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Business rerearch  survey_analysis__intention to use tablet p_cs among university students Business rerearch survey_analysis__intention to use tablet p_cs among university students Document Transcript

  • VINOD GUPTA SCHOOL OF MANAGEMENTIIT KHARAGPURSurvey on the Intention to use TabletPCs among university studentsLecturer: Prof. Kalyan Kumar GuinAbhitosh Daw (12BM60078), Dev Karan Singh Maletia (12BM60060) ,Divij Sharma (12BM60046) ,Hitarth Saini (12BM60077), Koyel Dutta (12BM60080)
  • INDEX1.0 Introduction......................................................................................................................................41.1 Problem Statement...........................................................................................................................41.2 Purpose of study...............................................................................................................................41.3 Research Objectives..........................................................................................................................51.4 Research Questions...........................................................................................................................51.5 Definition of Key Variables................................................................................................................62.0 Literature Review..............................................................................................................................72.1 Innovation Diffusion Theory .............................................................................................................72.1.1 Innovation spread successfully through what qualities. ................................................................72.1.2 How important are the peer-peer conversations and peer networks. ...........................................72.1.3 Understanding the needs of different user segments. ...................................................................83.0 Methodology...................................................................................................................................93.1 Introduction:.....................................................................................................................................93.2 Research design and procedures.......................................................................................................93.2.1 Type of study .................................................................................................................................93.2.2 Nature of study..............................................................................................................................93.2.3 Research Site..................................................................................................................................93.3 Sample size and Population ..............................................................................................................93.4 Scales and measurement ..................................................................................................................93.4.1 Independent variable...................................................................................................................103.4.1.1 Relative advantage....................................................................................................................103.4.1.2 Compatibility.............................................................................................................................103.4.1.3 Image ........................................................................................................................................103.4.1.4 Ease of use ................................................................................................................................103.4.1.5 Result of Demonstrability .........................................................................................................103.4.1.6 Visibility ....................................................................................................................................103.4.1.7 Trialability.................................................................................................................................113.4.1.8 Innovativeness..........................................................................................................................113.4.1.9 Attitude.....................................................................................................................................113.4.2 Dependent Variable.....................................................................................................................113.4.2.1 Intention of use.........................................................................................................................113.5 Questionnaire Design......................................................................................................................113.6 Data collection method...................................................................................................................123.7 Statistical Data Analysis..................................................................................................................123.7.1 Goodness and correctness of data entry......................................................................................123.7.2 Validity and reliability..................................................................................................................133.7.3 Descriptive analysis......................................................................................................................133.7.4 Regression Analysis......................................................................................................................134.0 Data Analysis ..................................................................................................................................144.1 Introduction....................................................................................................................................144.2 Data Profile.....................................................................................................................................144.3 Goodness of measure .....................................................................................................................144.3.1 Reliability of measurement..........................................................................................................144.3.2 Descriptive statistics ....................................................................................................................214.4 Hypotheses testing .........................................................................................................................22
  • 4.4.1 Multiple Regression .....................................................................................................................234.4.2 Residual & outlier analysis...........................................................................................................264.4.3 Profiling........................................................................................................................................295.0 Summary.........................................................................................................................................335.1 Limitations......................................................................................................................................335.2 Conclusion.......................................................................................................................................33 View slide
