Abstract
Purpose
The research aims to examine the influence of perceived value (PV) dimensions on brand loyalty of luxury car owners and to examine the mediating role of attitudinal loyalty (AL) between PV dimensions and behavioral loyalty (BL).
Design/methodology/approach
Primary data for the study were gathered from the luxury car owners in Kerala, India. The construct measurements have been adopted from previous research studies. Structural equation modeling with the partial least square (PLS) technique was used to analyze the measurements and conceptual model.
Findings
The findings show that out of four PV dimensions among luxury car owners, the hedonic value (HV) significantly influences their AL. Economic value influences BL, and social values have an impact on AL as well as BL, but the relationship of functional value with any is not supported by the results. AL is a strong predictor of BL, and it actively mediates the relationship of HV and symbolic value with BL.
Practical implications
The manufactures of luxury cars provide more importance to hedonic and symbolic elements while launching new models and consider the price perceptions of the targeted customers while making decisions related to brand attachment and brand loyalty.
Originality/value
This study contributes to the decision-making of the rapidly growing vehicle market by examining the perceptions and by providing the effects of perceived values among luxury car owners. Also, it extends the literature by developing a framework for PV dimensions on AL and BL and also incorporated the mediating role of AL.
Keywords
Citation
Femina, E.P. and Santhi, P. (2024), "Effects of perceived value dimensions on customer brand loyalty towards luxury cars", Rajagiri Management Journal, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/RAMJ-01-2024-0006
Publisher
:Emerald Publishing Limited
Copyright © 2024, E.P. Femina and P. Santhi
License
Published in Rajagiri Management Journal. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
1. Introduction
When a brand is perceived as renowned, customers increasingly identify themselves with it. The customers' perception of the product’s level of prestige affects how much they think it is worth (Kim et al., 2019). Popular firms provide uniqueness and cue signals like quality cue and social status cue to their clients, which enhances the sense of customer value (Nishikawa et al., 2017). Each brand offers unique traits and features that are connected to its line of products. The advertisements influenced the buyers to perceive certain qualities and features of the brand (Severi and Ling, 2013). When these perceptions are confirmed, customers plan to purchase products from the same brand; this dedication develops brand loyalty (Lam et al., 2004).
Perceived value (PV) of the customers influences their future purchase intention, commitment and loyalty toward the brand (Chen and Hu, 2010). Customers’ PV significantly influences the brand trust and satisfaction, which leads to attitudinal loyalty (AL) (Shirin and Puth, 2011). According to Sirdeshmukh et al. (2002), behavioral intents of loyalty toward the company are governed by the superior customer value provided by the company. A close correlation pertains among PV and brand loyalty when that brand is purchased from a high luxury tier (Chung and Kim, 2020). Customers’ positive perceptions of a brand develop a strong relationship with the brand. This relationship improves attitudinal and behavioral brand loyalty (Zhang et al., 2020).
Luxury refers to high-involvement products and services that have high standards, relevant implications and public appreciation (Shukla, 2011). While compared to other goods, luxury products are the most expanding and profitable segment of a brand (Berthon et al., 2009). The luxurious product provides pleasure, comfort and individual and other values to the customers (Wiedmann et al., 2009).
As India is among the fastest growing luxury car markets in the world, it provides a larger scope for luxury brands. Through the superior design, engineering and image, the luxury segment in the automotive industry offers uniqueness and differentiation to the customers beyond their needs and expectations (Nunes et al., 2016). Luxury car dealers have successfully made use of this opportunity by introducing a line of entry-level models. There are so many different automobile kinds and models, which are growing more similar and increasing competition among automotive manufacturers, making brand loyalty an essential competitive factor. There are 52 varieties of luxury cars currently on sale in India from various manufacturers. BMW, Audi, Toyota, Porsche, Jaguar and Mercedes Benz are few among them.
The increasing demand and emergence of new brands in the car industry increase the competition among the luxury segment of cars. It is vital for companies to analyze the factors that influence and lead to satisfaction and loyalty toward a particular brand of car.
