionnaire was developed and distributed in Zaka, Chiredzi, Gutu and Chivi rural districts Out of the 400 questionnaires, only 275 useable questionnaires were returned, yielding a response rate of 69%.Results were subsequently analyzed by the SPSS package. The findings indicate that the extended TAM can predict consumer intention to use mobile banking.

14 2012 Geetha

Kallanmartho

di and

Malarvizhi

Vaithiyanatha

n

E-Banking Financial liberalization and technology revolution have allowed the developments of new and more efficient delivery and processing channels as well as more innovative products and services in banking industry. A strategic challenge facing banking institutions today is the growing and changing needs and expectations of consumers in tandem with increased education levels and growing wealth. Consumers are becoming increasingly discerning and have become more involved in their financial decisions. This study determines the factors influencing the consumer’s adoption of e-banking in India and hence investigates the influence of perceived usefulness, perceived ease of use and perceived risk on use of e-banking. It is an essential part of a bank’s strategyformulation process in an emerging economy like India. Survey based questionnaire design with empirical test was carried out. The results have supported the hypothesis that banks need to highlight the benefits of e-banking, make it easy to use, and enhance



its security to improve consumers’ trust.

15 2014 Dany Fabian

&

Römer,

Benedikt

Health care Today’s healthcare systems face tremendous challenges: demographic change and an ageing society lead to increasing healthcare needs and costs. Telemedical systems (TMS) might be an answer by improving healthcare systems’ efficiency and effectiveness. However, the diffusion of such systems is still low. A major barrier is the lack of acceptance by the key players in healthcare: physicians. To enhance the understanding of their intention to use TMS, we propose a comprehensive conceptual model and tested it empirically with survey data gathered from 213 medical doctors in Germany. Our statistical analysis confirms a very high explanatory power of the model. We extend the body of knowledge in this field of research by showing significant influences on physicians’ intentions to use TMS. The influencing factors stem from physicians’ technological contexts (data security and data reliability), financial contexts (billability and costs), individual contexts (technology affinity, subjective norms and motivations), and organizational contexts (compatibility of TMS with existing processes).

16 2013 Belghis Bavarsad

&

Mohammad Ali

Mennatyan

E-Government This paper tries to study the effects that the technology acceptance factors have on e-government services users’ satisfaction. The study data were gathered from a sample of 396 users of e-government services in Booshehr Province, Iran. The data collection tool was a structured questionnaire, its reliability was confirmed by Cronbach's alpha coefficient (α=0.91). Data were analyzed by Structural equation modeling (SEM) usingAMOS software. The analysis results indicated a good fit for the proposed model and the research findings also supported the positive and significant effect of the ease of use, trust, content and appearance of information and perceived usefulness on e-service



users’ satisfaction. However, no significant relationship was found between citizens support with the users’ satisfaction of e-service quality.

17 2013 Rawan T.

Khasawneh,

Wafa'a A.

Rabayah &

Emad A. Abu-

Shanab

E-Government Governments, all over the world, are trying so hard to increase the efficiency of their departments by using automated systems, replacing traditional services and providing online service channels which could be described as the primary features of technological revolution. This paper identifies trust and risk as important factors that could affect the usage of e-government application in a way that more trust of e-government application will decrease fear of using it and reduce risk issue. In order to achieve the goal of this paper that focused on trust and risk as two important factors that affect Jordanians’ intentions to use technology, an empirical test was conducted and resulted in moderate means regarding 5 major constructs.

18 2011 Panagiotis

Ketikidis,

Tomislav,

Dimitrovski,

Peter Bath,

Lambros Lazuras

Health Care The response of Health Professionals to the use of health information technology (IT)

is an important research topic that can partly explain the success or failure of any

Health IT application. The present study applied a modified version of the revised

Technology Acceptance Model1 to assess the relevant beliefs, and acceptance of

Health IT systems in a sample of health professionals (N = 133). Structured

anonymous questionnaires were used and a cross-sectional design was employed. The

main outcome measure was the intention to use Health IT systems. Analysis of

Variance (ANOVA) was employed to examine differences in TAM-related variables

between nurses and medical doctors, and no significant differences were found.

Multiple linear regression analysis was used to assess the predictors of Health IT usage



intentions. The findings showed that perceived ease of use, but not usefulness,

relevance and subjective norms directly predicted Health IT usage intentions. The

present findings suggest that a modification of the original TAM approach is needed to

better understand health professionals’ support and endorsement of Health IT.

Perceived ease of use, relevance of Health IT to the medical and nurse professions, as

well as social influences should be tapped by information campaigns aiming to enhance

support for Health IT in healthcare settings.

19 2013 Rahmath

Safeena, Hema

Date, Nisar

Hundewale, and

Abdullah

Kammani

Internet Banking Internet banking (IB) is the latest and most innovative service and is the new trendamong the consumers. The transformation from the traditional banking to e-banking has been a 'leap' change. This study determines the factors for the consumer acceptance of internet banking and hence investigates the influence of perceived usefulness, perceived ease of use, subjective norm, attitude and perceived behavioral control on use of IB among consumers. It is an essential part of a bank‘s strategy to formulate a model for popularizing the technology adopted to provide customer services. Therefore in this study an integration of TAM and TPB is done. Survey based questionnaire design with empirical test was carried out.

20 2010 Yitbarek Takele

&

E-Banking This study is undertaken to analyze factors that influence customers’ intention to adopt e-banking service channels in Bahir Dar city. A conceptual framework was developed by integrating six variables from theory of planned behavior, technology acceptance model and previous studies. The findings revealed that attitude, subjective norm,



Zeleke Sira perceived behavioral control, perceived usefulness and perceived ease of use and perceived risk were significant in affecting users’ intention to use e-banking service channels. The construct perceived behavioral control emerged as a dominant factor followed by attitudes and perceived usefulness in predicting an individual’s intention to adopt e-banking service channels. Finally, attitude is jointly predicted by perceived behavioral control, perceived usefulness, perceived ease of use and perceived risk while perceived ease of use contributed more for the variation in attitude.

21 2012 Mohammed

Alshehri, Steve

Drew and Rayed

AlGhamdi

E-Government this paper explores the key factors of Saudi citizens’ acceptance through a research survey and by gathering empirical evidence based on the Unified Theory of Acceptance and the Use of Technology (UTAUT). Survey Data collected from 400 respondents was examined using structural equation modeling (SEM) technique and utilized AMOS tools. The study results explored the factors that affect the acceptance of e-government services in KSA based on UTAUT model. Moreover, as a result of this study an amended UTAUT model was proposed. Such a model contributes to the discussion and development of adoption models for technology.

22 2012 José Asua,

Estibalitz

Orruño, Eva

Reviriego

Healthcare A pilot experimentation of a telemonitoring system for chronic care patients is conducted in the Bilbao Primary Care Health Region (Basque Country, Spain). It seems important to understand the factors related to healthcare professionals’ acceptance of this new technology in order to inform its extension to the whole healthcare system.This study aims to examine the psychosocial factors related to telemonitoring acceptance among healthcare professionals and to apply a theory-based instrument.



and

Marie Pierre

Gagnon

23 2014 Mohammad

Kamel Alomari

E-Government E-government has been considered as one approach for changing the face of government in the eyes of the citizenry. Therefore, citizens’ socialization in relation to their engagement with e-government should be explored. This study argues that citizens played a significant role in determining the success of an e-government project in the Middle Eastern country of Jordan. This paper aims to provide insight and evaluation into the factors that could influence e-government’s effective functioning in the Jordanian social community through its interaction with citizens. The study collected data from 356 Jordanian citizens via a survey, to ascertain their understanding of 10 factors that may influence their intention to use e-government services.

24 2011 Md Gapar Md

Johar and Janatul

Akmar Ahmad

Awalluddin

E-Commerce As the use of the Internet continues to grow in all aspects of daily life, there is an increasing need to better understand what trends of internet usage and to study the barriers and problem of ecommerce adoption. Hence, the purpose of this research is to define how far Technology Acceptance Model (TAM) contributed in e-commerce adoption. Data for this study was collected by the means of a survey conducted in Malaysia in 2010. A total of 611 questionnaire forms were delivered to respondents. The location of respondents was within Penang state. By studying this sample, conclusions would be drawn to generalize the interests of the population.

25 2014 Ali AlSoufi Mobile Banking Mobile applications have been rapidly changing the way business organizations deliver their services to their customers and how customers can interact with their service



and Hayat Ali providers in order to satisfy their needs. The use of mobile applications increases rapidly, and has been used in many segments including banking segment. This research aims at extending the Technology Adoption Model (TAM) to incorporate the role of factors in influencing customer’s perception towards M-banking adoption.

26 2014 Ni Nyoman

Kerti Yasa,

Luh Putu Rara

Ayu

Ratnaningrum &

Putu Gde

Sukaatmadja

Internet Banking The analysis unit of this study was clients of the five major banks in Denpasar. This study aimed to analyze the implementation of internet banking using Technology Acceptance Model (TAM) approach. The research method was SEM which was processed by using SPSS dan AMOS. The results of this study showed that both perceived ease of use and perceived usefulness had significant and positive effects on the attitude towards using internet banking. Both perceived ease of use and perceived usefulness also had positive and significant effects on actual usage. Attitude toward using had a significant and positive relationship with actual usage.

27 2010 Adesina

Aderonke

E-Banking This paper focuses on determining the level of users’ acceptance of the electronic banking services and investigating the factors that determine users’ behavioral intentions to use electronic banking systems in Nigeria.