  • 1.0 IntroductionIntroduction to Tablet PCsA tablet PC is a personal computer which is portable equipped with wireless access and touch screenand offers the users the advantage of mobility and ease. It is smaller than a notebook computer butlarger than the biggest smart phone. Convertible styles are those in which it is available in the marketare convertible, slate, hybrid and rugged. In some styles it allows users to input just as if they arewriting 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 tabletsare designed to withstand rough handling and extreme conditions.Due to technological development like wireless internet access, display resolution and handwritingrecognition in software, it has been a good combination of hardware and software in a tablet PCwhich enables users to get a rich, interactive, and productive computing experience. The ease of useand low hardware requirements of a tablet PC has made it a product subject to various studies anddesign 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 graduatestudies. 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’sintention to use such devices.1.1 Problem StatementThe usage of tablet PCs is on the rise recently. New models are being introduced with betterperformances 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 computingbehavior. 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 studyIn terms of education, this study intends to enable students to understand that the tablet PC is agadget of many functions. The results of the study can be used by the higher officials in the Universityto encourage switching from the traditional notebook to the tablet PC as it is very useful tool forstudies. 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 tobe in touch with the current flow of technology as the latest technology gadgets are giving moremobility. Besides, technology gadgets such as the Tablet PC are made of many functions. Thenstudents’ personal and professional productivity will increase. The Tablet PC can be used any time, athome, at work, in a bus or even away on a holiday. Hence understanding the importance of the tabletPC will enable students to purchase a Tablet PC for those who don’t have one and it would increaseefficiency in the area of study for those who have it. View slide
  • 1.3 Research ObjectivesThe research objective can be separated into primary objective and other objectives. The primaryobjective 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 outcausal relationship.1.4 Research QuestionsIn 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 VariablesKey Terms DefinitionRelative Advantage It stands for an advantage of new products tocustomers over the competing brands. It alsorelates to the prospective customer perception onadapting new offering products depending onrelative advantage.Compatibility Assimilation of individual life and innovation forthe level of compatibility.Image Image often related with brands. Consumer’s mindtowards a brand personality which includes itsquality and shows how impressive the image is.Also, image may be developed over time throughmarketing and deteriorate if there is lack ofadvertisement and other factors.Ease of Use Artificially made object usability. It indicateswhether a product or property may be used by theuser without much overcoming the steep oflearning 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 isobservable to others.Trialability Trialed and modified results of innovation.Innovativeness Modified, changed, enhanced, from originalproducts to new ideas.Attitude The feeling associated with adopting the newproduct regardless of the present scenario ofaffordability.Intent of Using The readiness of using the product if available.
  • 2.0 Literature Review2.1 Innovation Diffusion TheoryThis theory explains how, why, and what level of rate new ideas and technology are influenced bycultures. 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 individualsand groups. The pace of changes, success or failure in changes is determined by five qualities.1. Relative AdvantageThe greater the perceived relative advantage of innovation, the more rapid the adaptation islikely to be. For example, the better the idea (economic advantage, social prestige, convenienceor satisfaction) is superseded by the users the more rapid is the adoption likely to happen.2. Existing Values and Practices CompatibilityIt explains how the innovation is perceived as being consistent with the values, pastexperiences, and the need of the potential adopters. Incompatible values, norms or practiceswill not be adopted as rapid as compatible innovation.3. Simplicity and Ease of useIt explains understanding and use of innovation which is perceived. Newer ideas that are simplerto understand are adopted more rapidly than innovations which are more complicated.4. Trial abilityIt explains can experiment be done on innovation through limited basis. Trial able innovationmeans higher certainty to the individual who is considering it.5. Observable ResultsThe 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 innovationand conversations spread adoption.This happens because the adoption of new products involves management risk and uncertainty. Closepeople like family and friends that we trust give us credible reassurances.Face to face communications becomes more influential and mass media becomes less as innovationspreads 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. Innovators2. Early Adopters3. Early Majorities4. Late majorities5. Laggards
  • 3.0 Methodology3.1 Introduction:The methodology mainly describes the progress and steps of our study on the research problems. Thispart will include research design and procedures, variables and measurement, data collectionmethods, questionnaire design and data analysis.3.2 Research design and procedures3.2.1 Type of studyHere we have followed the correlation study. It mainly focuses on university students’ intention onusing Tablet PCs. Hypothesis testing is used to find the relationship between the variables.3.2.2 Nature of studyThis study was conducted in the natural environment. The variables have not been manipulated. Thedata for this study was collected in a span of 1 week from respondents in different colleges.3.2.3 Research SiteThe unit of analysis is the students from different universities across India and some foreignuniversities.3.2.4 Research SiteThe research site includes the universities in India and abroad.3.3 Sample size and PopulationThe 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 independentvariables to be analyzed. The list of users of tablet PCs cannot be obtained therefore probabilitysampling could not be done.3.4 Scales and measurementThe 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 ofagreement or disagreement to given statements in the survey form:
  • Strongly agree – 5Agree – 4Neutral – 3Disagree – 2Strongly Disagree – 1The first section is further broken down into 10 parts each with a topic related to its statements. Thesecond section is the personal profile required by the respondents. The section is measured using anominal scale.3.4.1 Independent variableIt is manipulated by the researcher which causes an effect on the dependent variable.3.4.1.1 Relative advantageIt was measured on four items using a five point scale ranging from “strongly disagree” to “stronglyagree”.3.4.1.2 CompatibilityIt was measured on three items using a five point scale ranging from “strongly disagree” to “stronglyagree”.3.4.1.3 ImageIt was measured on three items using a five point scale ranging from “strongly disagree” to “stronglyagree”.3.4.1.4 Ease of useIt 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 DemonstrabilityIt was measured on four items using a five point scale ranging from “strongly disagree” to “stronglyagree”. Example “I believe I can communicate the pros and cons of a tablet PC to others”.3.4.1.6 VisibilityIt was measured on three items using a five point scale ranging from “strongly disagree” to “stronglyagree”. Example “It is easy for me to see others using a tablet PC”.
