Equivalent: Jurnal Ilmiah Sosial Teknik

Vol. 6, No. 1, January 2024

THE INFLUENCE OF THE QUALITY OF BRAND IMAGE AND GREEN MARKETING SERVICES ON THE BODY SHOP CONSUMERS' PURCHASING DECISIONS AT MALLS IN SOUTH JAKARTA

Amanda Rachmawati Rasyid¹, Resti Hardini², Kumba Digdowiseiso^3*

Faculty of Economics, Universitas Nasional, Indonesia^1,2,3

Email: amandarasyid@gmail.com¹, resti.hardini@civitas.unas.ac.id², kumba.digdo@civitas.unas.ac.id^3*

ABSTRACT

This study aims to analyze the effect of service quality, brand image, and green marketing on consumer purchasing decision of The Body Shop at mall in South Jakarta. The result of this research is using primary data in the form of questionnaires to 100 respondents of The Body Shop consumers in mall in South Jakarta using Statistical Product and Service Solutions (SPSS) method. Data collection techniques in this study by observation and survey, unstructured interviews, and using questionnaires. The result of the research using F test and t test indicate that there is influence of service quality, brand image and green marketing towards purchasing decision of The Body Shop at mall in South Jakarta.

Keywords: Service Quality, Brand Image, Green Marketing, Purchase Decision

INTRODUCTION

The increasingly rapid development of the business world today causesCompanies have to face tough competition. In this era of increasingly rapid development, especially in terms of fulfilling consumer needs and desires. Consumers today tend to be more individualistic and demand things that are more personal or personalized. To meet these needs, companies are required to be able to understand consumers' desires and needs in order to survive. Whether the product being sold is accepted or not really depends on the consumer's perception of the product. If consumers feel that the product meets their needs and desires, consumers will definitely buy the product. So companies are required to always meet consumer needs and desires. Besides that, providing something different (different) as a strategy to meet competition should also be done by companies. The number of brands circulating in Indonesia is very large, meaning consumers are faced with many choices and it makes it difficult for them to choose. The Body Shop is a company that operates in the beauty business in the form of cosmetic or make-up products. The Body Shop was born with the idea of reusing, refilling and recycling what they could reuse. The advantage of The Body Shop is the use of natural ingredients in its products. The Body Shop is a cosmetics company that carries an environmentally friendly concept in its marketing strategy. There are three supporting pillars whose principles are Profit, People and Planet.

The Body Shop is available throughout Indonesia, The Body Shop in Jakarta can be found in 5 areas, namely Central Jakarta, East Jakarta, West Jakarta, North Jakarta and South Jakarta. Based on information obtained, compared to other areas of DKI Jakarta, malls in South Jakarta have more visitors on average, namely almost 100 thousand visitors per day. (http://www.cyapila.com/2014/09/12/jakarta-kota-mal//, 2014). This research took the location of The Body Shop outlets in malls in South Jakarta, including: MallGandaria City, Kemang Village Mall, Pejaten Village Mall, Pondok Indah Mall, Kota Kasablanca Mall.

Based on the background, the author is interested in conducting research with the title "The Influence of Service Quality, Brand Image, and Green Marketing on Consumer Purchasing Decisions of The Body Shop at Malls in South Jakarta"

Based on the background of the problem above, research questions can be formulated as follows:

1) Is there a positive and significant influence of service quality on consumer purchasing decisions for The Body Shop at malls in South Jakarta?

2) Is there a positive and significant influence of brand image on consumer purchasing decisions for The Body Shop at malls in South Jakarta?

3) Is there a positive and significant influence of green marketing on consumer purchasing decisions for The Body Shop at malls in South Jakarta?

RESEARCH METHODS

In this research, the object of research is consumer purchasing decisions for The Body Shop at malls in South Jakarta. Purchasing decisions are influenced by service quality, brand image, and green marketing. The data source used in this research is primary data, namely data obtained directly from original sources (without intermediaries) providing questions by distributing questionnaires to respondents where the author makes written questions related to the research, with the requirement that consumers use cosmetic products. The Body Shop at a mall in South Jakarta. By adding data in the form of literature, documents and other information to strengthen the primary data.

The type of data used in this research is descriptive qualitative data, which was obtained directly from the research object through distributing questionnaires. According to Sugiyono (2013:23) Population is a generalized area consisting of objects/subjects that have certain qualities and characteristics which are applied by researchers to study and then draw conclusions. According to Sugiyono (2010, 118) what is meant by sample is part of the number and characteristics possessed by the population. The sampling technique used by the author is non-probability sampling. According to Sugiyono (2010: 120), non-probability sampling is: "A sampling technique that provides equal opportunities for each element or member of the population to be selected as a sample.

