Business rerearch survey_analysis__intention to use tablet p_cs among university students

VINOD GUPTA SCHOOL OF MANAGEMENT
IIT KHARAGPUR
Survey on the Intention to use Tablet
PCs among university students
Lecturer: Prof. Kalyan Kumar Guin
Abhitosh Daw (12BM60078), Dev Karan Singh Maletia (12BM60060) ,
Divij Sharma (12BM60046) ,Hitarth Saini (12BM60077), Koyel Dutta (12BM60080)

INDEX
1.0 Introduction......................................................................................................................................4
1.1 Problem Statement...........................................................................................................................4
1.2 Purpose of study...............................................................................................................................4
1.3 Research Objectives..........................................................................................................................5
1.4 Research Questions...........................................................................................................................5
1.5 Definition of Key Variables................................................................................................................6
2.0 Literature Review..............................................................................................................................7
2.1 Innovation Diffusion Theory .............................................................................................................7
2.1.1 Innovation spread successfully through what qualities. ................................................................7
2.1.2 How important are the peer-peer conversations and peer networks. ...........................................7
2.1.3 Understanding the needs of different user segments. ...................................................................8
3.0 Methodology...................................................................................................................................9
3.1 Introduction:.....................................................................................................................................9
3.2 Research design and procedures.......................................................................................................9
3.2.1 Type of study .................................................................................................................................9
3.2.2 Nature of study..............................................................................................................................9
3.2.3 Research Site..................................................................................................................................9
3.3 Sample size and Population ..............................................................................................................9
3.4 Scales and measurement ..................................................................................................................9
3.4.1 Independent variable...................................................................................................................10
3.4.1.1 Relative advantage....................................................................................................................10
3.4.1.2 Compatibility.............................................................................................................................10
3.4.1.3 Image ........................................................................................................................................10
3.4.1.4 Ease of use ................................................................................................................................10
3.4.1.5 Result of Demonstrability .........................................................................................................10
3.4.1.6 Visibility ....................................................................................................................................10
3.4.1.7 Trialability.................................................................................................................................11
3.4.1.8 Innovativeness..........................................................................................................................11
3.4.1.9 Attitude.....................................................................................................................................11
3.4.2 Dependent Variable.....................................................................................................................11
3.4.2.1 Intention of use.........................................................................................................................11
3.5 Questionnaire Design......................................................................................................................11
3.6 Data collection method...................................................................................................................12
3.7 Statistical Data Analysis..................................................................................................................12
3.7.1 Goodness and correctness of data entry......................................................................................12
3.7.2 Validity and reliability..................................................................................................................13
3.7.3 Descriptive analysis......................................................................................................................13
3.7.4 Regression Analysis......................................................................................................................13
4.0 Data Analysis ..................................................................................................................................14
4.1 Introduction....................................................................................................................................14
4.2 Data Profile.....................................................................................................................................14
4.3 Goodness of measure .....................................................................................................................14
4.3.1 Reliability of measurement..........................................................................................................14
4.3.2 Descriptive statistics ....................................................................................................................21
4.4 Hypotheses testing .........................................................................................................................22

4.4.1 Multiple Regression .....................................................................................................................23
4.4.2 Residual & outlier analysis...........................................................................................................26
4.4.3 Profiling........................................................................................................................................29
5.0 Summary.........................................................................................................................................33
5.1 Limitations......................................................................................................................................33
5.2 Conclusion.......................................................................................................................................33

