Conceptual Analysis of Brand Image and Perceived Value: Assessing Its Impact on Brand Loyalty

doi:10.21203/rs.3.rs-4545986/v1

This research tries to establish an understanding between the customer perception and loyalty towards a brand. The primary issues this study tries to explore are does brand image, perceived risk, perceived price, and perceived quality affect the perceived value for cosmetic products and does perceive value lead towards brand loyalty in the cosmetic product category. Data has been collected from 532 Indian female respondents who have recently shopped for cosmetic products. Exploratory factor analysis was carried out in SPSS (24), followed by CFA and path analysis to validate the results. It has been found that brand image is significantly related to the perceived value. Perceived risk and perceived price are negatively associated with the perceived value. Perceived quality significantly affects the perceived value. Finally, perceived value is positively associated with brand loyalty. Limitations and scope for further research is also discussed in this study.

Brand Image

Perceived Quality

Perceived Price

Perceived Risk

Perceived Value

Brand Loyalty

Customers do not buy products solely for their functions. The customer purchases the product for the expected benefit that he or she can derive from it. Along with their own opinion, the expected benefit is what generates the perceived value for the consumer. Early researchers like Zeithaml (1988) describe perceived value as “consumer’s overall assessment of the utility of a product (or service) based on perceptions of what is received and what is given” (p. 14). Thus, the effective use of perceived value in a business may impact the brand’s approach towards the consumer (Pandža Bajs, 2015).

Perceived value is considered an outcome in various studies (Wang & Tsai, 2014; Jeng, 2016) and a means to an end in other studies (Punniyamoorthy & Raj, 2007; Chi et al., 2009). This study attempts to understand the antecedents of perceived value. At the same time, we are exploring the relationship between perceived value and brand loyalty. Factors such as perceived quality (Tzavlopoulos et al., 2019), perceived risk (Liang et al., 2018), and perceived price (De Toni et al., 2018) have been identified to affect perceived value. Along with these three factors, the present study incorporates the role of brand image in affecting a product’s perceived value. However, no study is conducted with the Indian cosmetic industry in the backdrop. The present study extends the role of perceived value in determining loyalty towards a brand. However, researchers have studied the relationship between the value perceived and brand loyalty (Ishaq et al., 2014), but not in the Indian cosmetic industry context.

Customers who show brand loyalty are committed to a product shown by their frequent purchases (Kopp, 2019). Besides, knowing how the consumer perceives the product will add a benefit. The present study tries to explore the same. To be precise, the study is trying to explore two issues. (1) Does brand image, perceived risk, perceived price, and perceived quality affect the perceived value for cosmetic products? (2) Does perceived value lead towards brand loyalty in the cosmetic product category?

The remainder of this paper is organized as follows. The chosen type of product category, i.e., cosmetic, is first introduced. In addition to the research model and hypotheses, the primary constructs’ literature review is carried out. The methodology and results are then addressed. Finally, the conclusion section includes discussion, implications, limitations, and future study.

1.1 Why Cosmetics

Cosmetics is a general category amongst young people and adults because it represents them with a confident lifestyle, increased flexibility, and solace (Eze et al., 2012). When a female consumer engages in cosmetics, they feel younger, more embraced and beautiful, which helps make them loyal to the use of a particular brand (Hashem et al., 2020). Moreover, cosmetics are not just used to enhance beauty but are a part of daily life (Marto et al., 2018), especially for women.

Yearly, Indian cosmetic and personal care product sales are growing at 15-20 percent from the past five years. The Indian cosmetic market, valued at $11.16 billion (2017), estimates a CAGR of 5.91 percent till 2025 (Srinivasan, 2020). At this rate, by 2025, the said market is expected to touch the $20 billion mark (PTI, 2018). PTI (2018) also reported the launch of “Cosmoprof India,” an international beauty event being held in cities like Bologna and Las Vegas.

What was once like a drop in the ocean for women purchasing cosmetic items has already been flooded with diverse offerings like never before. The early 2010s saw a boom of online players selling anything and everything in India. Cosmetic and personal care products were no different. Brands like Nykaa, founded in 2012, tapped the online cosmetic market most efficiently. Although lagging in the number games, with a valuation of $743 million, Nykaa forced big players like Amazon India, Myntra, Bigbasket to venture into the online cosmetic market (Ghosh, 2020). This signifies the potential this market offers.

