Smartphone Advertising And Its Impact On Fashion Purchase Decision
Added on 2020-02-03
33 Pages8145 Words62 Views
Data Science and Big Data
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Dissertation- Data Analysisand DiscussionSmartphone Advertising: TheImpact on Fashion PurchaseDecision Making in ChiangMai, Thailand
INTRODUCTIONCurrent chapter is all about exploring the key aspects that relates with the smart phoneadvertising. In this chapter the data analysis and discussion about the subject will be provided sothat better findings can be attained. After research methodology, data analysis is the next sectionin the dissertation. This deals with evaluation and appraisal of the data that has been collected bythe researcher. In addition to this, it can be said that the chapter provides findings of responsesthat are collected by citizens. It will assist in drawing final conclusion so that objectives of thestudy can be accomplished in appreciate manner. Present study is based on smartphoneadvertising and its Impact on Fashion Purchase Decision Making in Chiang Mai, Thailand.Quantitative methods will be used by researcher to have effective evaluation of informationgathered so that issues can be overcome effectively. Along with this, the hypothesis will also bedesigned as per consideration of literature review so that objectives of the study can beaccomplished effectively. In addition to this, it can be stated that the literature review indicatesthe information about impact of age factor on the fashion purchase decision making in relation tothe smart phone advertising so hypothesis 1 has been designed as per consideration of literaturereview. Information gathered in literature review also focuses on significance of marketing mixso it is one of key reason that the hypothesis 3 is related to product, price, place and promotion. Itclearly indicates that there is link between the hypotheses and the literature review. DATA ANALYSISHypothesis*Hypothesis 1*H0 – There is no impact of age on the fashion purchase decision making in relation to the smartphone advertisingH1 – There is an impact of age on the fashion purchase decision making in relation to the smartphone advertising*Hypothesis 2*H0 – There is no significant association between monthly income and fashion purchase decisionmaking in relation to the smart phone advertising
H1 – There is a significant association between monthly income and fashion purchase decisionmaking in relation to the smart phone advertising*Hypothesis 3*H0 – There is a negative significance influence between factors (product, price, place andpromotion) and fashion purchase decisions towards smart phone advertising. H1– There is a positive significance influence between factors (product, price, place andpromotion) and fashion purchase decisions towards smart phone advertising. Refer to Appendix for further informationInterpretation of T-TestGenerally, T-test level of significance is accepted at 5%. In this regard, alternativehypothesis is accepted when group means significantly differ and the value of significance twotailed is less than 0.05. From the conducted analysis, if it is found that two tailed significancevalue is incurred as 0.777, null hypothesis will be accepted and alternative is rejected. As aresult, from this study, it can be found that there is no impact of gender on the fashion purchasedecision making in relation to the smart phone advertising. Interpretation of One Way ANOVAIn One Way ANOVA test, null hypothesis is rejected and alternative hypothesis isaccepted. This is because the level of significant occurred is less than 0.05. Thus, in this context,it can be said that there is a significant association between monthly income and fashionpurchase decision making in relation to the smart phone advertising.Interpretation of factor analysisAccording to the review of the literature review author has found that marketing mix ofan organization has direct impact on customer’s purchase decision making process. So, on thebasis of this insights author has developed hypothesis for determining the most important factorwhich can influence the customer’s behaviour towards the fashion organization. So, author hasformulated this hypothesis. Along with this, factor analysis is appropriate for determining somespecific factor so, application of this tool is presented as under:Table 1: Factor analysis of respondentsCommunalities
InitialExtractionVariety of products1.000.576Trendy1.000.683Quality1.000.746Product information1.000.750Able to compare price1.000.878Reasonable price1.000.951Traffic issues1.000.982Ease to access1.000.878Free delivery1.000.567Discount1.000.951Bonus gift1.000.982Extraction Method: PrincipalComponent Analysis.TotalVarianceExplainedComponentInitial EigenvaluesExtractionSumsofSquared
LoadingsTotal% ofVarianceCumulative%Total% ofVarianceCumulative%13.67933.44433.4443.67933.44433.44422.30620.96154.4052.30620.96154.40531.74615.87070.2751.74615.87070.27541.21411.03381.3081.21411.03381.3085.8938.11589.4236.5615.10394.5267.4053.68098.2068.1971.794100.00092.615E-162.377E-15100.000101.109E-161.008E-15100.00011-3.466E-17-3.151E-16100.000ExtractionMethod:PrincipalComponentAnalysis.ComponentMatrixaComponent1234Variety of products-.291-.343-.405.458Trendy.118.215.378-.693