  • 3.4.1.7 TrialabilityIt was measured on four items using a five point scale ranging from “strongly disagree” to “stronglyagree”. Example “I want to try out various applications of a tablet PC”.3.4.1.8 InnovativenessIt was measured on six items using a five point scale ranging from “strongly disagree” to “stronglyagree”. Example “I am among the first of my friends to acquire the new technology”.3.4.1.9 AttitudeIt was measured on four items using a five point scale ranging from “strongly disagree” to “stronglyagree”. Example “using a tablet PC would be a pleasant experience”.3.4.2 Dependent VariableIt is measured, predicted or otherwise monitored and is expected to be effected by the manipulationof an independent variable.3.4.2.1 Intention of useIt was measured on four items using a five point scale ranging from “strongly disagree” to “stronglyagree”. Example “Whenever possible, I intend to use the tablet PC”.3.5 Questionnaire DesignThe questionnaire is designed to measure the university students’ intention to use the tablet PC. Ituses 9 constructs to do the same. Below, the figure gives the description of the constructs used in thequestionnaire. This questionnaire contains a total of 39 questions. The survey also containsclarification questions.
  • 3.6 Data collection methodThe measurement questions in the questionnaire served to collect the student’s responses towardtheir intention to use the tablet PCs. Participation in this survey is completely voluntary.3.7 Statistical Data AnalysisThe data collected was analyzed and coded using SPSS software version 16. The data was thensummarized through appropriate descriptive and inferential analysis.3.7.1 Goodness and correctness of data entryGoodness and correctness of the data can be tested using the reliability and validity of the analysisand 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 reliabilityValidity and reliability are required to measure the goodness of measures. Reliability analysis is usedto test the internal consistency among the items and validity of the overall scales. Validity is the extentto which a scale fully and unambiguously captures the underlying unobservable construct it isintended to measure.3.7.3 Descriptive analysisIt is useful for any further statistical analysis. This analysis aims to provide an overview of therespondents and the understanding of theory behavioral patterns. It involves range and frequency,count and relationships among the variables.3.7.4 Regression AnalysisRegression analysis is best applied to analyze the effect of two or more independent variables on asingle scaled dependent variable. There are several important issues considered as most suitableassumption to incorporate the test.1. NormalityNormality was measured using histogram and normality distribution. The normality requirementmust be met only if the histogram shows the resemblance to a bell curve.2. HomoscedasticityHomoscedasticity happens when the constant regression model produce error variances. It meansthat the error variances are all similar for all level of independent variables.3. Independence of error termIt indicates the independent predicted values of other predicted variables.4. MulticollinearityIt will be used when two or more independent variables in a multiple regression model are highlycorrelated. When Variance Inflation Factor (VIF) value falls below 10 and 30 for conduction index,it indicates that there are no multicollinearity issues.5. OutliersOutlier in a regression can be observed by using case wise diagnostic. The standard value that fallsabove of 2.50 shall be dropped.
  • 4.0 Data Analysis4.1 IntroductionBased on the survey data submitted by the respondents, the result of the study has been analyzedHypothesis Testing, ANOVA, Reliability Analysis, Multiple regression and factor analysis.4.2 Data ProfileKey observations from the survey data collected:• There are total 83 respondents, out of which there are majority of male respondents; 60 malesand 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 therespondents were students, the objective of the analysis being studying the Intention of use ofTablet PC among students.• Precisely 45 of the respondents are pursuing Masters, next highest is the number pursuingBachelors degree ( 24 ) while there are 7 PHD students.• The students are pursuing varied courses like Engineering, MBA, Social Sciences, Arts andFashion 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 veryhigh usage of internet with 34 of the 83 respondents using internet for more than 3 hours per daywhile other 34 use internet from 1-3 hours.4.3 Goodness of measure4.3.1 Reliability of measurementAll the data collected for the survey was tested for reliability. The purpose of reliability test is todetermine whether the variables represent the whole research framework. In our research we areinterested to examine the extent to which relative advantage, compatibility, image etc., are related tothe intent of using a tablet PC among the university student. Cronbach’s Alpha was used to test thereliability of all the variables in the survey. According to Nunally, Cronbach’s alpha value greater than0.7 is considered reliable. In our findings in the tables given below all alpha values are greater than 0.7hence none of the items is deleted from the study.