The survey instrument employed involved design and administration of a total of 500 survey questionnaires within the Lagos metropolis and its environs. An extended Technology Acceptance Model (TAM) was employed as a conceptual framework to investigate the factors that influence users’ acceptance and intention to use electronic banking. To test the model, data was collected from 292 customers from various



commercial banks in Nigeria. The model measured the impact of Perceived Credibility (PC), Computer Self-Efficacy (CSE), Perceived Usefulness (PU), and Perceived Ease of Use (PEOU) on customer attitude and customer attitude on customer adaptation

.28 2011 Shih-Chih Chen,

Shing-Han Li

&

Chien-Yi Li

E-Learning

&

Mobile Banking

Technology Acceptance Model is widely applied to accessusers’ usage in various information system/information technology areas. Learning the critical role of Technology Acceptance Model can guide researchers to design different users’ interface for different online customers, and consequently achieve high user usage in different application areas. This study reviewed 24studiesto understand the past, nowand future of Technology Acceptance Model. We discussedthe related studies to clarify the extension of Technology Acceptance Model. Besides, the application areas are elaborated including electronic service, mobile data service, self-service technology, electronic learning and so on. Finally, the article concluded the conclusions and future research direction.

29 2012 David W.S. Tai,

Ren-Cheng

Zhang,

Sheng-Hung

E-Learning This study reports results of a meta-analytic path analysis e-learning Acceptance Model with k = 27 studies, Databases searched included Information Sciences Institute (ISI) website. Variables recorded included perceived usefulness, perceived ease of use, attitude toward behavior, and behavioral intention to use e-learning. A correlation matrix of these variables was derived from meta-analytic data and then analyzed by using structural path analysis to test the fitness of the e-learning acceptance model to the observed aggregated data. Results showed the revised hypothesized model to be a reasonable, good fit to aggregated data.



Chang,

Chin-Pin Chen,

Jia-Ling Chen

30 2010 Bo Cheng &

Minhong Wang

E-Learning Investigating the influences of organizational contexts on employees’ perception on competency-based workplace E-learning and their intention to adopt this new learning approach in work environment. whether organizational context factors will impact employees’ perception of competency-oriented workplace E-learning; or whether employee’s perceptions have influences on their intention to use competency-oriented workplace E-learning.

31 2009 C. Boshoff Mobile Banking The role of consumer behavior in the marketing of new technology, and gain an understanding of the TAM and identify beliefs about internet banking that could influence Perceived ease of use and Perceived usefulness of cell phone banking.

32 2013 Tony Dwi

Susanto

E-government In order to develop more acceptable e-government services, government needs to understand the factors influencing citizens to use the services. This paper reviews prior studies on acceptable e-government services and accepting users of e-government services. Demographic characteristics of the users, the impact of culture, and the psychological factors for using e-government services are discussed. By understanding and measuring the adoption factors, government may predict acceptance of a new e-government service, evaluate an existing e-government service, and improve acceptance of the service by defining and running management strategies.



33 2012 Alfie Chacko

Punnoose

E-Learning The purpose of this study was to find some of the predominant factors that determine the intention of students to use eLearning in the future. Since eLearning is not just a technology acceptance decision but also involves cognition, this study extended its search beyond the normal technology acceptance variables into variables that could affect the cognition of an individual due to his or her unique characteristics.

The variables in the literature of technology acceptance studies can be classified broadly into 5 categories. They are Individual Differences, Beliefs, Attitude, Behavioral Intention, and Actual Behavior. Since the Technology Acceptance Model (TAM) is the most widely used model to study the acceptance of technology, this study adopted TAM and further extended it based on the recommendations from the literature of information systems and information technology.

34 2010 Ayo, C.K E-Banking The most widely used e-Banking instrument in nigeria is e-Payment, particularly the automatic teller machine (ATM) card. However, with the adoption of e-Banking by all the banks in nigeria, the volume of cash in circulation has continued to increase pre-and-post bank recapitalization/consolidation exercise. Furthermore, some of the 25banks that survived the exercise were found lately to have depleted their capital base and have lost credibility before the consumers, e-Banking implementation notwithstanding.

This paper, we review the state of e-Banking implementation in _igeria and evaluate the influence of trust on the adoption of e-Payment using an extended technology acceptance model (TAM). Similarly, we investigate organizational reputation, perceived risk and perceived trust in the management of banks as a factor for enhancing customer loyalty.



35 2011 Abdelghani

Echchabi

Internet Banking The main purpose of this paper is to study the future prospects of online banking in Morocco, based on the technology acceptance model, by examining the intention of theMoroccan customers to adopt online banking and the factors that influence it. The questionnaire used in this study was distributed to 300 Moroccan banks’ customers, and the data gathered were then analyzed using structural equation modelling. The results indicate that perceived ease of use has a significant positive influence on the perceived usefulness of online banking, and both the variables have a significant positive influence on the attitude towards online banking. The latter further has a significant positive influence on the intention to adopt online banking services in Morocco. Furthermore, the invariance analysis showed that the influence is different for male and female customers. It is noteworthy that this is the first study to be conducted on online banking services in Morocco.

36 2013 Amer Al-

Adwan

&

Ahmad Al-

Adwan

E-Learning Today’s rapid changing world highlights the influence and impact of technology in all aspects of learning life. Higher Education institutions in developed Western countries believe that these developments offer rich opportunities to embed technological innovations within the learning environment. This places developing countries, striving to be equally competitive in international markets, under tremendous pressure to similarly embed appropriate blends of technologies within their learning and curriculum approaches, and consequently enhance and innovate their learning experiences. Although many universities across the world have incorporated internet based learning systems, the success of their implementation requires an extensive understanding of the end user acceptance process. Learning using technology has become a popular approach within higher education institutions due to the continuous growth of Internet innovations and technologies.



This paper focuses on the investigation of students, who attempt to successfully adopt e-learning systems at universities in Jordan. The conceptual research framework of e-learning adoption, which is used in the analysis, is based on the technology acceptance model. The study also provides an indicator of students’ acceptance of e-learning as well as identifying the important factors that would contribute to its successful use.

37 2009 Sung Youl Park E-Learning It is obvious that the number of e-learning opportunities provided by higher educational institutes continues to grow in Korea. Yet little research has been done to verify the process of how university students adopt and use e-learning. A sample of 628 university students took part in the research. The structural equation modeling (SEM) technique was employed with the LISREL program to explain the adoption process. The general structural model, which included e-learning self efficacy, subjective norm, system accessibility, perceived usefulness, perceived ease of use, attitude, and behavioral intention to use e-learning, was developed based on the technology acceptance model (TAM). The result proved TAM to be a good theoretical tool to understand users’ acceptance of e-learning. E-learning self efficacy was the most important construct, followed by subjective norm in explicating the causal process in the model.

38 2012 Kirendharen

Nadarajh Pillay

E-Government This research project examines the predictors that make e-government projects successful or unsuccessful. The aim of this research is to determine the factors that can lead to an e-government project's success or failure. This is done within the South African context. The factors are determined via a Literature survey of selected implementations around the world. Existing e-government implementations, SARS e-Filing and eNaTIS were assessed using the Technology Acceptance Model(TAM). Factors such as having a governmental policy, marketing, training and change



management are identified as positive factors. Impediments such as the digital divide, lack of skills, lack of penetration of technologies to all citizens have been determined as challenges to e-government. It is recommended that investigation into mobile phone technologies be done to bridge the telecommunications gap.

39 2010 Kelvin Joseph

Bwalya and

Mike Healy

E-Government There has recently been an escalation of e-Government initiatives in the Southern African Development Community (SADC) region, with South Africa, Mauritius, Seychelles and Botswana leading the way towards this cause. Evidence indicates e-Government implementation projects in this region either fail or succeed. Therefore it is important that before actual implementation is commissioned, there is need to understand the different challenges that come with e-Government implementations such as investment risks, failure to be adopted by the general citizenry, abandoning already-commissioned e-Government activities, and so forth. Such problems can be avoided by putting in place a properly and carefully authored e-Government adoption strategy that takes care of the local context and the multi-dimensionality of e-Government. This paper, with strong reference to Davis’ 1989 Technology Acceptance Model (TAM) theoretical underpinning, proposes a conceptual e-Government adoption model that may be commensurate with promoting the growth of e-Government in the SADC region. However, the limitation of this proposed model is that it has not been empirically tested and leaves room for its further validation. The paper follows up on the status of e-Government implementation in the SADC region by presenting two case studies that detail what interventions and initiatives have been put in place to encourage e-Government in Botswana and Zambia.

40 2010 Anna Che Azmi E-Filing The e-filing system is an important e-government service in Malaysia. This paper



and Ng Lee Bee investigates the factors that lead to the acceptance of e-filing among taxpayers by using TAM. This study proposes a model consisting of three constructs, which are perceived usefulness, perceived ease of use and perceived risk. The model proposed by this study is a simpler model compared to other studies on e-filing. The confirmatory factor analysis shows that the model is an adequate fit. Based on the data collected from 166 respondents, the results showed that the proposed model explained up to 61% of the variance in behavioral intention. All of the variables significantly influence behavioral intention. The perceived risk construct has a negative association with the perceived usefulness construct. However, there is no significant association between the perceived risk and perceived ease of use constructs.

41 2010 Cora Sio Kuan

Lai and

Guilherme Pires

E-Government Overall, the study proposes that user perceptions about the e-Government portal influence user attitude towards the portal. An Internet survey collected data from 464 online users of Macao‟s e-government portal. The model was found to explain a large proportion of the variance in citizen’s intention to reuse the portal. The portal partially mediates the relationship between success factors and intention-to-reuse. The results provide evidence that Information Quality, System Quality and Social Influence (but not Perceived Effectiveness) are success factors influencing user satisfaction and adoption. It is recommended that portal management needs to ensure ease-of-use, currency and accuracy of the supplied information. Timely information updating is a major concern for the e-Government portal in Macao. The content an e-government portal that is perceived by users to be easier to navigate is likely to facilitate satisfaction and reuse.

