Why Is Brand Perception More Important Than Product Quality?

 

 

Name
Age	18yrs - 25yrs.         36yrs - 45yrs         46yrs - 55yrs.		56yrs –up         26 -35yrs
Gender	Male
Education Level	o   High school or Equivalent o   Bachelor’s degree	o   Master’s degree o   Doctoral Degree o   Other
Marital status	o   Single o   Married	o        Divorced o        Widowed o        Separated

 

1		2	3	4		5
Strongly Disagree		Disagree	Neither agree nor disagree	Agree		Strongly Agree
Brand Image: Koubaa, Y. (2008).					1		2	3	4	5
1	COO information will affect significantly brand image perception.				○		○	○	○	○
2	Well-known COO for the product in question will have a significant positive effect on brand image perception while unknown COO will have a negative impact on brand image perception.				○		○	○	○	○
3	Brand level of reputation will moderate the effect of country of production on brand image.				○		○	○	○	○
4	Brand origin will have a significant effect on brand image perception.				○		○	○	○	○
Brand Awareness: Radder, L., & Huang, W. (2008).
5	I usually remember brand names that are easy to pronounce.				○		○	○	○	○
6	I usually remember brand names that are easy to spell.				○		○	○	○	○
7	I usually remember brand names that remind me of something.				○		○	○	○	○
8	I usually choose well-advertised brands.				○		○	○	○	○
Brand Attitude: Zimmer, M., & Bhat, S. (2004).
9	Attitude toward the parent brand will be more positive when the extension is of high quality than when the extension is of medium quality.				○		○	○	○	○
10	Attitude toward the parent brand will either remain the same or be more positive when a high-quality extension has been introduced compared to when no extension has been introduced.				○		○	○	○	○
11	Attitude toward the parent brand will be less positive when a medium quality extension has been introduced compared to when no extension has been introduced.				○		○	○	○	○
12	Attitude toward the parent brand will be more positive when the fit between the extension and the parent brand is good than when the fit is poor.				○		○	○	○	○

Bibliography

 

Koubaa, Y. (2008). Country of origin, brand image perception, and brand image structure. Asia Pacific Journal of Marketing and Logistics, 20(2), 139 - 155.

Radder, L., & Huang, W. (2008). High-involvement and low-involvement products. Journal of Fashion Marketing and Management, 12(2), 232 - 243.

Zimmer, M., & Bhat, S. (2004). The reciprocal effects of extension quality and fit on parent brand attitude. Journal of Product & Brand Management, 13(1), 37 - 46.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Why Is Brand Perception More Important Than Product Quality?

 

1-    INTRODUCTION:

 

BACKGROUND OF STUDY:

Brand perception refers to how customers perceive a product or service. It comes from customer use, experience, functionality, practicality, reputation, and word of mouth recommendation whether it's on social media or in person. Product quality is the degree to which a product satisfies customer needs, meets industry standards, and serves its intended purpose. Common factors that influence how consumers perceive your brand include personal experience, advertising, reputation, branding, customer service, price, and positioning (Merriam-Webster Online, Internet, 2010).

 

When it comes to branding, first impressions are said to be everything. Brand perception is more important than the quality of a product because the first thing a customer notices about a product is its brand (Ferrell & Hartline, 2008, p. 282). Many reasons contribute to brand perception, including sending out multiple messages, increasing awareness, having a purpose for the brand, and maintaining a consistent personality throughout.

 

Brand perception is crucial to the success of any company. It's your feelings, attitudes, and experiences with the product or service that will determine whether you'll buy it or not. Every car ad during football season taps into a viewer's emotions about the brand (Nasar et al., 2012).

 

Skincare ads are designed to convince you that their product is better than the one you're currently using. They use three components to achieve this: product quality, brand perception, and emotions. Quality is the only one that's objective and measurable.

 

The creativity of the product name and the quality of the product image are completely subjective. When it comes to brand perception, it is clear how important that is in consumer behavior. A loyal customer may have a less-than-desirable product, but they are still loyal to that brand. This gives the company a competitive advantage over other brands with similar products.