1.0 Introduction
Introduction to Tablet PCs
A tablet PC is a personal computer which is portable equipped with wireless access and touch screen
and offers the users the advantage of mobility and ease. It is smaller than a notebook computer but
larger than the biggest smart phone. Convertible styles are those in which it is available in the market
are convertible, slate, hybrid and rugged. In some styles it allows users to input just as if they are
writing in their own handwriting in a notebook through a digital pen.
A slate tablet is one which is integrated in the touch screen unit but lacks a hardware keyboard.
Hybrid tablets are similar to regular notebooks but with removable display functions. Rugged tablets
are designed to withstand rough handling and extreme conditions.
Due to technological development like wireless internet access, display resolution and handwriting
recognition in software, it has been a good combination of hardware and software in a tablet PC
which enables users to get a rich, interactive, and productive computing experience. The ease of use
and low hardware requirements of a tablet PC has made it a product subject to various studies and
design for use in various developing countries while at the same time helping reduce the digital gap.
Tablet PCs nowadays are widely used for learning across a variety of undergraduate and graduate
studies. However its impact on learning whether positive or negative is still not clearly defined.
Since tablet PCs have become more and more popular, the goal of this study is to investigate student’s
intention to use such devices.
1.1 Problem Statement
The usage of tablet PCs is on the rise recently. New models are being introduced with better
performances and features and consequently the demand for Tablet PCs has risen multifold.
The introduction of Tablet PC has brought about a paradigm shift towards consumer’s computing
behavior. Our research is focused on university students. Hence our research problem is
“what leads to consumer’s intention to use Tablet PCs, in particular university students?”
1.2 Purpose of study
In terms of education, this study intends to enable students to understand that the tablet PC is a
gadget of many functions. The results of the study can be used by the higher officials in the University
to encourage switching from the traditional notebook to the tablet PC as it is very useful tool for
studies. It can be used as an interactive tool with the lecturers during lessons.
The study would enable us students to be in touch with current technology gadgets. It is important to
be in touch with the current flow of technology as the latest technology gadgets are giving more
mobility. Besides, technology gadgets such as the Tablet PC are made of many functions. Then
students’ personal and professional productivity will increase. The Tablet PC can be used any time, at
home, at work, in a bus or even away on a holiday. Hence understanding the importance of the tablet
PC will enable students to purchase a Tablet PC for those who don’t have one and it would increase
efficiency in the area of study for those who have it.

1.3 Research Objectives
The research objective can be separated into primary objective and other objectives. The primary
objective is to understand and investigate the university student’s intention of using Tablet PC.
Other objectives are to evaluate determinants of intention of Tablet PC usage and attempt to find out
causal relationship.
1.4 Research Questions
In order to achieve the objectives mentioned, the study attempted to answer the following question:-
• What are the key factors influencing intention of students to use Tablet PC?
• What are the relationships among ten variables towards the usage of Tablet PC?
(1) Relative Advantage
(2) Compatibility
(3) Image
(4) Ease of Use
(5) Result Demonstrability
(6) Visibility
(7) Trialability
(8) Innovativeness
(9) Attitude
(10) Intent of using Tablet PC

1.5 Definition of Key Variables
Key Terms Definition
Relative Advantage It stands for an advantage of new products to
customers over the competing brands. It also
relates to the prospective customer perception on
adapting new offering products depending on
relative advantage.
Compatibility Assimilation of individual life and innovation for
the level of compatibility.
Image Image often related with brands. Consumer’s mind
towards a brand personality which includes its
quality and shows how impressive the image is.
Also, image may be developed over time through
marketing and deteriorate if there is lack of
advertisement and other factors.
Ease of Use Artificially made object usability. It indicates
whether a product or property may be used by the
user without much overcoming the steep of
learning curve.
Result Demonstrability Product demonstrability shown by result.
Capability of being proved by experiments,
through lab or some other ways.
Visibility It means the result of an innovation such as is
observable to others.
Trialability Trialed and modified results of innovation.
Innovativeness Modified, changed, enhanced, from original
products to new ideas.
Attitude The feeling associated with adopting the new
product regardless of the present scenario of
affordability.
Intent of Using The readiness of using the product if available.