The cosmetic industry, just like any other industry, has faced the wreckage caused by the recent pandemic. The $500 billion (global) industry has to face the heat. However, experts vocalize for a speedy recovery. In China, the industry’s February sales decreased by up to 80 percent compared to 2019. In March, the Y-O-Y drop was 20 percent, a fast turnaround under such conditions. Moreover, the pandemic is expected to intensify developments that have already shaped the economy, including the growth of the global middle class and the proliferation of e-commerce (Gerstell et al., 2020).

2.1 Brand Image

A purchase decision is not solely dependent on the functional aspects of the brand. The symbolic aspects, such as consumers’ status, self-esteem (Levy, 1959), and congruence between brand image and self-image, are equally important (Sirgy, 1985). Brand’s image recognizable by the customer allows businesses to introduce new products and boost revenues from the existing brand (Diallo et al., 2013).

Brand image is defined as a “set of brand associations that are anything linked in memory to a brand, usually in some meaningful way” (Aaker, 1991). While Aaker focussed on the composition of brand association, Kotler and Armstrong (1996) viewed brand image as “a set of beliefs held about a particular brand.” While the definition is decades old, it still holds. A consumer values a brand with a strong image, which helps differentiate one brand from its rivals (Mabkhot et al., 2017). Brand image, referred to as the “soul of the product” (Chinomona, 2016), makes the customer believe in the brand at a particular level which thereby allows them to reach a decision (Torres & Bijmolt, 2009).

The brand reflects a business’s ethos that is constantly expressed in all its marketing activities (Ramesh et al., 2019). The consumer tries to align all of this, creating a brand image; because they trust the skills and credibility of the business (Popoli, 2011). An impactful brand image helps deliver a value-laden product that creates a lasting, as well as a profitable relationship (Tu & Chih, 2013).

H1: Brand image is positively associated with the perceived value.

2.2 Perceived Risk

Customers perceive a significant risk level while making buying decisions for unfamiliar brands because they do not have exposure to such brands (Bhukya & Singh, 2015). Perceived risk, a subjective fear of loss (Sweeney et al., 1999), is a customer’s behavior creating results that he/she cannot predict with accuracy (Liljander et al., 2009).

Peter and Ryan (1976) defined perceived risk, at a brand level, as “the expectation of losses associated with the purchase and, as such, acts as an inhibitor to purchase” (p. 185). Any discrepancy between actual purchasing experience and purchase objectives would make consumers perceive a more significant risk and, in effect, such risk would rely on the level of subjective ambiguity of outcomes (Roy et al., 2012). Whenever a customer postpones or cancels a purchase or opts for an alternative brand, it indicates the presence of perceived risk (Hong & Yi, 2012).

To better perceive the value derived from the product, a proper investigation must be done for the perceived risk that may hinder (Chen & Dubinsky, 2003). E.g., Yang et al. (2016) found that the threat of perceived risk reduces in case of the product or brand already used by the customer since they have enough information about the product to overcome the fear of potential risk. A customer perceives more risk when buying products online or making an electronic payment. The risk associated with a product’s performance and finance negatively affects its perceived value (Yang et al., 2015). Brands strive for loyal customers but may end up losing customers owing to the perceived risk. A customer’s perception of risk not only diminishes the perceived value but also reduces their repurchase intention (Liang et al., 2018). While mentioning the perceived value as a combination of “quality”; “sacrifice,” and “risk,” Based on the findings of previous studies, following hypothesis is proposed:

H2: Perceived risk is negatively associated with the perceived value.

2.3 Perceived Price

Price is considered monetary compensation for the consumption of a product (Lichtenstein et al. 1993) or even a quality indicator (Zeithaml, 1988). The product’s price has a primary indicator of consumer preference (Kim et al., 2012). The quality, as well as the attributes of different brands being at par, price is often considered as a differentiator (Reibstein, 2002). Perceived price is considered as a combination of two costs associated with the products.

Before dwelling on perceived price and consumer buying behavior, it becomes imperative to understand the concept of price from the consumer’s perspective. Kotler and Armstrong (1996) defined price as “the nominal value charged to the customer to acquire products and to be benefited from the ownership or use of products.”

