Analysts believe that the Vietnamese airline industry's profit growth will be higher. There is a need for a strategy to manage customer relationships in the airline industry. To attract new customers and retain old ones without spending too much, airline businesses have built and invested in customer loyalty programs [1]. It is not difficult to see that the games of the "big guys" are becoming increasingly diverse in the international airline market. However, in Vietnam, the appeal of airline loyalty programs is still limited. Although the alliance between airlines and other brands is growing stronger, some current programs have bonus points and gifts, but do not bring much value and are not suitable for tastes, low frequency of use, short preferential use period, few choices and forcing customers to meet several additional conditions. It is now more important than ever to recapture the functionality of loyalty programs so as to achieve their objectives of gaining and maintaining customer relationships. In previous research, customer perceived benefits have been found out to reinforce loyalty; however, the benefits evaluated by respondents were varied from place to place, time to time [2,3]. Therefore, it is significant for Vietnam businesses to fully have an insight into customer perceived benefits, which in turn drives customer loyalty, especially in the last stage of recovering from pandemic. 

Based on intensive literature reviews, this study began with (1) examining the drives of airline loyalty program, which were customers’ perceived benefits affecting perceived relationship investment in Vietnam based on the model of Mimouni-Chaabane and Volle [2]. Afterward, following Wang et al.’s research [3], (2) the relationship between perceived relationship investment and brand relationship quality (connection and partner quality), which influences the loyalty to a specific airline brand, also investigated. With loyalty programs, airlines may establish a close bond with their customers, facilitating open communication between them and among the airlines. This research gives a managerial complication for airlines to recognize the benefits customers value combining with brand relationship quality in order to invest in a more effective loyalty program.

Literature Review

Customer Loyalty Programs: Loyalty programs are promotional activities in which businesses reward loyal consumers with benefits. Consumers that participate in a loyalty program desire to get more connected with the business and as a result, a portion of the customers become more loyal to the company [4]. These programs encourage repeat purchases and boost client retention rates by encouraging customers to make more frequent and larger purchases.

The Frequent Flyer Program is a loyalty program of an airline. Many airlines have Frequent Flyer Programs in place to encourage customers to earn points that can then be redeemed for air tickets or other things. Points are awarded based on the pricing class, distance traveled on that airline or its partners and the amount paid under FFPs [5].

Perceived Relationship Investment

Perceived relationship investment means how much time and money an airline puts into enhancing the perceived quality of its client relationship development; because the cost of losing the customers’ engagement is significant [6, 7]. This perceived relationship investment is frequently assessed by customers [8]. The organization's efforts have a positive effect on how people see its ability and involvement in investment to the relationships with customers. People will automatically conclude how much effort the brand is making to preserve a loyal member [9].

Perceived Benefits

Some benefits chosen to evaluate the effectiveness of loyalty programs are utilitarian benefits (monetary savings), hedonic benefits (exploration and entertainment) and symbolic benefits (recognition and social benefits) [2]. In reality, a combination of benefits exists in one service as well as one frequent flyer program.

Utilitarian value in loyalty programs comes in part from economic incentives [10]. The primary incentive for joining airline loyalty programs is the eagerness to save money [2]. Members of loyalty program who routinely make their purchases from the same brand get cash-back and discounts, which reflect financial savings [11]. Monetary savings are known as the most powerful tool of airline loyalty programs influencing customer satisfaction, in turn significantly increase loyalty. As a result, a business that undertakes various efforts to provide extra financial savings raises the perceived relationship investment of passengers [2]. Therefore, the below hypothesis can be proposed.

Hypothesis 1: Monetary Savings Benefit Positively Affects Perceived Relationship Investment

Hedonic benefits are based on customers’ positive emotions and experiences in the early stage of purchasing or the final stage of practical involvement in using the products or services [12,13]. Exploration and entertainment are two attractive areas for members who like to enjoy and discover things. In this scenario, customers are players and the program is an entertained game [2]. These values are perceived variedly based on each’s perspective [14]. As consumers learn more and fulfill their mental requirements for discovery, their perceived relationship investment builds, leading them to take the company into account when reserving flights. Therefore, the below hypothesis can be proposed.

