UNDERSTANDING THE ANTECEDENTS OF BRAND LOYALTY FOR IMPROVED BRAND SUSTAINABILITY
Kunjal Sinha, Rajesh Khajuria, Hetal Thakar Summary
Understanding the loyalty factors which affect consumers while selecting a brand becomes the need of an hour, which in turn makes brand sustainable. The current study is based on understanding the antecedents of brand loyalty for improved brand sustainability for cosmetic industry. The data is collected based on descriptive re-search design. The sample size is 500 working women of Gujarat (India). A well-de-signed structured questionnaire consisting of 29 statements related to brand associa-tion, brand equity and brand trust, is used to collect the responses measured on a five-point Likert scale (Strongly Disagree to Strongly Agree). The factor analysis is per-formed to draw factors of importance. The results revealed that the factors such as brand trust, brand association, perceived quality, brand name, brand preferences, perceived value and risk, product attributes and risk are the major factors affecting brand loyalty.
Keywords: Brand Loyalty, Sustainability, Brand Association, Brand Equity, Brand Trust Introduction
The cosmetics and personal care industry is one of the fastest growing sectors in India. The cosmetic sector in India is continuously rising and increasing shelf space in retail stores as well as becoming most popular stocking products from around the world. According to a Times of India report, cosmetic and beauty industry in India is expected to reach INR 170 billion by 2020from the current INR 60 billion, which shows 15–20% growth rate per annum.
The Indian population comprises of 623.7 million (51.54%) males, compared to 586.4 million (48.46%) females. A total of 20.4% women were employed in the organized sector in 2010 with 17.9% working in the public sector and 24.5% in the private. In the rural sector, 55.7% females were selfǦemployed, 4.4% females had regular wage/salaried employment and 39.9% females were casual labors [11]. The Indian demographics shows that as number of working women are increasing day by day awareness about beauty and cosmetic usage is also increasing that is the major reason of growth of the cosmetic industry in India. The current study focuses on understanding the antecedents of brand loyalty in cosmetic industry for working women in the state of Gujarat.
Table 1. Gender Composition of Population 2011 (India)
2001 2011
Population
(in mn) Proportion (in %) Population (inmn) Proportion (in %)
Male 532.2 51.74 623.7 51.54
Female 496.5 48.26 586.4 48.46
Gender Ratio 933 940
Sources: Census Report, 2011.
As per census 2011 (Table 2), Gujarat Female workforce in rural were 32% while in urban it was 11.4% whereas total female workforce was 23.38%. Hence it is showing that contribution of total female workforce population is increasing. The increasing ratio of number of working women is the motive behind this research. The researchers have identified that population of number of working women is increasing day by day as well as the working women are the major prospec-tus/customers of the cosmetic products. Hence, researchers have selected population of the working women in the state of Gujarat.
Table 2. State Wise Workforce Population Rate (%) in 2011 (Gujarat)
1. Literature Review
Brand Association – [3]have conducted a study on using free association to examine the rela-tionship between the characteristics of brand associations and brand equity. The objective of this study was to identify the types of brand association and examine the relationship between associa-tion characteristics and brand equity. The researcher has concluded from the study that greater the numbers of the core brand association, the higher the brand equity which has significant relationship with brand loyalty also. However, there is no significant difference for the other brand associations between the high and low equity brands.
Sasmita and Mohd[12] have studied young consumers’ insights on brand equity: Effects of brand association, brand loyalty, brand awareness, and brand image. The purpose of this study was to examine the effects of brand association, brand loyalty, brand awareness, and brand image on brand equity among young consumers. Data from 200 young consumers were analyzed using de-scriptive, correlation and multiple regression analysis. The result of the authenticated that brand awareness affects brand equity among young consumers. Further it shows that there is a positive relationship among brand association, brand loyalty, brand awareness, and brand image on brand equity.
Brand Equity – Aaker [1] have quoted that there are five categories of assets underlying brand equity: brand loyalty, name awareness, perceived quality, brand associations, and other proprietary brand assets such as patents and channel relationships. Further Yoo et. al. [14] have studied that there exists positive relationship between brand loyalty, perceived quality, and brand awareness/as-sociations and it has positive effect on brand equity.