2. Review of literature
2.1 Perceived value
PV is the opinions of customers about what they have given and what they have availed based on their overall assessment of a product, a store and image (Zeithaml, 1988). It is the benefits obtained from products which are measured in terms of costs incurred or perceived sacrifices (Monroe, 2002; Almeida et al., 2022). The past literature has identified PV on the basis of two motives. Functional motivations are the first type, emphasizing more on concrete and real necessities like price, convenience and quality, whereas nonfunctional motivations place more emphasis on abstract goals such as social needs and emotional needs (Chen and Hu, 2010). As per Lin et al. (2022), perceived discomfort is a major obstacle to PV, but economic rewards and identity expressiveness are important facilitators.
A product’s functional value (FV) is the extent to which it possesses the desired properties or serves the intended purpose (Tynan et al., 2010). Customers’ expectations on luxury products are to be more functional, with high quality, and different enough to meet the desires to stand out (Wiedmann et al., 2009). While compared to the nonluxury things, luxury goods stand out due to their superior design, manufacture and functionality (Vigneron and Johnson, 2004).
When it comes to luxury, greater financial sacrifice is positively correlated with the connected brand’s overall worth (Thomas, 2007). As a result, the economic value (EV) contributes positively to the purchase of luxury goods. In other words, a luxury brand’s distinctiveness and appealing attributes are enhanced by its greater cost of purchase.
The extent to which a customer accords his psychological significance to a product determines its symbolic value (SV) (Smith and Colgate, 2007). Purchasing or gifting luxury items makes people feel good about themselves. The attractiveness of luxury goods to the feeling of self-concept has been noticed in a number of earlier research studies (Tsai, 2005; Vigneron and Johnson, 2004). The symbolic aspects or sign value of the luxury items, which result from their desirability, give its owners a sense of status and self-actualization (Moore and Birtwistle, 2005).
Hedonistic value describes aspects of consumer behavior relating to sensory, imaginative and emotive contact of a person with the products (Srinivasan and Srivastava, 2010). Hedonic value (HV) is the perceived usefulness and inherent traits obtained through purchase and use of a premium brand in order to elicit feelings and affection, earned from the personal pleasures and fulfillment (Sheth et al., 1991; Westbrook and Oliver, 1991; Schnebelen and Bruhn, 2018).
Marketing is the prime driver of customer value as the firms offer differentiated offerings that have both tangible and intangible benefits for customers. Customer PV is intrinsically linked to the overall assessment of the utility of the product and the customer’s buying decision and is a highly personal and idiosyncratic constituent. It is a trade-off between what customers “give” and “get” (Misra et al., 2022).
2.2 Dimensions of brand loyalty
Gaining customer loyalty to a brand is becoming crucial for long-term profitability and the competitive advantage. It is not mere the repeat business but the psychological attachment of the customers toward the brand (Rehman et al., 2012). Marketers can utilize the framework of brand loyalty to investigate a variety of marketing methods, and it is necessary to manage brand connections in a way that would appeal to customers with varying degrees of brand loyalty (Ramesh Kumar and Advani, 2005). Khan (2010) identified two prime dimensions of the term brand loyalty: “attitudinal loyalty” and “behavioral loyalty”. Behavioral aspect refers to real behavioral interactions, while the attitudinal component refers to customers' attitudes and feelings regarding the brand (Arens et al., 2011). Behavioral loyalty (BL) is the customers’ repeat purchase of a specific brand or product, exhibiting through their frequent spending and patronage behavior (Bennett and Bove, 2002). It is the future repurchase intention of a customer that develops from their past purchasing behavior (Rauyruen and Miller, 2007). AL is the positive bonding toward a brand or product, created through emotional attachments (Theng So et al., 2013). It is emphasized that as the psychological component of brand loyalty, it embraces promises, preferences and purchase targets of the customers (Bennett et al., 2014). As per Cachero-Martínez and Vázquez-Casielles (2021), customers' AL strengthens their BL since it is a sign of their behavioral intentions, which influence their future actual conduct and behavior. Companies prioritize the satisfaction of most profitable customers in order to strengthen the relationship, prevent them from being tempted by competing offers and boost their loyalty: behavioral and attitudinal. These customers can be identified by analyzing their future values through various measures like the customer lifetime value metric (Kumar et al., 2013).