 

PROBLEM STATEMENT:

This research intends to look at the influence of Why is brand perception more important than product quality? means how consumers perceive your brand include personal experience, advertising, reputation, branding, customer service, price, and positioning. Quality is viewed as a factor of progress, effectiveness, and profitability just as a critical element of seriousness. Consumer loyalty is a champion among the principal MOST examination subjects for as long as a couple of many years (Gallifa and Batalle, 2010; Mbarek et al., 2017).

 

CONTRIBUTION OF STUDY:

 

1)      It's no surprise that consumers today are more likely to try new products. With better safety records and social media reviews, many people take less risk with trying new products because of the low risk of danger.

 

2)      Familiarity bias makes customers return for familiarity, even if it's not the best price or performance. Fifty percent of consumers will choose a familiar product over an unknown one.

 

3)      The strongest motivators for purchases are emotional connections with other people. The first step to doing that is building the image that you want the customer to see. For example, if you're selling a product that's meant for children, then your marketing story needs to be built around something that captures their imagination.

 

 

 

 

 

 

2-    LITERATURE REVIEW:

 

2.1  Perceived Product Value:

The perceived value of the customer represents the overall mental evaluation of a particular item or service (Peterson and Yang, 2004). This construction is often described in terms of equity theory, which defines perceived value in terms of what is deemed appropriate, reasonable, or deemed worthy of the offer, while considering appropriate competitor alternatives Keeping. (Khalifa, 2004; Zeithaml, 1988).

Research by Monroe (2002) shows that one of the basic definitions of this construction is the ratio or trade between quality and price, so it represents the concept of value for money. The perceived value of the customer is one of the most important factors in the purchase intention and, consequently, the desire to buy. Although research has shown that this construction is difficult in both concept and measurement, it is universally accepted that if a consumer considers the value of a product or service to be relatively high, they are more likely to purchase it. Increases (Monroe, 2002; Zeithamal, 1988). Therefore, this study assumes that: H1. Perceived value influences a customer’s willingness to buy private label household cleaning products.

 

Evidence has been produced to reveal that customer perceived product value could be a multidimensional and highly subjective evaluation of things, thus gaining an understanding of the varied dimensions of customer perceived value becomes crucial for developing effective positioning strategies.

This is because customer-perceived product value not only dictates how the organization is seen within the mind of its customers but also provides insight into the kinds of communication channels that an organization might use to maximize the probability that messages are interpreted as intended. As per research by Agarwal and Teas (2001), Sweeney et al. (1999), and Zeithaml (1988), we advocate that customer perceived product value be investigated for its effect on the indirect relationships involving perceived relative price, perceived product quality, perceived risk and willingness to buy. The following hypotheses are therefore set out for empirical testing:

H2a. Perceived value mediates the influence of perceived quality on a customer’s willingness to buy private label household cleaning products.

H2b. Perceived value mediates the influence of perceived relative price on a customer’s willingness to buy private label household cleaning products.

H2c. Perceived value mediates the influence of perceived risk on a customer’s willingness to buy private label household cleaning products.

 

2.2  Perceived Relative Price:

Literature offers different perspectives on the role that value plays in influencing the perceived customer value of a product. Jacobi, etc. (1971) Explain the relative value perceived as the price encoded by the customer by referring to the price of the product as compared to the price of other alternative products. By applying the principles contained in the works of Sweeney et al. (1999) and Kwon et al. (2008),

Accordingly, it has been found that a significant negative relationship exists between perceived price and perceived value (Boksberger and Melsen, 2011; DeSarbo et al., 2001; Kashyap and Bojanic, 2000) in that a high price erodes purchasing power.

Authors such as Huber et al. (2007), Petrick (2002), and Lapierre (1997) emphasize that price is but one variable in the value equation. Other such aspects may include the time or effort in making the purchase as well as service quality, thus not all consumers are fixated on the price-value relationship. Dickson and Sawyer (1986) add that customers do not always recall the exact prices of all products. For such reasons, the pricing of merchandise is seldom the deciding factor.

