The Influence of Brand Image, Brand Trust and Price on Samsung Television Purchase Decisions at Hartono
Elektronik Surabaya Store
Gita Suganda, R. Agus Baktiono, Muchamad Arif
Department of Management Faculty of Economics and Business Narotama University Surabaya
Arief Rahman Hakim no 51 , Surabaya , Indonesia
[email protected], [email protected], [email protected]
Abstract
The high growth of television users makes television electronics industry manufacturers compete with each other to understand market needs, so it is very important to understand the factors that influence purchasing decisions. This research was conducted at the Hartono Electronic Store in Surabaya with the aim of knowing (1) the influence of brand image on purchasing decisions (2) the influence of brand trust on purchasing decisions (3) the effect of price on purchasing decisions (4) the influence of brand image, brand trust, price in general and purchase decision. Itwas a quantitative study. It had 97 respondents. The instrument was a questionnaire. Data processing in this study used SPSS ver. 26.00. Based on the results of this study, brand image, brand trust and price had a significant effect partially and simultaneously on purchasing decisions.
Keyword :
Brand Image, Brand Trust, Price, Purchase of Decision
1. Introduction
The progress of the electronics industry makes the growth of electronic users among the community increasingly rapid. The high growth of television users makes television electronics industry manufacturers compete with each other to understand market needs, so it is very important to understand the factors that influence purchasing decisions. Increasingly fierce business competition as it is today requires companies to be more aggressive in marketing to attract and retain consumers. This requires companies to be more creative in carrying out their business activities. One of the industrial clusters focused on encouraging economic growth to above 7% is the electronics industry and electronic components. In addition to contributing to GDP, the electronics and electronic components industry also plays a role in creating foreign exchange through exports.
The tight competition in the electronic industry, both gadgets and home appliances, has forced electronic companies in Indonesia to compete to attract the hearts of consumers so that they are able to convince the choice of purchasing decisions for our products.
Therefore, in winning the competition, every company must have an appropriate marketing strategy for the products it produces. Among the many marketing strategies, companies are faced with brands, namely Brand Image, Brand Trust and Price.
According to Kotler (2000) explains that brand image is the perception and belief made by consumers, as reflected in the associations that occur in the memory of consumers. According to Tjiptono Fandy (2005), Brand Image or brand image is a description of consumer associations and beliefs about certain brands (Sunarti et al., 2018). Brand trust or trust in the brand is also one of the benchmarks for prospective customers in determining a product purchase decision, brand trust has an important role in the industrial world because every prospective buyer hopes that there is minimal risk to the product purchased so that brand trust becomes so important that it spurs actors Businesses in the electronics industry must be more creative, innovative and competitive to make their products the number one choice of customers. In this discussion, Samsung also carries out various marketing strategies to increase customer trust by extending the product warranty period and improving post- sales service. According to Swastha (2008) "Price is the amount of money that must be paid by consumers or buyers to get the products offered by the seller. The determination of the selling price must be adjusted to the purchasing power of the intended consumer and taking into account the factors of cost, profit, competitors, and changing market desires (Vinet & Zhedanov 2011). Purchasing decisions according to Schiffman dan Kanuk (2004) are the selection of two or more alternative purchasing decision choices, which means that a person can make a decision, there must be several alternative choices. Decision making is a thought made after evaluating several options. In other words, in order for someone to make a decision, there must be alternative options available (Neisia et al., 2018). Here the researchers conducted research on Samsung Television at the Hartono
Electronics Store Surabaya. Hartono Elektronika Surabaya shop is a large store that sells all electronic equipment completely. Of course, Hartono Store already has a good brand image in the eyes of consumers, especially consumers in Surabaya.
2. Method
2.1 Types of Research
This research uses a quantitative approach research type, is a research method based on the philosophy of positivism, is used to examine certain populations or samples, data collection using research instruments, data analysis is quantitative / statistical, with the aim of describing and testing predetermined hypotheses.
2.2 Time and Place of Research
This research will be conducted at the Hartono electronics store located at Maspion Square, G.01 CS, Jl.
Ahmad Yani No.73, Margorejo, Kec. Wonocolo, SBY City, East Java 60238. This research will be conducted by giving questionnaires to all consumers who purchase Samsung Television products who have purchased these products at the Hartono electronics store Maspion square Surabaya.
This reseach plan will be carried out in January 2021 to April 2021.
2.3 Population and Sampling
The population in this study are consumers who buy and use Samsung Television products, the number is not known with certainty. In this study the sampling technique used Probability Sampling, precisely Simple Random Sampling, with 97 respondents.