2.0 Literature Review
2.1 Innovation Diffusion Theory
This theory explains how, why, and what level of rate new ideas and technology are influenced by
cultures. The three major valuable insights in the process of social change are:
• Innovation spreads successfully through what qualities.
• How important are the peer-peer conversations and peer networks.
• What are the needs of different user segments?
2.1.1 Innovation spread successfully through what qualities.
It sees changes primarily as evolution so the product becomes better fit for the needs of individuals
and groups. The pace of changes, success or failure in changes is determined by five qualities.
1. Relative Advantage
The greater the perceived relative advantage of innovation, the more rapid the adaptation is
likely to be. For example, the better the idea (economic advantage, social prestige, convenience
or satisfaction) is superseded by the users the more rapid is the adoption likely to happen.
2. Existing Values and Practices Compatibility
It explains how the innovation is perceived as being consistent with the values, past
experiences, and the need of the potential adopters. Incompatible values, norms or practices
will not be adopted as rapid as compatible innovation.
3. Simplicity and Ease of use
It explains understanding and use of innovation which is perceived. Newer ideas that are simpler
to understand are adopted more rapidly than innovations which are more complicated.
4. Trial ability
It explains can experiment be done on innovation through limited basis. Trial able innovation
means higher certainty to the individual who is considering it.
5. Observable Results
The harder the individuals view the results of the innovation, the harder they adopt it.
These five qualities help identify weakness to improve products or behaviors.
2.1.2 How important are the peer-peer conversations and peer networks.
The second insight is that impersonal marketing methods spread information about new innovation
and conversations spread adoption.
This happens because the adoption of new products involves management risk and uncertainty. Close
people like family and friends that we trust give us credible reassurances.
Face to face communications becomes more influential and mass media becomes less as innovation
spreads from early adopters to majority audience.

2.1.3 Understanding the needs of different user segments.
Experts believe that population propensity to adopt a specific innovation can be broken into:
1. Innovators
2. Early Adopters
3. Early Majorities
4. Late majorities
5. Laggards

3.0 Methodology
3.1 Introduction:
The methodology mainly describes the progress and steps of our study on the research problems. This
part will include research design and procedures, variables and measurement, data collection
methods, questionnaire design and data analysis.
3.2 Research design and procedures
3.2.1 Type of study
Here we have followed the correlation study. It mainly focuses on university students’ intention on
using Tablet PCs. Hypothesis testing is used to find the relationship between the variables.
3.2.2 Nature of study
This study was conducted in the natural environment. The variables have not been manipulated. The
data for this study was collected in a span of 1 week from respondents in different colleges.
3.2.3 Research Site
The unit of analysis is the students from different universities across India and some foreign
universities.
3.2.4 Research Site
The research site includes the universities in India and abroad.
3.3 Sample size and Population
The population is the students who have the intention to use the tablet PCs. The general rule,
minimum number of respondents or sample size is five to one ratio of the number of independent
variables to be analyzed. The list of users of tablet PCs cannot be obtained therefore probability
sampling could not be done.
3.4 Scales and measurement
The survey form is divided into two main sections.
The first section is where the respondents need to tick on a five point scale with the following level of
agreement or disagreement to given statements in the survey form:

Strongly agree – 5
Agree – 4
Neutral – 3
Disagree – 2
Strongly Disagree – 1
The first section is further broken down into 10 parts each with a topic related to its statements. The
second section is the personal profile required by the respondents. The section is measured using a
nominal scale.
3.4.1 Independent variable
It is manipulated by the researcher which causes an effect on the dependent variable.
3.4.1.1 Relative advantage
It was measured on four items using a five point scale ranging from “strongly disagree” to “strongly
agree”.
3.4.1.2 Compatibility
It was measured on three items using a five point scale ranging from “strongly disagree” to “strongly
agree”.
3.4.1.3 Image
agree”.
3.4.1.4 Ease of use
It was measured using a five point scale ranging from “strongly disagree” to “strongly agree”. Example
“using a tablet PC will require a lot of mental effort”.
3.4.1.5 Result of Demonstrability
agree”. Example “I believe I can communicate the pros and cons of a tablet PC to others”.
3.4.1.6 Visibility
agree”. Example “It is easy for me to see others using a tablet PC”.

