Gatton College of Business and Economics



The precursors/factors affecting purchase intention of smartphones; A comparative study of faculty members of The University of Science and Technology Bannu and Gomal University Dera Ismail Khan, KPK, PakistanSohail RahmanInstitute of Management Sciences, University of Science and Technology, Bannu, KPK, PakistanEmail: sohailaormarh@DR. Walter FarrierGatton College of Business and EconomicsUniversity of Kentucky, Lexington, Kentucky, USAEmail: walter.ferrier@uky.edu Dr. Mohammad Imran KhanDepartment of Management SciencesCOMSATS Vehari Campus, Vehari, PakistanEmail: imrankhan@ciitvehari.edu.pkAbstractThis research Article reveals the precursors affecting the purchase intention of smartphones. The research after conducting factor analysis obtained the independent variables i.e. Product usefulness, price, celebrity endorsement, customer problem resolution, load speed and customer product education. The affect of these independent variables on Purchase intention during 12 months was observed.IntroductionIn a study by Heggestuen (2013) stated that Global per-capita analysis reveals that smartphone has crossed the personal computers in a study conducted by June 2012. There are other astonishing data given by author as that in 4 years, 1.3 billion increase in smartphone has been observed, also it was indicated that by year ending 2013 in average nine customers will possess (or 1.4 billion), two smartphones. Furthermore personal computers penetration rate in market is lowest than that of tablets and smartphones. In an article by (Jan 16, 2014) expects that worldwide in 2014, 4.55 billion customers will possess cell phones. There is less penetration of mobile phones but in Asia-Pacific, Middle East and Africa there will be growth in adoption of cell phones. In the year 2013 to 2017 cell phones penetration will increase from 61.1 % to 69.4 % worldwide.According to Misbah (2014) there is worldwide acceptance of smartphones. According to Business recorder in 2013 the customers of smartphone touched 79% and in 2014 worldwide distribution of smartphone would be 450 million. Furthermore there has been increase in smartphones instead of ordinary cell phones by mobile manufacturing organizations. Companies like Zong and ufone are manufacturing android low price smartphones. Mobilink Company has introduced Black Berry in Pakistan. Ufone and Warid companies are making smartphones more attractive. There are 5-6 million users of smartphone in Pakistan. By the year of 2016 the smartphone users will be 50 million.There is no single study done on smartphones in Dera Ismail Khan and Bannu cities of Pakistan. The researcher has done innovation in this regard by conducting study on smartphone in these two cities.Independent and dependent Variables definedPrice: The amount of money or other item with utility needed to acquire a product or patibility: It tells that how matching is smartphone with consumer’s value, past experience and needs.Relative Advantage: If a customer has a smartphone then how much it is beneficial than ordinary phone a customer have in comparing in terms of money, social image, ease of use and contentment.Technicality: The complex nature of smartphone.Perceived Value: The customer’s perception about the benefits and price.Customer personal reciprocity: The comparison between what customers pays for what he/she obtains.Celebrity Expertise: Celebrity endorsement of product.Satisfaction with Recovery: The satisfaction obtained when the network problem is resolved.Purchase intention: The intent to purchase in coming time.Saif et al (2012) has explored the factors which a customer bring into consideration before customer finally selects a cell phone. The research problem of this study is that there is low penetration of smartphones in Bannu and Dera Ismail Khan Cities of Pakistan also that there is no research conducted in these two cities on smartphone.Diffusion of innovation TheoryRobinson (2009) says that Innovation means newness and has given the following factors which spread innovation.Relative Advantage: Which says that a customer having new product than how much it is beneficial than the product he/she has patibility: IT tells us that how matching is a product with customers values, past experience and needs.Simplicity: It says that there is greater acceptability of simple ideas than complex ones.Trial ability: when a product is given for trial basis.Observability: A thing which is noticed prior to other thing will be accepted and adopted.Furthermore peers information passing will lead to adoption of product because peers rely on each other. The same is case with face to face communication in which when positive word of mouth is created will lead to adoption of product. There are five categories of adopters i.e. Innovators, early adopters, early majority, late majority and laggards.Rogers