Souri [13] has investigated the relationship between brand equity, brand loyalty and customer satisfaction. The sample of 384 customers was selected as a stepwise clustering. Data gathered by standard questionnaire with 23 questions that its validity and reliability confirmed and was distrib-uted among the statistical population. Data analysis was performed using descriptive statistics and inferential statistics. At the level of Descriptive statistics, indices such as frequency and frequency percentage were used and in inferential statistics, correlation methods, structural equation modeling, path analysis has been done. The result of the analysis was showing the existence of a significant and positive relationship of brand equity on customer satisfaction and loyalty, as well as correlation is also found among the brand equity and loyalty. Hence, it is concluded that brand equity has sig-nificant positive effect on brand loyalty.
Brand Trust – Choirulal [2] have conducted study on building brand loyalty through increasing brand trust and brand affect. The research was conducted to test the influence of brand trust and brand affect toward brand loyalty. This research uses descriptive analytical method, which describes a phenomenon that occurs at the object of research and explanatory method. In the study model is tested to study the relationship between latent variables using multiple regression analysis. Based on the result it is concluded that there is a positive and significant influence of brand trust and it affects brand loyalty.
Matzler et. al. (2008)have studied risk aversion and brand loyalty – the mediating role of brand trust and brand affect. The purpose of this paper is to explore the relationship between the customer's risk aversion and its relationship with brand loyalty and to test empirically whether this relationship is mediated by brand trust and brand affect. A randomly selected sample of Austrian mobile phone users was drawn. Their risk aversion, two forms of loyalty (attitudinal and repurchase loyalty), brand trust and brand affect have been measured with existing and tested scales. The hypothesized model
has been tested using PLS (Partial least squares). The outcome of study revealed that customer's risk aversion is significantly related to the two forms of loyalty (attitudinal loyalty and brand loyalty). When brand affect and brand trust are introduced into the model, the previously highly significant relationship between domainǦspecific risk aversion and attitudinal loyalty becomes insignificant and the risk aversionǦrepurchase relationship becomes much weaker, while risk aversion strongly influ-ences brand trust and brand affect. Hence, it shows that brand trust has positive significant effect on brand loyalty.
Brand Sustainability – When someone talks about sustainability, the first thought which comes to mind is being green. However, the brand sustainability means the brands capability to endure over the long term and talking about a sustainable brand it can also mean how long the brand will survive and thrive. The term sustainable brands in form of creating/increasing number of brand loyal cus-tomers. The loyalty these days is a biggest challenge for the marketers due to the competitive market for each and every products/service.
Kuchinka et. al. [5] conducted a study on Consumer Attitudes toward Sustainable Development and Risk to Brand Loyalty. The study reveals the importance of understanding how business deci-sions focused on sustainability can impact companies, due to the risks associated with brand loyalty. The study was aiming to study that what extent will brand loyalty be impacted once consumers are exposed to an organization’s sustainable development plan? The study results indicate that there is a strong, positive correlation between attitudes towards sustainability and brand.
Moisescu [7] have conducted research on from perceptual corporate sustainability to customer loyalty: a multi-sectorial investigation in a developing country. The purpose of this study was to investigate the impact of customer based perceptual corporate sustainability on customer loyalty in a comparative manner, in four important industries (mobile telecommunications services, retail banking services, dairy products and personal care products) in a developing country. A consumer survey was implemented among a sample of 1464 consumers from the urban area of a developing European country. The research reveals that customer-based perceptual corporate sustainability sig-nificantly and positively impacts customer loyalty in all investigated industries, with a stronger im-pact in retail banking services and a lower one in the case of personal care products. Further, it proves that there is relationship between customer loyalty and perceived corporate sustainability as a complex construct, yielding relevant multi-sectorial insights and filling a knowledge gap in the particular socio-cultural and economic context of a developing country.
Haket (2016) have conducted a study on the customer perceived value of sustainability. The study contributes to this important topic by exploring the potential value-adding capabilities of sus-tainability within a B2B industry that has been insignificantly studied, and where there is an eminent importance for sustainability. The study reveals that there is a positive and significant relation be-tween the B2B customer satisfaction and their price acceptance and B2B customer loyalty, has been established with the specific sustainability measurements. Sustainability can be used to increase the satisfaction of the B2B customer, and subsequently, increase their loyalty. Furthermore, as a result of increasing the satisfaction of the facility manager through sustainability, the loyalty of these cus-tomers could also be positively affected. Because of the various long-term benefits of loyal custom-ers, a company should focus on obtaining their loyalty.
