Researchby;                   HASSAH ASGHAR                   RASHID MAHMOOD                   HAROON SABIR                   ATIF RAZZAQ                   MOHAMMAD USMAN            “IMPACT OF GREEN MARKETING ONPERCEIVED VALUE MEDIATING ROLE OF PERCEIVED QUALITY”Abstract:The purpose of thisstudy is to examine the relationship of green products, perceived quality and perceivedvalue. The variables are divided into three models where Perceived Quality isacting as mediating variable & perceived value is acting as dependentvariable. There is a relation between consumer green awareness, perceivedquality and perceived value. 1.Introduction:Agreen product can be defined as “a product which uses recycling and whichbenefits the effect on environment or reduce toxic damage on the environment inthe life cycle as a whole”(Durif,Boivin, & Julien, 2010). The green products have becomevery popular in few previous years. In the, tourism, and higher institution among others(Ariffin,Yusof, Putit, & Shah, 2016)Thisstudy motivated the following research objectives (1) to examine the impact ofgreen value on contextof green marketing, many researchers have proposed that environmental issue hasbecome a major concern of the current generation in a wide range of areas suchas property, businesses perceived quality.

(2)  to examine the factor that has good effect onperceived quality.(3) to examine the effect of perceived quality on perceivedvalue.Literature review:Green marketingis an organized and environmental protection campaign which general publiccares about it because it improves the environment.

(Philip & Gary, 2008),. Greenproducts give same quality and performance which non-green gives which strongthe value of products in customers mind and boost-up the sale. Green value notonly play an important role in effecting the purchase intension of products butit is the essential determinant for a strong and long term relation ofcustomers. (Zhuang et al., 2010).Perceived quality meansconsumers perceptions on products quality ((Tsiotsou, 2006).

In this studyperceived quality can be measured through four dimensions of Patrick (2002)Dependability, reliability, consistency and superiority, it measure the overalljudgment of product and service of customers. Tsiotsou(2006)prove that perceived quality and purchase intension is directly corelated, soperceived quality can be use to predict the purchase intension.   Perceived value (Sweeney & Soutar, (2001) definespercieved value into four dimensions Quality ,price, emotional and social. Themotive of green products for purchasing is that green products give extra valueto them 1.     Research Framework:                                    H2    H1 H3                MethodologyThe target populationsfor this research are students at Universityof the Punjab Gujranwala Campus the population chose due to greaterenvironmental awareness and they know the concept of green products.

In thisstudy we apply close-ended questions because it can save the time ofrespondents. A total 100 questions were distributed and 80 were consider good.And the age, gender and Qualification of respondents were, Age   Frequency Percent Valid Percent Cumulative Percent   Less then 20 27 27.6 27.6 27.6 21-30 69 70.4 70.4 98.

0 31-40 1 1.0 1.0 99.0 Above 50 1 1.

0 1.0 100.0 Total 98 100.0 100.

0       Gender   Frequency Percent Valid Percent Cumulative Percent Valid Male 25 25.5 25.5 25.5 Female 72 73.5 73.5 99.0 4 1 1.

0 1.0 100.0 Total 98 100.0 100.0      Qualification   Frequency Percent Valid Percent Cumulative Percent Valid Intermediate 10 10.

2 10.2 10.2 Graduation 49 50.0 50.0 60.

2 Master 30 30.6 30.6 90.8 MS/M.Fhil 7 7.1 7.1 98.0 PHD 2 2.

0 2.0 100.0 Total 98 100.0 100.0     Hypothesis:H1; Greenmarketing has positive impact on perceived quality.H2; Perceivedquality is positively associated with customer’sperceived value.H3;Perceived value has positive impact on Green products.

H4; Greenmarketing awareness has significant relationship withperceived value      and positivelyeffected through perceived quality.ResultOutliers No. Name of variable Questionnaire no.

1 Green marketing awareness 0 2 Perceived quality 0 3 Perceived value 34 , 55 & 85  Reliability:To examine the internalconsistency/reliability of the instrument, Cronbach’s alpha was used. Its valueabove 0.70 was acceptable (Nunnally et al., 1967). And Cronbach’s alphafor all the variables was above 0.

70 that showed the internal consistency and reliabilityof our instrument Reliability Statistics Cronbach’s Alpha N of Items .869 19                 Correlation Correlations   GM PQ PV GM Pearson Correlation 1 .649** .475** Sig. (2-tailed)   .000 .

000 N 98 98 98 PQ Pearson Correlation .649** 1 .630** Sig. (2-tailed) .000   .000 N 98 98 98 PV Pearson Correlation .475** .

630** 1 Sig. (2-tailed) .000 .000   N 98 98 98 **. Correlation is significant at the 0.01 level (2-tailed).