2.3 Perceived value and brand loyalty
Social, financial, emotional and utilitarian values affect the brand loyalty of customers (Kim et al., 2010). Customer functional, social, emotional and perceived sacrifice values have found a substantial impact on brand loyalty through satisfaction (Wang et al., 2004). Pura (2005) analyzed that monetary value, emotional value and social value have effects on loyalty. Kim et al. (2019) identified the favorable effect of brand prestige on functional, hedonic, social and financial values. Among these four constructs of PV, function, hedonic and financial values significantly influence brand loyalty. According to Vera and Trujillo (2017), perceived brand value has a higher impact on brand loyalty measurements. Yeh et al. (2016) found that individual-related values such as functional and emotional values have a more significant effect on brand loyalty than interpersonal factors such as social value. Sun et al. (2021) discovered that HV, in addition to utilitarian value, had a major impact on enhancing AL. Customers will purchase a product if it is viewed as having a high value to them (Thanasrichatthon, 2023).
As per Haghkhah et al. (2020), customers’ value in the automobile industry has an effect on their brand loyalty. PV has an effect on automobile usage intention through directly and through the level of satisfaction (Boonchunone et al., 2023). Customers' perceived symbolic and social values have the greatest influence on their purchase intention when it comes to luxury brands (Petravičiūtė et al., 2021). Using five perceived values, Rouhani and Hanzaee (2012) examined consumers' perceptions of luxury car brands and how these affected their propensity to repurchase. The results demonstrate that uniqueness, quality and hedonic values are substantially more important and the purchase intention is greatly influenced by all four values including conspicuous value, with the exception of social values. The intention of consumers to purchase luxury products can be influenced by their perceived social, personal and functional values (Salehzadeh and Pool, 2017).
The research findings of Rizan et al. (2020) indicate a positive association between PV and customer loyalty with the mediation of customer satisfaction; they also discovered that although PV has a small but favorable impact, it does affect attitude and BL as well as the overall customer loyalty dimension. Bui et al. (2023) examined how perception characteristics connected to experiential assessment and how this affects brand loyalty using attitude toward brand as a mediator. The study findings suggest that three PV dimensions, informational, entertaining and social, have a favorable effect on how consumers perceive a brand, which in turn increases their brand loyalty. However, there is no mediation of brand attitude noticed among experiential assessments and brand loyalty. Perceived brand value can be influenced by brand attitude, which fosters brand loyalty (Islam et al., 2023; Xie et al., 2023).
As per Imtiaz et al. (2019), AL acting as a mediator between brand commitment and BL as well as between brand trust and BL is a powerful prerequisite for BL. AL also acts as a powerful mediator between the affective trust and BL in the automotive sector (Liu et al., 2021).
This article addresses the behavioral aspects of luxury cars. Earlier studies on customer brand loyalty were mainly focused on the direct relationship between customer PV and brand loyalty (Wang et al., 2004; Pura, 2005; Kim et al., 2010; Yeh et al., 2016; Kim et al., 2019; Haghkhah et al., 2020; Sun et al., 2021; Thanasrichatthon, 2023). A number of studies incorporated AL as a mediator to relate various brand-related traits, namely affective trust, brand commitment and brand trust, to BL or repurchase intention (Imtiaz et al., 2019; Liu et al., 2021), and studies applied customer satisfaction and brand attitude as mediators among PV and BL (Rizan et al., 2020; Bui et al., 2023; Xie et al., 2023). Since brand loyalty is a constituent of attitude and behavior, literature on the relationship between AL and BL is very scanty. The present study unveils the influence of customer PV about luxury cars on BL through AL, and the four PV dimensions included in the study are FV, EV, SV and HV.
3. Objectives
The objectives framed for the study include
To examine the value perception of luxury car owners toward their brand,
To analyze the influence of value dimensions on AL and BL
To study the relationship between AL and BL
To identify the mediating effect of AL among the PV dimensions and BL
4. Conceptual model and hypothesis development
The growth of luxury goods can be observed for the last two decades; hence, researchers are paying closer attention to the phenomenon associated with the consumption of these items. The PV consists of FV, EV, SV and HV. Hence, the study makes an attempt to analyze the influential effects of PV dimensions of luxury cars on both types of loyalty, attitudinal and behavioral, and to analyze the mediating effect of AL between value perceptions and BL (Figure 1). For this, the following hypotheses were formulated.