Hypothesis 2: Exploration Benefit Positively Affects Perceived Relationship Investment

Customers increasingly become aware of the appealing aspects of loyalty programs as they love exchanging points, which makes them value the entertainment advantages and increases their commitment to consistently maintain a bilateral connection with the airline [3]. Customers' perceived relationship investment grows as they have more enjoyable encounters [2]. Therefore, the below hypothesis can be proposed.

Hypothesis 3: Entertainment Benefit Positively Affects Perceived Relationship Investment

Symbolic benefits are the intangible gain for customers from loyalty programs and this gain differentiates from one person to another and treats unequally regarding self-expression, self-worth and societal acceptance [15]. Consumers are treated better when they join loyalty programs and meet the recognition benefits [16]. They are now a part of privileged customers and have the ability to try the add-on services [17]. 

Frequent flyers are readily identified by front-line staff during check-in procedure whenever entering flights, according to the recognition privileges offered by airline loyalty programs. Additionally, they feel appreciated and receive more attention in terms of services. As customers perceive that airlines respect them more, perceived relationship investment steadily rises. Therefore, the below hypothesis can be proposed.

Hypothesis 4: Recognition Benefit Positively Affects Perceived Relationship Investment

Social advantages frequently match more complex psychological requirements. They can improve their sense of self-esteem and capture the superiority of the community [18]. Considering the social rewards of airline loyalty programs, participants will feel that they are a significant and highly appreciated segment of the customer base when an airline has positive, high-value, honorable, or luxurious brand image [3]. When consumers become more appreciated and respected by the airline, members sense that their status is steadily rising, boosting perceived relationship investment [2]. Therefore, the below hypothesis can be proposed.

Hypothesis 5: Social Benefit Positively Affects Perceived Relationship Investment

Brand Relationship Quality: Although there are seven aspects of Brand Relationship Quality (BRQ) founded by [19], this research followed Smit et al. [20], results to examine only connection and partner quality aspects. Connection means the similarity in value customers perceive towards a brand [20]. Customers can feel the common of the brand that other brands cannot arise. And a feeling of loss occurs when they do not purchase that airline’s products or services in a long time. Besides, partner quality is the term to describe a brand’s quality of products or services toward a specific customer. This is also assessed by customers after receiving the treatment and behaviors of the company. In return, the partner quality also illustrates the extent of the back-and-forth trust between the customer and the brand, which means the brand build trust towards the customer and then the customer rebuilds that trust towards the brand.

When connections are stronger, people are more willing to give up some privacy by exchanging personal information with the company behind the brand. In respond, airlines constantly upgrade their offerings to draw clients’ involvement. After travelers consider flying with a specific airline as the norm, their relationship with that airline broadens. If they are ever unable to purchase at such airline, they have a negative feeling [20]. Therefore, the below hypothesis can be proposed.

Hypothesis 6: Perceived Relationship Investment Positively Affects Brand Connection

When airlines provide key clients with extra services, from the standpoint of the airline business, the consumers feel more appreciated and important. Due to this reason, an airline might become the top choice for some clients through long-term partner partnerships. As a consequence, that airline is no longer concerned about potential airline competition because partner quality combined with trust, personal commitment and love [3,6]. Therefore, the below hypothesis can be proposed.

Hypothesis 7: Perceived Relationship Investment Positively Affects Partner Quality

Customer Loyalty: Customer loyalty refers to the consistent engagement of a customer to a specific brand above other competitors in the market [21]. Furthermore, customer loyalty, according to Aaker, [22], indicates the probability that a customer's choices will alter if the price or kind of service/product given changes. Customer satisfaction is crucial to airlines and it has an impact on clients returning to the firm thanks to its service. The COVID-19 outbreak helps companies determine whether their customers are loyal. Customers must now prioritize their brands because demand will be reduced because of the financial crisis induced by the epidemic. Customers of a brand can be described as loyal if their sales do not shift significantly. Marketing departments may now distinguish between actual loyalty consumers and people who purchase their brand on a regular basis as a result of this overwhelming worldwide problem [23].