As well as Jacoby et al. (1971), support the notion that there is a distinction between actual (absolute) price and perceived relative price. To this end, information may be recalled based on other product knowledge or it could be directly recollected from a stored representation. Thus, pricing is seen holistically as being relative within the particular merchandise context. As a result of Sweeney et al.’s (1999) conceptualization, the price construct of this study is measured comparatively as the perceived relative price. Thus, we hypothesize that:

H3. Perceived relative price influences the perceived value of private label household cleaning products.

 

2.3  Perceived Product Quality:

Perceived product quality may be defined as how a customer views a product’s brand equity and overall superiority compared to the available alternatives (Aaker, 1991; de Chernatony, 2009; Richardson, 1997). It relates to a customer’s attitude towards the overall brand experience as opposed to just a product’s particular characteristics. Quality perceptions are thus created when active relationships between suppliers and customers exist (Eriksson et al., 1999). According to some researchers, customers will use product performance, as well as the degree to which the product conforms to manufacturing standards and product-specific attributes, to judge the product quality.

Multiple studies have found a correlation between perceived product quality and perceived value (Dodds et al., 1991; Khalifa, 2004; Rangaswamy et al., 1993;). Literature suggests that there is a positive relationship between the perceived quality and perceived value of a product, thus when comparing private label brands to manufacturer brands, higher perceived product quality may increase the perceived value and, consequently, a customer’s willingness-to-buy (Cronin et al., 2000; Snoj et al., 2004). Therefore, this study hypothesizes that:

H4. Perceived quality influences the perceived value of private label household cleaning products.

Numerous studies by authors such as Varki and Colgate (2001), Etgar and Malhotra (1981) and Gerstner (1985) share the view that perceived relative price is also a determinant of perceived product quality, whereby a positive correlation exists between the variables. Hence, this study hypothesis that:

H5. Perceived relative price influences the perceived quality of private label household cleaning products.

 

Pioneering research by Monroe and Krishnan (1985) profiled the positive relationship that price has with perceived product value, through its influence on perceived quality. This highlights the possible mediating nature of perceived product quality with regards to perceived relative price among customers purchasing private label products. To allow compliance with this, and test the effect, we hypothesize the following:

H6. Perceived quality mediates the influence of perceived relative price on the perceived value of private label household cleaning products.

 

2.4  Perceived Risk:

Dowling (1986) defines perceived risk as the uncertainty of the desired performance that all customers experience when making purchasing decisions. Mitchell (1998) contends that perceived risk is a “multidimensional phenomenon” that can be segmented into different risk components. The more common components of perceived risk include functional/performance, physical, financial, social, and psychological risk (Jacoby and Kaplan, 1972; Laforet, 2007; Murphy and Enis, 1986; Peter and Tarpey, 1975; Schiffman and Kanuk, 2009; Shimp and Bearden, 1982). Customers are certainly conscious of the losses that may arise due to product failure (Sweeney et al., 1999), hence a product with a relatively high perceived likelihood of malfunction will have a lower perceived value (Livesey and Lennon, 1993; Narasimhan and Wilcox, 1998; Tam, 2012). Richardson et al. (1996) advocate that the level of perceived risk in a specific product category is a vital factor in private label brand purchases. Thus, certain categories of merchandise are more suitable for private labels than others. We, therefore, hypothesize that:

H7. Perceived risk influences the perceived value of private label household cleaning products.

 

There is strong support from the literature that consumers rely on quality concepts to create perceptions about hazards (Batra and Sinha, 2000; Sweeney et al., 1999; Seattle & Elric, 1989). Previous research has shown that the higher the level of perceived quality, the lower the risk in a particular product category. (Batra and Sinha, 2000; Hoch and Banerji, 1993; Narasimhan and Wilcox, 1998; Sabiote et al., 2012). Therefore, this study hypothesizes that:

H8. Perceived quality influences the perceived risk of private label household cleaning products.