FV has a significant influence on AL
FV has a significant influence on BL
EV has a significant influence on AL
EV has a significant influence on BL
SV has a significant influence on AL
SV has a significant influence on BL
HV has a significant influence on AL
HV has a significant influence on BL
AL has a significant influence on BL
AL mediates the relationship of FV, EV, SV and HV with BL
5. Methodology
Ernakulam district of Kerala is the locale of the study. The multistage sampling method was adopted to select sample respondents of luxury car owners. Ernakulam town in Kerala was purposively selected for the study as it is one of the leading commercial cities in Kerala. Dealers of luxury brand cars were identified and approached to collect the database of their customers who purchased cars from April 2019 to March 2022. There were 1,267 customers in total. Of them, proportionate sampling of 10% of customers would constitute the sample size, resulting in 127 customers. From the database, a random sampling method, namely a tippet table of random numbers, was used to identify 127 customers. The study was conducted between the period of April 2022 and September 2022 by using primary and secondary data. A well-structured questionnaire was created for collecting data from the selected customers. Of the 127 customers, seven did not respond; hence, the final sample is 120 customers. Secondary data for the study were obtained from the published reports and journals. The framework of analysis includes percentage analysis and structural equation modeling.
The questionnaire used for the survey was designed as per the measurement items derived from the literature review. Three sections were included in the questionnaire. The first section deals with the demographic factors of the respondents. The second section aimed to analyze the various PV dimensions of the customers adopted from Smith and Colgate (2007), Lee et al. (2015) and Chung and Kim (2020). The third section included the attributes on attitudinal and behavioral brand loyalty, prepared based on Zhang et al. (2020) and Hassan (2015). The items were evaluated by a five-point Likert scale, from strongly disagree – 1 to strongly agree – 5.
Demographic characteristics of the respondents were analyzed on the basis of gender, age, income, educational qualification and occupation; the results are shown in Table 1.
The sample respondents were aged above 18 years; 35% of them belong to above 50 years of age. Based on gender, 78% of them are male and only 22% are female. Forty-eight percent of the respondents belonged to the income of ₹ 10 lakhs to ₹ 25 lakhs, and 40% of respondents are graduated. As regards to the occupation of the respondents, 48% do their own businesses, 35% of them are employed in private sectors and the remaining 18% of the respondents are government employees.
6. Results and analysis
Structural equation modeling through SmartPLS was utilized for analyzing the data. FV, EV, SV and HV are independent variables; BL is the dependent variable, and AL is considered as the intervening variable. In the first stage, the measurement model was examined for its validity and reliability; Tables 2 and 3 present the values.
Values of Cronbach’s alpha and composite reliability were used to evaluate the internal consistency of the constructs (Table 2). The generally acceptable values for these two are 0.7 (Fornell and Larcker, 1981). In the study, Cronbach alpha value is higher for HV at 0.852 and the FV shows the lowest value of 0.733, which is beyond 0.7; the acceptable value also proposed by Nunnally and Bernstein (1994). All the indices for the composite reliability exceed the necessary threshold of 0.70. Thus, the constructs have adequate internal consistency. The study also measured convergent and discriminant validity by performing the tests of factor loading and average variance extracted (AVE). The factor loadings of items ranged between 0.662 and 0.951, which were above 0.6, indicating a percentage of convergent validity (Hair et al., 2010). The AVE of BL is the lowest value of 0.645, which covers the recommended value 0.5, stated by Fornell and Larcker (1981), which confirms the existence of discriminant validity. These results indicate and ensure the reliability and validity of the measurements.
The discriminant validity was also analyzed through the criteria framed by Fornell and Larcker (1981). The square root of the AVE for every construct (Table 3) is higher than the square of each pair of correlation. These confirm that the variables are distinct and mutually exclusive.
7. Evaluation of research relationship
The t-statistics and path co-efficient obtained through SmartPLS software is used to evaluate the significance of parameters in the model. If the t-statistics is higher than 2(1.96), the relationship is statistically proved as significant, and standardized path co efficient are expected to be at least 0.2 (Chin, 1998). Figure 2 and Table 4 present the results of model fit and hypothesis tests.