Stronger ties between consumers and businesses promote greater loyalty [24]. Customers have a tendency to show a strong preference for an airline when they have a better understanding of the business and a more favorable perception of it. This helps to forge strong connections and encourages clients to discover links between themselves and the virtues and standards of business conduct of the airline [2]. Therefore, the below hypothesis can be proposed.

Hypothesis 8: Brand Connection Positively Affects Loyalty

By keeping in touch with customers and building corporate image, high-quality partners help companies build strong customer connections that in turn increase customer loyalty [25]. The necessity of improving partner quality is further heightened in the airline business since airlines need to attract new consumers as well as keep their current ones [26]. Only partner relationships can enhance customer loyalty. Therefore, the below hypothesis can be proposed.

Hypothesis 9: Partner Quality Positively Affects Loyalty

Figure 1: Conceptual Framework

This study used both qualitative and quantitative research to gather primary data based on prior studies and theoretical foundations before building a conceptual framework and collecting market data using a questionnaire. To be more specific, hypotheses were formed in qualitative research based on all data gathered and connected from secondary research in prior studies as well as theoretical foundations. Then, to show the hypothesis regarding the link between variables, a conceptual framework would be developed. Finally, all these hypotheses will be tested using a quantitative technique that relies on questionnaires to conduct surveys and gather data. Following that, all raw data will be evaluated and identified before final findings and suggestions are formed, which will be valuable for thorough comprehension and subsequent application.

This study collected initial data samples using a survey questionnaire method. Variables were assessed on a 7-point Likert scale to correlate with the service-oriented questions created for this study. The measurement scales were adapted from Mimouni-Chaabane and Volle [2], Smit et al., [20], de Wulf et al. [6] and Aydin et al. [27].

This survey was carried out from September 2022 to December 2022, in Ho Chi Minh City and online platform. The respondents were required to have membership cards of airlines, which was the only condition to do survey. Data of 247 was analyzed using the statistical software package SPSS version 26 and SPSS AMOS version 26. Regression, factor analysis, correlation and analysis of variance are elements of typical multivariate analytic techniques that can be developed. P-values of less than 0.05 were utilized to make statistical significance decisions. The statistical analysis methods employed for this study included descriptive statistical analysis, reliability analysis, validity analysis and Structural Equation Modeling (SEM) analysis.

Data Description

Table 1 shows ways to collect data and the number of respondents. When gathering data in the early days, people with middle-to-high income were more interested in the content and willing to do the survey since almost all of them had loyalty program memberships. Therefore, to increase the rate of response, the later stage took notice on upper-level consumers.

Table 1: Rate of Response

*The member number of 4 airline-related groups was 24,000 with an engagement rate of 10% (based on Pages, M. (2020)). **Estimated ***Approximate

Reliability Assessment

Cronbach's coefficient alpha, which assesses the internal consistency and coherence of the scale, was estimated to be 0.857 for the entire model. The Cronbach’s alpha values for monetary savings, exploration, entertainment, recognition, social, perceived relationship investment, connection partner quality, loyalty, switching costs and internet experience were 0.916, 0.832, 0.757, 0.784, 0.767, 0.796, 0.891, 0.969, 0.821, 0.946 and 0.978 respectively, which are shown in Table 2.

Table 2: Cronbach's Coefficient Alpha Values

Exploratory Factor Analysis (EFA)

In the first round running EFA, the factor loadings of EN1, EN2 and EN3 were 0.552, 0.662 and 0.534 respectively. According to the equations of Fornell and Larcker [28] and Jöreskog [29], AVE was calculated to be 0.343 (<0.5) and CR to be 0.608 (<0.7), which meant construct EN not having any influence on the model. So, construct EN (measurements EN1, EN2 and EN3) was eliminated from the model.

The EFA test was done once again without the presence of “entertainment benefit” factor loadings. Table 3 and Table 4 demonstrate the results of reliability. The KMO value for the whole model is 0.862, which is a pretty great outcome; and along with the results of the Bartlett's Test, with Sig. being 0.000 and the percentage of each Total Varian Explained is 79.798% (>50%), demonstrating the overall effectiveness of factor analysis. These findings support suitable measurement items for this research.