2.4 Data and Data Collection Methods
The data used in this study are primary data and secondary data. The data collection method used in this study was a questionnaire.
2.5 Hypothesis Development
The hypotheses in this research are:
H1: Brand Image partially significant effect on Purchase Decision H2: Brand Trust partially significant effect on Purchase Decision H3 : Price has partial significant effect on Purchase Decision
H4: Brand Image, Brand Trust, Price have a significant effect simultaneously on Purchase Decision
Figure 1 Conceptual Framework 1. The Effect of Brand Image (X1) on Purchase Decision (Y)
Based on the results of partial regression analysis that the value of t count > t table is 4.392 > 1.986 or the value of sig. t 0.00 < = 0.05 , then H0 which reads that there is no significant positive effect on Purchase Decisions, is rejected and Ha which reads that there is a significant positive effect on Purchase Decisions, is accepted. The value of the partial regression coefficient of the Brand Image variable is 0.395, which means that if the Brand Image is increased, the Purchase Decision will increase by 0.395. Thus, the conclusion is that the Brand Image Variable (X1) has a positive influence on the Purchase Decision variable (Y).
2. The Effect of Brand Trust (X2) on Purchase Decision (Y)
Based on the results of partial regression analysis that the value of t count > t table is 4,867 > 1,986 or the value of sig. t 0.00 < = 0.05, then H0 which reads that there is no significant positive effect on the Purchase Decision, is rejected and Ha which reads that there is a significant positive effect on the Purchase Decision, is accepted. The value of the partial regression coefficient of the Brand Trust variable is 0.106, which means that if the Brand Trust is increased, the Purchase Decision will increase by 0.106. Thus, the conclusion is that the Brand Trust variable (X2) has a positive influence on the Purchase Decision variable (Y).
3. The Effect of Price (X3) on Purchase Decisions (Y)
Based on the results of partial regression analysis that the value of t count > t table is 4.678 > 1.986 or the value of sig. t 0.00 < = 0.05, then H0 which reads that there is no significant positive effect on the Purchase Decision, is rejected and Ha which reads that there is a significant positive effect on the Purchase Decision, is accepted. The value of the partial regression coefficient of the price variable is 0.567, which means that if the price is increased, the purchasing decision will increase by 0.567. Thus, the conclusion is that the price variable (X3) has a positive influence on the purchasing decision variable (Y).
4. The Effect of Brand Image (X1) Brand Trust (X2) Price (X3) on Purchase Decision (Y)
In the F (simultaneous) test, the calculated F value is 32,982. While F table = f(k ; n – k ), F = (3 ; 97– 3), F table = (3 ; 94) = 2.70 . Because F count > F table that is 32,982 > 2.70 or sig. F (0.000) < = 0.05 then the regression analysis model is significant. This means that H0 is rejected and Ha is accepted so that it can be concluded that Brand Image, Brand Trust and Price have a significant effect simultaneously on Purchase Decisions.
2.6 Data analysis technique 1. Validity Test
Validity testing can be done by correlating each factor or variable with the total factor or variable using correlation (r) . Test criteria to accept or reject the hypothesis of a valid statement or not, can be done by:
The null hypothesis (H0) is accepted if r count < r table, and The alternative hypothesis (H1) is accepted if r count > r table
2. Reliability Test
The reliability testing technique is to use the Spearman Rho reliability coefficient value. The decision- making criteria is if the Cronbach's Alpha value is more than 0.60.
3. Normality test
This test is conducted to determine whether the residual values are normally distributed or not. The test procedure was carried out using the Kolmogorov-Smirnov test, with the following hypotheses:
H0: The residuals are normally distributed and H1: the residuals are not normally distributed.
If the value of sig. (p-value) > 0.05 then H0 is accepted, which means normality is met.
4. Multicollinearity Test
Multicollinearity test is conducted to find out that there is no very strong relationship or there is no perfect linear relationship or it can also be said that the independent variables are not interrelated. The test method is to compare the tolerance value obtained from multiple linear regression calculations, if the tolerance value is > 0.10 then there is no multicollinearity. Then, it can also be done by comparing the VIF (Variance Inflation Factor) value with the number 10. If the VIF value is < 10 then multicollinearity occurs.