42 2013 Ali Tarhini, Kate E-Learning A number of studies have shown that e-learning implementation is not simply a technological solution, but a process of many different factors such as social and



Hone, and

Xiaohui Liu

behavioral contexts. Yet little is known about the important rule of such factors in technology adoption and use in the context of developing countries such as Lebanon. Therefore, the main objective of our study is to empirically validate an extended Technology Acceptance Model (TAM) (to include Social Norms and Quality of Work Life constructs) in the Lebanese context.

43 2009 Raies Ahmad

Mir &

Dr. Altaf A Dar

E-Banking Financial liberalization and technology revolution have allowed the developments of new and more efficient delivery and processing channels as well as more innovative products and services in banking industry. Banking institutions are facing competition not only from each other but also from non - bank financial intermediaries as well as from alternative sources of financing. Another strategic challenge facing banking institutions today is the growing and changing needs and expectations of consumers in tandem with increased education levels and growing wealth. Consumers are becoming increasingly discerning and have become more involved in their financial decisions. The world is changing at a staggering rate and technology is considered to be the key driver for these changes around us. An analysis of technology and its uses show that it has permeated in almost every aspect of our life. Many activities are handled electronically due to the acceptance of information technology at home as well as at workplace. Slowly but steadily, the Indian customer is moving towards the internet banking. The ATM and the Net transactions are becoming popular. This paper investigates the factors which are affecting the acceptance of e- banking services among the customers. An initial conceptualization was developed from mainstream literature to be validated through empirical research. The conceptualization was then tested with primary quantitative survey data collected from students studying in different colleges/Universities of Kashmir Division of state J&K. Correlation and regression analysis and Sign. two-tailed were used to test the key hypothesis derived



from literature.

44 2013 Tapani Rinta-

Kahila

Retail Self-Service Self-service technologies (SSTs) are becoming increasingly essential drivers of business success. A large-scale utilization tends to be a prerequisite for a successful information technology (IT) investment. This study investigates the determinants of technology adoption in the case of self service checkouts (SCOs) in Finnish grocery stores. The objectives are to confirm the determinants of intention to use SCOs, examine the link between behavioral intention to use and actual use, and study how a contextual variable may act as a trigger that turns the intention into actual use. In addition, the influence of some relevant control variables is taken under scrutiny.

45 2009 Hassan M. Selim E-Learning This study develops an E-Learning Acceptance Model (ELAM) to investigate the relationships among the factors affecting students’ acceptance of e-learning. In line with the literature, three critical success factors were used, namely instructor characteristics, information technology infrastructure, and support. ELAM was analyzed and validated using data collected from 538 university students through structural equation modeling (LISREL 8.54). The influence of the three factors on students’ decision of accepting e-learning was empirically examined. The results showed that all three factors significantly and directly impacted the students’ decision of accepting e-learning-based university program. Information technology infrastructure and the institution support were proven to be key determinants of the instructor characteristics as a critical success factor of e-learning acceptance by students. Implications of this work are very important for higher education institutions, researchers, and instructors.

46 2009 S. Poelmans, P. E-learning E-learning systems, also known as a virtual learning environments (VLE’s), are



Wessa, K. Milis,

E. Bloemen, C.

Doom

systems that use modern information and communication technology to support education and training efforts. In this paper we present the evaluation of a newly developed Compendium Platform (CP) that can be used to create educational applications that support effective learning of statistics and related analytical skills. Using the web-enabled CP, students are empowered to easily archive, exchange and reproduce statistical computations. The CP was applied in three statistics courses. Based on behavioral concepts from the Technology Acceptance Model (usefulness, ease of use and future usage intention) and object-based beliefs about the e-learning environment (information and system qualities), we tested an integrated and predictive e-learning acceptance model. Using a sample of 200 students, we report that the CP was well accepted and that the majority of our hypotheses are confirmed. System quality has a considerable impact on ease of use and does directly influence the students’ intention to use the CP in the future. The effect of information quality on intention is fully mediated by relative advantage. Relative advantage was used as an alternative to usefulness and is clearly a better predictor of usage intention. A detailed analysis indicates that the attractiveness of the user interface, the presence of appropriate search options and the availability of sufficient relevant information are critical success factors of the CP’s acceptance.

47 2013 Eugenia M. W.

Ng, Ronnie H.

Shroff, and Cher

Ping Lim

E-Portfolio The study involved student teachers enrolled in the Bachelor of Education English Language Programme at the Hong Kong Institute of Education. Students (N = 77) participated in a pilot study by electronically submitting their field experience portfolios in their third and fourth year of study. Student teachers were invited through e-mails to participate in focus group interviews. The purpose of this interview was to examine the merits and challenges of digitising the existing FE paper-based portfolio, using a digital portfolio platform, and to plan for future development using Technology



Acceptance Model (TAM) as the research framework. All participants were requiredto create e-portfolios to showcase their achievements, the effects of actual system used led to long-term behavioural intention to use, diverging from the TAM’s original model, which predicted actual system use. Student teachers either participated in a semi-structured interview (n = 7) or replied via e-mails (n = 2). The results indicated that attitude towards usage (ATU) evidenced a direct relationship to behavioural intention to use. Furthermore, for those who had mixed ATU, perceived usage was the determining factor. The findings provide insightful information not only for the next implementation phase of an e-portfolio, but also for those considering implementing e-portfolios.

48 2014 Chung-Hung

Tsai

Healthcare

(tele health)

Tele health has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use.



49 2010 Norazah Mohd

Suki &

T. Ramayah

E-Government This paper identifies the factors that determine users’ acceptance of e-Government services and its causal relationships using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents in Malaysia and subjected to Structural Equation Modeling analysis. The proposed model fits the data well. Results indicate that the important determinants of user acceptance of the e-Government services are perceived usefulness, ease of use, compatibility, interpersonal influence, external influence, self efficacy, facilitating conditions, attitude, subjective norms, perceived behavioral control, and intention to use e-Government services/system. Finally, implications and recommendations of these finding are discussed.

50 2014 Hellena Mohamed

Mushi

Mobile Banking This paper intends to explore the most important dynamics that impact individual’s decision toward accepting and adopting a mobile service. The overall objective of this is to identify several mobile service characteristics which have were not previously discussed in traditional acceptance theories. It will then be easier to differentiate the importance of service characteristics over the concepts in traditional acceptance theories. Moreover, the discussion sheds some light to our understating regarding the individual IT acceptance.

51 2009 Su-Houn Liu

&

Jean A. Pratt

E-Learning Advances in e-learning technologies parallels a general increase in sophistication by computer users. The use of just one theory or model, such as the technology acceptance model, is no longer sufficient to study the intended use of e-learning systems. Rather, a combination of theories must be integrated in order to fully capture the complexity of e-learners, who are both system users and learners. The current research presents an integrated theoretical framework to study users’ acceptance of streaming media for e-



learning. Three streams of research provide the basis for this integrated framework: the technology acceptance model, flow theory and media richness theory. Students enrolled in an online section of an information systems course used one of three different combinations of text, streamed audio and streamed video.

Regression analysis was used to test the hypotheses in this field experiment. Perceived ease of use was a predictor of perceived usefulness; both the perceived usefulness and the attitude of the user were predictors of intention to use.

52 2010 Bander Alsajjan Internet Banking This article proposes a revised technology acceptance model to measure consumers’ acceptance of Internet banking, the Internet Banking Acceptance Model (IBAM). Data was collected from 618 university students in the United Kingdom and Saudi Arabia. The results suggest the importance of attitude, such that attitude and behavioral intentions emerge as a single factor, denoted as “attitudinal intentions” (AI). Structural equation modeling confirms the fit of the model, in which perceived usefulness and trust fully mediate the impact of subjective norms and perceived manageability on AI. The invariance analysis demonstrates the psychometric equivalence of the IBAM measurements between the two country groups. At the structural level, the influence of trust and system usefulness on AI vary between the two countries, emphasizing the potential role of cultures in IS adoption. The IBAM is robust and parsimonious, explaining over 80% of AI.

53 2011 Rahmath

Safeena, Hema

Internet Banking Information technology Services is considered as the key driver for the changes taking place around the world. Internet banking (IB) is the latest and most innovative service and is the new trend among the consumers. The shift from the formal banking to e-



Date and

Abdullah

Kammani

banking has been a 'leap' change. This study determines the factors influencing the consumer’s adoption of internet banking in India and hence investigates the influence of perceived usefulness, perceived ease of use and perceived risk on use of IB. It is an essential part of a bank’s strategy formulation process in an emerging economy like India. Survey based questionnaire design with empirical test was carried out. The results have supported the hypothesis.

54 2012 Alfie Chacko

Punnoose

E-Learning The purpose of this study was to find some of the predominant factors that determine the intention of students to use eLearning in the future. Since eLearning is not just a technology ac-acceptance decision but also involves cognition, this study extended its search beyond the normal technology acceptance variables into variables that could affect the cognition of an individual due to his or her unique characteristics. The variables in the literature of technology acceptance studies can be classified broadly into 5 categories. They are Individual Differences, Beliefs, Attitude, Behavioral Intention, and Actual Behavior. Since the Technology Acceptance Model (TAM) is the most widely used model to study the acceptance of technology, this study adopted TAM and further extended it based on the recommendations from the literature of information systems and information technology.