3.4.1.7 Trialability
agree”. Example “I want to try out various applications of a tablet PC”.
3.4.1.8 Innovativeness
It was measured on six items using a five point scale ranging from “strongly disagree” to “strongly
agree”. Example “I am among the first of my friends to acquire the new technology”.
3.4.1.9 Attitude
agree”. Example “using a tablet PC would be a pleasant experience”.
3.4.2 Dependent Variable
It is measured, predicted or otherwise monitored and is expected to be effected by the manipulation
of an independent variable.
3.4.2.1 Intention of use
agree”. Example “Whenever possible, I intend to use the tablet PC”.
3.5 Questionnaire Design
The questionnaire is designed to measure the university students’ intention to use the tablet PC. It
uses 9 constructs to do the same. Below, the figure gives the description of the constructs used in the
questionnaire. This questionnaire contains a total of 39 questions. The survey also contains
clarification questions.

3.6 Data collection method
The measurement questions in the questionnaire served to collect the student’s responses toward
their intention to use the tablet PCs. Participation in this survey is completely voluntary.
3.7 Statistical Data Analysis
The data collected was analyzed and coded using SPSS software version 16. The data was then
summarized through appropriate descriptive and inferential analysis.
3.7.1 Goodness and correctness of data entry
Goodness and correctness of the data can be tested using the reliability and validity of the analysis
and findings. It ensures credibility of all the data and the results. It is tested by calculating the mean,
median, range, variance and standard deviation in the data collected from the standard questionnaire.
By this, respondents’ reaction can be checked and provide us the clear idea.

3.7.2 Validity and reliability
Validity and reliability are required to measure the goodness of measures. Reliability analysis is used
to test the internal consistency among the items and validity of the overall scales. Validity is the extent
to which a scale fully and unambiguously captures the underlying unobservable construct it is
intended to measure.
3.7.3 Descriptive analysis
It is useful for any further statistical analysis. This analysis aims to provide an overview of the
respondents and the understanding of theory behavioral patterns. It involves range and frequency,
count and relationships among the variables.
3.7.4 Regression Analysis
Regression analysis is best applied to analyze the effect of two or more independent variables on a
single scaled dependent variable. There are several important issues considered as most suitable
assumption to incorporate the test.
1. Normality
Normality was measured using histogram and normality distribution. The normality requirement
must be met only if the histogram shows the resemblance to a bell curve.
2. Homoscedasticity
Homoscedasticity happens when the constant regression model produce error variances. It means
that the error variances are all similar for all level of independent variables.
3. Independence of error term
It indicates the independent predicted values of other predicted variables.
4. Multicollinearity
It will be used when two or more independent variables in a multiple regression model are highly
correlated. When Variance Inflation Factor (VIF) value falls below 10 and 30 for conduction index,
it indicates that there are no multicollinearity issues.
5. Outliers
Outlier in a regression can be observed by using case wise diagnostic. The standard value that falls
above of 2.50 shall be dropped.