5. Heteroscedasticity Test
This test uses Spearman Rho correlation using the SPSS program, with the following hypothesis:
Value of Sig. 2-tailed ( > 0.05 ) = Heteroscedasticity does not occur Value of Sig. 2-tailed ( < 0.05 ) = Heteroscedasticity occurs 6. Multiple Linear Regression
Multiple linear regression analysis from this study was used to determine whether or not the relationship between Brand Image (X1), Brand Trust (X2), Price (X3) variables such as independent variables on purchasing decisions (Y) was a kind of dependent variable. Multiple linear regression equations are enabled from the results of data processing with the SPSS program such as the following:
Y = 3.910 + 0,395X1 + 0,106X2 + 0,567X3 + e Description :
Y = Purchase of Decision
a = Value of Contanta b1, b2, b3 = Variabel of Coefficient
X1 = Brand Image
X2 = Brand Trust
X3 = Price
e = Error
2.7 Hypothesis Testing 1. T Test
To test the first hypothesis, the T test is used, which is to test the significance of the effect of the independent variable partially on the dependent variable. The F test aims to be able to determine the effect of the independent variables Brand Image (X1), Brand Trust (X2), Price (X3) on the dependent variable is Purchase Decision (Y). The criteria for accepting and rejecting the hypothesis used are as follows:
1) If t count > t table then the result is significant and means H0 is rejected and H1 is accepted.
2) If t count < t table then the result is not significant and means H0 is accepted and H1 is rejected.
2. F Test
Then test the second hypothesis, namely the F test is used to simultaneously test the significance of the effect of the independent variables (X) on the dependent variable (Y). The criteria for accepting and rejecting the hypothesis used are as follows:
1) 1. If F count > F table then the result is significant with H0 rejected, Ha accepted 2) 2. If F count < F table then the results are not significant with H0 accepted, Ha rejected 3. Coefficient of Determination Test (R2)
To determine the magnitude of the variable brand image, brand trust and price in explaining purchasing decisions can be seen from the magnitde of the coefficient of determination (R2).
3. Results of Analysis and Discussion
3.1 Validity Test
Table 1. Validity Test Variabel Indicator
Corrected Item-Total Correlation
R-
Table Description
Brand Image (X1)
X1.1 0,848 0,1996 Valid
X1.2 0,873 0,1996 Valid
X1.3 0,830 0,1996 Valid
Brand Trust (X2)
X2.1 0,698 0,1996 Valid
X2.2 0,607 0,1996 Valid
X2.3 0,659 0,1996 Valid
X2.4 0,797 0,1996 Valid
Price (X3)
X3.1 0,712 0,1996 Valid
X3.2 0,748 0,1996 Valid
X3.3 0,645 0,1996 Valid
X3.4 0,638 0,1996 Valid
Purchase of Decision (Y)
Y.1 0,732 0,1996 Valid
Y.2 0,748 0,1996 Valid
Y.3 0,690 0,1996 Valid
Y.4 0,472 0,1996 Valid
Y.5 0,440 0,1996 Valid
From the table above, it can be seen that the value of r count > r table , which means that each item variable is valid, so it can be concluded that these items can be used to measure research variables.
3.2 Reliability Test
Table 2. Reliability Test
No. Variabel Reliability of Coefficient Description
1. Brand Image (X1) 0.807 Reliabel
2. Brand Trust (X2) 0.603 Reliabel
3. Price (X3) 0.623 Reliabel
4. Purchase Of Decision (Y) 0.612 Reliabel
Based on the table above, the reliability test of the research variables above shows that the entire Cronbach alpha value of each variable is more than 0.06. In both dependent and independent variables stated reliable or able to be accepted because it has a value above 0.6 which means that the questions from this research questionnaire are said to be reliable.
3.3 Normality Test
Table 3. Normality Test One-Sample Kolmogorov-Smirnov Test
Unstandardize d Residual
N 97
Normal Parametersa,b Mean .0000000 Std.
Deviation
1.61261209 Most Extreme
Differences
Absolute .078 Positive .052 Negative -.078
Test Statistic .078
Asymp. Sig. (2-tailed) .173c a. Test distribution is Normal
b. Calculated from data
c. Lilliefors Significance Correction
Based on the results of the normal distribution test above, the significance value is 0.173 or greater than 0.05. Then the provisions of H0 are accepted, namely that the assumption of normality is met.
3.4 Multicollinierity Test
Table 4.Multicollinierity Test Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t Sig.