Based on literature review antecedents and structure were identified. The variables derived from literature review have direct effect on building brand loyalty. Conceptually it is proved that brand association, brand equity and brand trust are significantly influenced brand loyalty.
2. Objective of the Study and Research Methodology
The study is performed with an objective to understand the antecedents of brand loyalty, which in turn can improve brand sustainability.
The current study is based on understanding the antecedents of brand loyalty for improved brand sustainability for cosmetic industry. The data is collected based on descriptive research design. As the researchers aim to study the antecedents of brand loyalty while examining the relationships of various variables under study, descriptive research design is used. The sample size is 500 working women of Gujarat. The samples were collected from cities of Gujarat (India) like Ahmedabad, Surat, Rajkot, Bhavnagar and Vadodara. Non-Probability Convenience Sampling technique is used for sampling as it was not possible to know the exact population data. A well-designed structured ques-tionnaire consisting of 29 statements related to brand association, brand equity and brand trust, is used to collect the responses measured on a five-point Likert scale (Strongly Disagree to Strongly Agree).
3. Data Analysis
For the current study factor analysis is used to reduce the number of factors that are used to measure antecedent affecting brand loyalty. Respondents were asked to give their responses on five-point likert scale (1 – Strongly disagree to 5 – Strongly agree).
The Reliability statistics values (Table 3) indicates high level of internal consistency in the items used for analysis. The value of Cronbach’s Coefficient (Alpha) is acceptable and desirable confirm-ing that the scale is reliable to be used.
Table 3. Construct Reliability Statistics
Constructs Cronbach's Alpha
Brand Association 0.764
Brand Trust 0.883
Brand Equity 0.859
Brand Loyalty Antecedents 0.889
Bartlett’s Test of Sphericity: The data as shown in (Table 4) reveals that the significance value of Bartlett’s Test is 0.000, this leads to rejection of the idea that the correlation matrix is identity matrix.
Kaiser-Meyer-Olkin Test for Sampling Adequacy: The Kaiser-Meyer-Olkin (KMO) meas-ure if sampling adequacy is an index used to examine the appropriateness of factor analysis. It com-pares the magnitudes of observed correlation coefficients to magnitude of partial correlation coeffi-cients. High value (between 0.5 and 1.0) indicates factor analysis is appropriate.
Small values of KMO Statistic indicate that correlations between pair of variables cannot be explained by other variables, and hence, factor analysis is not suitable. The data has KMO statistic as 0.870 (Table 4), which is greater than 0.5. Hence, this value is acceptable and justifies the appro-priateness of factor analysis.
Table 4. KMO and Bartlett's Test KMO
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .870 Bartlett's Test of Sphericity
Approx. Chi-Square 7535.706
Df 406
Sig. 0.000
4. Communalities
Communality is the amount of variance a variable can explain with all the factors being consid-ered. This is also the percentage of variance explained by the common factors. The method selected for conducting the factor analysis here is Principal Component Analysis. In this method the total variance in the data is considered. The initial communalities for Principal Component Analysis are 1. However, the primary concern is the extracted communalities, which are achieved after extraction of factors. The communalities are shown in below table 3. The table shows that the extracted com-munalities are high, and hence, acceptable for all the statements.