While perceiving fairness in the price being charged for a brand, value for the same is bound to be affected positively and vice-versa (Wang & Chen, 2016; De Toni et al., 2018). Depending on the product’s nature, the customer may not emphasize its price, thereby not establishing a relationship with perceived value (Shintaputri & Wuisan, 2017). Still, in an industry where competition is high, brands are providing products at a reduced cost to increase customers’ perceived value (Heda et al., 2017). Setiawan and Achyar (2013) came out with a similar finding, where they found a negative relationship between perceived price and perceived value, owing to the lowered utility acquisition for a higher-priced brand. Thus, this study proposes the following hypothesis:

H3: Perceived price is negatively associated with the perceived value.

2.4 Perceived Quality

This certainly is not a valid reason to raise the price; however, it is an indirect assurance of offering high value (Vera, 2015).

More the customer perceives a quality in a brand or product, more will be the value derived from it (Moreno et al., 2015; García-Fernández et al., 2018). A similar finding was made by Cheung et al. (2015), albeit for green products. Not only in products, but perceived quality also has a positive relationship with perceived value for the service sector (Keshavarz & Jamshidi, 2018). Perceived quality and value are inter-linked in traditional commerce and extend to the e-commerce scenario (Tzavlopoulos et al., 2019). A highly perceived quality product or brand is deemed to deliver a better cost-benefit analysis, and thereby, a better value. The role of perceived quality in self-serving banking facilities is also found to have a positive relationship with the perceived value (Pooya et al., 2020). However, no research has studied the said relationship in the cosmetic industry. To explore this research gap, following hypothesis is stated:

H4: Perceived quality is positively associated with the perceived value.

2.5 Perceived Value

Boksberger et al. (2011) differ on the “trade-off” point of view. In their view, perceived value is a composite measure of customer’s perception of “benefits and sacrifices”, such as quality and price. In the marketing literature, value has been categorized as “preferential”, “perceptual”, and “cognitive-affective” (Sánchez-Fernández & Iniesta-Bonillo, 2007).

Authors have had differing views while defining the construct, perceived value. While some consider it as “unidimensional” (Dodds et al., 1991), others refer to it as “multi-dimensional” (Ruiz et al., 2008). Regardless of how authors interpret this concept, by developing an awareness of how consumers perceive the value they obtain from the purchase of goods or services, brands can formulate an ecosystem to provide better value (Marbach et al., 2016). Perceived value is a significant element in customers’ decision to accept new products or services, as it has been shown to affect both potential and existing consumers (Yang et al., 2016).

Perceived value is found to influence the customer’s loyalty towards a brand (Ishaq et al., 2014). Perceived value is considered significant in determining satisfaction level and gaining a competitive advantage (Day, 2002), which eventually leads to brand loyalty (Ashraf et al., 2018). A brand offering a high-quality product can deliver a value-laden product, paving a path towards loyalty (Rahi et al., 2017). Along with the product, the store plays a crucial role in delivering a higher value to the customer. Once satisfied, the customer is highly likely to become brand loyal (Nikhashemi et al., 2016). The brands experiencing more engagement from customers witness a higher perceived value, leading to a higher level of brand loyalty (Leckie et al., 2017). Along with customer-brand engagement, a brand offering special discounts or running a promotional offer encourages customers to extract value benefits from buying those products, which helps create loyalty towards the brand (Atulkar, 2020). A compelling association promoting a competitively enticing and distinctive brand position may generate positive brand values and contribute to brand loyalty (Su & Chang, 2018).

2.6 Brand Loyalty

Customers either exhibit inconsistent behavior so that previous habits do not condition their buying behavior. Whereas repetitive purchase can also arise from external factors, The former is known as the stochastic view, while the latter is known as the deterministic view of brand loyalty (Huang, 2017).

A level of attachment that a customer displays for a particular brand is represented by brand loyalty (Liu et al., 2012). Brand loyalty is significant from the company’s point of view, as it increases brand equity by reducing the susceptibility to competitor’s marketing behavior. It is also critical from the consumer’s point of view since that brand functions as an indicator of the expectations attained (Al-Msallam, 2015).