55 2009 Yanika

Kowitlawakul

Healthcare The Technology Acceptance Model (TAM) is one of the promising models that represent an important theoretical framework to explain and predict an individual’s technology acceptance. TAM has been used extensively in the business, education, and information technology settings, but rarely in a health care setting. Rapid growth of investment worldwide in information technology by health care organizations has dramatically raised the importance of technology acceptance as an issue. Technology systems can not enhance the performance of health care providers or improve patient outcomes if the technology systems are not accepted by the end users. In the health care industry, nurses are often identified as end users. Therefore, more investigation for



better understanding of why nurses accept or reject new technology is needed. This research study attempted to examine the applicability of the TAM in explaining nurses’ acceptance of telemedicine technology (eICU®) in a health care setting, and also determined factors and predictors that influenced the probability of the nurses’ acceptance of this technology. The psychometric evidence (validity and reliability) of the measurement scales used in the study was discussed.



TECHNOLOGY (TRAT)

It can be observed from the above review that Technology Adoption Model has been widely

used or applied in sectors like Online shopping, Online Banking, Mobile technology, Health

care, Education, Self-Service Technologies in Banks, E-Government, E- Banking, Customer

Self-Service Portals, E-Filing, Retail Self-Service, E-Portfolio, etc… The studies are both

qualitative and quantitative. Further these studies have used constructs like Behavioural

Intention to Use (BIU), Attitude (A), Perceived Ease Of Use (PEOU), Perceived Use (PU),

Subjective norms, Compatibility, Habit, Facilitators, Intention, Trust, Fun, Enjoyment, and

learning, etc.. also we see that the above papers examine the different aspects of consumer

behavior like Trust, Fun, Enjoyment, and learning, etc. The above studies focus to highlight

the significance of TAM factors in the light of some external factors.

Most of the papers have used Structural Equation Modeling and Confirmatory Factor analysis

to validate and analyze the factors involved in their respective studies. Almost all the studies

have used primary data and individual responses from the actual and potential users of the

technology.

The above studies of TAM have shown positive results in the different technology adoption

areas and most of the models were statistically significant. The trend in the findings has

shown that perceived usefulness has a direct and positive relationship with satisfaction.

Behavioural Intention in turn leads to formation of brand relationship. Overall it is learnt

from the above studies that the user adoption is significantly affected by perceived

usefulness, relative advantage and trust. Perceived usefulness is directly affected by

subjective norms, image, output quality and perceived ease of use. The result shows that

TAM is efficient model to explain the intention to use the technology.



TECHNOLOGY (TRAT)

5. GAPS Identified from the Literature

From the above studies the following gaps have identified.

1. It is observed from the above studies that most of the technology adoption studies,

irrespective of the model used to assess the same have been conducted in US,

European or the South East Asian context. There are very limited studies which have

been reported in the Indian context. It would be interesting to see how these models

behave in the Indian context.

2. The studies reviewed in this report lay more emphasis in understanding the

acceptance of the technology products like computer usage, internet usage, and

mobile technologies. However there remains a scope to understand these models from

the view point of the emerging technologies like adoption of social networking

medium, E-Learning, cloud computing, online recharge of mobile phones, online

purchase of term insurance, direct to home television services etc.

3. The earlier research studies have so far used a specific model from the literature like

innovation diffusion, Unified Theory of Use and Acceptance of Technology, TRA,

TPB, TAM TAM2 or TAM 3. Very few studies have laid emphasis on developing and

validating integrated models. By doing so we can have meaningful investigations and

draw valid conclusions.

The proposed research study will attempt to address the above research gaps and the

future review will be taken in that direction



TECHNOLOGY (TRAT)

6. Proposed Model and Development of HypothesisThe review of literature carried in the previous section identifies many different

models and constructs that have been reported in various research studies.This study

integrates TAM and TRI due to the following reasons. First, both TAM and TRI can be used

to explain peoples’ technology acceptance (Davis 1989; Parasuraman, 2000). Second, the

major difference between these two models lies in that TAM uses system-specific perceptions

to explain technology acceptance while TRI is via individuals’ general inclination (Tung

2003). Third, individual differences (i.e., psychological traits) are mediated by the cognitive

dimensions (i.e., PU and PEOU) in predicting people’s acceptance of technology (Agarwal

1999).Considering the product scope (i.e E-learning) for the present study the following

constructs were reviewed in further detail, which are selected from the TRI (2000) & TAM

(1989) Model.The same has led to propose an integrated model for research in this study

6.1 Effect of Optimism (Opti.) on Perceived Usefulness (PU) & Perceived

Ease of Use (PEU)

Optimism refers to “a belief that technology offers people increased control, flexibility and

efficiency in their lives” (Parasuraman, A 2000), and represents a positive view and a

dimension of confidence in technology. People who are optimistic and innovative with

reference to technology in general are thought to hold positive attitudes toward new

technology and technology use. Optimists perceive technologies as being moreuseful and

easy to use in that they are less irritated about the negative outcomes of technology(Kuo et.

al., 2013). Therefore, it is hypothesized that optimism and innovativeness are enablers that

have positive effects on how people perceive and relate to new technology (Parasuraman and

Colby, 2001; Tsikriktsis, 2004). Therefore, it is assumed that an optimist perceives a

technology as being more use fuland easier to use because he or she worries less about

possible negative out comes. In this research it is proposed to test following hypothesis

H1: Optimism is positively influence customers’ perceived usefulness of Tablet Pc Adoption

H2: Optimism is positively influence customers’ perceived ease of use Tablet Pc Adoption



TECHNOLOGY (TRAT)

6.2 Effect of innovativeness on Perceived Usefulness(PU) and Perceived

Ease of Use (PEU)

Innovativeness is defined as an individual’s tendency to be more receptive to new ideas

(Leung and Wei, 1998; Lin, 1998; Lin and Jeffres, 1998; Li, 2003; Rogers, 1995).

Innovativeness depends on individuals and is seen as critical in consumers’ technology

adoption. Individual innovativeness tends to differentiate adopters from non–adopters of new

technologies (Lin, 1998; Lin and Jeffres, 1998; Busselle, et al., 1999). (Rogers 1995) argued

that a high degree of individual innovativeness triggers early adoption of a new technology

and/or idea. Individual innovativeness is also introduced into the TAM research to expand the

scope of TAM applicability. (Lin 2004) pointed out that recent studies on innovative

attributes and computer–mediated technology adoption generally support the influences of

this personality trait on adoption of an innovation. Innovativenesshas a significant effect on

PEOU but not on PU(Kuo et. al., 2013)in Mobile electronic medical records.(Busselle, et

al.1999) found that an individual’s innovativeness is a positive predictor for the frequency of

Internet use. (Lin 1998) and (Lin 2004) also demonstrated that innovativeness is a significant

predictor for adoption. Thus it is proposed to test the following hypothesis

H 3: Innovativeness is positively influence customers’ Perceived Ease of Use of Tablet pc

Adoption

H 4: Innovativeness is positively influence customers’ Perceived Usefulness of Tablet pc

Adoption



TECHNOLOGY (TRAT)

6.3 Effect of discomfort on Perceived Usefulness(PU) and Perceived Ease of

Use (PEU)

Discomfort is defined as "a perceived lack of control over technology and a feeling of being

overwhelmed by it" (Parasuraman and Colby 2001, p. 41).People who have high level of

discomfort toward new technologies tend to find technology less easy to use (Walczuch et al.,

2007).Similarly, discomfort may have negative effect on perceived usefulness, because it is

an inhibitor of using new technologies (Parasuraman, 2000; Walczuch et al., 2007 and Kuo

et. al., 2013).This dimension generally measures the fear and concerns people experience

when confronted with technology. Discomfort, on the other hand, is not expected to have a

negative impact on perceived usefulness.

One would expect people to see the main value of a system, regardless of how they handle it.

Still, discomfort is expected to affect perceived ease of use. Discomfort can be reduced

through informative feedback and augmented ease of use (Dabholkar, 1996; Walczuch et al.,

2007).A system that is not manageable is more likely to be a non-user-friendly system. Thus,

it is hypothesized

H 5: Discomfort is not significantly related to Perceived Usefulness of Tablet pc Adoption

H 6: Discomfort is negatively related to Perceived Ease of Use of Tablet pc Adoption

6.4 Effect of Insecurity (Insc)Perceived Usefulness(PU) and Perceived Ease

of Use (PEU)

Insecurity is the result of a lack of trust in technology and its ability to work properly

(Parasuraman, 2000). A perceived lack of security is generally acknowledged to be important

and to have contributed to the slow adoption of e-commerce (Hoffman et al., 1999).

Insecurity is also related to the expected benefits of an innovation, or its realization (Ram,

1987).Previous researches suggest that the lower the expected realization, the higher the

resistance to innovation will be. The insecurity is related to technology are on the other hand

associated with ambiguity and low usage (Parasuraman and Colby, 2001; Tsikriktsis, 2004

and Kuo et. al., 2013). In accordance with earlier research we therefore assume that insecurity

predicts lower levels of perceived usefulness and perceived ease of use. Thus, we

hypothesize:



TECHNOLOGY (TRAT)

H 7: Insecurity is negatively related to Perceived Usefulness of Tablet pc Adoption

H8: Insecurity is negatively related to Perceived Ease of Use of Tablet pc Adoption

6.5 Effect of Perceived Usefulness (PU) on Attitude

Perceived usefulness has been defined as “the degree to which a person believes that using a

particular system would enhance his or her job performance” (Davis, 1989, p. 320).

According to (Gong and Xu 2004) he defines perceived usefulness as the user’s “subjective

probability that using a specific application system will increase his or her expectations.