Table 3: AVE and CR of the Constructs

Table 4: Pearson Correlation Matrix

* Correlation is significant at the 0.05 level (2-tailed). ** Correlation is significant at the 0.01 level (2-tailed).

Average Variance Extracted (AVE) and Composite Reliability (CR)

Table 6 demonstrates that each question's factor loading (λ) was greater than 0.5 and each dimension's average variance extracted (AVE) was greater than 0.5, guaranteeing the criteria for convergent validity. Measurement of the same dimension's internal consistency is shown by composite reliability (CR). Higher construct validity of variables means that variables can be detected more effectively by observable variables. According to the study's findings, each CR value was greater than 0.7 indicating that the survey's questionnaire had a high level of validity as can be seen in Table 5.

Table 5: Structural Equation Modeling Results

Pearson Correlation

The Pearson correlation analysis is shown in Table 6. The independent variables separately had different correlations with perceived relationship investment. Monetary savings and social benefits had a significant relationship with perceived relationship investment (r = -0.271, p<0.01; r = -0.169, p<0.01 respectively), whilst exploration and recognition benefits seemed to show no correlation with perceived relationship investment.

In addition, perceived relationship investment indicated a correlation with connection (r = 0.304, p<0.01) and partner quality (r = 0.272, p<0.01). Next, connection and partner quality did reveal the high correlations with customer loyalty (r = 0.614, p<0.01; r = 0.418, p<0.01 respectively). In terms of moderating effects, it is good when 2 moderators did not show any direct correlation with the variables.

Hypothesis Testing

The indicators of the various model fit indices should be taken into consideration before analyzing the model fit of Confirmatory Factor Analysis (CFA). For the model acceptable, the CMIN/DF value was 3.085 which was less than 5, showing a reasonable fit [30]. The GFI and AGFI were relatively lower than the 0.8 reasonable goodness-of-fit, 0.785 and 0.738 respectively, yet it is known that these measurements rely on the sample size. Furthermore, even though no longer being recommended, they are kept for comparison [31,32]. A CFI value of 0.861, which was larger than 0.85, should be considered satisfactory because it demonstrates significant progress [33]. NFI (0.808) and TLI (0.841), the other fit indices, should be over 0.9 for a good fit [34], however in our sample, they fall just below the standards. Finally, RMSEA levels between 0.05 and 0.08 are considered acceptable, those between 0.08 and 0.1 are considered marginal and those beyond 0.1 are considered poor [35]. As a result, the sample's RMSEA value of 0.092 was worthy of being accepted. Thus, the model, which is demonstrated in Table 8, for brand relationship quality and loyalty in airline industry is acceptably fit.

A significant and negative relationship is present between monetary savings benefit and perceived relationship investment (p-value = 0.000, standardized estimated coefficient = -0.289). There is no significant relationship between exploration benefits and perceived relationship investment (p-value = 0.640) and no significant relationship between recognition benefits and perceived relationship investment (p-value = 0.512). A significant and positive relationship exists between social benefits and perceived relationship investment (p-value = 0.014, standardized estimated coefficient = 0.186). Therefore, Hypothesis 1 and Hypothesis 5 are supported while Hypthesis 2 and Hypothesis 4 are not supported.

Figure 2: Structural Equation Pathway

In terms of the impact on brand relationship quality, brand relationship quality has a significant and positive relationship with connection (p-value = 0.011, standardized estimated coefficient = 0.165) and the same with partner quality (p-value = 0.040, standardized estimated coefficient = 0.143). As a result, Hypothesis 6 and Hypothesis 7 are supported. In terms of the impact on loyalty, there is a significant and positive relationship between connection and loyalty (p-value = 0.000, standardized estimated coefficient = 0.604) and there is no significant relationship between partner quality and loyalty (p-value = 0.497). Thus, Hypothesis 8 is supported while Hypthesis 9 is not supported. The structural equation pathway results are shown in Figure 3.

