Prerpints.org logo
Preprint
Article

Can Social Media-Driven Trust and Customer positive Emotions with a Car Dealership Increase Brand Love?

Altmetrics

Downloads

284

Views

140

Comments

0

Submitted:

18 January 2024

Posted:

12 February 2024

You are already at the latest version

Alerts
Abstract
The purpose of this study is to analyse the drivers and outcomes of the brand love derived from consumption experiences in the automobile retail sector. We examine the effects of consumers’ perceptions of perceived service quality and the trust they feel towards a car dealership (cognition) on emotions and brand love (affection), and the effects of brand love on consumers´ behavioural intentions (conation). This research provides insights into customer brand love in the automobile industry.
Keywords: 
Subject: Business, Economics and Management  -   Marketing

1. Introduction

Brand love is a reflection of the emotional responses of satisfied consumers. This ‘love-like’ attachment stems from a deep satisfaction with the brand. Researchers have argued that positive emotions play a strong role in brand love [5]. Positive emotions are associated with consumers’ willingness to invest time, effort and resources into the brands they love [1]. In the highly competitive automobile business environment, every car dealer tries hard to make their customers happy. There is evidence in the previous literature that the customer´s positive emotions with service facilities is the key to increasing his/her brand love [6].
Although brand love is acknowledged as being an important construct in consumer–brand relationships [1], only limited research has taken place into the combined influence of the cognitive and affective drivers of brand love, and its consequences for these relationships. Offering automobile customers high-quality services, based on their needs and expectations, is increasingly seen as a condition for developing successful marketing strategies that satisfy and retain customers. The novelty of the present study lies in its exploration of the links between the dimensions of perceived service quality, brand love and its effects on behavioural intentions.

2. Literature Review and Hypotheses Development

The cognition-affection-conation (C-A-C) framework [10] is based on the sequential linkages of cognition-affection and conation in human decision-making processes: cognitive factors lead to affective outcomes that consequently impact on conation, which ultimately stimulates actual behaviours. Cognition relates to a person’s thoughts, beliefs and values regarding an object; affect relates to a person’s feelings or emotions felt towards the object; and conation represents the development of the individual´s behavioural intentions and actual behaviours towards that object. The C-A-C framework illustrates how consumers translate their experiences, learning and perceptions into behaviours through affect, which is precisely in line with our objective of understanding the behaviours of car brand loving clients. Based on literature review, we propose that:
Hypothesis 1 (H1).
Positive emotions evoked by the car purchasing experience at the dealership increases brand love for the car brand.
Hypothesis 2 (
H2). Trust in the car dealership influences car brand love:
Hypothesis 3 (H3).
The perceived service quality provided by the car dealership influences the customer´s trust in the car dealership.
Hypothesis 4 (H4).
The perceived service quality provided by the car dealership evokes customer positive emotions.

3. Methodology

The empirical study took place March-October 2023, in collaboration with a leading automobile dealership. The quantitative study was based on data obtained from an online questionnaire.
We operationalised the study constructs using multi-item scales measured mostly by five-point Likert scales, ranging from ‘strongly disagree’ (1) to ‘strongly agree’ (5).
Car brand love was measured using a 10-item scale adapted from [2]. The respondents´ self-reported trust was measured using a 3-item scale adapted from [36]. Perceived service quality (PSQ) was measured as a formative second-order construct. We used three dimensions to capture PSQ, that is “personnel”, “price” and “operational service performance”.

4. Results

4.1. Psychometric Properties of the Measurement Model

We established the theoretical structure of the model using the “repeated indicator approach” [39] and partial least squares (PLS). We opted for PLS-SEM as the estimation method due to the complexity of the model, which involves numerous constructs (including a second-order formative construct), indicators and model relationships [40].
The parameter estimation was carried out using Smart-PLS 4.0 [41], and we performed bootstrapping with 5,000 samples to determine the significance of the parameters (see Table 2). The composite reliability of the constructs exceeded the recommended threshold of 0.60 [42]. In addition, the average variance extracted (AVE) for all constructs surpassed the 0.50 threshold [43]. As an indicator of convergent validity, the confirmatory factor analysis (CFA) demonstrated that all items were significantly related (p < 0.01) to their respective factors [44].
Table 1 displays also the mean factor loadings for all the dimensions, each of which exceeds the criteria for convergent validity. Finally, the results show that the model has no collinearity problems in the reflective-formative second-order construct of perceived service quality.
Table 1. Reliability and convergent validity of the measurement instrument.
Table 1. Reliability and convergent validity of the measurement instrument.
First order factors Item Std loadings t value (bootstrapping) rho_A CR AVE
PSQ Personnel
(PER)		 PER1 .93 130.40** .97 .98 .88
PER2 .94 158.42**
PER3 .94 173.62**
PER4 .95 167.98**
PER5 .93 153.46**
PSQ Price (PRI) PRI1 .95 171.37** .97 .98 .88
PRI2 .93 98.73**
PRI3 .95 132.73**
PRI4 .94 145.13**
PRI5 .93 139.50**
PSQ Operational service performance
(OSP)		 OSP1 .90 80.12** .97 .98 .86
OSP2 .94 120.20**
OSP3 .93 99.78**
OSP4 .95 189.26**
OSP5 .95 184.06**
OSP6 .89 64.49**
OSP7 .93 99.65**
Car dealership trust (TRU) TRU1 .96 203.12** .95 .97 .90
TRU2 .95 168.17**
TRU3 .95 165.75**
Car brand love (LOV) LOV1 .92 129.47** .98 .98 .85
LOV2 .91 69.69**
LOV3 .93 140.14**
LOV4 .88 54.4**
LOV5 .94 152.08**
LOV6 .92 100.07**
LOV7 .93 138.51**
LOV8 .93 151.48**
LOV9 .93 135.56**
LOV10 .92 94.97**
Second-order factor VIF
Perceived Service Quality (PSQ) Personnel .48 20.732** 2.24
Price .31 12.484** 2.58
Oper. service performance .32 10.567** 3.56
N/A: Single item latent variable (Not applicable). VIF: Variance Inflation Factor. rho_A=Dijkstra-Henseler rho; CR=Composite reliability; AVE=Average variance extracted. **p<0.0
The measurement model’s ability to discriminate between constructs was verified using the [43], the square roots of the AVEs exceeding the inter-construct correlations. In addition, the heterotrait-monotrait ratio values support the conclusion that the measurement model possesses discriminant validity.
Table 2 presents the outcomes of the hypotheses testing and displays the standardised coefficients for each structural relationship and the corresponding significance levels of the t statistics.
Table 2. Hypotheses testing.
Table 2. Hypotheses testing.
Hypotheses Std. beta t value (bootstrapping) f2 95% CI
2.50% 97.50%
H1 Positive emotions -> Car brand love .42* 6.79* .10 .29 .54
H2 Car dealership trust -> Car brand love .28* 4.40* .05 .16 .41
H3 Perceived service quality -> Car dealership trust .82* 40.94* 2.02 .78 .86
H4 Perceived service quality -> Positive emotions .81* 37.09* 1.85 .76 .850
The results show that all the structural paths achieved bootstrap t values over 2.326, at a significance level of 1%, that is, 99% confidence. The estimation of the model confirms that PSQ is a powerful predictor of trust in the car dealership (β=.82) and the emotions experienced by the customer (β=.82), and that these two emotional responses towards the car dealership translate into greater car brand love for the manufacturer (emotions: β=.42, H1 accepted; trust: β=.81). This satisfactory estimation was accompanied by R2 and Q2 values that met the minimum established criteria; thus, the structural model shows predictive relevance