Perceived usefulness is the primary antecedent that determines the behaviouralaimto use a

computer system (Venkatesh and Davis, 2000).Davis et al. (1989) proposed that perceived

ease of use is an antecedent of Perceived usefulness. Results from previous research also

revealed the significant effect of perceived ease of use toperceived usefulness (Kleijnen et al.,

2004; Wang et al., 2003; Davis et al., 1989). Huang,J. Linn Y., and Chuang S. (2007) posits

that two particular behavioural beliefs, perceived usefulness (PU) and perceived ease of use

(PEOU), are two fundamental factors for predicting user acceptance, and that the effect of

external variables on intention are mediated by these two key beliefs (Adams et al., 1992;

Davis, 1989; Davis et al., 1989; Mathieson, 1991).Perceived usefulness is also known as

performance expectancy (Venkatesh et al., 2003). Perceived usefulness is recognized as

having strong positive effect on the intention of adopters to use the innovation. Numerous

studies have shown that perceived usefulness is the primary predictor of information

technology usage (Davis, 1989; Davis, Bagozzi and Warshaw, 1989; Gefen, Karahanna and

Straub, 2003; Venkatesh and Morris, 2000). Previous researches have shown that perceived

usefulness influenced computer usage directly (Ha and Stoel, 2009; Huang, 2008;Sudha et al,

2010). Perceived usefulness directly affected attitudes towards E-Learning, and that attitude

was the major determinant of Tablet pc Adoption (Akturan and Tezcan, 2012). Yang (2005)

showed that perceived usefulness influence attitude toward using m-commerce. Usefulness,

ease of use of the system awareness about Tablet pc Adoption and risks related to it are the

main perusing factors to accept online banking system. These factors have a strong and

positive effect on customers to accept Tablet pc Adoption system (Rahamatet.al., 2012).

Thus, this research proposes the following hypothesis

H 9: Perceived Usefulness will have a positive effect on attitude towards use of Tablet Pc

Adoption



TECHNOLOGY (TRAT)

6.6 Effect of Perceived Ease of Use (PEU) on Perceived Use (PU) and

Attitude (Atti)

Perceived ease of use is the degree to which a person believes that using a particular system

would be free of effort (Dholakia and Dholakia, 2004). Numerous researches have provided

support that perceived ease of use had a significant effect on usage intention; it is an

important forecaster of technology adoption. Perceived ease of use refers to the degree to

which a person believes that using a particular system would be free of effort (Davis, 1989;

Liu and Li, 2010). Perceived ease of use (perceived complexity) has been found to be an

important determinant of technology usage, both in a direct and indirect manner, and

technology users have been proven to “attempt to minimize their cognitive effort on their

behaviours” (Cho, 2011). Individuals will thus exhibit a higher intention to use a system,

when it is perceived to be easy to use. As described, this has been found to operate mainly

through perceived usefulness, for when system is difficult to use, its usefulness is harder to

identify.

Thus, this research proposes the following hypothesis:

H 10: Perceived ease of use will have a positive effect on attitude of E-Learning

H 11: Perceived ease of use will have a positive effect on perceived usefulness of E-Learning

6.7 Effect of Attitude (Atti) on Behavioral Intention (BI)

Attitude is considered a multidimensional construct comprised of cognitive, affective, and

conative components. Yet, most attitude measurement techniques resulted in capturing only

the affective side of the concept (Ajzen et al. 2005). IS research has widely accepted the

attitude definition by Fishbein and Ajzen (Fishbein et al. 1975) in that attitude is “an

individual’s positive or negative feelings (evaluative affect) about performing the target

behavior” (Davis et al. 1989; Moonetal. 2001; Venkatesh et al. 2003). That is, attitudes are

often considered overall affective evaluations (Ajzen et al. 1980). The attitude is the

psychological tendency depending on a degree of favour or disfavor (Eagly and Chaiken

1993). Attitude is defined as “the degree to which a person has a favourable or unfavourable

evaluation or appraisal of the behavior in question” (Ajzen, I., 1991). Attitude toward user



TECHNOLOGY (TRAT)

acceptance of technology is defined as an individual’s overall affective reaction

(liking,enjoyment, joy, and pleasure) to use a technology (Davis, 1989; Taylor and

Todd,1995). Attitude also has a significant impact and appears to be the second positive

determinant of a consumer’s intention to accept Tablet Pc Adoption. This leads to hypothesis:

H12: Attitude will have a positive effect on Behavioral Intention of Tablet pc adoption

6.8 Effect of Subjective Norm (SN) on Behavioral Intention (BI)

The construct Subjective Norm (SN) was promoted by FishbeinandAjzen (1975), and was

developed by Mathieson (1991). Subjective Norm (SN) or Normative Pressure (NP) is

defined as a person‘s perception that most people who are important to her or him should or

should not perform the behavior in question (Fishbein and Ajzen, 1975).Subjective norm is

usually separated in interpersonal and external influences (Lin, 2007 and Bhattacherjee,

2000).Subjective Norms explain how thebehavior of an individual is influenced or changed

based on how other important people to him/her think he/she should behave.Subjective norm

is believed to influence intention to use because people may choose to perform behavior,

even if they are not themselves favorable toward the behavior or the consequences

(Venkatesh and Davis, 2000). What other individuals or groups will think, agree or disagree

about the decision of a person to perform a given behavior and how important these other

individuals or groups play a vital role for the decision maker. So sometime people may be

seek advice from others before them making any decisions.

Social norms have been widely validated in group-oriented I.T (Taylor and Todd, 1995),

email acceptance (Gefen and Straub, 1997; Karahana and Limayem, 2000), E-Learning

(Chan and Lu, 2004) and Tablet Pc adoption (Riquelme and Rios, 2010; Schepers and

Wetzels, 2007). The social context of the consumer should not be neglected (Schierz, et al.,

2010). The empirical research conducted by (Yu, 2012) in Taiwan by sampling 441

respondents, the most significant predictor was social influence, in the individual intention to

adopt Tablet Pc.

The opinion of other individuals or groups will think, agree or disagree about the decision of

a person to perform a given behaviour and how important these other individuals or groups



TECHNOLOGY (TRAT)

play a vital role for the decision maker. So sometime people may be seek advice from others

before them making any decisions.

H 13: Subjective norms will have positive effect on behavioural intention of Tablet pc

adoption

Research model

Figure 17:



TECHNOLOGY (TRAT)

7. Proposed Research Methodology

A two phase research methodology is proposed to be used for the study. An effective

instrument should cover the content domain of each construct (Nunnally, 1978; Churchill,

1979).The items that measure a construct should agree (converge) with each other, and the

items of one construct should disagree (discriminate) with measures of the other constructs.

Each construct should be reliable and short and easy to use. The study will adopt a two-phase

approach. In the first phase, the definitions of the constructs as well as the measurement items

for each construct will be established. In this phase, we will also provide tentative indications

of reliability and validity. This phase will include item generation, pre-pilot study, and pilot

study. In the second phase, we propose to further refine this scale and validate the measures

using Likert scale survey data based on the scales developed in the first phase. Stratified

Sampling technique will be used to select the sample so that the selected sample has a

representation of the respondents from different strata’s on the basis of age, gender,

qualification and profession. The survey will be conducted in Bijapur with 200 respondents

from each city. The survey instrument will be developed in order to test the research model.

The items and questions in the proposed questionnaire will be adopted from existing studies;

the questionnaire will be pre-tested with reputed experts from Education sector (Technical

Students) to ensure that the wording and format of the questions are appropriate.



TECHNOLOGY (TRAT)

Questionnaire

The questionnaire included the technology readiness index (TRI) developed by A.

Parasuraman and Rockbridge Associates (2000) and the technology acceptance model (TAM)

as introduced by Davis (1989) (see Appendix A and B for a complete list of the items in the

TRI and TAM). The technology readiness index (TRI) is a multi-item scale compromising 36

technology belief statements, both positive and negative, related to one of the four TR

dimensions. Each statement is scored on a 5-point scale (from 1 = strongly disagree, to 5 =

strongly agree).

Perceived usefulness and perceived ease of use are measured as distinct dimensions in

the technology acceptance model. Each dimension comprises 6 statements, scored on a 7-

point scale (from 1 = extremely unlikely, to 7 = extremely likely).

Students many very from factor to factor were translated into Norwegian and then

back translated by a third independent person. The TAM scales were modified in accordance

to the technology used by the respondents. Actual use was self-reported on a 7-point scale

(from 1 = not at all, to 7 = several times a day).

Procedure

The research model was tested using structural equation (SEM) modeling which

allows researchers to perform path analytic modeling with latent variables (Bollen, 1989). In

our research design the latent variables represented by the TRI were optimism,

innovativeness, insecurity and discomfort. TAM consists of the two cognitive dimensions

perceived usefulness and perceived ease of use. Items associated with each latent dimension

were included in the structural model in Amos 21st.



TECHNOLOGY (TRAT)

8. Data analysis and results

This section will analysis the result obtained from the questionnaire that was

distributed to respondents using research questionnaire.

This analysis will also look at the students knowledge of tablet Pc Adoption and also

adoption rate. The finding from the students shows that more students are ready to adopt

Tablet Pc.

A) Respondents demographic characteristics

The frequency where use to determine how often respondents made a certain response

in answering questions, and this allowed general information about the information collected

to be analyze. Questionnaire was constructed and also distributed among students through

using google Doc. The demographic detail shows Gender, Age, Academic Year and these are

shown in the table below.