E. (1995) has said that innovators are accepted in a culture and the five factors mentioned priory will lead to diffusion of innovations in cultures which enhances the purchase intention of innovations.Theory of MaterialismIt says that people try to accumulate wealth. Also to have social image and respect people will buy expensive products. (Tim 2002, Yousaf & Abdullah, 2003). People assign high value to expensive products (Vitzthum , 1995; Lange, 1925). As smartphones are also luxurious products so people will buy them and purchase intention will increase. As the purchasing power of people will increase then smartphones will no longer be a luxurious products. (Moser & J.D 1995; Jee Han, Joseph & Xavier, 2010).Till & Busler (2000) have given an idea about celebrity and its endorsement. They have explained different models in their study like Elaboration likelihood model, associative learning, social adoption theory, schema theory, attribution theory and cultural meaning transfer. They used two studies in one study physical attractiveness of celebrity and other was about celebrity expertise. It was checked that the celebrity endorsement of something and its match with it. The dependent variables were brand attitude and purchase intention. It was resulted that physical attractiveness of celebrity endorsing something results an increase in purchase intention also when celebrity endorses products or services than his/her worth also increases. He further said that if there is match between a product and celebrity expertise endorsing it then it will increase brand attitude and vice versa. This hypothesis was significant. In another study by Maxham III & Netemeyer (2002) it was found that when an employee gives good feedback to customers about his problem and resolves it then the customer satisfaction increases. Cronin Jr et al (2000) has worked on the effect of service quality, service value and satisfaction on customer purchase intention. Convergent and divergent theory, Baozi’s 1992 model and service value literature were used by researcher. In his results price is having relation to service value, service quality has relation to service value and satisfaction and service quality has relation with behavioral intention. The study reveals that three variables when increase then behavioral intention increases. The hypothesis that customer service quality and value when increases the behavioral intention increases was significant. Qun et. al (2012) has proved that when social influence, compatibility and price increases the purchase intention increases but the relationship of relative advantage and purchase intention was not significant. Ibrahim et al (2013) in his study found insignificant relationship of relative advantage, price and compatibility to purchase intention. Osman et al. (2012) have done a study on smartphones in Malaysia in which they reveal that what customers uses in smartphones and why they gave edge to smartphones. In this study price is under consideration but having minimum importance as the smartphone is durable good but design, connectivity and performance have more worth than price. Young generation prefer smartphones as compared to old generation. The factors like trends in community, needs, software, cost, hardware are under consideration while opting for smartphone. Madahi & Inda (2012) proved in their research that age, gender, Race, geography and groups when increase the purchase intention also increases. Kim (2005) has researched that mobile penetration is minimum in many countries. He proved that usefulness and enjoyment when increase the perceived value also increases. Bukhari et al. (2013) has done study on purchase intention of expensive cell phones. They have found that perceived price when increases the perceived value also increases which results an increase in the purchase intention of expensive cell phones. In a book by Kotler & Armstrong (2005) have given an idea about how customer makes decisions. In first instance a customer faces a need, the he/she searches the information during which he /she gets alternatives and makes purchase intention then he/she selects a specific alternative and buy product or service. After that post purchase behavior appears. In another book by Kotler & Armstrong (2005) the factors that enhances accepting rate of new product are, the value a product give as compared to existing product plus a product suitability with beliefs and practices of customers, the operational difficulty of product, the partial use of product and at last how a product is seen by others according to its use. Kotler (1997) Kotler & Keller (2005) has said that a customer makes purchase intent regarding a product which has been selected among alternatives. Furthermore between purchase intention and purchase decision the tendency of others (attitude of others) and contingency variables affect them.Research