Table 5.Communalities
Statements Initial Extraction
Products from my brand are authentic 1.000 .638
My brand gives me glamorous look 1.000 .690
Products of my brand gives high performance 1.000 .764
I trust quality of my brand 1.000 .599
My brand offers me innovative products 1.000 .550
My brand gives me sensuous feelings 1.000 .611
The products offered by my brand are trendy 1.000 .606 Brand name attracts me to purchase the products 1.000 .798 Image of my brand attracts me to purchase 1.000 .762 Brand name is most important regardless of price 1.000 .669 I can recognize my brand among competing brands 1.000 .627 Even if other brand have same feature I would prefer to buy from my brand 1.000 .706 My brand helps to attain the life I strive for 1.000 .780 I use this brand to define and express I and me within myself 1.000 .796 I can make many association between my life and brand 1.000 .795 I think other judge me as person by brand which I use 1.000 .717 I feel that well known brand/s perform better as compared to less known brands 1.000 .721 Cosmetics products from well known brands are always stylish as compared to
less known brands 1.000 .803
Cosmetics products from well known brands are always durable as compared
Statements Initial Extraction A high-priced cosmetic product usually has all day staying power 1.000 .662 I feel risky while using new products from the same brand 1.000 .690 I always check expiry date before using cosmetic products 1.000 .650
My brand is reasonably priced 1.000 .721
My brand offers value for the money 1.000 .627
I can rely on my brand 1.000 .647
My brand is an honest brand 1.000 .738
My brand meets my expectations 1.000 .710
Cosmetic products from my brand are safe to use 1.000 .650 Celebrity of my brand does influence my buying decision 1.000 .598
Extraction Method: Principal Component Analysis. 5. Variance explained
It is required that the scale constructed and the components extracted should be able to explain maximum variance in the data. For this, an analysis of the Eigen values is required. Eigen value represents the total variance explained by each factor. The data (Table 6) shows that Eigen values of all the components that can be extracted. A maximum of 29 components can be extracted as there are 29 statements. The table also shows the cumulative variance. However, it is required that the maximum amount of variance should be explained in minimum number of components – for this reason extraction of the components is required. Only those factors are extracted for which the Eigen values are greater than one. These factors are eight in number and together contribute 69.273% of total variance. This is a fair percentage of variance to be explained and assumes of the appropriate-ness of the factor analysis. Thus, to measure antecedent of brand loyalty extracted eight dimensions from a total of 29 items through factor analysis.
Table 6. Total Variance Explained
Com-ponent
Initial Eigen Values Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Va-riance Cumula-tive % Total % of Va-riance Cumula-tive % Total % of Va-riance Cumula-tive % 1 8.659 29.858 29.858 8.659 29.858 29.858 3.828 13.201 13.201 2 2.660 9.174 39.031 2.660 9.174 39.031 3.543 12.217 25.418 3 2.302 7.937 46.969 2.302 7.937 46.969 3.505 12.086 37.504 4 1.887 6.508 53.476 1.887 6.508 53.476 2.835 9.776 47.280 5 1.330 4.585 58.061 1.330 4.585 58.061 2.402 8.283 55.564 6 1.143 3.943 62.004 1.143 3.943 62.004 1.429 4.929 60.493 7 1.092 3.766 65.770 1.092 3.766 65.770 1.417 4.888 65.380 8 1.016 3.503 69.273 1.016 3.503 69.273 1.129 3.893 69.273 9 .856 2.953 72.226 10 .805 2.776 75.002 11 .765 2.637 77.639
Com-ponent
Initial Eigen Values Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings Total % of Va-riance Cumula-tive % Total % of Va-riance Cumula-tive % Total % of Va-riance Cumula-tive % 12 .600 2.070 79.710 13 .590 2.033 81.743 14 .560 1.929 83.672 15 .550 1.896 85.568 16 .485 1.672 87.240 17 .454 1.566 88.806 18 .399 1.374 90.180 19 .388 1.338 91.518 20 .336 1.158 92.676 21 .307 1.060 93.736 22 .298 1.026 94.762 23 .276 .952 95.714 24 .269 .929 96.643 25 .227 .784 97.426 26 .222 .765 98.192 27 .196 .677 98.869 28 .176 .606 99.475 29 .152 .525 100.00
Extraction Method: Principal Component Analysis.
Further (table 6) data shows that extraction sum of square loadings for the scale for measuring the antecedents. However, a careful look at table 4 shows that 69.273% variance is not uniformly distributed across all components where only the first component accounts for 29.858% of variance. Thus, in order for the variance to be uniformly distributed across all the components a rotation of the components matrix is required. Components matrix is the loadings of various variables to the extracted components.
Although the initial or unrotated matrix indicates the relationship between the factors and indi-vidual variables, it seldom results in factors that can be interpreted, because the factors are correlated with many variables. In such a complex matrix it is difficult to interpret the factors. Therefore, through rotation, the factor matrix is transformed into a simpler one that is easier to interpret. The rotation method used is Varimax procedure – This is an orthogonal method of factor rotation that minimizes the number of variables with higher loadings on a factor, thereby enhancing the interpret-ability of the factors.
The variance explained by each component after the rotation method is shown in the table (Ta-ble 6). It is visi(Ta-ble from this ta(Ta-ble that the variance is now evenly distributed in a range of 13.201% – 3.893%, which was 29.858%–3.503% before rotation.