TECHNOLOGY (TRAT)

Table 3: Frequency distribution

Age In Years

Frequency Percent Valid Percent

Cumulative Percent

Valid

18-20 66 32.8 32.8 32.821-22 104 51.7 51.7 84.623-24 31 15.4 15.4 100.0Total 201 100.0 100.0

Chart No 1:Interpretation

As per the respondents above table shows that 18-24 Age students are 32.8% , 21-22

Age students are 51.8% and reaming 23-24 Age students are 15.4% they given responses.

Table No 4 :Respondents of Gender



TECHNOLOGY (TRAT)

Chart No 2:

Interpretation

As per the respondents above table shows that Female Gender students are 34.8% ,

Male Gender students are 65.8% .

Table No 5 : Respondents of academic year


GnderFrequency Percent Valid

PercentCumulative

Percent

ValidFemale 70 34.8 34.8 34.8Male 131 65.2 65.2 100.0Total 201 100.0 100.0

93 93


TECHNOLOGY (TRAT)

Academic YearFrequency Percent Valid

PercentCumulative

Percent

Valid

I st 27 13.4 13.4 13.4II nd 42 20.9 20.9 34.3III rd 97 48.3 48.3 82.6IV th 35 17.4 17.4 100.0Total 201 100.0 100.0



TECHNOLOGY (TRAT)

Chart No 3:Interpretation

As per the respondents above table shows that Ist year students are 13.4% , II nd year

students are 20.9%, III rd year students are 48.3% and reaming IV th year students are

17.4% they given responses.

8.1 Results

Preliminary analyses

Before testing our hypotheses we assessed the reliability and validity of the translated

TRI and TAM. A confirmatory factor analyses (CFA) using structural equation modeling

(SEM) was conducted in Amos 6.0 to examine how well each item corresponded to the latent

dimensions. Our limit for low factor loadings was set to .30, as recommended by Ulleberg

and Nordvik (2001). Further, we assessed the Cronbach’s alphas to test the internal

consistency reliability for each dimension. According to Nunnally (1978) alphas above .70

are acceptable.

The CFA of TRI revealed four items with low factor loadings. Hence, they were

excluded from subsequent analyses. With these items excluded, the alpha for the TRI

dimensions ranged from .68 to .84. The alpha values are presented in Table 2 along with the

alphas obtained by Parasuraman (2000) in the United States and Tsikriktsis (2004) in Great



TECHNOLOGY (TRAT)

Britain. Three of the four dimensions show acceptable internal consistency reliability for

group analysis. The Cronbach’s alpha for discomfort is just below the acceptance criteria

suggested by Nunnally (1978).

Table 6

Comparison of Cronbach’s alphas on TRI dimensions in the US, Great Britain and Norway

Country Optimism Innovativeness Discomfort Insecurity

Norway .84 .83 .68 .75

United States .81 .80 .75 .74

Great Britain .83 .85 .74 .88

Regarding the CFA of TAM, all items showed high factor loadings (above .70).

Hence, there was no need to exclude items from these scales. Both dimensions exhibited

strong alphas (above .90) indicating good measures for the internal consistency reliability.



TECHNOLOGY (TRAT)

In sum, seven of thirteen hypotheses were supported. The relationships between the

variables are depicted in Figure 18, showing the standardized estimates for significant results

only. Regarding the complete model fit, this was found to have an acceptable fit at best (2 =

1764.2, d.f. = 935, 2 /d.f. = 1.89, RMSEA = .087, CFI = .663, TLI = .647). The 2 /d.f. ratio

and the RMSEA are acceptable, but the CFI and TLI are below the general cutoff criteria

(.95) for acceptable fit as proposed by Schreiber, Nora, Stage, Barlow, and King (2006).



Figur 18. The integrated model, as depicted, shows standardized estimates of the hypothesized path analysis. All estimates are significant, unless noted as not significant by “n.s.”.



TECHNOLOGY (TRAT)9. Discussion

This study has investigated the relationship between the personality

dimensions in the TRI and main elements of the TAM (i.e. perceived usefulness,

perceived ease of use and Behavioral intention ).

Our findings reveal that some, but not all, personality dimensions of the TRI

influence technology acceptance and Behavioral intention. Optimism and

innovativeness were the only personality dimensions that significantly affected

perceived usefulness and perceived ease of use. The positive relationship between

optimism and the cognitive dimensions of TAM makes logical sense. An individual

that in general is optimistic about technology will find a specific system more useful,

and easier to use, than someone less optimistic.

The effect of innovativeness was more intriguing. As expected there was a

positive relationship between innovativeness and perceived ease of use. This implies

that innovative Students find it easier to use a system. Unexpectedly, however, the

relationship between innovativeness and perceived usefulness was negative. Thus,

highly innovative Students find systems less useful than less innovative Students.

This is somewhat contradicting to previous findings were innovativeness is

found to have a positive effect on the adoption level of technology (Jong, Ruyter, &

Lemmink, 2003; Ward, Chitty, & Graham, 2007). Then again, Walczuch et al. (2007)

found the exact same negative relationship between innovativeness and perceived

usefulness as the present study. They concluded “that innovative people are more

critical towards technology since they are aware of the newest developments and

possibilities, and expect all technology to fulfill highest demands” (p. 212).

The question that arises here is how innovativeness can be positively related

with technology adoption, and at the same time be negatively related with perceived



TECHNOLOGY (TRAT)usefulness. One possible explanation is that highly innovative people are more willing

to adopt and try new technologies than other people. However, they easily cease to

use a system due to their high standards for new technological development.

Insecurity and discomfort had no significant effect on the cognitive

dimensions of TAM. Except for the relationship between discomfort and perceived

usefulness, this was not as expected. However, the beta coefficients were in the

predicted direction, and a larger sample size could give a significant result. Yet, even

with a larger sample size and significant relationships, the effects would be small due

to the low standardized beta coefficients.

Further, our results revealed that actual use was directly affected by perceived

usefulness, but not perceived ease of use. However, the positive relationship between

perceived ease of use and perceived usefulness indicate an indirect influence of

perceived ease of use on actual use. In sum, the perceived characteristics of the

systems, influence actual usage; and perceived usefulness is found to be the main

contributor to system usage. These findings are in accordance with the majority of

previous research on TAM (e.g. King & He, 2006; Legris et al., 2003; Schepers &

Wetzels, 2007).



TECHNOLOGY (TRAT)

9.1 Limitations and perspectives for future research

There are several limitations with this study. First, when testing the model on

two different technologies the total outcome may have been biased. This may have

caused little variation in the dependent variable (actual use). An investigation of how

mandatory use affects adoption of technology compared with voluntary use would be

of major interest for the field.

Second, the subgroups are quite different demographically. The group consists

of mostly women (89,4%), while age is evenly distributed. This homogeneity may

have biased the results. Future research should take care to eliminate possible

confounding effects of age and gender. It is also advisable to assess age in a more

specific metric manner.

Third, deleting items from the TRI scales may cause a validity problem.

However, only four out of a total of 36 items were deleted. Removing two items from

the insecurity dimension, and two items in the discomfort dimension led to higher

alphas values of the two dimensions and a better overall fit of the model; hence

improving the internal consistency. It is recommended by Ulleberg and Nordvik

(2001) to exclude low factor loadings, and as long as the majority of items on each

dimension of the TRI are still included it may be argued that the reduced subsets still

measures the constructs in question. One reason for the low factor loadings may be

due to poor translations. Further, it is possible that the some of the TRI items are

outdated. Some of the statements in the test may therefore begin to lose what they are

meant to capture. For example, the statement “The human touch is very important

when doing business with a company” could be related to stronger feelings ten years

ago than it does now. Hence, a scale revision may be a direction for future research.



TECHNOLOGY (TRAT)Fourth, the Cronbach’s alpha for discomfort is below Nunnally’s (1978)

suggested cutoff for acceptance (.70). It is also lower compared to the alphas obtained

in the United States and Great Britain, as presented in Table 2. The reasons for low

alpha in the Norwegian study could be related to poor translations of some items.

However, according to Sekaran (2000) alphas between .60 and .70 may be acceptable

for studies with group analysis design.

Fifth, when translating the TRI and TAM further assessment of reliability

should have been undertaken. It is argued above that we did get acceptable results for

the internal consistency reliability for each dimension in the test. There is, however,

no guarantee for this consistency over time. A test-retest could have dealt with this

limitation and strengthened the study.

Sixth, TRAM represents a fairly complex model and the complexity could

easily expand further with additional paths and variables. It is no limit to the

complexity of a model, however it is a very fine line between what is understandable

and what is not. Research that examines TRAM connections beyond those that have

been presented in this study, will add to the understanding of implementation of new

technologies in general. It would be interesting to see how the TRI dimensions

correspond with actual use directly. If insecurity and discomfort are not mediated

through TAM, the dimensions may have direct effects on actual use. It is also possible

that the effect of these dimensions are mediated through other variables not included

in this study, such as for example social norm. Further, this study has focused on

technology related beliefs and perceptions. How this corresponds with more generic

personality traits has to our knowledge not been investigated thus far. We encourage

future research to look into these aspects.



TECHNOLOGY (TRAT)Finally, care should also be taken in generalizing these results to other

technologies. IM and EHR can be categorized as interactive technology as they both

simplify communication and sharing of information via computer networks. They are

also fairly novel in the organizational settings where they were tested. It is probable

that the results are adaptable to other novel technologies, especially in organizational

contexts. Adopting the results to well established technologies is however more

problematic as the TRI is less applicable regarding such systems. We believe that the

link between technological readiness and technological acceptance is worth taking a

step further by testing the TRAM model on different new technologies in different

settings (e.g. organisational, educational and private). Only thorough research in this

area can determine how the relationship between the different dimensions in the

model depends on different technologies and contexts.