Hypothesis (old)There is positive relationship between relative advantage and purchase intention.There is positive relationship between price and purchase intention.There is positive relationship between compatibility and purchase intention.There is positive relationship between technicality and purchase intention.There is positive relationship between perceived value and purchase intention.There is positive relationship between customer personal reciprocity and purchase intention.There is positive relationship between celebrity expertise and purchase intention.There is positive relationship between satisfaction with recovery and purchase intention.Research Design and methodThe researcher has used quantitative approach and factor analysis, correlation, regression and t-test has been applied by researcher. The factor analysis minimizes the greater number of constructs in to smaller number. The quantitative research is mostly used and researcher has done the same. A lot of research has been conducted on the precursors affecting purchase intention. Many articles and books have been studied by researcher. There are plenty of variables (even more than 20) affecting Purchase Intention of smartphones. The researcher has identified many variables which have shown up a positive correlation to purchase intention but researcher has taken those variables which have insignificant relationship to purchase intention. Qun, 2012 has proved that when social influence, price and compatibility effects purchase intention while relative advantage have shown non-significant effect on purchase intention. Usman (2012) has proved that price has non-significant relationship to buying smartphone while design, connectivity and performance has more value than price. A study by Wang et al. (2012) has said that technicality has negative correlation to perceived value in case of online content services which was insignificant. In a study by Kim et al (2005) Technicality has slightly negative relationship to perceived value and perceived value has significant relationship to purchase intention. Customer personal reciprocity is negatively correlated to purchase intention by Vinynda Sabrina (2013). Till & Busler (2000) reached to opinion through research that celebrity endorser’s expertise has negative correlation to purchase intention. Maxham III & Netemyer (2000) has said that satisfaction with recovery when increase the purchase intention decreases.So all those variables were taken which have shown negative relation to purchase intention. Survey MethodIn most of the studies survey method has been used. The researcher opted for the same and did questionnaire survey. The researcher distributed 200 questionnaires and got 170 response out of which 165 were workable and 5 had missing values. The response was 82.55%.Sample and populationThe population for this study is faculty members of University of Science and Technology Bannu and Gomal University Dera Ismail Khan, KPK, Pakistan. The simple random sampling technique has been adopted by researcher. Both users and non-users of smartphone were taken. The non-users were taken because nowadays every person has some information about smartphones.Pilot study for reliability and validity testsThe researcher did pilot test for questionnaire reliability and validity. Cronbach’s alpha was computed by researcher and validity of questionnaire was checked by Factor loading analysis by the help of SPSS software.Reliability Analysis of Questionnaire (Cronbach’s alpha)The researcher distributed 20 questionnaires in University of Science and Technology Bannu, KPK, Pakistan and got 15 complete responses from the said university. From Gomal University Dera Ismail Khan, KPK, Pakistan 16 Questionnaires were collected for pilot study but 15 were considered. Which were then feed to SPSS 17 version which we got the following resultsS/NOConstructCronbach’s AlphaRelative Advantage0.861Price0.694Compatibility0.848Purchase intention0.782Technicality0.606Perceived value0.808Satisfaction with Recovery0.282Customer personal reciprocity0.498Celebrity/endorsers Expertise0.843Questionnaire as a whole0.892Research Method from Gujarati (2003)Specifying the theory or hypothesisIn preliminary stage the researcher mentions the theory or hypothesis which are as followingThere is positive relationship between relative advantage and purchase intention.There is positive relationship between price and purchase intention.There is positive relationship between compatibility and purchase intention.There is positive relationship between technicality and purchase intention.There is positive relationship between perceived value and purchase intention.There is positive relationship between customer personal reciprocity and purchase intention.There is positive relationship between celebrity expertise and purchase intention.There is positive relationship between satisfaction