The non-probability sampling technique used in sampling in this research is purposive sampling and quota sampling techniques. The definition of purposive sampling according to Sugiyono (2010: 122) is "a technique for determining samples with certain considerations."

Understanding quota sampling According to Sugiyono (2013: 60) states that quota sampling is a technique for determining samples from a population that has certain characteristics up to the desired number (quota). In this study, the following criteria were used:

1) The Body Shop customers who have previously purchased The Body Shop at that outlet.

2) They decide to buy The Body Shop products based on their own decisions

The population in this study is large and the number is unlimited, in this study the population cannot be known, so the number of samples in this study is calculated using the Wiliam formula (2011:34), as follows:

(Zα / P* (1-P*)

n =

Information :

P* = Population proportion

E = Error tolerance limit 10%= 0.10

α = 0.05

(Zα/ =Normal distribution score with a significance level of 5% = 1.96

0.5 (1-0.5)

n=

0.10²

= 96.04 rounded to 100

From the results of these calculations, this research took a sample of 100 respondents. The Body Shop outlets are found throughout Indonesia, especially in Jakarta. Judging from the number of visitors to The Body Shop customers at malls in South Jakarta, it is higher than at malls in Central Jakarta, East Jakarta, West Jakarta and North Jakarta. There are 13 The Body Shop outlets in malls in South Jakarta, but due to several limitations including limited time and energy, the researchers conducted this research at 5 The Body Shop outlets in malls in South Jakarta. The malls are as follows:

1) Gandaria City Mall

2) Kemang Village Mall

3) Pejaten Village Mall

4) Pondok Indah Mall

5) Kasalanca City Mall

Data Collection Techniques and Tools

Data collection techniques in this research were carried out using 3 methods, namely:

1) Observation and survey

2) Unstructured interviews (unstructured interviews

3) The data collection method that will be used in this research is using personal questionnaires (Personally Administered Questionnaires).

RESULTS AND DISCUSSION

Inferential Analysis

According to Sugiyono (2012:207) inferential statistics is a statistical technique used to analyze sample data and the results are applied to the population. This statistic is suitable for use if the sample is taken from a clear population, and the sampling technique from that population is carried out randomly.

Table 1. Multiple Regression Test Results

Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.	Collinearity Statistics
		B	Std. Error	Beta			Tolerance	VIF
1	(Constant)	1,472	1,939		,759	,450
	Service Quality	,193	,095	,171	2,031	,045	,725	1,379
	Brand Image	,368	,085	,365	4,352	,000	,725	1,379
	Green Marketing	,334	,082	,347	4,066	,000	,701	1,427
a. Dependent Variable: Purchase Decision

Source: Process data with SPSS 24.0

Based on the results of the analysis, it can be seen that the multiple regression equation can be formulated as follows:

Y= 1.472 + 0.193 + 0.368 + 0.334

Instrument Test

Validity Test Results

The validity test is used to test the extent to which the accuracy of the measuring instrument can reveal the concept of the symptom/event being measured. The R table used in this research is 0.197 (100 respondents with a significance level of 5%). The results of the validity test can be seen in Table 2 as follows:

Table 2. Validity Test Results

Variable	R Count	R Table	Sig	Results
Service Quality
X1_1	0.586	0.197	0,000	Valid
X1_2	0.681	0.197	0,000	Valid
X1_3	0.762	0.197	0,000	Valid
X1_4	0.682	0.197	0,000	Valid
X1_5	0.669	0.197	0,000	Valid
Brand Image
X2_1	0.648	0.197	0,000	Valid
X2_2	0.663	0.197	0,000	Valid
X2_3	0.806	0.197	0,000	Valid
X2_4	0.695	0.197	0,000	Valid
X2_5	0.773	0.197	0,000	Valid
Green Marketing
X3_1	0.744	0.197	0,000	Valid
X3_2	0.758	0.197	0,000	Valid
X3_3	0.711	0.197	0,000	Valid
X3_4	0.650	0.197	0,000	Valid
X3_5	0.567	0.197	0,000	Valid
Buying decision
Y_1	0.593	0.197	0,000	Valid
Y_2	0.661	0.197	0,000	Valid
Y_3	0.719	0.197	0,000	Valid
Y_4	0.642	0.197	0,000	Valid
Y_5	0.785	0.197	0,000	Valid

Source: Process data with SPSS 24.0

ResultsReliability Test

Table 3. Reliability Test Results

Variable	Cronbach's Alpha	Results
Purchasing Quality (Y)	0.770	Reliable
Service Quality (X1)	0.769	Reliable
Brand Image (X2)	0.786	Reliable
Green Marketing (X3)	0.772	Reliable

Source: Process data with SPSS 24.0

Based on Table3 above, shows that each item from each dependent variable, namely purchasing decisions, and the independent variables, namely service quality, brand image, and green marketing, have a Cronbach alpha's value greater than 0.60. So it can be concluded that the variable indicators of purchasing decisions (Y), service quality (X1), brand image (X2), and green marketing (X3), are all declared reliable or trustworthy as variable measuring instruments.