Pearson correlationanalysis of all the variables also had positive significant relationship.Correlation among all the independent variables had less than 0.80 that showedthat our data did not contain any multicolinearity issues  Regression: Hypotheses R R Square Adjusted R Squared ANOVA Sig. Coefficients constant B H1 .

712 .506 .501 .000 1.044 .

754 H2 .675 .455 .450 .000 1.165 .

696 H3 .662 .439 .

433 .000 1.277 .680        MediatingAnalysis:Run MATRIX procedure: **************** PROCESS Procedure for SPSS Release2.13.2 **************          Written by Andrew F. Hayes, Ph.

D.      www.afhayes.com   Documentation available in Hayes (2013). www.guilford.com/p/hayes3 **************************************************************************Model = 4    Y = PV    X = GM    M = PQ Sample size         98 **************************************************************************Outcome: PQ Model Summary          R       R-sq        MSE          F        df1        df2          p      .

6488      .4210     .3422    69.8003     1.0000   96.0000      .0000 Model             coeff         se          t          p       LLCI       ULCIconstant    1.

2809      .2835     4.5181     .0000      .7181     1.8436GM           .6833      .0818     8.

3547     .0000      .5209      .8456 **************************************************************************Outcome: PV Model Summary          R       R-sq        MSE          F        df1        df2          p      .6358      .4043     .2191    32.2333     2.

0000   95.0000      .0000 Model             coeff         se          t          p       LLCI       ULCIconstant    1.6310      .2498     6.5293     .

0000     1.1351     2.1269PQ           .4356      .0817    5.3336      .0000      .

2734     .5977GM           .0951      .0860     1.1062     .2714     -.0756      .2659 ************************** TOTAL EFFECT MODEL****************************Outcome: PV Model Summary          R       R-sq       MSE          F        df1        df2          p      .

4753      .2259     .2817    28.0109     1.0000   96.0000      .0000 Model             coeff         se          t          p       LLCI       ULCIconstant    2.1889      .

2572     8.5094      .0000    1.6783     2.6995GM           .3927      .0742     5.2925     .

0000      .2454      .5400 ***************** TOTAL, DIRECT, AND INDIRECT EFFECTS******************** Total effect of X on Y     Effect         SE          t          p      LLCI       ULCI      .3927      .0742    5.2925      .0000      .2454     .

5400 Direct effect of X on Y     Effect         SE          t          p       LLCI       ULCI      .0951      .0860    1.1062      .2714     -.

0756     .2659 Indirect effect of X on Y      Effect    Boot SE   BootLLCI  BootULCIPQ     .2976      .0691      .1858     .4787 Partially standardized indirect effect of X on Y      Effect    Boot SE   BootLLCI  BootULCIPQ     .

4959      .0987      .3246     .7277 Completely standardized indirect effect of X on Y      Effect    Boot SE   BootLLCI  BootULCIPQ     .3601      .0770      .2310     .5366 Ratio of indirect to total effect of X on Y      Effect    Boot SE   BootLLCI  BootULCIPQ     .

7578      .2213      .4286    1.3505 Ratio of indirect to direct effect of X on Y      Effect    Boot SE   BootLLCI  BootULCIPQ    3.1285   177.8424      .6354 2983.

9066 R-squared mediation effect size (R-sq_med)      Effect    Boot SE   BootLLCI  BootULCIPQ     .2182      .0682      .0951     .3621 Preacher and Kelley (2011) Kappa-squared      Effect    Boot SE   BootLLCI  BootULCIPQ     .3169      .0621      .

2093     .4584 Normal theory tests for indirect effect     Effect         se          Z          p      .2976      .0665    4.

4729      .0000 ******************** ANALYSIS NOTES AND WARNINGS************************* Number of bootstrap samples for bias correctedbootstrap confidence intervals:     1000 Level of confidence for all confidence intervals inoutput:    95.00 —— END MATRIX —–            References: (Tsiotsou, 2.

(2006). The Role Of Perceived Product Quality And Overall Satisfaction On Purchase Intentions. International Journal of Consumer , 391-397. Tsiotsou. (n.d.). The Role Of Perceived Product Quality And Overall Satisfaction On Purchase Intentions.

International Journal of Consumer. Durif, F., Boivin, C., & Julien, C.

(2010). In search of a green product definition. Innovative Marketing, 6(1), 25–33. Philip, K.

, & Gary, A. (2008). Prinsip-Prinsip Pemasaran, 342. Sweeney, J., & Soutar, G. (2001).

Consumer perceived value: the development of a multiple item scale. Journal of Retailing, 77(2), 203–220. https://doi.org/10.1016/S0022-4359(01)00041-0  Nunnally J C, Bernstein I H, Berge J M T. 1967.

Psychometric theory. (226): McGraw-Hill, New York. pp. 7-21      

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