The testing of hypotheses and the structural equation model (Figure 2, Table 4) revealed that the results supported five hypotheses (H4, H5, H6, H7 and H9), with path coefficients of 0.332, 0.295, 0.296, 0.491 and 0.640, respectively. The other four hypotheses H1, H2, H3 and H8 are not supported as these did not fulfil the requisite path coefficient value of above 0.2. The results also indicate that the BL is significantly influenced by AL (0.640). HV has a stronger effect on AL (0.491), while the EV strongly affects BL (0.332). SV has an impact on AL as well as BL, with path coefficients of 0.295 and −0.296, respectively, but FV did not show any effect on both types of loyalty.
The mediating effect of AL was examined by bootstrapping with a resample of 5,000, and the results are shown in Table 5. The findings showed that the relationship between HV and BL is mediated by AL, with a path coefficient of 0.315 (t statistics = 4.748, p = 0.000). Luxury car owners seek value, based on the pleasure and luxurious experience gained by using the cars. It is a spontaneous response by the customers that is highly subjective and personal; it forms the basis for positioning luxury car brands among consumers and has a beneficial impact on their attitudinal and behavioral brand loyalty. AL also mediates the SV with BL, with a path coefficient of 0.198 (t statistics = 2.283, p = 0.022). Luxury car customers also search for self-expressive and social values while selecting a luxurious brand. They have to gain prestige and social status through their luxury brand of cars, and these values impact their emotional attachment to the brand and their intention to repurchase it. There is no evidence of a mediating influence in the link between FV, EV and BL.
8. Conclusion
This study attempted to analyze the influence of four main PV dimensions: FV, EV, SV and HV on AL and BL among the luxury car owners. The results evidenced that out of the total 9 hypotheses related to the direct effect, only five hypotheses are supported, the results showing the substantial influence of AL on BL, also revealing the significant influences of HV on AL and the EV on BL among the customers of luxury cars. SV of the customers influences their AL as well as BL. In contrast to the previous literature (Hassan, 2015, Yeh et al., 2016; Kim et al., 2019), the relationship of FV with AL and BL is not supported by the results; because the respondents are luxury car owners, they are looking for something more than tangible and material aspects. As per the finding of the indirect effect, AL strongly mediates and relates the HV and SV with BL.
9. Implications of the study
Today’s rapidly growing vehicle markets are the major avenues for luxury car companies for their expansion and income generation. The study identified the indicators or dimensions of perceived values which directly influence the AL and BL among luxury car owners; this study also examined the indirect effect of these values on BL through the mediator of AL. The results proved that at first the owners of luxury cars provide more importance to the experience and pleasure they availed from their branded car, i.e. the Hedonic dimensions have a great impact on AL and which leads to BL, indicating that HV is a major predictor of loyalty. Hence, while launching new models, the manufactures of luxury cars provide more importance to hedonic elements and add more features and configurations, which increase the pleasure and emotional attachments of customers. Second, luxury car owners have some price perception about their brand car, and therefore, EV significantly influences repurchase intention or BL; these are to be considered by the manufacturers and dealers to try to give price reduction and charge fair and reasonable price for spares and components. SV represents how customers gain pleasure in the style and appearance of the luxury car they owned; individuals and others have strong perceptions about the social status and symbolic dimensions they acquired; this will have an impact on the brand attachment, AL and BL. Management takes more efforts to improve these values among luxury car owners and to develop a favorable attitude and emotional bond toward the brand. The study findings also demonstrate that when a business can foster a relationship with its clients, it will pay off in the form of consumer recommendations and repurchase intent. Nowadays, while purchasing, using and gifting luxury cars, the owners look for their esteem and prestige, rather than functional utility.
10. Limitations and directions for future research
The present study has some limitations and directions for future research like other studies. Since only customers of luxury car owners are focused in the study, parallel studies may be undertaken in other segments of cars like premium or compact segments, and the geographical area of the study was limited to Ernakulam district, Kerala. Further studies could be carried out in other states or countries. Researchers who are interested in the area of PV and brand loyalty may conduct a survey with a bigger sample to validate the theoretical model and the effectiveness of the implications of this study.