4.0 Data Analysis
4.1 Introduction
Based on the survey data submitted by the respondents, the result of the study has been analyzed
Hypothesis Testing, ANOVA, Reliability Analysis, Multiple regression and factor analysis.
4.2 Data Profile
Key observations from the survey data collected:
• There are total 83 respondents, out of which there are majority of male respondents; 60 males
and 23 females.
• The respondents were mostly Indians along with few Chinese and Malaysian.
• The average age of the respondents is 24.3 years and expectedly so since most of the
respondents were students, the objective of the analysis being studying the Intention of use of
Tablet PC among students.
• Precisely 45 of the respondents are pursuing Masters, next highest is the number pursuing
Bachelors degree ( 24 ) while there are 7 PHD students.
• The students are pursuing varied courses like Engineering, MBA, Social Sciences, Arts and
Fashion Designing etc.
• Most of the respondents (73 out of 83) surveyed have access to Internet.
An important observation from the responses collected is that, the sample of the students have very
high usage of internet with 34 of the 83 respondents using internet for more than 3 hours per day
while other 34 use internet from 1-3 hours.
4.3 Goodness of measure
4.3.1 Reliability of measurement
All the data collected for the survey was tested for reliability. The purpose of reliability test is to
determine whether the variables represent the whole research framework. In our research we are
interested to examine the extent to which relative advantage, compatibility, image etc., are related to
the intent of using a tablet PC among the university student. Cronbach’s Alpha was used to test the
reliability of all the variables in the survey. According to Nunally, Cronbach’s alpha value greater than
0.7 is considered reliable. In our findings in the tables given below all alpha values are greater than 0.7
hence none of the items is deleted from the study.

Variables Cronbach's Alpha
Total
Item
Items
deleted
Relative Advantage 0.95 4 -
Compatibility 0.911 3 -
Image 0.858 3 -
Ease of Use 0.514 4 -
Result demonstrability 0.88 4 -
Visibility 0.897 3 -
Trialability 0.896 4 -
Innovativeness 0.918 6 -
Attitude 0.946 4 -
Intent 0.921 4 -
Reliability Analysis of Relative advantage
Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.950 .950 4
Item-Total Statistics
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v2 10.93 9.922 .843 .718 .945
v3 10.87 9.702 .878 .785 .934
v4 10.89 9.561 .902 .813 .927
v5 10.83 10.118 .893 .803 .930

Reliability Analysis of Compatibility
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.910 .911 3
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v6 6.81 4.255 .826 .700 .867
v7 6.92 4.200 .785 .619 .901
v8 6.83 4.093 .851 .732 .845
Reliability Analysis of Image
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.858 .859 3
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v9 6.88 4.595 .663 .466 .867
v10 6.83 3.996 .817 .680 .717
v11 6.65 4.718 .726 .593 .809

Reliability Analysis of Ease of use
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.514 .585 4
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v12 10.35 5.157 .406 .538 .358
v13 11.27 7.490 -.159 .117 .855
v14 10.36 4.331 .634 .549 .142
v15 10.31 4.169 .646 .651 .116
----------------After removing v13---------------
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.855 .855 3
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v12 7.52 3.765 .676 .485 .845
v14 7.53 3.667 .706 .542 .817
v15 7.48 3.277 .805 .650 .721

Reliability Analysis of Result Demonstration
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.880 .880 4
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v16 10.67 7.393 .755 .618 .839
v17 10.73 7.222 .810 .685 .818
v18 10.76 7.551 .707 .521 .858
v19 10.95 7.900 .688 .541 .865
Reliability Analysis of Visibility
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.897 .898 3
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v20 7.04 3.743 .810 .670 .844
v21 7.10 3.869 .832 .697 .822
v22 7.12 4.449 .757 .576 .888

Reliability Analysis of Trial ability
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.896 .896 4
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v23 11.30 8.115 .786 .639 .860
v24 11.34 7.714 .788 .674 .859
v25 11.35 7.767 .798 .656 .855
v26 11.23 8.471 .708 .536 .888
Reliability Analysis of Innovativeness
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.918 .919 6

Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v27 17.25 22.411 .742 .581 .907
v28 17.57 21.980 .736 .579 .908
v29 17.12 21.107 .873 .786 .888
v30 17.18 21.784 .793 .681 .900
v31 17.22 23.123 .701 .557 .912
v32 17.22 23.099 .768 .653 .904
Reliability Analysis of Attitude towards using tablet PCs
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.946 .947 4
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v33 11.29 9.062 .825 .695 .944
v34 11.11 9.000 .876 .771 .928
v35 11.29 8.354 .895 .829 .923
v36 11.17 8.825 .891 .830 .924