Classic assumption test

ResultsNormality test

The normality test is one of the requirements before carrying out regression testing. This test was carried out using the Kolmogorov – Smirnov test. The normality test results can be seen in Table 4 as follows:

Table 4. Normality Test Results

One-Sample Kolmogorov-Smirnov Test
		Unstandardized Residuals
N		100
Normal Parameters, b	Mean	,0000000
	Std. Deviation	1.58998609
Most Extreme Differences	Absolute	,080
	Positive	,062
	Negative	-,080
Kolmogorov-Smirnov Z		,804
Asymp. Sig. (2-tailed)		,538
a. Test distribution is Normal.
b. Calculated from data.

Source: Process data with SPSS 24.0

The normality test results in Table 4 using the One-Sample Kolomogorov-Smirnov Test obtained a significance value or Asymp Sig. (2-tailed) is 0.538 which is above 0.05 so it can be concluded that the data is normally distributed and suitable for use in the regression model.

Autocorrelation Test Results

The autocorrelation test is used to determine whether or not there are deviations from the classic assumption of autocorrelation, namely the correlation that occurs between the residuals in one observation and other observations in the regression model. The results of the autocorrelation test can be seen in Table 5 as follows:

Table 5. Autocorrelation Test Results

Model Summary^b

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Durbin-Watson
1	.714a	,509	,494	1.61464	2,095

Source: Process data with SPSS 24.0

Table 5 shows that the value of Durbin-Watson (d) in this study is 2.095. This study used a sample size of 100 (n=100) with du (inner limit) = 1.758 and dl (outer limit) = 1.592. The upper limit of the du value for this study is 1.758 so 4-du is 2.242. Thus, it can be concluded that the d value of 2.095 is located between du and 4-du (1.758 < 2.095 < 2.242) so it can be concluded that there is no autocorrelation in the regression model used in this research.

Multicollinearity Test Results

Table 6. Multicollinearity Test Results

Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	Q	Sig.	Collinearity Statistics
		B	Std. Error	Beta			Tolerance	VIF
1	(Constant)	1,472	1,939		,759	,450
	Service Quality	,193	,095	,171	2,031	,045	,725	1,379
	Brand Image	,368	,085	,365	4,352	,000	,725	1,379
	Green Marketing	,334	,082	,347	4,066	,000	,701	1,427
a. Dependent Variable: Purchase Decision

Source: Process data with SPSS 24.0

The results of the multicollinearity test in Table 4.34 above show that all independent variables, namely suit quality, brand image and green marketing, have a tolerance value greater than 0.1 and the variance inflation factor (VIF) value is below 10, which means there are no symptoms. multicollinearity in this regression model. The service quality variable has a tolerance value of 0.725 and a VIF value of 1.379. For the brand image variable, it has a tolerance value of 0.725 and a VIF value of 1.379. Meanwhile, the green marketing variable has a tolerance value of 0.701 and a VIF value of 1.427.

Heteroscedasticity Test Results

Heteroscedasticity testing aims to test whether the regression model has unequal variance from the residuals of one observation to another. A good regression model isnot occurheteroscedasticity and to determine the presence of heteroscedasticity using the Glejser test. If the three independent variables are statistically significant and do not influence the dependent variable, then there is an indication that heteroscedasticity does not occur. The following are the results of the heteroscedasticity test on the regression model in this study:

Table 7. Heteroscedasticity Test Results

Corellations

Variable	Sig	Results
Service Quality	0.932	Not occurheteroscedasticity
Brand Image	0.946	Not occurheteroscedasticity
Green Marketing	0.910	Not occurheteroscedasticity

Source: Process data with SPSS 24.0

Table 7 shows that all variables have a significant value greater than 0.05, so it can be concluded that the regression model in this study does not have heteroscedasticity.

Model Feasibility Test

Simultaneous Test Results (F test)

This technique is used to determine the influence of independent variables together on the dependent variable. To find out whether simultaneously, the regression coefficient of the independent variable has a real influence on the dependent variable or not.