 

It has also been put forward that perceived risk is a mediator between perceived product value and perceived product quality (Agarwal and Teas, 2001; Snoj et al., 2004; Sweeney et al., 1999). In this light, we too suggest that:

H9. Perceived risk mediates the influence of perceived quality on the perceived value of private label household cleaning products.

 

3- DATA & METHODOLOGY

 

 

 

Factor Analysis

 

 

KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.656
Bartlett's Test of Sphericity	Approx. Chi-Square	298.956
	df	66
	Sig.	.000

 

 

Communalities
	Initial	Extraction
BI1	1.000	.506
BI2	1.000	.400
BI3	1.000	.656
BI4	1.000	.661
BA1	1.000	.708
BA2	1.000	.809
BA3	1.000	.536
BA4	1.000	.674
BAT1	1.000	.572
BAT2	1.000	.706
BAT3	1.000	.550
BAT4	1.000	.776
Extraction Method: Principal Component Analysis.

 

 

Total Variance Explained
Component	Initial Eigenvalues			Extraction Sums of Squared Loadings
	Total	% of Variance	Cumulative %	Total	% of Variance	Cumulative %
1	3.385	28.209	28.209	3.385	28.209	28.209
2	1.554	12.953	41.162	1.554	12.953	41.162
3	1.401	11.673	52.835	1.401	11.673	52.835
4	1.212	10.104	62.939	1.212	10.104	62.939
5	.923	7.692	70.631
6	.833	6.939	77.570
7	.625	5.210	82.780
8	.589	4.910	87.689
9	.466	3.881	91.570
10	.431	3.590	95.160
11	.335	2.790	97.949
12	.246	2.051	100.000
Extraction Method: Principal Component Analysis.

 

 

 

 

Component Matrixa
	Component
	1	2	3	4
BI1	.397	.053	-.537	.240
BI2	.576	.145	-.193	-.098
BI3	.531	.289	-.535	-.071
BI4	.678	.006	-.331	.302
BA1	.569	-.504	.305	.194
BA2	.588	-.505	.419	.181
BA3	.617	-.380	-.069	-.079
BA4	.581	-.146	-.091	-.553
BAT1	.475	.429	.260	.308
BAT2	.269	.510	.314	.524
BAT3	.585	.188	.274	-.311
BAT4	.352	.542	.397	-.448
Extraction Method: Principal Component Analysis.
a. 4 components extracted.

 

 

Reliability

 

 

 

Scale: ALL VARIABLES

 

 

 

Case Processing Summary
		N	%
Cases	Valid	100	80.6
	Excludeda	24	19.4
	Total	124	100.0
a. Listwise deletion based on all variables in the procedure.

 

 

Reliability Statistics
Cronbach's Alpha	N of Items
.673	4

 

 

Reliability

 

 

Scale: ALL VARIABLES

 

Case Processing Summary
		N	%
Cases	Valid	100	80.6
	Excludeda	24	19.4
	Total	124	100.0
a. Listwise deletion based on all variables in the procedure.

 

 

 

Reliability Statistics
Cronbach's Alpha	N of Items
.713	4

 

 

Reliability

 

 

Scale: ALL VARIABLES

 

 

Case Processing Summary
		N	%
Cases	Valid	100	80.6
	Excludeda	24	19.4
	Total	124	100.0
a. Listwise deletion based on all variables in the procedure.

 

 

Reliability Statistics
Cronbach's Alpha	N of Items
.608	4

 

 

Reliability

 

 

Scale: ALL VARIABLES

 

 

 

 

Case Processing Summary
		N	%
Cases	Valid	100	80.6
	Excludeda	24	19.4
	Total	124	100.0
a. Listwise deletion based on all variables in the procedure.