Brand loyalty is affected by a particular brand’s perceived value (Punniyamoorthy & Raj, 2007; Yang & Wang, 2010). To understand Taiwanese women’s cosmetic buying behavior, Chi et al. (2009) found that perceived value acted as an antecedent to brand loyalty. Perceived value played an essential role in the “exchange relationship”. Brands offer a diverse product portfolio and value-added services which are in popularity to boost their competitive edge and ultimately their loyalty (Yang & Peterson, 2004). Hence, to check whether the value perceived by the customer leads to brand loyalty, the following hypothesis is proposed:

H5: Perceived value is positively associated with the brand loyalty.

With theoretical support derived from previous studies, a framework is proposed, as shown in Figure 1. A diagrammatic representation of hypothesized relationship is shown in the conceptual framework.

The constructs shown in Figure 1 are computed with a standardized scale derived from various sources. To remain true to the study’s objective, slight amendments have been made to the measurement items. A 7-point Likert scale is utilized to evaluate the items, (1) as “Strongly Disagree” and (7) as “Strongly Agree.” Minimum three and maximum five statements are used to measure different constructs. The scale provided by Hsieh and Li (2008) for “brand image” has been implemented. “Perceived Risk” has been assessed by the implementation of measurement scales from Jun (2020) and Eastman et al. (1999). The measurement scale of Gecti (2014) has been used for “Perceived Price.” Tsiotsou (2005); Pisnik Korda et al. (2012); Bou-Llusar et al. (2001) measurement scale for “perceived quality” has been implemented. Items included by Kantamneni and Coulson (1996) were adopted for “Perceived Value.” Chaudhuri and Holbrook’s (2001) scale is implemented for “Brand Loyalty.”

Table 1 shows the tabular description of the measurement items.

Table 1 Measurement Items

Construct	Items	Authors
Brand Image	I believe that my preferred brand’s product has a functional purpose. I believe that the product of my preferred brand has a positive symbolic significance. I believe that the product of my favourite brand can be linked to a good experience.	Hsieh and Li (2008)
Perceived Risk	I’m worried that the product would not fit the specifications posted on the internet. I’m worried that purchasing products online may lead to monetary losses. The idea of shopping online makes me anxious. I’d be conceived of as naive by individuals whose views I respect if I shop online.	Jun (2020)
Perceived Price	Products that work appropriately and reliably would have a higher value. Aesthetic appeal in a product adds to its value. Products purchased from a reputable brand would have a higher value. Fairly priced goods are going to have a higher value. High-quality goods would be of greater value.	Gecti (2014)
Perceived Quality	My preferred brand offers me a wide range of products. My preferred brand fulfils my personal needs. I like to assess the quality of products I purchase. There seems to be no discrepancy between the shown and the actual product.	Tsiotsou (2005); Pisnik Korda et al. (2012); Bou-Llusar et al. (2001)
Perceived Value	The knowledge of the service provider gives me confidence in buying my preferred brand. Satisfaction with prior experiences gives me confidence in buying my preferred brand. Product performance gives me trust in buying my preferred brand. Older the product, the more the value.	Kantamneni and Coulson (1996)
Brand Loyalty	I hope to keep purchasing from this brand. I will continue to buy my favorite brand even if I receive information that undermines my preference for the brand. I will be willing to pay extra for this brand, even if I'm receiving a similar value from the cheaper alternative.	Chaudhuri and Holbrook, 2001

To verify that the respondents would readily understand the final version of the questionnaire, pilot testing was performed on a sample of 60 participants. This contributed to the removal of some measurement items, together with the modification of unclear items. Since this study pertains to cosmetics, the target group chosen for this study was female consumers searching for purchases or recently purchased cosmetics. When purchasing cosmetics, women shoppers are familiar with collecting information from various sources and well-versed in offline and online activities (Anjana, 2018). A total of 600 questionnaires have been distributed via online as well as offline channels. A total of 532 questionnaires were used in the final review after the screening of the answers. Google forms have been administered to the participants for an online survey. Whereas, in the case of offline channels, the mall intercept approach has been implemented to collect responses. This approach has helped the respondents be screened, as the research is being performed for individuals belonging to a particular gender. Table 2 shows the other relevant demographic identifiers of the sample.