with recovery and purchase intention.Specifying the mathematical modelThe model is mathematically expressed below:PI = βο + β1RA +β2P+β3C+β4PV+β5CPR+β6EE+β7SWR+ β8T+ β9PVWhereas PV= Perceived value, T= Technicality, PI= Purchase intention, RA= Relative advantage, P= Price, C= Compatibility, PV= Perceived value, CPR= Customer personal reciprocity, EE= Endorsers expertise, SWR=Satisfaction with recoverySpecifying econometric modelThe econometric model is expressed as PI = βο + β1RA +β2P+β3C+β4PV+β5CPR+β6EE+β7SWR+ β8T+ β9PV+ ? or eThe researcher then factor analysis in SPSS software for the following items in questionnaireRelative Advantage 1 to Relative advantage 5Price 1 to Price 3Compatibility 1 to Compatibility5Technicality 1 to Technicality4Perceived Value 1 to Perceived value 4Satisfaction with recovery 1 to Satisfaction With Recovery 3Customer personal reciprocity 1 to Customer Personal Reciprocity 3Celebrity Endorsement 1 to Celebrity Endorsement 6 (while CE6 = Average of CE6 and CE7) Then the researcher run Regression Analysis.Dependent variable (Purchase intention with in coming 12 months)Descriptive analysisDescriptive statistics 1NMinimumMaximumMeanStd. DeviationSkewnessStatisticStatisticStatisticStatisticStatisticStatisticName of the University165121.58.496-.309Department/Institute166121.22.4171.344Age1661.005.002.11451.02344.901Gender1661.002.001.1386.346532.112Income per month1661.005.003.44581.11467-.500Education1661.004.002.0361.75391.026Are you having any smartphone?1661.002.001.3373.47424.694Your tribe please?1661.008.003.78922.46136.311Valid N (listwise)165Descriptive Statistics 2 Skewness Kurtosis Std. Error Statistics Std. ErrorName of the University.189-1.928.376Department/Institute.188-.197.375Age.188.412.375Gender.1882.488.375Income per month.188-.384.375Education.188-1.013.375Are you having any smartphone?.188-1.537.375Your tribe please?.188-1.139.375Table 1The descriptive statistics shows we have found 165 responses for the Universities name and for the Demographic constructs the responses were 166. Factor AnalysisKMO and Bartlett's TestBartlett's Test of SphericityKaiser-Meyer-Olkin Measure of Sampling Adequacy..869Approx. Chi-Square4842.827Df861Sig..000Table 2 We have applied KMO (Kaiser – Meyer-Olkin) method and Bartlett’s test of sphericity (BTS). They were very suitable for factor Analysis because KMO value was 0.869 which is more than 0.6 and significance value is 0.000 which is less than 0.05 so we resort to factor analysis as a result of this.Total Variance ExplainedComponentRotation Sums of Squared Loadings Total % of Variance Cumulative %18.37619.94219.94225.01411.93831.88033.7909.02440.90443.4028.09949.00352.2105.26254.26562.0134.79359.05871.8974.51663.57481.4453.44067.013Extraction Method: Principal Component Analysis.Table 3Table 3 gives idea about variances of each factors of our model. We have 8 constructs and in this table Total Variance, % of variance and cumulative variance is given of the eight constructs. First construct got maximum variance of 19.942 and got cumulative variance of 19.942 while 8th construct got minimum variance of 3.440 while its cumulative variance is 67.013. Chart 1Component MatrixaComponent12345678Cm1.843Cm2.809Perv4.799RelAdv3.767-.315Cep2.746-.337RelAdv5.745-.365Cm4.745.324PIn7.733Pr3.732Cep7.725Perv2.723Cep3.722RelAdv1.705Cupr3.703Cm3.701Cep6.698-.410Pr2.671Cm5.670-.328.305PIn5.617.322PIn8.614-.316Perv3.609-.458RelAdv4.576-.565Cep1.576-.356-.395RelAdv2.546-.398Cep5.511-.368-.372Cupr1.495.332-.360Perv1.492-.304-.316PIn6.452.374.430Tec2.444-.329-.361PIn3.769PIn2.685.364Pr1.401-.535.421PIn4.357.532PIn1.495.325Cep4.470.489-.311Tec4.668.357Tec1.541.389Tec3-.343.528.305Sawr1.376.663Sawr3.385.510Cupr2.453.392-.546Sawr2.333.363.386-.357Extraction Method: Principal Component Analysis.8 components extracted.Table 4Table 4 gives idea of loading the different questions (items) on different factors. The question Purchase Intention2 i.e. PIn 2loading on factor two is 0.685 while its loading on factor four is 0.364 so researcher will consider highest value that is its loading on second factor. In the same way the question technicality four loads highest on factor three i.e. 0.668 and while it’s loading on factor six is 0.375. So researcher will consider its loading on factor three. The Factors Loaded Together:The factor analysis loaded the following items togetherVariable old nameItems loaded togetherVariable new nameCompatibilityRA1 C1 C2 C3 C4 C5Product UsefulnessPriceP1PriceCelebrity EndorsementCEE1 CEE4 CEE5Celebrity EndorsementSatisfaction with recoverySWR1 SWR2Customer problem resolutionTechnicalityT3 T4Load speedTechnicality and satisfaction with recoveryT1 SWR2Customer product EducationTable 5“In table 5 we found several new dimensions of factors in our current research study. As factor loading of various items were cross load on other than its own factor and the Eigen values