 

 

Reliability Statistics
Cronbach's Alpha	N of Items
.579	3

 

 

Frequencies

 

 

Statistics
		Brand Image	Brand Awareness	Brand Attitude
N	Valid	100	100	100
	Missing	24	24	24
Mean		3.3925	3.7525	3.4250
Median		3.5000	3.7500	3.5000
Mode		4.00	4.00a	3.50
Std. Deviation		.78355	.89506	.76335
Variance		.614	.801	.583
Skewness		-.982	-.581	-.005
Std. Error of Skewness		.241	.241	.241
Kurtosis		.970	-.139	.091
Std. Error of Kurtosis		.478	.478	.478
Range		4.00	4.00	3.75
Minimum		1.00	1.00	1.25
Maximum		5.00	5.00	5.00
a. Multiple modes exist. The smallest value is shown

 

 

Frequency Table

 

 

Brand Image
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	1.00	2	1.6	2.0	2.0
	1.25	1	.8	1.0	3.0
	1.75	2	1.6	2.0	5.0
	2.00	3	2.4	3.0	8.0
	2.25	4	3.2	4.0	12.0
	2.50	4	3.2	4.0	16.0
	2.75	5	4.0	5.0	21.0
	3.00	8	6.5	8.0	29.0
	3.25	11	8.9	11.0	40.0
	3.50	13	10.5	13.0	53.0
	3.75	16	12.9	16.0	69.0
	4.00	20	16.1	20.0	89.0
	4.25	7	5.6	7.0	96.0
	4.50	2	1.6	2.0	98.0
	4.75	1	.8	1.0	99.0
	5.00	1	.8	1.0	100.0
	Total	100	80.6	100.0
Missing	System	24	19.4
Total		124	100.0

 

 

Brand Awareness
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	1.00	1	.8	1.0	1.0
	1.75	1	.8	1.0	2.0
	2.00	4	3.2	4.0	6.0
	2.25	2	1.6	2.0	8.0
	2.50	5	4.0	5.0	13.0
	2.75	2	1.6	2.0	15.0
	3.00	11	8.9	11.0	26.0
	3.25	5	4.0	5.0	31.0
	3.50	8	6.5	8.0	39.0
	3.75	12	9.7	12.0	51.0
	4.00	13	10.5	13.0	64.0
	4.25	8	6.5	8.0	72.0
	4.50	6	4.8	6.0	78.0
	4.75	13	10.5	13.0	91.0
	5.00	9	7.3	9.0	100.0
	Total	100	80.6	100.0
Missing	System	24	19.4
Total		124	100.0

 

 

Brand Attitude
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	1.25	1	.8	1.0	1.0
	1.75	1	.8	1.0	2.0
	2.00	2	1.6	2.0	4.0
	2.25	3	2.4	3.0	7.0
	2.50	9	7.3	9.0	16.0
	2.75	5	4.0	5.0	21.0
	3.00	16	12.9	16.0	37.0
	3.25	6	4.8	6.0	43.0
	3.50	21	16.9	21.0	64.0
	3.75	8	6.5	8.0	72.0
	4.00	14	11.3	14.0	86.0
	4.25	3	2.4	3.0	89.0
	4.50	4	3.2	4.0	93.0
	4.75	1	.8	1.0	94.0
	5.00	6	4.8	6.0	100.0
	Total	100	80.6	100.0
Missing	System	24	19.4
Total		124	100.0

 

 

 

 

 

Correlations

 

 

 

Descriptive Statistics
	Mean	Std. Deviation	N
Brand Image	3.3925	.78355	100
Brand Awareness	3.7525	.89506	100
Brand Attitude	3.4250	.76335	100

 

 

Correlations
		BI	BA	BAT
Brand Image	Pearson Correlation	1	.374**	.302**
	Sig. (2-tailed)		.000	.002
	N	100	100	100
Brand Awareness	Pearson Correlation	.374**	1	.270**
	Sig. (2-tailed)	.000		.007
	N	100	100	100
Brand Attitude	Pearson Correlation	.302**	.270**	1
	Sig. (2-tailed)	.002	.007
	N	100	100	100
**. Correlation is significant at the 0.01 level (2-tailed).

 

 

Regression

 

 

Variables Entered/Removeda
Model	Variables Entered	Variables Removed	Method
1	Brand Awareness, Brand Imageb	.	Enter
a. Dependent Variable: Brand Attitude
b. All requested variables entered.