Collinearity Statistics
B Std. Error Beta Tolerance VIF
1 (Constant) 3.910 1.750 2.235 .028
Brand Image .395 .090 .375 4.392 .000 .715 1.398
Brand Trust .106 .122 .087 4.867 .000 .514 1.947
Price .567 .121 .424 4.678 .000 .634 1.576
a. Dependent Variable: Purchase of Decision
Table 5.Multicollinierity Test Variabel Bebas Collinearity
Statistics Tolerance VIF
X1 0.715 1.398
X2 0.514 1.947
X3 0.634 1.576
Based on the table above, it can be seen that the regression model does not experience multicollinearity disorders. This can be seen in the tolerance value of each independent variable which is greater than 0.1. The results of the VIF calculation also show that the VIF value of each independent variable is less than 10. So it can be concluded that there is no multicollinearity between the independent variables in the regression model.
3.5 Heteroscedasticity Test
Table 6. Heterocedasticity Test Correlations
Brand Image Brand Trust Harga
Unstandardized Residual Spearman's rho Brand Image Correlation Coefficient 1.000 .524** .329** .044
Sig. (2-tailed) . .000 .001 .666
N 97 97 97 97
Brand Trust Correlation Coefficient .524** 1.000 .587** .069
Sig. (2-tailed) .000 . .000 .587
N 97 97 97 97
Price Correlation Coefficient .329** .587** 1.000 .046
Sig. (2-tailed) .001 .000 . .657
N 97 97 97 97
Unstandardized Residual
Correlation Coefficient .044 .069 .046 1.000
Sig. (2-tailed) .666 .499 .657 .
N 97 97 97 97
**. Correlation is significant at the 0.01 level (2-tailed).
Based on the table above, the three figures obtained are Sig.2 Tailed Variable Brand Image (X1), Brand Trust (X2), Price (X3), Purchase Decision (Y) of 0.66 , 0.58 , 0.657 then the problem of heterokesatisity can be said not to be. occurs because the spearman rho rank value is greater than 0.05.
3.6 Multiple Linear Regression
Table 7. Multiple Linier Regression Test
Based on the table above, the linear regression equation is obtained as follows:
Y = 3.910 + 0,395X1 + 0,106X2 + 0,567X3 + e Description :
Y = Purchase of Decision
a = Value of Constanta
b1, b2, b3 = Variabel of Coefficient
X1 = Brand Image
X2 = Brand Trust
X3 = Price
e = Error
So it can be concluded that:
a. The constant value is 3.910, this shows that if the brand image (X1), brand trust (X2), price (X3) , then the purchase decision is 3.910.
b. Brand image value (X1) is 0.395. This shows that if the brand image (X1) increases by one unit, it will increase the purchasing decision (Y) by 0.395 with the assumption that the brand trust variable (X2) and price (X3) are constant.
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
T Sig.
Collinearity Statistics B
Std.
Error Beta Tolerance VIF
1 (Constant) 3.910 1.750 2.235 .028
Brand Image .395 .090 .375 4.392 .000 .715 1.398 Brand Trust .106 .122 .087 4.867 .000 .514 1.947
Price .567 .121 .424 4.678 .000 .634 1.576
c. The value of the brand trust coefficient (X2) is 0.106 . This shows that if brand trust increases by one unit, it will increase purchasing decisions (Y) by 0.106 units with the assumption that the brand image variable (X1) and price (X3) are constant.
d. The value of the price coefficient (X3) is 0.567 . This shows that if the price increases by one unit, it will increase purchasing decisions (Y) by 0.567 units with the assumption that the brand image (X1) and brand trust (X2) variables are constant.
3.7 T Test
Table 8. T Test
VariabelTerikat VariabelBebas t hitung t Tabel Keterangan Purchase Of
Decision (Y)
X1 4.392 1.986 Significant
X2 4.867 1.986 Significant
X3 4.678 1.986 Significant
Based on the table, the results of hypothesis testing are obtained as follows:
1. Brand Image (X1)
The t-test between X1 (Brand Image) and Y (Purchase Decision) shows t count = 4.392. While t table = t (α / 2 ; n – k – 1= 0.05 / 2 ; 97 – 3 – 1) = ( 0.025 ; 93 ) = 1.986. Because t count > t table that is 4.392 > 1.986 or sig. t 0.00 < = 0.05 then the effect of X1 (Brand Image) on the Purchase Decision is significant.
2. Brand Trust (X2)
The t-test between X2 (Brand Trust) and Y (Purchase Decision) shows t count = 4.867. While t table = t (α / 2 ; n – k – 1= 0.05 / 2 ; 97 – 3 – 1) = ( 0.025 ; 93 ) = 1.986. Because t count > t table that is 4,867 > 1,986 or sig. t 0.00 < = 0.05 then the effect of X2 (Brand Trust) on the Purchase Decision is significant.