of all the loaded items are higher than 0.1. So we group them in newly establish factor titles as Product usefulness is emerged from the cross loading of different factors, while the old variable title was compatibility. And Item that are loaded on the new factor are (Compatibility1, Compatibility2,Compatibility3,Compatibility4, Compatibility5, and one factor from Relative advantage1).The other factor is Price and the item loaded on it was (Price 1) and its new name is as old one i.e. Price. In The celebrity endorsement variable the items which loaded together were Celebrity endorsement 1, Celebrity endorsement 4, Celebrity endorsement 5 and its new name remained the same as celebrity endorsement. In the satisfaction of recovery the items which loaded together were satisfaction of recovery1, satisfaction of recovery 2, and its new name was given as customer problem resolution. In the variable Technicality after factor analysis the items Technicality 3, Technicality 4 were loaded together and its new name is Load speed. Also the two variables Technicality and satisfaction with recovery the items loaded together were Technicality 1 and satisfaction with recovery 2 and the new variable name was given Customer product education.”RegressionCorrelationsPurchIn12AGEYOUNGHighIncomeProductUsefulnessPricePearson CorrelationPurchIn121.000.040-.182.144-.120AGEYOUNG.0401.000-.443.017.011HighIncome-.182-.4431.000.029.104ProductUsefulness.144.017.0291.000.235Price-.120.011.104.2351.000CelebrityEndorsement.318.161-.143.436.092CustomerProblemResolution.219-.008-.139.294.216LoadSpeed.272-.095-.009-.151.160CustomerProductEducation.169-.058-.123.031.085Sig. (1-tailed)PurchIn12..303.010.032.062AGEYOUNG.303..000.416.444HighIncome.010.000..355.092ProductUsefulness.032.416.355..001Price.062.444.092.001.CelebrityEndorsement.000.019.033.000.120CustomerProblemResolution.002.460.037.000.003LoadSpeed.000.111.454.026.020CustomerProductEducation.015.230.057.347.137NPurchIn12166166166166166AGEYOUNG166166166166166HighIncome166166166166166ProductUsefulness166166166166166Price166166166166166CelebrityEndorsement166166166166166CustomerProblemResolution166166166166166LoadSpeed166166166166166CustomerProductEducation166166166166166Table 6CorrelationsCelebrity EndorsementCustomer Problem ResolutionLoad SpeedCustomer Product EducationPearson CorrelationPurchIn12.318.219.272.169AGEYOUNG.161-.008-.095-.058HighIncome-.143-.139-.009-.123ProductUsefulness.436.294-.151.031Price.092.216.160.085CelebrityEndorsement1.000.240-.014.139CustomerProblemResolution.2401.000-.031.095LoadSpeed-.014-.0311.000.355CustomerProductEducation.139.095.3551.000Sig. (1-tailed)PurchIn12.000.002.000.015AGEYOUNG.019.460.111.230HighIncome.033.037.454.057ProductUsefulness.000.000.026.347Price.120.003.020.137CelebrityEndorsement..001.428.037CustomerProblemResolution.001..345.112LoadSpeed.428.345..000CustomerProductEducation.037.112.000.NPurchIn12166166166166AGEYOUNG166166166166HighIncome166166166166ProductUsefulness166166166166Price166166166166CelebrityEndorsement166166166166CustomerProblemResolution166166166166LoadSpeed166166166166CustomerProductEducation166166166166Table 7“Table 7 shows that the correlation among variables, the celebrity Endorsement is correlated to Purchase intention and the coefficient of correlation is (0.318), Load speed is correlated to PI by (0.272), Customer problem resolution is correlated to PI by (0.219), Customer product education is correlated to PI (0.169) which is very weak and low significant. Product usefulness is correlated to PI by correlation coefficient by the value (0.144) and price is correlated negatively to PI by the value (-0.120)”Model SummarybModelRR SquareAdjusted R SquareStd. Error of the Estimate1.519a.270.2321.080a. Predictors: (Constant), Customer Product Education, Product Usefulness, AGEYOUNG, Price, Customer Problem Resolution, Load Speed, CelebrityEndorsement, HighIncomeDependent Variable: PurchIn12Table 8Table 8 reveals that R square value is 0.270 which shows that 27% change is brought in independent variable i.e. Purchase intention within 12 months by the independent variables and 73% change in dependent variables is due to other variables. ANOVAbModelSum of SquaresDfMean SquareFSig.1Regression67.62788.4537.245.000aResidual183.1921571.167Total250.819165a. Predictors: (Constant), CustomerProductEducation, ProductUsefulness, AGEYOUNG, Price, CustomerProblemResolution, LoadSpeed, CelebrityEndorsement, HighIncomeb. Dependent Variable: PurchIn12Table 9Table 9 shows that F value is 7.245 and is significant because the level of significance is less than 5 percent.Coefficientsa Model Unstandardized Standardized Coefficients Coefficient B Std. Error Beta T Sig.1(Constant)-1.420.586-2.424.016AGEYOUNG-.024.210-.009-.112.911HighIncome-.243.196-.099-1.241.217ProductUsefulness.117.102.0931.150.252Price-.241.072-.247-3.348.001CelebrityEndorsement.334.106.2473.145.002CustomerProblemResolution.279.115.1822.438.016LoadSpeed.425.098.3314.358.000CustomerProductEducation.008.108.005.072.943Table 