Rotated Factor Matrix: An analysis of factor loadings in the rotated factor matrix helps in interpreting and naming the factors that have been extracted in the earlier section. Interpretation is done by identifying the statements that have very high loadings on the same component. These fac-tors can then be interpreted in terms of the statements that load highly on it. The (Table 7) shows the rotated component matrix.
Table 7. Rotated Component Matrixa
Component
1 2 3 4 5 6 7 8
Products from my brand
are authentic .740 .208 .049 .062 .127 .133 .068 .051
My brand gives me
glamorous look .789 .133 .071 .109 .064 .157 –.045 .046
Products of my brand
gives high performance .810 .251 .048 .138 .094 .123 –.013 –.022
I trust quality of my
brand .710 .245 .149 .046 .090 .046 –.008 –.016
My brand offers me
in-novative products .637 .229 .101 .130 .210 .011 .101 –.097
My brand gives me
sen-suous feelings .431 –.030 .175 .032 .128 –.241 .080 .559
The products offered by
my brand are trendy .513 .274 .048 –.033 .477 –.048 .067 .176
Brand name attracts me
to purchase the products .205 .161 .097 .268 .798 .104 –.030 –.003
Image of my brand
at-tracts me to purchase .131 .147 .115 .180 .817 .101 –.002 –.004
Brand name is most im-portant regardless of price
.258 –.060 .115 .151 .590 .380 .264 .017
I can recognize my brand
among competing brands .234 .028 .120 .010 .341 .601 –.051 .276
Even ifother brand have same feature I would pre-fer to buy from my brand
.167 .226 .192 .085 .117 .745 .006 –.115
My brand helps to attain
the life I strive for .160 .079 .798 .071 .001 .322 .028 .040
I use this brand to define and express I and me
within myself .101 .084 .871 .032 .029 .130 –.007 .028
I can make many associ-ation between my life
and brand .033 .138 .854 .159 –.027 .102 .043 .083
I think other judge me as person by brand which I use
.085 .185 .747 .151 .238 –.148 –.032 –.125
I feel that well known brand/s perform better as compared to less known brands
.061 .182 .198 .771 .171 –.039 –.032 .137
Cosmetics products from well known brands are always stylish as com-pared to less known brands
.114 .129 .086 .853 .187 .015 –.035 .039
Cosmetics products from
Component
1 2 3 4 5 6 7 8
always durable as com-pared to less known brands
A high priced cosmetic products usually has all day staying power
.108 .153 .034 .659 .186 .060 .376 –.107
I feel risky while using new products from the same brand
–.010 –.024 –.025 .177 –.035 –.033 .808 .050
I always check expiry date before using
cos-metic products –.125 .177 –.197 .072 –.023 .135 .033 .735
My brand is reasonably
priced .082 .547 .092 .056 .195 .058 .601 .024
My brand offers value
for the money .213 .616 .175 .076 .128 –.021 .341 .180
I can rely on my brand .237 .739 .144 .111 .032 .076 –.005 .069
My brand is an honest
brand .308 .745 .147 .228 .024 .113 –.008 –.019
My brand meets my
ex-pectations .274 .747 .185 .171 .036 .103 –.007 .049
Cosmetic products from
my brand are safe to use .211 .728 .129 .127 .205 .028 –.008 .000
Celebrity of my brand does influence my
buy-ing decision .082 .263 .662 –.026 .191 –.058 .034 –.204
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 8 iterations.
Under Varimax rotation, 6 out of 29 statements have factor loadings ≥0.550 in case of Factor 1. This reveals that 20.68% of the statements are clubbed into Factor 1. In the similar way 5 out of 29 statements have factor loading ≥0.550 in case of Factor 2. This reveals that 17.24% of the statements are clubbed into Factor 2. Further 5 out of 29 statements have factor loading ≥0.550 in case of Factor 3, which reveals that 17.24% of the statements are clubbed in Factor 3. In similar way 4 out of 29 statements have factor loading ≥0.550 in case of Factor 4 and which reveals that 13.79% of the statements are clubbed in Factor 4. There are 3 out of 29 statements have factor loading ≥0.550 in case of Factor 5, which reveals that 10.34% of the statements are clubbed in Factor 5. Further there are 2 out of 29 statements have factor loading ≥0.550 in case of Factor 6, Factor 7 and Factor 8, which reveals that 6.89% of the statements are clubbed in Factor 6, Factor 7 and Factor 8. On the basis of Varimax rotation with Kaiser Normalization, 8 factors have emerged.