3. Price (X3)
The t test between X3 (Price) and Y (Purchase Decision) shows t count = 4.678. While t table = t (α / 2 ; n – k – 1= 0.05 / 2 ; 97 – 3 – 1) = ( 0.025 ; 93 ) = 1.986. Because t count > t table that is 4.678 > 1.986 or sig. t 0.00 < = 0.05 then the effect of X3 (Price) on the Purchase Decision is significant.
3.8 F Test
Table 9. F test ANOVAa Model
Sum of
Squares df Mean Square F Sig.
1 Regression 265.608 3 88.536 32.982 .000b
Residual 249.650 93 2.684
Total 515.258 96
a. Dependent Variable: Purchase of Decision b. Predictors: (Constant), Price, Brand Image, Brand Trust
Based on table 4.16 above in the F test (simultaneous) the calculated F value is 32,982. While F table = f(k ; n – k ), F = ( 3 ; 97 – 3 ), F table = (3 ; 94) = 2.70 . Because F count > F table that is 32,982 > 2.70 or sig. F (0.000) < = 0.05 then the regression analysis model is significant. This means that H0 is rejected and Ha is accepted so that it can be concluded that Brand Image, Brand Trust and Price have a significant effect simultaneously on Purchase Decisions.
3.9 Coefficient of Determination Test (R2)
Table 10. R2 Test Model Summaryb
Model R R Square
Adjusted R Square
Std. Error of the Estimate
1 .718a .515 .500 1.63842
a. Predictors: (Constant), Price, Brand Image, Brand Trust b. Dependent Variable: Purchase of Decision
Based on table above, the R square determination test can be obtained by an adjusted R value of 0.50 and an R square coefficient of 0.515. This means that 0.50 or 50% variation of the independent variables brand image (X1) , brand trust (X2), and price (X3) affect purchasing decisions (Y) by 0.515 or 51.5% and is influenced by other variables that are not included and described in this study by 48.5%.
3.10 Discussion
The results of hypothesis testing indicate that the variables of brand image, brand trust, price together have a significant simultaneous effect on purchasing decisions. Partially shows that the brand image variable has a significant effect on purchasing decisions. Partially brand trust has a significant effect on purchasing decisions.
Partially the price also has a significant effect on the Purchase Decision.
4. Conclusion
Based on the results of research and analysis of data obtained on "The Influence of Brand Image, Brand Trust, and Price on Purchase Decisions for Samsung Television at Hartono Elektronika Surabaya Store" it can be drawn from the following conclusions:
1. Brand Image has a significant effect partially on the Purchase Decision of Samsung Television, at Hartono Elektronik Surabaya. This is evidenced by t arithmetic > t table, namely 4.392 > 1.986 or the value of sig t (0.000) < = 0.05.
2. Brand Trust has a significant effect partially on the Samsung Television Purchase Decision, in Hartono Elektronik Surabaya. This is evidenced by t arithmetic > t table, namely 4.867 > 1.986 or the value of sig t (0.000) < = 0.05.
3. Price has a significant effect partially on Samsung Television Purchase Decisions, at Hartono Elektronik Surabaya. This is evidenced by the t count > t table, namely 4.678 > 1.986 or the value of sig t (0.000) < = 0.05.
4. Brand Image, Brand Trust, Price have a significant effect simultaneously on Samsung Television Purchase Decisions, at Hartono Elektronika Surabaya. This is evidenced by F count > F table, which is 32,982 > 2.70 or sig value. F (0.000) < = 0.05.
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Biographies
Gita Suganda, born in Surabaya, East Java , is currently pursuing a bachelor's degree in management economics at Narotama University, Surabaya.
R. AgusBaktiono, born in Pasuruan, studied Bachelor of Economics at Narotama University graduating in 1986, further study in Master of Management Program graduated in 2002 at Narotama University Surabaya. His career in the field of education began in 1985 as a lecturer assistant, and at this time has achieved the academic position of Head Lector, certified lecturer and assessor of LKD serdos, as well as internal auditor for Higher Education Quality Assurance. In addition, since 1989 he has been active in various professional organizations, including ISEI, REI, as a management expert at various Consultants. Structural positions he has held in the field of education, among others, as Head of the Department.
Muchamad Arif, is a lecturer at Narotama University, Surabaya, Indonesia. He is also as Head of Narotama Language Center at Narotama University, Surabaya, Indonesia. He got master degree in English Education from UnikaWidya Mandala, Surabaya, Indonesia