TECHNOLOGY (TRAT)10. Conclusion

The results from this study to a large extent replicate and extend the findings

from Walczuch et al. (2007). The personality dimensions of TRI influences the

cognitive dimensions of TAM and subsequently technology usage. An integrated

model expands the applicability of the prior models due to the focus on both

individual and system specific characteristics. On one hand there should be

considerable emphasis on the users and their general attitudes toward technology,

especially in settings where it may be impractical to test the system before it is

adopted. With general user knowledge, the necessary steps could be taken to initiate

successful implementations.

On the other hand the model explains why some systems are rejected even in

organizations where people are highly optimistic towards technology in general. If the

system specific characteristics (i.e. perceived usefulness and perceived ease of use)

are too low, a system will be rejected regardless of people’s general technology

readiness. Hence, measures of the perceived usefulness and perceived ease of use add

valuable information for those designing and implementing new technology.

In sum, a combination of these two models comprises a holistic view. It indicates that

adoption of new technologies involves individual as well as system specific factors. In

our view, a fundamental aspect of research is that it should be applicable. An

integration of psychometric constructs and system-related experiences will in this

respect be future-oriented, innovative and useful.



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AnnexureQuestionnaire

Dear Respondent,Myself Arun M Savukar. I am fellow student of B.L.D.E.A’s MBA A.S.Patil College of Commerce Bijapur.I am doing Research on

Understanding New technology by Engineering Students application of TRAT. This is survey tries to capture attitude towards using Tablet

Pc adoption of Engineering Students. This Questionnaire was two sections, Section A and B. We request you spare around 5 to 10 minutes for

giving your response to the items below. We thank you in anticipations.

This is an anonymous survey about the use of Tablet Pc.

Age :-Gender :- Academic Year :-

Sl.No Items Ratings1 2 3 4 5

Perceived usefulness (PU)01 PU1 Using Tablet PC will save my time in Learning

02 PU2 Using Tablet PC would improve my performance in Learning

03 PU3 Using Tablet PC would improve my productivity in Learning

04 PU4 Using Tablet PC would improve my effectiveness in Learning

05 PU5 I find Tablet PC to be useful in Learning



Attitude (ATTI)06 ATTI1 In my opinion it is desirable to use Tablet PC for learning

07 ATTI2 I think it will be good for me to use Tablet PC for learning

08 ATTI3 I think learning through Tablet PC is a good idea

09 ATTI4 Overall, my attitude toward Tablet PC is favourable

10 ATTI5 Generally speaking, I like the idea of Tablet PC for learning

Perceived Ease of Use (PEU)11 PEU1 I find Tablet PC easy to use

12 PEU2 Use of Tablet PC is clear and understandable

13 PEU3 It is easy for me to remember how to perform tasks using Tablet PC

14 PEU4 Overall, I find the Tablet PCis easy to use

Subjective Norm (SN)15 SN1 Most people who are important to me expect me to use Tablet

16 SN2 Most of my friends believe using Tablet PC is a wise decision.

17 SN3 People whose opinions I valued preferred that I use Tablet PC

Optimism (Opti)

18 OPTI1 Tablet PC gives more control on my daily life

19 OPTI2 Tablet PCis much more convenient to use

20 OPTI3 I like the idea of learning via Tablet pc because I am not limited to manual



transactions

21 OPTI4 I prefer to use the most advanced technology available

22 OPTI5 I like Tablet PC that allow you to tailor things to fit your own needs

23 OPTI6 Tablet PC makes you more efficient in your occupation

24 OPTI7 I find Tablet PC to be mentally stimulating

25 OPTI8 Tablet PC gives you more freedom of mobility

26 OPTI9 Learning about technology can be as rewarding as the technology itself

27 OPTI10 I feel confident that Tablet PC will follow through with what you instructed them

to do

Innovativeness (Inn)28 INNO1 Other people come to me for advice on Tablet PC

29 INNO2 It seems my friends are learning more about the Tablet PC than me

30 INNO3 In general, I am the first among in my circle of friends to acquire Tablet PC when

it appears

31 INNO4 I can usually figure out Tablet PC without help from others

32 INNO5 I keep up with the latest technological developments in my areas of interest

33 INNO6 I enjoy the challenge of figuring out high-technologies

34 INNO7 I find i have fewer problems than other people in making technology work for me

Discomfort (Disc)



35 DISC1 Technical support lines are not helpful because they do not explain things in terms

you understand

36 DISC2 Sometimes, I think that Tablet PC is not designed for use by ordinary people

37 DSIC3 There is no such thing as a manual for a high-tech product or service that is written

in plain language

38 DSIC4 When i get technical support from a provider of a Tablet PC, in sometimes i feel as

if i being taken advantage of by someone who knows more than i do

39 DSIC5 If I useTablet PC,I prefer to have a lot of features

40 DSIC6 It is embarrassing when I have trouble with a Tablet PCsystem while people are

watching

41 DSIC7 Tablet PC makes it too easy for teachers to monitor student performance

42 DSIC8 Technology always seems to fail at the worst possible time

Insecurity (INSC)

43 INSC1 I do not consider it safe in adopting Tablet PC

44 INSC2 I do not consider it safe to learn online

45 INSC3 I worry that information you send over the Internet will be seen by other people

46 INSC4 I do not feel confident doing banking with a place that can only be reached online

47 INSC5 Any business transaction I do electronically should be confirmed later with

something in writing



48 INSC6 Whenever something gets automated, I need to check carefully that the Tablet pc

or software is not making mistakes

49 INSC7 The human touch is very important while transacting through Tablet PC

50 INSC8 When I call a business, I prefer to talk to a person rather than a machine

51 INSC9 If I am provided information to a machine or over the Internet, I can never be sure

it really gets to right place

Behavioural Intention (BI)52 BI1 I predict that I will use Tablet PC on a regular basis in the future

53 BI2 I expect that I will use Tablet PC system, or a similar type of system for Learning

54 BI3 I will use Tablet PC in future



TECHNOLOGY (TRAT)Constructs and Item Measures From the Questionnaire

1. Perceived Usefulness (PU)

PU1 Using Tablet PC will save my time in Learning

PU2 Using Tablet PC would improve my performance in Learning

PU3 Using Tablet PC would improve my productivity in Learning

PU4 Using Tablet PC would improve my effectiveness in Learning

PU5 I find Tablet PC to be useful in Learning

2. Attitude (Att)

ATTI1 In my opinion it is desirable to use Tablet PC for learning

ATTI2 I think it will be good for me to use Tablet PC for learning

ATTI3 I thinklearning through Tablet PC is a good idea

ATTI4 Overall, my attitude toward Tablet PC is favourable

ATTI5 Generally speaking, I like the idea of Tablet PC for learning

3. Perceived Ease of Use (PEU)

PEU1 I find Tablet PC easy to use

PEU2 Use of Tablet PC is clear and understandable

PEU3 It is easy for me to remember how to perform tasks using Tablet PC

PEU4 Overall, I find the Tablet PCis easy to use

4. Subjective Norm (SN)

SN1 Most people who are important to me expect me to use Tablet PC

SN2 Most of my friends believe using Tablet PC is a wise decision.

SN3 People whose opinions I valued preferred that I use Tablet PC



TECHNOLOGY (TRAT)5. Optimism (Opti)

OPTI1 Tablet PC gives more control on my daily life

OPTI2 Tablet PCis much more convenient to use

OPTI3 I like the idea of learning via Tablet pc because I am not limited to

manual transactions

OPTI4 I prefer to use the most advanced technology available

OPTI5 I like Tablet PC that allow you to tailor things to fit your own needs

OPTI6 Tablet PC makes you more efficient in your occupation

OPTI7 I find Tablet PC to be mentally stimulating

OPTI8 Tablet PC gives you more freedom of mobility

OPTI9 Learning about technology can be as rewarding as the technology itself

OPTI10 I feel confident that Tablet PC will follow through with what you

instructed them to do

6. Innovativeness (Inn)

INNO1 Other people come to me for advice on Tablet PC

INNO2 It seems my friends are learning more about the Tablet PC than me

INNO3 In general, I am the first among in my circle of friends to acquire

Tablet PC when it appears

INNO4 I can usually figure out Tablet PC without help from others

INNO5 I keep up with the latest technological developments in my areas of

interest

INNO6 I enjoy the challenge of figuring out high-technologies

INNO7 I find i have fewer problems than other people in making technology

work for me

7. Discomfort (Disc)

DISC1 Technical support lines are not helpful because they do not explain

things in terms you understand

DISC2 Sometimes, I think that Tablet PC is not designed for use by ordinary

people

DSIC3 There is no such thing as a manual for a high-tech product or service

that is written in plain language



TECHNOLOGY (TRAT)DSIC4 When i get technical support from a provider of a Tablet PC, in

sometimes i feel as if i being taken advantage of by someone who knows

more than i do

DSIC5 If I useTablet PC,I prefer to have a lot of features

DSIC6 It is embarrassing when I have trouble with a Tablet PCsystem while

people are watching

DSIC7 Tablet PC makes it too easy for teachers to monitor student

performance

DSIC8 Technology always seems to fail at the worst possible time

8. Insecurity (Insc)

INSC1 I do not consider it safe in adopting Tablet PC

INSC2 I do not consider it safe to learn online

INSC3 I worry that information you send over the Internet will be seen by

other people

INSC4 I do not feel confident doing banking with a place that can only be

reached online

INSC5 Any business transaction I do electronically should be confirmed later

with something in writing

INSC6 Whenever something gets automated, I need to check carefully that the

Tablet pc or software is not making mistakes

INSC7 The human touch is very important while transacting throughTablet

PC

INSC8 When I call a business, I prefer to talk to a person rather than a

machine

INSC9 If I am provided information to a machine or over the Internet, I can

never be sure it really gets to right place

9. Behavioural Intention (BI)

BI1 I predict that I will use Tablet PC on a regular basis in the future

BI2 I expect that I will use Tablet PC system, or a similar type of system for

Learning

BI3 I will use Tablet PC in futur



TECHNOLOGY (TRAT)

Table No 7

Descriptive StatisticsN Mean Std.