  • Variables Cronbachs AlphaTotalItemItemsdeletedRelative 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 advantageReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.950 .950 4Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv2 10.93 9.922 .843 .718 .945v3 10.87 9.702 .878 .785 .934v4 10.89 9.561 .902 .813 .927v5 10.83 10.118 .893 .803 .930
  • Reliability Analysis of CompatibilityReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.910 .911 3Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv6 6.81 4.255 .826 .700 .867v7 6.92 4.200 .785 .619 .901v8 6.83 4.093 .851 .732 .845Reliability Analysis of ImageReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.858 .859 3Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv9 6.88 4.595 .663 .466 .867v10 6.83 3.996 .817 .680 .717v11 6.65 4.718 .726 .593 .809
  • Reliability Analysis of Ease of useReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.514 .585 4Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv12 10.35 5.157 .406 .538 .358v13 11.27 7.490 -.159 .117 .855v14 10.36 4.331 .634 .549 .142v15 10.31 4.169 .646 .651 .116----------------After removing v13---------------Reliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.855 .855 3Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv12 7.52 3.765 .676 .485 .845v14 7.53 3.667 .706 .542 .817v15 7.48 3.277 .805 .650 .721
  • Reliability Analysis of Result DemonstrationReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.880 .880 4Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv16 10.67 7.393 .755 .618 .839v17 10.73 7.222 .810 .685 .818v18 10.76 7.551 .707 .521 .858v19 10.95 7.900 .688 .541 .865Reliability Analysis of VisibilityReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.897 .898 3Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv20 7.04 3.743 .810 .670 .844v21 7.10 3.869 .832 .697 .822v22 7.12 4.449 .757 .576 .888
  • Reliability Analysis of Trial abilityReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.896 .896 4Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv23 11.30 8.115 .786 .639 .860v24 11.34 7.714 .788 .674 .859v25 11.35 7.767 .798 .656 .855v26 11.23 8.471 .708 .536 .888Reliability Analysis of InnovativenessReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.918 .919 6
  • Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv27 17.25 22.411 .742 .581 .907v28 17.57 21.980 .736 .579 .908v29 17.12 21.107 .873 .786 .888v30 17.18 21.784 .793 .681 .900v31 17.22 23.123 .701 .557 .912v32 17.22 23.099 .768 .653 .904Reliability Analysis of Attitude towards using tablet PCsReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.946 .947 4Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv33 11.29 9.062 .825 .695 .944v34 11.11 9.000 .876 .771 .928v35 11.29 8.354 .895 .829 .923v36 11.17 8.825 .891 .830 .924
  • Reliability Analysis of Intent of using tablet PCsReliability StatisticsCronbachs AlphaCronbachs AlphaBased onStandardizedItems N of Items.921 .921 4Item-Total StatisticsScale Mean if ItemDeletedScale Variance ifItem DeletedCorrected Item-Total CorrelationSquared MultipleCorrelationCronbachs Alphaif Item Deletedv37 11.36 8.356 .820 .726 .897v38 11.49 8.838 .792 .719 .907v39 11.28 8.178 .861 .807 .883v40 11.30 8.481 .801 .767 .9044.3.2 Descriptive statisticsThe overall descriptive statistics of the variables is given below in the attached table. All variables weremeasured on a 5 point Likert scale forming a continuum from 1 being strongly disagree on one end to 5being strongly agree at the other end.Descriptive StatisticsN Mean Std. Deviation Variancemode_RA 83 3.63 .959 .920mode_Compatibility 83 3.42 1.049 1.100mode_Image 83 3.47 1.016 1.033mode_Ease 83 3.64 .995 .990mode_Demo 83 3.57 1.002 1.005mode_visibility 83 3.47 .954 .911mode_Trialability 83 3.87 1.021 1.043mode_Innovation 83 3.41 1.169 1.367mode_Aattitude 83 3.66 1.015 1.031mode_Intent 83 3.83 .948 .898Valid N (listwise) 83