Table 2 Demographic profile

Descriptors		Frequency	Percentage
Employment Status	Paid Employment	325	61
Employment Status	Self-employed	207	39
Marital Status	Unmarried	282	53
Marital Status	Married	250	47
Education	Higher Secondary	122	23
	Graduate	170	32
	Post Graduate	218	41
	Other	22	4

Established methodology and procedures have been employed to analyse the data collected. Exploratory Factor Analysis (EFA) is performed using SPSS (24). This is proceeded by the Confirmatory Factor Analysis (CFA) for additional confirmation and, ultimately, the path analysis is carried out in AMOS (20).

5.1 Reliability Analysis

Every measurement item, along with the construct, is checked for reliability in this study (Fornell & Lacker1981). Construct’s reliability is calculated with the aid of Cronbach alpha (α) (Nunnally, 1978). Squared Multiple Correlation (SMC) is employed to determine the item's reliability (Bagozzi &Yi, 1988). Both the necessary values are calculated to be above the threshold of 0.7 (Table 4) and 0.3 (Table 3), respectively. Thus, the reliability coefficients are acceptable for further data analysis.

Table 3 Factor Extraction Results

Construct	Items	Mean	Std. Dev.	Factor Loading	SMC
Brand Image	BI1	4.61	1.587	.851	.737
	BI 2	5.05	1.610	.885	.723
	BI 3	5.23	1.631	.864	.766
Perceived Risk	PR1	4.47	1.712	.823	.707
	PR 2	4.51	1.675	.909	.854
	PR 3	4.73	1.731	.894	.779
	PR 4	4.79	1.571	.760	.708
Perceived Price	PP1	4.75	1.542	.907	.848
	PP 2	5.09	1.469	.765	.605
	PP 3	4.57	1.691	.845	.731
	PP 4	4.58	1.642	.883	.762
	PP 5	4.64	1.691	.879	.808
Perceived Quality	PQ1	5.82	1.607	.891	.817
	PQ 2	4.75	1.536	.805	.623
	PQ 3	4.47	1.509	.757	.523
	PQ 4	5.16	1.586	.789	.639
Perceived Value	PV 1	5.00	1.589	.866	.765
	PV 2	4.50	1.614	.875	.779
	PV 3	4.07	1.564	.809	.654
	PV 4	4.62	1.468	.820	.708
Brand Loyalty	BL 1	4.96	1.605	.942	.845
	BL 2	4.41	1.629	.842	.697
	BL 3	5.57	1.379	.874	.719

5.2 Exploratory Factor Analysis

It is important to determine the appropriateness as well as the suitability of the data prior to identifying the factors. For the same “Kaiser-Meyer-Olkin (KMO) sampling adequacy test” and “Bartlett’s sphericity test” is utilized. The Value of KMO is significant, 0.911, since it is higher than the threshold of 0.60. (Kaiser and Rice, 1974). The Bartlett test value is also shown to be significant (0.000), below the value of 0.05. The parameters are shown in Table 4.

Table 4 KMO and Bartlett’s Test

Kaiser-Meyer-Olkin (KMO) Measure of sampling adequacy		0.911
Bartlett’s Test of Sphericity	Approx. Chi-Square	4820.102
	df	241
	Sig.	0.000

The “Principal Components Analysis” (PCA), including “varimax rotation”, is employed in the SPSS (24) to perform the factor analysis. Six factors, composed of twenty-three variables, are extracted based on the eigenvalue of one or more. The five factors account for 80.153 percent of the total variance in variables. As shown in Table 3, the factor loadings are more than 0.50, meaning that the data is suitable for factor analysis (Stewart, 1981). Mean and standard deviation results are shown in Table 3. The core concept of the measurement items used for the study is checked with the assistance of the EFA.

5.3 Confirmatory Factor Analysis

Confirmatory Factor Analysis (CFA) is carried out on AMOS (20) to assess the adequacy as well as dimensionality of the measurement model. The CFA applies to all six constructs, i.e. brand image; perceived risk; perceived price; perceived quality; perceived value, and brand loyalty.

5.4 Validity

First, convergent validity is determined on the basis of three criteria The value of commonalities be greater than 0.5; the squared multiple correlations (SMC) be higher than 0.5; the values of Composite Reliability (CR) and Average Variance Explained (AVE) be higher than 0.7 and 0.5, respectively (Hair et al., 2012). As shown in Table 3, the factor loadings and SMC values are higher than 0.5 and are thus significant. Both CR and AVE are far above established parameters; thus, ample convergent validity is expressed, as seen in Table 5.

