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

1. Pre-Lancing Report
on
UNDERSTANDING NEW TECHNOLOGY BY ENGINEERING
STUDENTS: APPLICATION OF TECHNOLOGY READINESS
AND ACCEPTING TECHNOLOGY (TRAT)
By
Arun .M. Savukar
Roll No MBA13005
Under the Guidance of
Muragesh Y Pattanshetti
A S PATIL COLLEGE OF COMMERCE (AUTONOMOUS ),BIJAPUR
MBA-PROGRAMME

2. Presentation Flow
• Introduction
– Consumer behaviour
• Literature Review
• Research Gap
• Proposed model and development of hypothesis
• Proposed Research Methodology
• Result
• References

3. Tablet pc Adoption Model
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.

4.  “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

5. The above definition talks about various activities surrounding the
ultimate consumer and helps the marketer to measure 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.

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

7. 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

8. VARIOUS MODELS OF CONSUMER BEHAVIOUR
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.

9. 2. Howard – Sheth model
This model suggests three levels of decision making:
I. The first level describes the extensive problem solving.
II. The second level is limited problem solving.
III. The third level is a habitual response behavior.

10. 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 five stages;

11. 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.

12. 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:

13. Literature review
• The review literature is organized in the following
manner.
– Technology Adoption Models.
– Application Technology adoption models for different
technology products

14. Technology Adoption Models.

15. Technology Adoption Models (Conti..)

16. Application Technology adoption models for different
technology products

17. Summary
 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.

18. Research Gaps
• 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.
• However there remains a scope to understand these models from
the view point of the adoption of emerging technologies like social
networking medium, cloud computing, online recharge of Tablet ,
online purchase of term insurance, direct to home television
services etc.
• Tablet Pc services has received little attention

19. • For the purpose of this study, the scope has been
limited to the adoption of application of Tablet pc
because of the various reasons mentioned in the
introduction section of this report.
• The earlier research studies have so far used a
specific model from the literature like innovation
diffusion, TAM or TAM 2 or TAM 3. Very few
studies have laid emphasis on developing and
validating integrated models.
• There is growing need for developing integrated
models for meaningful investigations and drawing
valid conclusions.

20. Proposed Model and Development of Hypothesis

21. The proposed model conceptualized for the
present study

22. Proposed Research Methodology
• A two phase research methodology is proposed to be
used for the study.
• 1st Phase
– The definitions of the constructs as well as the measurement
items for each construct will be established.
– Tentative indications of reliability and validity
– Item generation, pre-pilot study, and pilot study.
• 2nd Phase
– Propose to further refine this scale and validate the measures
using likert-scale survey data based on the scales developed in
the first phase.

23. Data collection
 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.
Respondents demographic characteristics

24. Result
 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
1 along with the alphas obtained by Parasuraman (2000) in the United States
and Tsikriktsis (2004) in Great 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).

25. 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
Bijapur (karnataka) .93 .86 .64 .64

26. • In out of thirteen, nine of hypotheses were supported. The relationships
between the variables are depicted in Figure 2, 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).

27. 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.”

28. 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 ).

29. • 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). And as per my research also.

30. Limitations and perspectives for future
research

31. Conclusion
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.

32. References

33. Thank you..