Table 8. Grouping of Key Statements Based on Factor Loadings Sr.
No. Statements 1 2 3 4 5 6 7 8
1 Products from my brand are authentic .740 2 My brand gives me glamorous look .789 3 Products of my brand gives high perfor- .810 4 I trust quality of my brand .710 5 My brand offers me innovative products .637 6 The products offered by my brand are
t d .513
7 My brand offers value for the money .616
8 I can rely on my brand .739
9 My brand is an honest brand .745 10 My brand meets my expectations .747 11 Cosmetic products from my brand are safe to use .728 12 My brand helps to attain the life I strive for .798 13 I use this brand to define and express I and me within myself .871 14 I can make many association between my life and brand .854 15 I think other judge me as person by brand which I use .747 16 Celebrity of my brand does influence my buying decision .662 17 I feel that well known brand/s perform better as compared to less known brands .771 18 Cosmetics products from well known brands are always stylish as compared to .853 19 Cosmetics products from well known brands are always durable as compared .823 20 A high-priced cosmetic product usually has all day staying power .659 21 Brand name attracts me to purchase the products .798 22 Image of my brand attracts me to pur-chase .817 23 Brand name is most important regard-less of price .590 24 I can recognize my brand among com-peting brands .601 25 Even if other brand have same feature I would prefer to buy from my brand .745
Sr.
No. Statements 1 2 3 4 5 6 7 8
26 I feel risky while using new products
from the same brand .808
27 My brand is reasonably priced .601
28 My brand gives me sensuous feelings .559
29 I always check expiry date before using cosmetic products .735 6. Naming of the factors
The following eight factors were identified as per the factor loading given in above table (Table 8).
Product Attributes:
There are six statements in this factor which indicates that respondents would like to choose products from the authentic brand. Customers are of the opinion that products from their brand are innovative, trendy and give high performance which ultimately builds trust of the customers on cosmetic brands. The statements fall under this factor shows that product attributes are the key var-iable which is affecting brand loyalty.
x Brand Trust:
There are five statements in this factor which indicates that if brand meets customer’s expecta-tions that brand will become honest brand and they can rely on the cosmetic brand which they used A cosmetic brand helps customers not only to associate themselves but also it gives identity to their personality so that others can judge them easily. Thus, building brand trust is the key element which helps marketers to retain loyalty among the customers.
x Brand Association:
There are five statements in this factor. Association of the customers with the brand is the im-portant factor which helps them to become brand loyal. A cosmetic brand helps customers not only to associate themselves but also it also gives identity to their personality so that others can judge them easily. Easily recognition and meeting life standard through the cosmetic products from the brand of their choice will create strong association between brand and the customers.
x Perceived Quality:
There are four statements in this factor. Customers’ perception and expectations towards brand and meeting those expectations is the key challenge for the marketer. Customers perceived that if they buy products from the reputed brand then they will get stylish, durable, good performance and effect of these products will long last throughout the day.
x Brand Name:
There are three statements in this factor. Brand name, brand image are the important variables which attracts customers to purchase the products. Even respondents were agreeing that compare to price of the product brand name is most important before buying a cosmetic product. Thus, brand name is one of key factor and antecedent of brand loyalty.
x Brand Preference:
There are two statements is this factor. The customers are able to recognize their favorite brand among competing brands and once they are satisfied after using products if other brand is having
same feature they would not like to go for new brand. Thus, recognizing brand of their choice would help them to go for repeat purchase which will create brand loyalty in the mind of customers.
x Perceived Value and Risk:
There are two statements in this factor. Even though customers are having trust on the brand but still they feel risky while using new products from the same brand. They also value the price being charged for the products of their chosen brand. Thus, the factor perceived value and risk are associated with the customers buying behavior and it is influencing their loyalty.
x Product Attributes and Risk:
There are two statements in this factor. Customers have sensuous feelings for the brand which they used. But at the same time, they are also conscious for cosmetic products and always check expiry date before using any products. Product attributes are important to market the product but in the case of cosmetic products risk is also associated with it.
x Managerial Implications:
The factor analysis was conducted to study the factors which are affecting consumers’ brand loyalty. The results revealed that the factors such as product attributes, brand trust, brand association, perceived quality, brand name, brand preferences, perceived value and risk, product attributes and risk are the major factors affecting brand loyalty. The consumer brand loyalty in turn will increase the brand sustainability. Hence, it is recommended to brand managers that they should emphasis on above factors if they want to create sustainable brands.