Discussion and Managerial Implications

To increase competition, airlines enter an era building frequent flyer programs to retain current customers and attract potential ones. Although continuos improvement, it has been a problematic challenge for airlines to compete one another in … This study pointed out the significant influential factors in customers’ airline choices. Perceived benefits including monetary savings and social advantages had an effect on perceived relationship investment, hence influencing perceived relationship quality, particularly flyer-brand connection and partner quality. However, only connection drove loyalty through loyalty programs. Switching cost also altered the relationship between connection and loyalty. Internet experience acted on the relationship between partner quality and loyalty, which indicated internet use was able to strike on the significance of perceived partner quality on loyalty.

Monetary savings benefit and social benefit had direct influence on the perceived relationship investment of customers to a specific brand, which subconscously drove their behaviors to purchase services of that brand. From previous research, it was expected for monetary savings, exploration and entertainment benefits having a positive link with loyalty [2]. But, according to Wang et al. [3], recognition and social benefits were 2 benefits correlating with loyalty. In this study, it was found that monetary savings contrastingly had a negative return on customers’ perceived relationship investment and social benefits increased perceived relationship investment. An explanation for this finding is that if social advantages raise one’s position and sense of worth to another level, monetary savings are less likely to be cared of by that approximate amount. Specifically, customers having a loyalty membership seemed to be more interested in social advantages such as self-esteem and superiority from others rather than cheap ticket prices or discounts. Moreover, respondents were employees or employers who had a relatively high stable income, they preferred social values from the purchase even though paying higher amount. In this way, customers could be admired by others and meet customers being in the same communal group when walking to the VIP lounge, priority security check, etc. 

Customers acknowledged that they got what they paid for, so they were willing to purchase at any suitable cost to receive something equivalent in return. In this research, the return they wanted was social value. Now, managers can discover an insight into customers’ desired prospects when travelling. Managers are capable of comparing their programs with customers’ perceived benefits and with others’ programs to adjust and pay attention to push the criteria implemented to gain competitive advantage.

Furthermore, the level of perceived relationship investments impacts on the level of brand relationship connection and partner quality. When an airline offers a membership card with great services relating to social benefits, a member will decide to trust and value that brand. If customers value an airline’s investment in a loyalty program, they have better connections and strong partner quality relationship with that airline as a return for interrelation.

The brand relationship connection therefore had a significant impact on customer loyalty through frequent flyer program. Firms should focus on building long-lasting relationships with frequent customers by bonding and showing great hostapility. However, customer loyalty was surprisingly not affected by partner quality, which the highly qualified preference seemed to gain no interest in consumers. Exploration, recognition and entertainment benefits could clarify the uncorrelation between them. Trying new things, collecting and exchanging points were linked to the quality of loyalty programs and that airline brand in general. Customers did not really care about these benefits, which made them ignore the perceived partner quality and only repeat purchases based on the level of connection. It may be possible to think some airlines can offer a wide range of frequent flyer programs along with good services, so flyers are willing to stay if there are solid connection and advance trust rather than superior investment and untried quality. So, the stronger a connection is, the more loyal a customer is. Airline brands should focus on building favorable corporate image which is likely to be valued and adopted by customers, hence increasing the connection between 2 sides.

This research brought out a significant finding for Vietnam airline brands to improve their loyalty programs. For customers holding frequent flyer membership, it was not about entertainment, recognition, or exploration benefit, but social benefit was valued contrarily to monetary savings benefit. Therefore, brands should focus on building programs’ image to be adopted by customers. They will be willing to spend and spend more if the airline shares the same value with customers and its loyalty program also asserts customers’ positions in public. The airline industry is positively correlated with growth in per capita income, so in the context of rising average incomes and improved quality of life, mere competition on fares will only lead to race to cut utilities and test customer tolerance. Take, Vietnam Airlines, for example. It reminds of Vietnam due to its name, lotus logo, ao-dai uniform, etc. This can raise the patronism of Vietnamese, so customers pay extra amount to travel by Vietnam Airlines. And due to the similarity in its brand image, customers are likely to have a strong connection to make decisions rather than considering the quality of other airlines. The survey provided evidence by indicating about 64% airline membership holders chose Vietnam Airlines as their favorite brands. 