  • 4.4 Hypotheses testingPearson product moment correlation was used to study the inter correlation amongst all variables inthis 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 allvariables 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 at0.05 levels (2-tailed). In overall, there is a very strong correlation between all the variables in thesurvey.4.4.1 Multiple RegressionVariableStandardizedbetaRelative Advantage 0.071Compatibility 0.257Image 0.064Ease of Use -0.055Result demonstrability 0.045Visibility -0.045Trialability 0.389Innovativeness 0.107Attitude 0.148Multiple Regression has been used to investigate the study which is to analyze and test therelationship between relative advantage, compatibility, Image, ease of use, result, visibility, trialability, innovativeness and attitude toward the intention to use tablet PC. The hypotheses tested areas follows:1. H1 : Relative advantage of an innovation is positively related to its adoption2. H2 : Compatibility of an innovation is positively related to its adoption3. H3 : Positive image of an innovation is positively related to its adoption4. H4 : Ease of use of an innovation is positively related to its adoption5. H5 : Result demonstrability an innovation is positively related to its adoption6. H6 : Visibility of an innovation is positively related to its adoption7. H7 : Trial ability of an innovation is positively related to its adoption8. H8 : Innovativeness of an innovation is positively related to its adoption9. 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 meansapproximately 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 noautocorrelation of error terms. However from the ANOVA table, we can know that the model is fit asthe 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 & H7which relate Compatibility & trail-ability to the intent of using a tablet PC. These variables providepositive values of Beta (0.257 for Compatibility & for 0.389 Trial-ability) at acceptable p<0.05. Otherhypotheses are rejected due to non significance.
  • HypothesesResultSignificantlevelbetaValuesH1 Rejected 0.668 0.071H2 Accepted 0.032 0.257H3 Rejected 0.512 0.064H4 Rejected 0.701 -0.055H5 Rejected 0.771 0.045H6 Rejected 0.71 -0.045H7 Accepted 0 0.389H8 Rejected 0.35 0.107H9 Rejected 0.28 0.148The hypotheses H2 (Compatibility) and H7 (trial ability) are Accepted since the significant levels areless than 0.05 and the corresponding Beta values, 0.257 & 0.389 are non-negative.
  • CoefficientsaModelUnstandardized CoefficientsStandardizedCoefficientsT Sig.B Std. Error Beta1 (Constant) .570 .348 1.637 .106mode_RA .070 .163 .071 .430 .668mode_Compatibility .232 .106 .257 2.188 .032mode_Image .060 .091 .064 .659 .512mode_Ease -.052 .136 -.055 -.386 .701mode_Demo .043 .146 .045 .292 .771mode_visibility -.044 .119 -.045 -.374 .710mode_trail .361 .098 .389 3.693 .000mode_innovation .087 .093 .107 .940 .350mode_attitude .138 .127 .148 1.089 .280a. Dependent Variable: mode_intent4.4.2 Residual & outlier analysisStandard residuals that have values outside [-3, 3] can be problematic. From our analysis, no caserepresents those values hence no outliers are identified in the given data.Residuals StatisticsaMinimum Maximum Mean Std. Deviation NPredicted Value 1.46 5.04 3.83 .752 83Residual -1.101 1.113 .000 .576 83Std. Predicted Value -3.147 1.605 .000 1.000 83Std. Residual -1.803 1.823 .000 .944 83a. Dependent Variable: mode_intent
  • Casewise DiagnosticsaCaseNumber Std. Residual mode_intent Predicted Value Residual1 .240 4 3.85 .1462 -.304 2 2.19 -.1853 1.245 4 3.24 .7604 1.041 4 3.36 .6365 -1.145 3 3.70 -.6996 -1.399 3 3.85 -.8547 1.257 5 4.23 .7688 -.238 4 4.15 -.1459 .681 4 3.58 .41610 -1.649 3 4.01 -1.00711 -.381 4 4.23 -.23212 1.341 4 3.18 .81913 -.602 4 4.37 -.36814 .445 5 4.73 .27215 -.296 4 4.18 -.18016 .573 4 3.65 .35017 -.238 4 4.15 -.14518 1.273 4 3.22 .77719 -1.481 4 4.90 -.90420 1.059 4 3.35 .64621 .990 5 4.40 .60522 1.171 5 4.28 .71523 -.557 4 4.34 -.34024 -.557 4 4.34 -.34025 .314 5 4.81 .19226 .314 5 4.81 .19227 -1.803 3 4.10 -1.10128 .480 4 3.71 .293