Bibliography
[1] Aaker, D.A., (1991). Managing Brand Equity, The Free Press, New York.
[2] Choirul A. N., (2015). Building Brand Loyalty Through Increasing Brand Trust And Brand Affect, International Journal Of Scientific & Technology Research, November 4 (11): 336– 340.
[3] Chen A., (2001). Using free association to examine the relationship between the charac-teristics of brand associations and brand equity", Journal of Product & Brand Manage-ment, 10 (7), 439–451.
[4] Haket M., (2016). The customer perceived value of sustainability. Retrived: https://dspace.ou.nl/bitstream/1820/7447/1/Haket%20M%20scriptie.pdf.
[5] Kuchnika D. G. J., Balazs S., Gavriletea M. D., and Djokic B. B., (2018). Consumer Attitude towards Sustainable Development and Risk to Brand Loyalty, Multidisciplinary Digital Publishing Institute, Sustainability, 10(4), 997. Retrieved: www.mdpi.com/jour-nal/sustainability, https://www.mdpi.com/2071–1050/10/4/997.
[6] Matzler K., Grabner S., and Bidmon S., (2008). Risk aversion and brand loyalty: the mediating role of brand trust and brand affect, Journal of Product & Brand Management, 17(3), 154–162.
[7] Moisescu O. I., (2018). From perceptual corporate sustainability to customer loya lty: a multi-sectorial investigation in a developing country, Economic Research, 31(1), 55– 72. Retrived: https://doi.org/10.1080/1331677X.2017.1421998.
[8] Report on India’s cosmetics industry may treble by 2020. (2013). The Times of India. [9] Retrieved: http://www.indianmirror.com/indianindustries/2016/cosmetics-2016. [10] Report on Men and Women in 2016.
[11] (http://www.indiaenvironmentportal.org.in/files/file/Women%20and%20Men%20in%20In-dia-2016.pdf).
[12] Sasmita J., Suki M. N., (2015). Young consumers’ insights on brand equity: Effects of brand association, brand loyalty, brand awareness, and brand image, International Jour-nal of Retail & Distribution Management, 43(3), 276–292.
[13] Souri F., (2017) Investigate The Relationship Between Brand Equity, Brand Loyalty and Customer Satisfaction, International Journal Of Scientific & Technology Research, June, 6(6), 225–231.
[14] Yoo, B., Donthu, N. and Lee, S., (2000). An Examination of Selected Marketing Mix Ele-ments and Brand Equity. Journal of the Academy of Marketing Science, 28 (2), 195–211.
ZNACZENIE CZYNNIKÓW LOJALNOŚCI WOBEC MARKI DLA JEJ ZRÓWNOWAŻONEGO ROZWOJU
Sterszczenie
Zrozumienie czynników lojalności wobec marki jest kluczowe dla jej podtrzyma-nia i rozwoju. Przedstawione w artykule badanie miało na celu poznanie tych czynni-ków w branży kosmetycznej. Badana próba objęła 500 pracujących kobiet w stanie Gujarat w Indiach. Jako narzędzie badawcze zastosowano kwestionariusz składający się z 29 pytań dotyczących postrzegania marki, zaufania do marki i kapitału marki. Jako narzędzie pomiaru zastosowano 5-cio stopniową skalę Likerta. Do analizy pozy-skanych danych użyto statystykę opisową. Wyniki analizy wskazują, że do najważniej-szych czynników wpływających na lojalność wobec marki należą takie atrybuty jak zaufanie do marki i jej postrzeganie, rozpoznawalność i jakość produktu oraz prefe-rencje i ryzyko.
Słowa kluczowe: lojalność wobec marki, postrzeganie marki, kapitał marki, zaufanie do marki
Kunjal Sinha
CKSV Institute of Management R.V Desai Road, Pratapnagar, Vadodara – 390 004
Gujarat Technological University e-mail: kunjal.sinha@cksvim.edu.in Rajesh Khajuria
CKSV Institute of Management R.V Desai Road, Pratapnagar, Vadodara – 390 004
Gujarat Technological University e-mail: rajesh.khajuria@cksvim.edu.in Hetal Thakar
CKSV Institute of Management R.V Desai Road, Pratapnagar, Vadodara – 390 004
Gujarat Technological University e-mail: hetal.thakar@cksvim.edu.in