10Dependent Variable: PurchIn12Table 10 shows the beta values the age young has beta value of -1.420 and it is insignificant because of (0.911) , High income beta value is -0.243 and its significance value is 0.217 which means it’s not significant., product usefulness beta value is 0.117 and its significance value is 0.252 which means it is non-significant , price beta value is -0.241 and its significance value is .001 which is slightly significant, Celebrity endorsement has beta value of 0.334 and its significance value is 0.002 which means that it is significant., customer problem resolution has beta value of 0.279 and its significance value is 0.016 which means that it is significant , load speed has beta value of 0.425 and significance value is 0.000 which means that it is significant and customer product education has beta value 0.008 and its significance value is 0.943 which means that it is non-significant.New Hypothesis and their resultsIf celebrity endorses smartphone then there is increase in Purchase Intention (significant).If there is maximum uploading and downloading speed of smartphone then there would be increase in Purchase Intention. (Significant)If there is increase in smartphone mobile service problem resolution then there would be increase in Purchase Intention. (Significant)If there is increase in mobile service education of consumers of Smartphone then Purchase Intention would increase. (Non- Significant)If there is increase in smartphone ease of use and usefulness then there would increase in Purchase Intention. (Non-significant)If there would be increase in smartphone price then there would be increase in Purchase Intention. (Non-significant) but also minimum prices decreases the Purchase Intention and maximum prices indicates better quality and operations.CONCLUSIONAs stated by Till and Busler (2000) if there is increase in celebrity endorsement and celebrity attractiveness then it would increase the purchase intent and also Purchase Intent and celebrity endorsement have +ve intercorrelation. In this study researcher have proved that there is increase in Purchase Intention of smartphone if it is endorsed by celebrity. In this study if there is increase in technicality/load speed then Purchase Intention increases. (Significant) Wang et al.(2012) has proved that the technicality when increases the perceived value decreases. (Significant) Furthermore the satisfaction with recovery/ customer problem resolution when increases the Purchase Intention increases was found to be Significant. According to Maxham III & Netemeyer (2002) when customer problem is resolved quickly then satisfaction with recovery increases.In this study researcher has proved that if there is increase in mobile service education then Purchase Intention increases and was found significant. This result is matching with research of Maxham & Netemeyer (2002) which states that satisfaction with recovery has non-significant relationship with Purchase Intention. Also in this study ease of use and usefulness when increases than Purchase Intention does not increases. The new name given to compatibility was Product usefulness. The result discussed is same of that of the study of Ima IIyani Ibrahim et al.(2013) which says that there is non-significant relation between compatibility and Purchase Intention. Also in a study by Qun et al.(2012) which says that there is increase in compatibility then Purchase Intention would increase was found to be significant. In this study Price has non-significant relation to Purchase Intention. Furthermore Qun et al.(2012) has said that price increasethan Purchase Intention also increases was found to be significant. In research by Ima IIyani Ibrahim et al.(2013) price has non-significant relationship to Purchase Intention.RECOMMENDATIONSSmartphone when endorsed by celebrities then there would be maximum profitability to smartphone producing organizations.Smartphone Service providers if maximizes the uploading and downloading speed then people are more likely to buy smartphone in future which would increase sales and profit for organizations.If the customer problems of networks are solved many times of smartphone then people will buy in future the panies should not pay attention to customers while educating them as mobile service education does not enhances Purchase Intention.Ease of use and usefulness does not maximizes the chances of Purchase in future by customers so this should be neglected by companies producing smartphones.Price is a such type of variable that if it is increased the customer to buy in future does not maximizes, so price if kept low will increase Purchase Intention while price if kept high then it will indicate high quality. 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