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 ),BIJAPURMBA-PROGRAMME

Presentation Flow

• Introduction– Consumer behaviour

• Literature Review• Research Gap • Proposed model and development of hypothesis• Proposed Research Methodology• Result • References

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.

“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

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.

Consumer ModelingModel: “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.

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

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.

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.

3. Engel – kollat- ModelThis 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;

4. Bettman’s Information Processing Model of Consumer ChoiceBettman (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.

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:

Literature review

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

technology products

Technology Adoption Models.

Technology Adoption Models (Conti..)

Application Technology adoption models for different technology products

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.

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

• 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.

Proposed Model and Development of Hypothesis

The proposed model conceptualized for the present study

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.

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  

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).

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

• 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).

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.”

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 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.

Limitations and perspectives for future research

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.

References

Thank you..