Quality.807-.058.229.197Product information.529.489-.224-.425Able to compare price-.771-.194.494-.048Reasonable price.701-.361.551.158Traffic issues-.191.856.321.331Ease to access-.771-.194.494-.048Free delivery.636.312-.184.176Discount.701-.361.551.158Bonus gift-.191.856.321.331Extraction Method:PrincipalComponentAnalysis.a. 4 componentsextracted.Factor analysis table has reflected that there are some specific factors of smartphonemarketing which have direct influence on fashion purchase decision making. Analysis hasextracted four factors towards the same. As per the examination of data Reasonable price, Trafficissues, Discount and Bonus gift has the highest percentage from 98.2% to 95.1%. This wasfollowed by Able to compare price and Ease to access and other factors, which had 87.8%. Onthe other hand product information and quality are also considered as important factor which hasfollowed by 75.0% and 74.6% respectively. The least factors that faction purchase decision ofconsumers were affected by are trendy, variety of products and free delivery, which werefollowed by 68.3%, 57.6% and 56.7% respectively. Therefore, factor analysis has reflected thatdifferent factors associated with smartphone marketing which have positive and direct influenceon fashion purchase decision making of customers. But, fashion organizations needs to payattention towards the variety of products, trendiness and free delivery of the products andservices at the time of providing facilities of smartphone selling. These factors may influence thefashion purchase decisions of customers. Overall, as per the price, place and promotion areimportant factors in smartphone marketing which may affect the fashion purchase decisions ofcustomers. As per the factor analysis fashion organizations need to pay attention towards the
improving products for changing buying behaviour of consumers. So, vefrification of hypothesishas reflected that researcher needs to accept the alternative hypothesis and reject the null.Therefore, factor analysis has reflected that there is a positive significance influence betweenfactors (product, price, place and promotion) and fashion purchase decisions towards smartphone advertising.Arithmetic mean and Standard deviationStatisticsGenderAgeEducationOccupationMonthly incomeNValid150150150150150Missing00000Mean1.532.512.052.933.20Median2.002.002.003.003.00Mode22323aStd. Deviation.501.857.8171.4411.170a. Multiplemodes exist.Thesmallestvalue isshownThemesTheme 1: Demographic aspectsAs per detailed analysis of collected data, there are of 150 males and females. The ratioof males to females respondents are considered as a critical aspect. It is noticeable there are a lotmore females than males. In line with this, the arithmetic mean of 1.53 also reaffirms a high ratioof female respondents. A total number of male respondents are 71, accounted for 47.3 percent,while there are 79 female respondents or 52.7 percent. It should also be mentioned that thestandard deviation of gender is 0.501. In addition to this, analysis of primary research alsoindicates that the total number of female customers is 79 and 71 customers belong to male. Itreflects that the females are quite more attracted towards smart phone advertising in order toattain information about fashion products.
GenderFrequencyPercentValid PercentCumulativePercentValidmale7147.347.347.3female7952.752.7100.0Total150100.0100.0In statistical analysis, it can be identified that most of the respondents in the studybelongs to 21-30 years age group, representing 41.3 percent of total respondents. Cumulativepercent of 21-30 years age group accounts for 52.0. Additionally, it can also be seen that thereare 52 participants aged between 31 – 40, whereas the smallest number of respondents is fromunder 20 age group, accounting for a mere 16 respondents.Along with this, the age group ofcustomers can also be interpreted in the study. It has been noticed that out of 150 customers the62 of them are between age of 21-30. It means the young age people are more attracted towardssmart phone advertising. There is low level of old age customers because results indicates thatonly 20 of respondent belong to above 40 age group.AgeFrequencyPercentValid PercentCumulativePercentValidunder 201610.710.710.721-30 years6241.341.352.031-40 years5234.734.786.740 above2013.313.3100.0Total150100.0100.0A majority of respondents’ education level is master’s degree or above, accounting for 36percent. The frequency of diploma holder and lower education level is only 46 and its cumulativepercent equals to 30.7 percent. Mean of education is recorded as 2.05 which indicate thatmaster’s degree holders have effectively participated in the study. Standard deviation is equal to0.817, revealing that education qualification is also rseferred appropriately in this study.Education
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