Reliability Analysis of Intent of using tablet PCs
Cronbach's Alpha
Cronbach's Alpha
Based on
Standardized
Items N of Items
.921 .921 4
Scale Mean if Item
Deleted
Scale Variance if
Item Deleted
Corrected Item-
Total Correlation
Squared Multiple
Correlation
Cronbach's Alpha
if Item Deleted
v37 11.36 8.356 .820 .726 .897
v38 11.49 8.838 .792 .719 .907
v39 11.28 8.178 .861 .807 .883
v40 11.30 8.481 .801 .767 .904
4.3.2 Descriptive statistics
The overall descriptive statistics of the variables is given below in the attached table. All variables were
measured on a 5 point Likert scale forming a continuum from 1 being strongly disagree on one end to 5
being strongly agree at the other end.
Descriptive Statistics
N Mean Std. Deviation Variance
mode_RA 83 3.63 .959 .920
mode_Compatibility 83 3.42 1.049 1.100
mode_Image 83 3.47 1.016 1.033
mode_Ease 83 3.64 .995 .990
mode_Demo 83 3.57 1.002 1.005
mode_visibility 83 3.47 .954 .911
mode_Trialability 83 3.87 1.021 1.043
mode_Innovation 83 3.41 1.169 1.367
mode_Aattitude 83 3.66 1.015 1.031
mode_Intent 83 3.83 .948 .898
Valid N (listwise) 83

4.4 Hypotheses testing
Pearson product moment correlation was used to study the inter correlation amongst all variables in
this study. The table below provides the summary of the findings:

From the table above we can demonstrate that there is very high degree of association among all
variables because almost all variables show positive variables which are very significant at 0.01 levels
(2- tailed). However the Image only shows positive correlation with Ease of use by the value 0.279 at
0.05 levels (2-tailed). In overall, there is a very strong correlation between all the variables in the
survey.
4.4.1 Multiple Regression
Variable
Standardized
beta
Relative Advantage 0.071
Compatibility 0.257
Image 0.064
Ease of Use -0.055
Result demonstrability 0.045
Visibility -0.045
Trialability 0.389
Innovativeness 0.107
Attitude 0.148
Multiple Regression has been used to investigate the study which is to analyze and test the
relationship between relative advantage, compatibility, Image, ease of use, result, visibility, trial
ability, innovativeness and attitude toward the intention to use tablet PC. The hypotheses tested are
as follows:
1. H1 : Relative advantage of an innovation is positively related to its adoption
2. H2 : Compatibility of an innovation is positively related to its adoption
3. H3 : Positive image of an innovation is positively related to its adoption
4. H4 : Ease of use of an innovation is positively related to its adoption
5. H5 : Result demonstrability an innovation is positively related to its adoption
6. H6 : Visibility of an innovation is positively related to its adoption
7. H7 : Trial ability of an innovation is positively related to its adoption
8. H8 : Innovativeness of an innovation is positively related to its adoption
9. H9 : Attitude towards an innovation is positively related to its adoption

The output from regression analysis indicate that R squared value equals 0.63 which means
approximately 63% variation of intention to use tablet PCs was influenced by relative advantage,
image, attitude, ease of use, innovativeness etc., The adjusted R squared value is 0.585.
Besides, Durbin Watson shows a value in the acceptable range of 1.5 – 2.5 so there is no
autocorrelation of error terms. However from the ANOVA table, we can know that the model is fit as
the variables were tested significant (p<0.01) with F value equals to 13.835.
In overall, as the assumption is fulfilled, there are only two hypotheses that are accepted H2 & H7
which relate Compatibility & trail-ability to the intent of using a tablet PC. These variables provide
positive values of Beta (0.257 for Compatibility & for 0.389 Trial-ability) at acceptable p<0.05. Other
hypotheses are rejected due to non significance.