This study did not find partner quality significant in the context but that does not tell the service quality does not matter to an airline. Maybe airlines can offer the qualities which are valued the same and what retains them is the existing connection. Bamboo Airways believe that no matter what era, no matter the needs of customers’ change, the only thing that never changes is what goes from heart to heart. Attentive, meticulous and enthusiastic service will always be expected and appreciated, which in turn increases loyalty. 

This finding will directly benefit airlines to have a better understanding of customers’ preference in Vietnam and how they choose to use one’s services. Brands now can adjust or focus on some parts to retain loyalty and develop future plans for loyalty programs to influence purchasers’ intention.

Limitations and Recommendations

Even though this study made an effort to be careful and thorough, there were still certain limitations that could have led to some inaccuracies in the research. The following list contains some drawbacks of this study that can come up with further suggestions for researchers and investigations.

Firstly, the sample size was not varied. The respondents were primarily employees from mid- to large-range companies and a small number of university students in Ho Chi Minh City. Moreover, although the survey was spread out throughout the internet by airline-related websites, the number of responses were not enough to be diversified in terms of geographical background and demographic background. Further studies can conduct survey in other big cities in Vietnam such as Ha Noi, Nha Trang and Da Nang.

The model was an acceptable fit rather than a good fit or higher based on the results of CFA. So, the second limitation was the inadequate or excessive number of responses. Furthermore, some of the variables which were not achieved unexpectedly may be caused by the small and invariable sample size. The time limit should be somehow fixed so that researchers can have a larger sample size.

Thirdly, due to the difference in each industry and each market, perceived benefits might be significantly varied. Besides the proposed benefits, others should be paid attention to and tested in future. For example, the corporate image should be taken into consideration as customers treasure the shared value between the brand and them.

1. Gómez, B.G. et al. “The role of loyalty programs in behavioral and affective loyalty.” Journal of Consumer Marketing, vol. 23, no. 7, 2006, pp. 387–396. https://doi.org/10.1108/07363760610712920

2. Mimouni-Chaabane, A. and P. Volle. “Perceived benefits of loyalty programs: scale development and implications for relational strategies.” Journal of Business Research, vol. 63, no. 1, 2010, pp. 32–37. https://doi.org/10.1016/j.jbusres.2009.01.008

3. Wang, E.S.T. et al. “The antecedents and influences of airline loyalty programs: The moderating role of involvement.” Service Business, vol. 9, no. 2, 2015, pp. 257–280. https://doi.org/10.1007/s11628-013-0226-6

4. Yi, Y. and H. Jeon. “Effects of loyalty programs on value perception, program loyalty and brand loyalty.” Journal of the Academy of Marketing Science, vol. 31, no. 3, 2003, pp. 229–240. https://doi.org/10.1177/0092070303031003002

5. Boroh, J. “Investigation into the hub-and-spoke model using brand and frequent-flyer program.” Journal of Airline and Airport Management, vol. 11, no. 2, 2021, p. 73. https://doi.org/10.3926/jairm.190

6. de Wulf, K. et al. “Investments in consumer relationships: a cross-country and cross-industry exploration.” Journal of Marketing, vol. 65, no. 4, 2001.

7. Palmatier, R.W. et al. “Factors influencing the effectiveness of relationship marketing: A meta-analysis.” Journal of Marketing, vol. 70, 2006, pp. 136–153. http://www.marketingpower.com/jmblog.

8. Sung, Y. and S.M. Choi. “‘I won’t leave you although you disappoint me’: The interplay between satisfaction, investment and alternatives in determining consumer-brand relationship commitment.” Psychology and Marketing, vol. 27, no. 11, 2010, pp. 1050–1073. https://doi.org/10.1002/mar.20373

9. Recuero Virto, N. et al. “Perceived relationship investment as a driver of loyalty: The case of conimbriga monographic museum.” Journal of Destination Marketing and Management, vol. 11, 2019, pp. 23–31. https://doi.org/10.1016/j.jdmm.2018.11.001

10. Bolton, R.N. et al. “The theoretical underpinnings of customer asset management: A framework and propositions for future research.” Journal of the Academy of Marketing Science, vol. 32, no. 3, 2004, pp. 271–292. https://doi.org/10.1177/0092070304263341