  • 29 -1.453 2 2.89 -.88730 1.823 4 2.89 1.11331 .751 4 3.54 .45932 .657 4 3.60 .40133 1.259 5 4.23 .76934 .880 5 4.46 .53735 -.862 3 3.53 -.52736 -1.269 2 2.77 -.77537 -.238 4 4.15 -.14538 -.168 4 4.10 -.10339 -.478 4 4.29 -.29240 -.759 1 1.46 -.46441 1.744 5 3.94 1.06542 -.585 2 2.36 -.35743 -.534 4 4.33 -.32644 -.759 1 1.46 -.46445 -1.758 2 3.07 -1.07446 -.843 2 2.51 -.51547 -.693 4 4.42 -.42348 .157 5 4.90 .09649 -.238 4 4.15 -.14550 -.585 2 2.36 -.35751 1.000 4 3.39 .61052 -.064 5 5.04 -.03953 -.308 4 4.19 -.18854 .014 4 3.99 .00855 -.238 4 4.15 -.14556 .240 4 3.85 .14657 -.304 2 2.19 -.18558 1.245 4 3.24 .76059 1.041 4 3.36 .63660 -1.145 3 3.70 -.69961 -1.399 3 3.85 -.85462 1.257 5 4.23 .768
  • 63 -.238 4 4.15 -.14564 .681 4 3.58 .41665 -1.649 3 4.01 -1.00766 -.381 4 4.23 -.23267 1.341 4 3.18 .81968 -.602 4 4.37 -.36869 .445 5 4.73 .27270 -.296 4 4.18 -.18071 .573 4 3.65 .35072 -.238 4 4.15 -.14573 1.273 4 3.22 .77774 -1.481 4 4.90 -.90475 1.059 4 3.35 .64676 .990 5 4.40 .60577 1.171 5 4.28 .71578 -.557 4 4.34 -.34079 -.557 4 4.34 -.34080 .314 5 4.81 .19281 .314 5 4.81 .19282 -1.803 3 4.10 -1.10183 .480 4 3.71 .293a. Dependent Variable: mode_intent4.4.3 ProfilingWhile 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 therespondent profile:1) Which program is the respondent pursuing?2) Whether the respondent lives inside or outside the campus?
  • Program – Bachelors / Masters / PhDModel SummaryModel R R Square Adjusted R SquareStd. Error of theEstimate1 .852a.726 .723 .499a. Predictors: (Constant), v6CoefficientsaModelUnstandardized CoefficientsStandardizedCoefficientst Sig.B Std. Error Beta1 (Constant) 5.504 .127 43.460 .000v6 -1.147 .078 -.852 -14.650 .000a. Dependent Variable: mode_intentHence 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 bebecause bachelor degree students are more tech savvy in general & are interested in latesttechnological developments. This may also be due to peer pressure & need for access to social mediathrough tablet PCs etc.In campus / Outside campusModel SummaryModel R R Square Adjusted R SquareStd. Error of theEstimate1 .798a.637 .633 .574a. Predictors: (Constant), v9
  • CoefficientsaModelUnstandardized CoefficientsStandardizedCoefficientst Sig.B Std. Error Beta1 (Constant) 6.419 .226 28.405 .000v9 -2.310 .194 -.798 -11.925 .000a. Dependent Variable: mode_intentHence we see that the R value is high at 0.798 for the regression model. V9 (Residence inside/outsidehostel) 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. Thismay 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 Summary5.1 LimitationsEven though this study has provided useful information about the factors influencing the decision touse 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 utmostimportance that all respondents fill the survey diligently. However, as is the case, individuals do notalways express the feelings truly and fully.Secondly, number of respondents or sample size is always an important factor in survey basedresearch. Since the sample size is 83, drawing generalized conclusions based on these sampleresponses is always risky.5.2 ConclusionTablet PC is a technological gadget whose popularity is rising, especially among the tech-savvyyouth. The Innovation Diffusion Theory ( IDT ) provides means to identify intentions to use tablet PCand 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 PCsamong the students. Thus the creators and the marketers might also get an hint on their targetsegments, sales and promotion strategies and for raising sell of tablet PCs. The present study mightpave way for more extensive future study on this topic using other variables and determinants.