Second, the measurement model’s discriminant validity is checked by comparing the correlation between the factors with the square root of the AVE (Fornell & Larcker, 1981). The diagonal value, represented by the square root of AVE, has to be greater than non-diagonal values, which is represented by the correlation between constructs, in order to ensure any validity issues (Kesharwani & Tiwari, 2011). This means the factors used for the analysis are unique.

Table 5 Validity Measurement Index

	Alpha	CR	AVE	BI	PR	PP	PQ	PV	BL
Threshold	>0.7	>.07	>0.5
BI	.913	.921	.744	.853
PR	.906	.910	.711	.511	.856
PP	.903	.904	.722	.171	.116	.834
PQ	.870	.906	.714	.636	.516	.115	.832
PV	.902	.879	.721	.243	.051	.348	.207	.822
BL	.873	.900	.730	.363	.276	.311	.477	.419	.844

BI=Brand Image; PR=Perceived Risk; PP=Perceived Price; PQ=Perceived Quality; PV=Perceived Value; BL=Brand Loyalty

5.5 Overall Model Fit

The indices of the model fit are shown in Table 6. The main model statistics show all the latent factor being modelled at the same time, for the measurement model, with CMIN (χ2) = 254.678, degree of freedom (df) = 204, CMIN/df (χ2/df) = 1.248, p< 0.05. Goodness-of-fit indices are represented by GFI, AGFI, NFI, IFI, CFI, and badness of fit by RMR and RMESA. The former indices suggest strong evidence of uni-dimensionality in the measurement model (Byrne, 2013) whereas the latter shows the difference in model fit. This research confirms with the suggestions given by Boomsma (2000); McDonald and Ho (2002) and Schreiber (2008).

Table 6 Model Fit Indices

Model Fit	Cut-off Criteria	Measurement Model Statistics
CMIN	--	254.678
DF	--	204
CMIN/Df	≥4	1.248
GFI	≥.9	0.911
AGFI	≥.8	0.901
IFI	≥.9	0.970
NFI	≥.9	0.926
CFI	≥.9	0.970
RMR	≤.1	0.076
RMSEA	≤0.08	0.030

5.6 Path Coefficients

After the assessment of psychometric properties, the structural model is evaluated using AMOS (20). The results show that all the hypotheses are found statistically significant, because the p-value is lower than 0.05, as shown in Table 7.

Table 7 Hypothesis Testing Result

Hypothesis Number	Hypothesized Relationships	Path Estimates	*t – Statistics*	Result
H1	BIàPV	.435	10.165***	Supported
H2	PRà PV	-.124	-3.167(.001)	Supported
H3	PPà PV	-.112	-2.557(.008)	Supported
H4	PQà PV	.307	4.330***	Supported
H5	PV àBL	.346	6.207***	Supported

Notes: *p<0.05; **p<0.01;***p<0.005

As shown above, in Table 7, brand image is significantly related to the perceived value (H1: β = 0.435; p < 0.005). The subsequent two relationships between perceived risk and perceived value; and perceived price and perceived value is computed to be negative, although statistically significant. As shown in the table above, the relationship between perceived risk and perceived value is statistically supported (H2: β = -.124; p < 0.005). The third hypothesis, depicting the relationship between perceived price and perceived value, shows a negatively significant relationship (H3: β = -.112; p < 0.005). The fourth hypothesis shows that the perceived quality is positively and significantly associated with the perceived value (H4: β = 0.307; p < 0.005). The final hypothesis establishes a positive and significant relationship between the perceived value and brand loyalty towards a product (H5: β = 0. 346; p < 0.005). A path diagram showing the coefficient values is shown in figure 2.

A loyal customer tends to display loyalty at a certain point in time, but if a brand creates value, the likelihood of retaining the customer gets higher (Mahajan, 2016). The study has been carried out keeping this in mind. Intending to understand the role of perception in building brand loyalty, the study first explores the antecedents of perceived value. It has been found that brand image positively affects the perceived value. This finding corresponds with the results of Tu and Chih (2013). This positive relationship shows that the brand’s image embodies an emotional value and not just a conceptual image. The symbolic image depicted by the brand adds to the perceived value. Moreover, if the brand can portray its image’s practical function, it makes the customer value the brand.