 

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.346a	.120	.102	.72347
a. Predictors: (Constant), Brand Awareness, Brand Image

 

 

ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	6.917	2	3.458	6.608	.002b
	Residual	50.771	97	.523
	Total	57.688	99
a. Dependent Variable: Brand Attitude
b. Predictors: (Constant), Brand Awareness, Brand Image

 

 

Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	2.068	.381		5.430	.000
	Brand Image	.228	.100	.234	2.275	.025
	Brand Awareness	.156	.088	.183	1.779	.078
a. Dependent Variable: Brand Attitude

 

 

Descriptive Statistics
	N	Minimum	Maximum	Mean	Std. Deviation	Skewness		Kurtosis
	Statistic	Statistic	Statistic	Statistic	Statistic	Statistic	Std. Error	Statistic	Std. Error
Brand Image	100	1.00	5.00	3.3925	.78355	-.982	.241	.970	.478
Brand Awareness	100	1.00	5.00	3.7525	.89506	-.581	.241	-.139	.478
Brand Attitude	100	1.25	5.00	3.4250	.76335	-.005	.241	.091	.478
Valid N (listwise)	100

 

4- RESULT:

variable	categories	frequencies	percentage
age	18 – 25 26 – 35 36 – 45 45 – older	90 10 4 0	90% 10% 0% 0%
education	Intermediate Bachelors Masters other	40 6 4 0	80% 12% 8% 0%
marital status	single Married Divorced Widowed Separated	41 8 1 0 0	82% 16% 2% 0% 0%
gender	Male Female	74 26	74% 26%

 

 

4.1 Demographic Description:

The data collected for this study were through survey questionnaire. The target population was the People of in Karachi Pakistan; the sample size is of 100 respondents.

The data of demographics collected was analyzed through SPSS where frequency test was applied. The respondents from different age group have contribution in this survey. The age group divided into 4 categories. According to Table 90% of the respondents belongs to the age group 1 i.e., 18-25 years, and 10% of the respondents belongs to the age group 2 i.e. 26-35 years, 0% of the respondents belongs to the age group 3 i.e. 36-45 years, and above 45 years having no participation, it is to be observed through the data among 100 respondents that 26 (26.0%) of the respondents were female and 74 (74.0%) of the respondents where male have participated in this research. The respondents have different education levels. The category of education level is divided into 4 categories. The respondents have different marital status group.

 

4.2       Chronabach’s Alpha:

It investigates the inter item correlation in all variables. Correlation between all responses checked by it. Table shows reliability analysis of all variables. According to Uma Sekaran

(2003), the closer the reliability coefficient Cronbach’s Alpha gets equal to 0.70, the better is the reliability. The first variable Brand Image value has 4 items and the value of alpha of these items is 0.673. In the second variable Brand Awareness have 4 items and the value of alpha is

0.713. The third variable Brand Attitude value has 4 items and the value of alpha of these items is 0.608. it means all the items of Brand Image and Brand Attitude are correlated.

Variables	items	Chronabach’s alpha
Brand Image	4	0.673
Brand Awareness	4	0.713
Brand Attitude	4	0.608

 

4.3       Factor Analysis:

The present analysis used principal components method to reduce its likert based questionnaire items into best manageable proposed factors. To determine the adequacy of the sample, Kaiser-Meyer-Olkin was used which, showed the value of 0.656 which is above 0.50 and suggests that the sample is sufficient to run factor analysis. Bartlett’s test of sphericity (Approx. Chi-Square = 298.956, df = 66, p < 0.05). All item of the variables are correlated with each other significant. All items under a specific variable are presenting itself.

KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		.656
Bartlett's Test of Sphericity	Approx. Chi-Square	298.956
	df	66
	Sig.	.000

 

4.4 Descriptive Analysis:

Data were analyzed using descriptive analysis via SPSS. Maximum Value of Brand Awareness is 5, Brand Attitude is 5 while 5 is for Brand Image.