11. Peterson, R.A. Relationship Marketing and the Consumer. 1995.

12. Babin, B.J. et al. Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value. 1994.

13. Holbrook, M.B. and E.C. Hirschman. The Experiential Aspects of Consumption: Consumer Fantasies, Feelings and Fun. http://jcr.oxfordjournals.org/

14. Chitturi, R. et al. “Delight by design: The role of hedonic versus utilitarian benefits.” Journal of Marketing, vol. 72, no. 3, 2008, pp. 48–63. https://doi.org/10.1509/jmkg.72.3.48

15. Gordon, M.E., et al “Relationship marketing effectiveness: the role of involvement.” Psychology and Marketing, vol. 15, no. 5, 1998. John Wiley and Sons, Inc.

16. Beatty, S.E. et al. “Customer-sales associate retail relationships.” 1996.

17. McAlexander, J.H. et al. “Building brand community.” Journal of Marketing, vol. 66, no. 1, 2002, pp. 38–54. https://doi.org/10.1509/jmkg.66.1.38.18451

18. Park, C.W. et al. “Strategic brand concept-image management.” Journal of Marketing, vol. 50, no. 4, 1986.

19. Fournier, S. and J.L. Yao. “Reviving brand loyalty: A reconceptualization within the framework of consumer-brand relationships.” International Journal of Research in Marketing, vol. 14, 1997.

20. Smit, E. et al. “Brand relationship quality and its value for personal contact.” Journal of Business Research, vol. 60, no. 6, 2007, pp. 627–633. https://doi.org/10.1016/j.jbusres.2006.06.012

21. Singh, R. and I.A. Khan. “An approach to increase customer retention and loyalty in B2C World.” International Journal of Scientific and Research Publications, vol. 2, no. 6, 2012.

22. Aaker, D.A. Measuring Brand Equity Across Products and Markets. 1995.

23. Knowles, J. et al. Growth Opportunities for Brands During the COVID-19 Crisis: A Shock to the System. https://mitsmr.com/3dgxjZG

24. Mele, D. “Loyalty in Business: Subversive doctrine or real need?” 2001.

25. Veloutsou, C. and L. Moutinho. “Brand relationships through brand reputation and brand tribalism.” Journal of Business Research, vol. 62, no. 3, 2009, pp. 314–322. https://doi.org/10.1016/j.jbusres.2008.05.010

26. Dick, A.S. and K. Basu. “Customer loyalty: Toward an integrated conceptual framework.” 1994.

27. Aydin, S. et al. “Customer loyalty and the effect of switching costs as a moderator variable: A case in the turkish mobile phone market.” Marketing Intelligence and Planning, vol. 23, no. 1, 2005, pp. 89–103. https://doi.org/10.1108/02634500510577492

28. Fornell, C. and D.F. Larcker. “Evaluating structural equation models with unobservable variables and measurement error.” Journal of Marketing Research, vol. 18, no. 1, 1981.

29. Jöreskog, K.G. “Simultaneous factor analysis in several populations.” December, vol. 36, no. 4, 1971.

30. Marsh, H.W. and D. Hocevar. “Application of confirmatory factor analysis to the study of self-concept: First- and higher order factor models and their invariance across groups.” Psychological Bulletin, vol. 97, no. 3, 1985.

31. Kline, R.B. Principles and Practice of Structural Equation Modeling. 2nd ed., Guilford Press, 2005.

32. Sharma, S. et al. “Potentiality of earthworms for waste management and in other uses—A review.” The Journal of American Science, vol. 1, no. 1, 2005. http://www.americanscience.org

33. Bollen, K.A. Structural Equations with Latent Variables. John Wiley and Sons, 1989. https://doi.org/10.1002/9781118619179

34. Mulaik, S.A. et al. “Evaluation of goodness-of-fit indices for structural equation models.” Psychological Bulletin, vol. 105, no. 3, 1989, pp. 430–445. https://doi.org/10.1037/0033-2909.105.3.430

35. Fabrigar, L.R. et al. “Evaluating the use of exploratory factor analysis in psychological research.” Psychological Methods, vol. 4, no. 3, 1999, pp. 272–299. https://doi.org/10.1037/1082-989X.4.3.272