The relationship between perceived risk and perceived value came out with a negative, although a significant relationship. This finding is in congruence with Liang et al. (2018). The finding states that the more the customer perceives the risk, the less the value is derived from it. Although consumer perceives risk in offline channels, this behavior is enhanced while shopping online. An anxious customer perceives that the seller might not deliver the exact product, which can lead to financial losses. Like perceived risk, perceived price is also negatively, yet significantly, associated with perceived value. Setiawan and Achyar (2013) also came out with a similar finding. The study found that customers perceive price based on the performance of the product. If the product performs as described and aesthetically appealing, the customer perceives the price as appropriate and vice-versa. Moreover, respondents perceive that higher-priced products are only able to deliver a better value.

Unlike perceived risk and price, perceived quality positively affected value towards a brand positively. This finding resonates the results of García-Fernández et al. (2018). A customer likes to identify the level of product quality before making any purchase decision. This helps in establishing the base for determining the value to be derived out of the product. The more the quality, the more the value. The study found that quality depends on the brand’s wide range of offerings that specifically meets the customer’s needs and/or requirements. After addressing the first issue of the study, i.e., to identify the role of brand image, perceived risk, price, and quality on perceived value, the study established the relationship between perceived value and brand loyalty. A positive association between the two constructs shows that the more the value derived from a product/brand, the more loyalty towards that product/brand. This result is congruent with Yang and Wang (2010). The study found that it is not just the previous interaction with the brand that makes the customer loyal; it is also the brand’s expertise that makes the customer value the product more and hence display more loyalty.

Studies conducted in the past have explored the factors affecting a brand’s perceived value (Achyar, 2013; Liang et al., 2018). This study also resonates with their findings. Also, the present study has identified the positive role of brand image with perceived value. This allows in establishing the indirect role of perceived value in establishing the relationship between brand image and brand loyalty. Moreover, the study highlights the importance of brand-related factors (brand image) and perception in establishing loyalty towards the brand. The present study can help marketers get equipped with the understanding of consumer perception in building brand loyalty.

Additionally, this study highlights the role of brand image in delivering a better value to customers. The marketer needs to deliver products that enhance the self-brand image congruence. To reduce the risk associated with the purchase, the marketer must stay true to their offerings and build robust firmware to stop any financial fraud, especially online sellers.

The study has incorporated only one brand-related factor, i.e., brand image, as an antecedent of perceived value. Future studies can incorporate the role of factors such as brand consciousness in understanding its role in the formation of perceived value. The present study has studied consumer behavior towards cosmetic products only. Moreover, only female respondents were considered in this study. The results may not be applied to other product categories. Future research could incorporate other product categories, and a cross-gender study could further enhance the results. Indian respondents may present results, which may not be generalized. So, a cross-cultural study can enhance the findings of this study. This study has skipped the role of perceived benefits and perceived stress in understanding their effect on perceived value. Future studies can highlight the importance of this aspect.

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No competing interests reported.

Participant Consent:
All participants (or the legal guardians) are my PhD supervisors, Prof.(Dr.) Amit Chawla and Dr. Shivendu Kumar Rai. Additionally, they consented to the publication of the findings. Amity University, ASCO has also waived the need for individual consent for publication due to the nature of the study.

The Research Ethics Committee of Amity School of Communication (ASCO), Amity University Haryana, endorses the research paper titled ‘Conceptual Analysis of Brand Image and Perceived Value: Assessing its Impact on Brand Loyalty’ authored by PhD research scholar Ms. Smitee Kumari (Enrolment No. A50460221005), on basis of the statement submitted by her to her supervisor, Prof (Dr) Amit Chawla, and the office of Director – ASCO. The above-said paper has been reviewed and is deemed compliant with our institution's ethical standards for research involving human subjects. The RAC has assessed the ethical considerations outlined in the submitted paper and acknowledges that the research conducted by her adheres to the principles of integrity, confidentiality, and respect for the participants involved.

Conceptual Analysis of Brand Image and Perceived Value: Assessing Its Impact on Brand Loyalty

Status:

Version 1

Abstract

Figures

1. Introduction

2. Literature Review

3. Measurement Items

4. Sample and data collection

5. Results and Analysis

6. Conclusion

7. Implications

8. Limitations and Future Scope

References

Additional Declarations

Status:

Version 1