Hypotheses
Result
Significant
level
beta
Values
H1 Rejected 0.668 0.071
H2 Accepted 0.032 0.257
H3 Rejected 0.512 0.064
H4 Rejected 0.701 -0.055
H5 Rejected 0.771 0.045
H6 Rejected 0.71 -0.045
H7 Accepted 0 0.389
H8 Rejected 0.35 0.107
H9 Rejected 0.28 0.148
The hypotheses H2 (Compatibility) and H7 (trial ability) are Accepted since the significant levels are
less than 0.05 and the corresponding Beta values, 0.257 & 0.389 are non-negative.

Coefficients
a
Model
Unstandardized Coefficients
Standardized
Coefficients
T Sig.B Std. Error Beta
1 (Constant) .570 .348 1.637 .106
mode_RA .070 .163 .071 .430 .668
mode_Compatibility .232 .106 .257 2.188 .032
mode_Image .060 .091 .064 .659 .512
mode_Ease -.052 .136 -.055 -.386 .701
mode_Demo .043 .146 .045 .292 .771
mode_visibility -.044 .119 -.045 -.374 .710
mode_trail .361 .098 .389 3.693 .000
mode_innovation .087 .093 .107 .940 .350
mode_attitude .138 .127 .148 1.089 .280
a. Dependent Variable: mode_intent
4.4.2 Residual & outlier analysis
Standard residuals that have values outside [-3, 3] can be problematic. From our analysis, no case
represents those values hence no outliers are identified in the given data.
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 1.46 5.04 3.83 .752 83
Residual -1.101 1.113 .000 .576 83
Std. Predicted Value -3.147 1.605 .000 1.000 83
Std. Residual -1.803 1.823 .000 .944 83

Casewise Diagnostics
a
Case
Number Std. Residual mode_intent Predicted Value Residual
1 .240 4 3.85 .146
2 -.304 2 2.19 -.185
3 1.245 4 3.24 .760
4 1.041 4 3.36 .636
5 -1.145 3 3.70 -.699
6 -1.399 3 3.85 -.854
7 1.257 5 4.23 .768
8 -.238 4 4.15 -.145
9 .681 4 3.58 .416
10 -1.649 3 4.01 -1.007
11 -.381 4 4.23 -.232
12 1.341 4 3.18 .819
13 -.602 4 4.37 -.368
14 .445 5 4.73 .272
15 -.296 4 4.18 -.180
16 .573 4 3.65 .350
17 -.238 4 4.15 -.145
18 1.273 4 3.22 .777
19 -1.481 4 4.90 -.904
20 1.059 4 3.35 .646
21 .990 5 4.40 .605
22 1.171 5 4.28 .715
23 -.557 4 4.34 -.340
24 -.557 4 4.34 -.340
25 .314 5 4.81 .192
26 .314 5 4.81 .192
27 -1.803 3 4.10 -1.101
28 .480 4 3.71 .293

29 -1.453 2 2.89 -.887
30 1.823 4 2.89 1.113
31 .751 4 3.54 .459
32 .657 4 3.60 .401
33 1.259 5 4.23 .769
34 .880 5 4.46 .537
35 -.862 3 3.53 -.527
36 -1.269 2 2.77 -.775
37 -.238 4 4.15 -.145
38 -.168 4 4.10 -.103
39 -.478 4 4.29 -.292
40 -.759 1 1.46 -.464
41 1.744 5 3.94 1.065
42 -.585 2 2.36 -.357
43 -.534 4 4.33 -.326
44 -.759 1 1.46 -.464
45 -1.758 2 3.07 -1.074
46 -.843 2 2.51 -.515
47 -.693 4 4.42 -.423
48 .157 5 4.90 .096
49 -.238 4 4.15 -.145
50 -.585 2 2.36 -.357
51 1.000 4 3.39 .610
52 -.064 5 5.04 -.039
53 -.308 4 4.19 -.188
54 .014 4 3.99 .008
55 -.238 4 4.15 -.145
56 .240 4 3.85 .146
57 -.304 2 2.19 -.185
58 1.245 4 3.24 .760
59 1.041 4 3.36 .636
60 -1.145 3 3.70 -.699
61 -1.399 3 3.85 -.854
62 1.257 5 4.23 .768