Figures
Demographic profile of the respondents
| Variables | Categories | No. of respondents (n = 120) | Percentage |
|---|---|---|---|
| Gender | Male | 94 | 78 |
| Female | 26 | 22 | |
| Age (in years) | 18–30 | 15 | 13 |
| 31–40 | 28 | 23 | |
| 41–50 | 35 | 29 | |
| Above 50 | 42 | 35 | |
| Income | Less than ₹ 10 lakhs | 23 | 19 |
| ₹ 10 lakhs -₹ 25 lakhs | 58 | 48 | |
| Above ₹ 25 lakhs | 39 | 33 | |
| Education | School | 34 | 28 |
| Graduate | 48 | 40 | |
| Postgraduate | 38 | 32 | |
| Occupation | Government employee | 21 | 18 |
| Private employee | 42 | 35 | |
| Business | 57 | 48 |
Source(s): Primary data
Accuracy analysis statistics
| Variables | Research constructs | Factor loading | Cronbach’s alpha | Composite reliability | Average variance extracted (AVE) |
|---|---|---|---|---|---|
| Functional value (FV) | FV1 | 0.854 | 0.733 | 0.849 | 0.652 |
| FV2 | 0.797 | ||||
| FV3 | 0.769 | ||||
| Economic value (EV) | EV1 | 0.901 | 0.823 | 0.893 | 0.736 |
| EV2 | 0.873 | ||||
| EV3 | 0.795 | ||||
| Symbolic value (SV) | SV1 | 0.870 | 0.825 | 0.886 | 0.722 |
| SV2 | 0.840 | ||||
| SV3 | 0.839 | ||||
| Hedonic value (HV) | HV1 | 0.951 | 0.852 | 0.930 | 0.869 |
| HV2 | 0.913 | ||||
| Attitudinal loyalty (AL) | AL1 | 0.941 | 0.821 | 0.894 | 0.738 |
| AL2 | 0.860 | ||||
| AL3 | 0.768 | ||||
| Behavioral loyalty (BL) | BL1 | 0.662 | 0.741 | 0.843 | 0.645 |
| BL2 | 0.840 | ||||
| BL3 | 0.889 |
Source(s): Computed data
Correlation matrix of select constructs (squares of AVE)
| Variable | AL | BL | EV | FV | HV | SV |
|---|---|---|---|---|---|---|
| AL | 0.859 | |||||
| BL | 0.757 | 0.803 | ||||
| EV | 0.461 | 0.617 | 0.858 | |||
| FV | 0.562 | 0.524 | 0.522 | 0.807 | ||
| HV | 0.718 | 0.629 | 0.560 | 0.664 | 0.932 | |
| SV | 0.657 | 0.491 | 0.501 | 0.801 | 0.730 | 0.850 |
Source(s): Computed data
Hypothesis test results of direct effect
| Hypotheses | Path | Path coefficient | T-statistics | p values | Results |
|---|---|---|---|---|---|
| H1 | FV → AL | −0.028 | 0.310 | 0.757 | Not supported |
| H2 | FV → BL | 0.170 | 1.828 | 0.068 | Not supported |
| H3 | EV → AL | 0.053 | 0.709 | 0.478 | Not supported |
| H4 | EV → BL | 0.332 | 4.854 | 0.000 | Supported |
| H5 | SV → AL | 0.295 | 2.557 | 0.011 | Supported |
| H6 | SV → BL | −0.296 | 2.586 | 0.010 | Supported |
| H7 | HV → AL | 0.491 | 5.987 | 0.000 | Supported |
| H8 | HV → BL | 0.086 | 0.839 | 0.402 | Not Supported |
| H9 | AL → BL | 0.640 | 7.891 | 0.000 | Supported |
Source(s): Computed data
Bootstrapping result of indirect effect
| Hypothesis | Path | Path coefficient | T-statistics | p values | Results |
|---|---|---|---|---|---|
| H10 | FV → AL → BL | −0.018 | 0.306 | 0.760 | Not supported |
| EV → AL → BL | 0.034 | 0.731 | 0.465 | Not supported | |
| SV → AL → BL | 0.198 | 2.283 | 0.022 | Supported | |
| HV → AL → BL | 0.315 | 4.748 | 0.000 | Supported |
Source(s): Computed data
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