DeviationVariance Skewness Kurtosis

Statistic

Statistic Statistic Statistic Statistic Std. Error Statistic Std. Error

PU1 201 3.93 .967 .935 -.865 .172 .745 .341

PU2 201 3.96 .976 .953 -.822 .172 .458 .341

PU3 201 4.00 .964 .930 -.811 .172 .207 .341

PU4 201 3.98 .938 .880 -.915 .172 .761 .341

PU5 201 3.99 1.049 1.100 -1.004 .172 .458 .341

ATTI1 201 3.80 1.063 1.130 -.805 .172 .163 .341

ATTI2 201 4.10 1.000 1.000 -1.171 .172 1.129 .341

ATTI3 201 4.11 .976 .952 -1.309 .172 1.801 .341

ATTI4 201 4.00 1.007 1.015 -.879 .172 .353 .341

ATTI5 201 4.00 1.044 1.090 -.985 .172 .554 .341

PEU1 201 4.14 1.025 1.050 -1.352 .172 1.503 .341

PEU2 201 4.05 1.073 1.152 -1.016 .172 .330 .341

PEU3 201 4.07 .982 .965 -.972 .172 .402 .341

PEU4 201 4.18 .985 .971 -1.359 .172 1.692 .341

SN1 201 3.86 1.093 1.194 -.801 .172 -.062 .341

SN2 201 3.94 1.068 1.141 -1.039 .172 .670 .341

SN3 201 3.85 1.043 1.088 -.899 .172 .458 .341

OPTI1 201 3.82 1.154 1.331 -.759 .172 -.356 .341

OPTI2 201 4.02 .985 .970 -.865 .172 .323 .341

OPTI3 201 3.92 1.093 1.194 -.886 .172 .173 .341

OPTI4 201 4.16 1.074 1.155 -1.470 .172 1.634 .341

OPTI5 201 4.01 1.075 1.155 -1.202 .172 1.067 .341

OPTI6 201 3.99 1.015 1.030 -.966 .172 .597 .341

OPTI7 201 3.75 1.145 1.310 -.721 .172 -.262 .341

OPTI8 201 4.08 1.065 1.134 -1.189 .172 .843 .341

OPTI9 201 4.05 .912 .832 -.867 .172 .621 .341

OPTI10 201 4.03 .919 .844 -.969 .172 .837 .341

INNO1 201 3.72 1.221 1.492 -.732 .172 -.408 .341

INNO2 201 3.69 1.215 1.476 -.645 .172 -.531 .341

INNO3 201 3.75 1.196 1.430 -.844 .172 -.100 .341

INNO4 201 3.94 1.125 1.266 -.987 .172 .315 .341

INNO5 201 4.06 1.013 1.026 -1.024 .172 .593 .341



TECHNOLOGY (TRAT)INNO6 201 4.15 .985 .971 -1.328 .172 1.622 .341

INNO7 201 3.77 1.153 1.330 -.836 .172 .029 .341

DISC1 201 3.59 1.218 1.483 -.586 .172 -.630 .341

DISC2 201 3.50 1.257 1.581 -.520 .172 -.714 .341

DISC3 201 3.69 1.079 1.164 -.638 .172 -.197 .341

DISC4 201 3.82 1.145 1.311 -.885 .172 .114 .341

DISC5 201 4.08 1.031 1.064 -1.045 .172 .517 .341

DISC6 201 3.74 1.176 1.383 -.751 .172 -.265 .341

DISC7 201 4.00 1.079 1.165 -1.099 .172 .734 .341

DISC8 201 3.48 1.249 1.561 -.454 .172 -.806 .341

INSC1 201 3.38 1.326 1.758 -.525 .172 -.913 .341

INSC2 201 3.36 1.386 1.921 -.459 .172 -1.033 .341

INSC3 201 3.58 1.189 1.414 -.656 .172 -.424 .341

INSC4 201 3.61 1.157 1.339 -.687 .172 -.318 .341

INSC5 201 3.77 1.034 1.070 -.558 .172 -.275 .341

INSC6 201 3.80 1.142 1.303 -.977 .172 .282 .341

INSC7 201 4.08 1.036 1.074 -1.114 .172 .754 .341

INSC8 201 3.86 1.106 1.224 -.785 .172 -.072 .341

INSC9 201 3.78 1.128 1.272 -.806 .172 .019 .341

BI1 201 4.03 1.012 1.024 -.948 .172 .448 .341

BI2 201 4.07 1.010 1.019 -1.122 .172 .953 .341

BI3 201 4.28 .982 .964 -1.492 .172 1.742 .341



Items Mean Cronbach’s

Alpha

Perceived usefulness (PU)PU1 Using Tablet PC will save my time in Learning 3.93 0.822

PU2 Using Tablet PC would improve my performance in Learning 3.96PU3 Using Tablet PC would improve my productivity in Learning 4.00PU4 Using Tablet PC would improve my effectiveness in Learning 3.98PU5 I find Tablet PC to be useful in Learning 3.99Attitude (ATTI)ATTI1 In my opinion it is desirable to use Tablet PC for learning 3.80 0.807

ATTI2 I think it will be good for me to use Tablet PC for learning 4.10ATTI3 I think learning through Tablet PC is a good idea 4.11ATTI4 Overall, my attitude toward Tablet PC is favourable 4.00ATTI5 Generally speaking, I like the idea of Tablet PC for learning 4.00Perceived Ease of Use (PEU)PEU1 I find Tablet PC easy to use 4.14 0.848

PEU2 Use of Tablet PC is clear and understandable 4.05PEU3 It is easy for me to remember how to perform tasks using Tablet PC 4.07



PEU4 Overall, I find the Tablet PCis easy to use 4.18Subjective Norm (SN)SN1 Most people who are important to me expect me to use Tablet 3.86 0.744

SN2 Most of my friends believe using Tablet PC is a wise decision. 3.94

SN3 People whose opinions I valued preferred that I use Tablet PC 3.85

Optimism (Opti)

OPTI1 Tablet PC gives more control on my daily life 3.82 0.904

OPTI2 Tablet PCis much more convenient to use 4.02OPTI3 I like the idea of learning via Tablet pc because I am not limited to manual

transactions 3.92

OPTI4 I prefer to use the most advanced technology available 4.16OPTI5 I like Tablet PC that allow you to tailor things to fit your own needs 4.01OPTI6 Tablet PC makes you more efficient in your occupation 3.99OPTI7 I find Tablet PC to be mentally stimulating 3.75OPTI8 Tablet PC gives you more freedom of mobility 4.08OPTI9 Learning about technology can be as rewarding as the technology itself 4.05OPTI10 I feel confident that Tablet PC will follow through with what you instructed them to

do 4.03

Innovativeness (Inn)



INNO1 Other people come to me for advice on Tablet PC 3.72 0.798

INNO2 It seems my friends are learning more about the Tablet PC than me 3.69INNO3 In general, I am the first among in my circle of friends to acquire Tablet PC when it

appears 3.75

INNO4 I can usually figure out Tablet PC without help from others 3.94INNO5 I keep up with the latest technological developments in my areas of interest 4.06INNO6 I enjoy the challenge of figuring out high-technologies 4.15INNO7 I find i have fewer problems than other people in making technology work for me 3.77Discomfort (Disc)DISC1 Technical support lines are not helpful because they do not explain things in terms

you understand 3.590.787

DISC2 Sometimes, I think that Tablet PC is not designed for use by ordinary people 3.50DSIC3 There is no such thing as a manual for a high-tech product or service that is written

in plain language 3.69

DSIC4 When i get technical support from a provider of a Tablet PC, in sometimes i feel as if

i being taken advantage of by someone who knows more than i do 3.82

DSIC5 If I useTablet PC,I prefer to have a lot of features 4.08DSIC6 It is embarrassing when I have trouble with a Tablet PCsystem while people are

watching 3.74

DSIC7 Tablet PC makes it too easy for teachers to monitor student performance 4.00



DSIC8 Technology always seems to fail at the worst possible time3.48

Insecurity (INSC)

INSC1 I do not consider it safe in adopting Tablet PC 3.38 0.851

INSC2 I do not consider it safe to learn online 3.36INSC3 I worry that information you send over the Internet will be seen by other people 3.58INSC4 I do not feel confident doing banking with a place that can only be reached online 3.61INSC5 Any business transaction I do electronically should be confirmed later with

something in writing 3.77

INSC6 Whenever something gets automated, I need to check carefully that the Tablet pc or

software is not making mistakes 3.80

INSC7 The human touch is very important while transacting throughTablet PC 4.08INSC8 When I call a business, I prefer to talk to a person rather than a machine 3.86INSC9 If I am provided information to a machine or over the Internet, I can never be sure it

really gets to right place 3.78

Behavioural Intention (BI)

BI1 I predict that I will use Tablet PC on a regular basis in the future 4.03 0.742

BI2 I expect that I will use Tablet PC system, or a similar type of system for Learning 4.07



BI3 I will use Tablet PC in future 4.28



TECHNOLOGY (TRAT)


Research on tablet pc adoption model

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