63 -.238 4 4.15 -.145
64 .681 4 3.58 .416
65 -1.649 3 4.01 -1.007
66 -.381 4 4.23 -.232
67 1.341 4 3.18 .819
68 -.602 4 4.37 -.368
69 .445 5 4.73 .272
70 -.296 4 4.18 -.180
71 .573 4 3.65 .350
72 -.238 4 4.15 -.145
73 1.273 4 3.22 .777
74 -1.481 4 4.90 -.904
75 1.059 4 3.35 .646
76 .990 5 4.40 .605
77 1.171 5 4.28 .715
78 -.557 4 4.34 -.340
79 -.557 4 4.34 -.340
80 .314 5 4.81 .192
81 .314 5 4.81 .192
82 -1.803 3 4.10 -1.101
83 .480 4 3.71 .293
4.4.3 Profiling
While studying the correlation between various personal details like Age, Gender, Program, CGPA,
In/Out of campus, Average internet usage etc.,
We found that various characteristics are not correlated to the intent except for two factors of the
respondent profile:
1) Which program is the respondent pursuing?
2) Whether the respondent lives inside or outside the campus?

Program – Bachelors / Masters / PhD
Model Summary
Model R R Square Adjusted R Square
Std. Error of the
Estimate
1 .852a
.726 .723 .499
a. Predictors: (Constant), v6
Coefficientsa
Model
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) 5.504 .127 43.460 .000
v6 -1.147 .078 -.852 -14.650 .000
Hence we see that the R value is high at 0.852 for the regression model. V6 (Program of respondent)
is negatively correlated to intent of using tablet PC which signifies that bachelor’s degree students (1)
have more intent of using a tablet PC & the PhD students(3) have the least intent. This may be
because bachelor degree students are more tech savvy in general & are interested in latest
technological developments. This may also be due to peer pressure & need for access to social media
through tablet PCs etc.
In campus / Outside campus
Model Summary
Model R R Square Adjusted R Square
Std. Error of the
Estimate
1 .798a
.637 .633 .574
a. Predictors: (Constant), v9

Coefficients
a
Model
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) 6.419 .226 28.405 .000
v9 -2.310 .194 -.798 -11.925 .000
Hence we see that the R value is high at 0.798 for the regression model. V9 (Residence inside/outside
hostel) is negatively correlated to intent of using tablet PC which signifies that students living inside
(1) have more intent of using a tablet PC & the students staying outside (2) have the least intent. This
may be due to reasons like availability of free Wi-Fi inside campus & better internet infrastructure.
Plots from regression analysis: Histogram & P-P plot of residual

5.0 Summary
5.1 Limitations
Even though this study has provided useful information about the factors influencing the decision to
use tablet PC, there are some limitations that were faced while completing the research.
Since the entire empirical study is based on data submitted by the respondents, it is of utmost
importance that all respondents fill the survey diligently. However, as is the case, individuals do not
always express the feelings truly and fully.
Secondly, number of respondents or sample size is always an important factor in survey based
research. Since the sample size is 83, drawing generalized conclusions based on these sample
responses is always risky.
5.2 Conclusion
Tablet PC is a technological gadget whose popularity is rising, especially among the tech-savvy
youth. The Innovation Diffusion Theory ( IDT ) provides means to identify intentions to use tablet PC
and determine the most likely factors influencing this. Our findings suggest that among students,
Compatibility and Trial-ability are the two main factors that influence the buying of tablet PCs
among the students. Thus the creators and the marketers might also get an hint on their target
segments, sales and promotion strategies and for raising sell of tablet PCs. The present study might
pave way for more extensive future study on this topic using other variables and determinants.

Business rerearch survey_analysis__intention to use tablet p_cs among university students

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