Descriptive Statistics
	N	Minimum	Maximum	Mean	Std. Deviation	Skewness		Kurtosis
	Statistic	Statistic	Statistic	Statistic	Statistic	Statistic	Std. Error	Statistic	Std. Error
Brand Image	100	1.00	5.00	3.3925	.78355	-.982	.241	.970	.478
Brand Awareness	100	1.00	5.00	3.7525	.89506	-.581	.241	-.139	.478
Brand Attitude	100	1.25	5.00	3.4250	.76335	-.005	.241	.091	.478
Valid N (listwise)	100

 

4.5. Correlation analysis:

 

Store environment has significate and positive correlation with Brand Attitude (r= .302**, P<0.05), Social influence (r= .270**, P<0.05). Highest correlation between Store environment and social influence is 30.2%.

 

Correlations
		BI	BA	BAT
Brand Image	Pearson Correlation	1	.374**	.302**
	Sig. (2-tailed)		.000	.002
	N	100	100	100
Brand Awareness	Pearson Correlation	.374**	1	.270**
	Sig. (2-tailed)	.000		.007
	N	100	100	100
Brand Attitude	Pearson Correlation	.302**	.270**	1
	Sig. (2-tailed)	.002	.007
	N	100	100	100
**. Correlation is significant at the 0.01 level (2-tailed).

 

 

4.6. Regression:

Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	2.068	.381		5.430	.000
	Brand Image	.228	.100	.234	2.275	.025
	Brand Awareness	.156	.088	.183	1.779	.078
a. Dependent Variable: Brand Attitude

 

ANOVAa
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	6.917	2	3.458	6.608	.002b
	Residual	50.771	97	.523
	Total	57.688	99
a. Dependent Variable: Brand Attitude
b. Predictors: (Constant), Brand Awareness, Brand Image

 

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.346a	.120	.102	.72347
a. Predictors: (Constant), Brand Awareness, Brand Image

 

4.7. Adjusted square:

 

Component Matrixa
	Component
	1	2	3	4
BI1	.397	.053	-.537	.240
BI2	.576	.145	-.193	-.098
BI3	.531	.289	-.535	-.071
BI4	.678	.006	-.331	.302
BA1	.569	-.504	.305	.194
BA2	.588	-.505	.419	.181
BA3	.617	-.380	-.069	-.079
BA4	.581	-.146	-.091	-.553
BAT1	.475	.429	.260	.308
BAT2	.269	.510	.314	.524
BAT3	.585	.188	.274	-.311
BAT4	.352	.542	.397	-.448
Extraction Method: Principal Component Analysis.
a. 4 components extracted.

 

5. REFERENCES:

 

Koubaa, Y. (2008). Country of origin, brand image perception, and brand image structure. Asia Pacific Journal of Marketing and Logistics, 20(2), 139 – 155.

Radder, L., & Huang, W. (2008). High-involvement and low-involvement products. Journal of Fashion Marketing and Management, 12(2), 232 - 243.

Zimmer, M., & Bhat, S. (2004). The reciprocal effects of extension quality and fit on parent brand attitude. Journal of Product & Brand Management, 13(1), 37 - 46.

Cervino, J., Sanchez, J. and Cubillo, J.M. (2005), ‘‘Made in effect, competitive marketing strategy and brand performance: an empirical analysis for Spanish brands’’, Journal of American Academy of Business, Vol. 6 No. 2, pp. 237-43.

Czepiec, H. and Cosmas, S. (1983), ‘‘Exploring the meaning of made in: a look at national stereotypes, product evaluations, and hybrids’’, paper presented at Annual Meeting of the Academy of International Business, San Francisco, CA.

D’Astous, A. and Ahmad, A.S. (1999), ‘‘The importance of the country images in the formation of the ‘consumer product perceptions’’, International Marketing Review, Vol. 16 No. 2, pp. 108-125.

Dobni, D. and Zinkhan, G. M. (1990), ‘‘In search of brand image: a foundation analysis’’, in Low, G. S. and Lamb, C. W. (2000), ‘‘the measurement and dimensionality of brand associations’’, The Journal of Product and Brand Management, Vol. 9 No. 6, pp. 350-62.