Table 8. Simultaneous F Test Results

ANOVAa
Model		Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	259,722	3	86,574	33,208	,000b
	Residual	250,278	96	2,607
	Total	510,000	99
a. Dependent Variable: Purchase Decision
b. Predictors: (Constant), Green Marketing, Brand Image, Service Quality

Source: Process data with SPSS 24.0

Table 8 shows the results of the simultaneous test or F test where the calculated F value was obtained at 33,208 with a significance level of .000. Because the significance level of the sig value is <0.05, this means that service quality, brand image and green marketing together influence purchasing decisions.

Coefficient of Determination (R2)

The purpose of this test is to find out how much the combination of independent variables is able to explain variations in the dependent variable. The results of the coefficient of determination test appear in Table 9.

Table 9. Coefficient of Determination Test Results

Model Summary b

Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	,714a	,509	,494	1.61464
a. Predictors: (Constant), Green Marketing, Brand Image, Service Quality
b. Dependent Variable: Purchase Decision

Source: Process data with SPSS 24.0

Based on Table 9, the Adjusted R Square is 0.494, this means that the dependent variable, namely purchasing decisions, can be explained by independent variables which include service quality, brand image and green marketing at 49.4 percent, while the remaining 50.6 percent is explained by factors. other than the independent variables used in this research.

Partial Hypothesis Test Results (t test)

The partial t test is used to determine the effect of each independent variable on the dependent variable. The partial t test is said to be significant if the sig value. each variable is no more than alpha (Sig. < 0.05). The results of the partial t test can be seen in Table 10 below:

Table 10. Partial t Test Results

Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	Q	Sig.	Collinearity Statistics
		B	Std. Error	Beta			Tolerance	VIF
1	(Constant)	1,472	1,939		,759	,450
	Service Quality	,193	,095	,171	2,031	,045	,725	1,379
	Brand Image	,368	,085	,365	4,352	,000	,725	1,379
	Green Marketing	,334	,082	,347	4,066	,000	,701	1,427
a. Dependent Variable: Purchase Decision

Source: Process data with SPSS 24.0

The influence of each variable of service quality, brand image and green marketing on purchasing decisions can be seen from the direction and level of significance (probability).

Based on the calculation results in table 4.39, it is explained as follows:

1) Testing the Service Quality Hypothesis (X1) on Purchasing Decisions (Y)

Based on the test results in table 4.39 above, it shows that the tcount value for the Service Quality variable (X1) is 2.031 with a significant value of 0.045, so the ttable value (α = 0.05) must be looked for which is 1.984, because the tcount value (2.031 > 1.984) with the level significant (0.045 < 0.05), then Ho is rejected, which means there is a positive and significant influence betweenService Quality (X1) on Purchasing Decisions (Y)

2) Testing the Brand Image Hypothesis (X2) on Purchasing Decisions (Y)

Based on the test results in table 4.39 above, it shows that the tcount value for the Brand Image variable (X2) is 4.352 with a significant value of 0.000, so the ttable value (α = 0.05) must be looked for which is 1.984, because the tcount value (4.352 > 1.984) with the level significant (0.000 < 0.05), then Ho is rejected, which means there is a positive and significant influence betweenBrand Image (X2) on Purchasing Decisions (Y)

3) Testing the Green Marketing Hypothesis (X3) on Purchasing Decisions (Y)

Based on the test results in table 4.39 above, it shows that the tcount value for the variableGreen Marketing(X3) is 4.066 with a significant value of 0.000, so you have to look for the ttable value (α = 0.05) which is 1.984, because the tcount value (4.066 > 1.984) has a significant level of (0.045 < 0.05), then Ho is rejected, which means there is a positive and significant influence betweenGreen Marketing(X3) on Purchase Decisions (Y).

CONCLUSION

Based on the results of the research and discussion, the following conclusions can be drawn; (1) service quality has a positive and significant effect on consumer purchasing decisions, which means that if service quality is improved, purchasing decisions for The Body Shop at malls in South Jakarta will increase, (2) brand image has a positive and significant effect on consumer purchasing decisions, which meaning that if a good company image is maintained, then purchasing decisions towards The Body Shop at the mall in South Jakarta will increase, and (3) green marketing has a positive and significant effect on consumer purchasing decisions, which means that if the company maintains and develops green marketing, then decisions purchases of The Body Shop at malls in South Jakarta will increase.

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Copyright holder:

Amanda Rachmawati Rasyid, Resti Hardini, Kumba Digdowiseiso (2024)

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