5. Conclusions

This research contributes to the existing literature on brand love and emotions and has implications for the automobile industry. The recent literature on emotions explains their importance in enhancing brand love. Understanding how perceived service quality generates brand love will help automobile retailers gain competitive advantage and respond to consumers’ demands.
The study has some limitations that open promising avenues for future research. First, the cross-sectional nature of the study can provide only a snapshot of the hypothesised paths; a longitudinal design could be used to identify time-based facets and provide more rigorous empirical support for the hypotheses.
Second, we are keenly aware that focusing on a single company and product type (new cars) limits the generalisability of the results (hence, it would be worthwhile to test the model with a sample of second-hand cars). Future studies might validate the results by examining other companies and product categories. For example, it is conceivable that perceived service quality could be a more important issue for service than for product providers, and for hedonic than for utilitarian offers.
Third, the present research is limited by the constructs examined. Future studies might delve into other brand-level effects and interactions, such as the role of brand uniqueness and brand desire, to shed light on the potential boundary conditions.

References

  1. Batra, R.; Ahuvia, A.; Bagozzi, R.P. Brand love. Journal of marketing 2012, 76, 1–6. [Google Scholar] [CrossRef]
  2. Carroll, B.A.; Ahuvia, A.C. Some antecedents and outcomes of brand love. Marketing letters 2006, 17, 79–89. [Google Scholar] [CrossRef]
  3. Ahmad, F.; Guzmán, F. Perceived injustice and brand love: the effectiveness of sympathetic vs empathetic responses to address consumer complaints of unjust specific service encounters. Journal of Product & Brand Management. 2023 Jan 12. [CrossRef]
  4. Le, M.T. The impact of brand love on brand loyalty: the moderating role of self-esteem, and social influences. Spanish Journal of Marketing-ESIC 2021, 25, 156–180. [Google Scholar] [CrossRef]
  5. Roy, S.K.; Eshghi, A.; Sarkar, A. Antecedents and consequences of brand love. Journal of Brand Management 2013, 20, 325–332. [Google Scholar] [CrossRef]
  6. Kumar, A. Analysing the drivers of customer happiness at authorized workshops and improving retention. Journal of Retailing and Consumer Services 2021, 62, 102619. [Google Scholar] [CrossRef]
  7. Liang, C.C.; Yu, A.P.; Le, T.H. Customers focus and impulse buying at night markets. Journal of Retailing and Consumer Services 2021, 60, 102434. [Google Scholar] [CrossRef]
  8. Gulzari, A.; Wang, Y.; Prybutok, V. A green experience with eco-friendly cars: A young consumer electric vehicle rental behavioral model. Journal of Retailing and Consumer Services 2022, 65, 102877. [Google Scholar] [CrossRef]
  9. Baumeister, C.; Scherer, A.; Wangenheim, F.V. Branding access offers: the importance of product brands, ownership status, and spillover effects to parent brands. Journal of the Academy of Marketing Science 2015, 43, 574–588. [Google Scholar] [CrossRef]
  10. Hilgard, E.R. The trilogy of mind: Cognition, affection, and conation. Journal of the History of the Behavioral Sciences 1980, 16, 107–117. [Google Scholar] [CrossRef] [PubMed]
  11. Qin, H.; Osatuyi, B.; Xu, L. How mobile augmented reality applications affect continuous use and purchase intentions: A cognition-affect-conation perspective. Journal of Retailing and Consumer Services 2021, 63, 102680. [Google Scholar] [CrossRef]
  12. Yang, J.; Mundel, J. Effects of brand feedback to negative eWOM on brand love/hate: an expectancy violation approach. Journal of Product & Brand Management 2022, 31, 279–292. [Google Scholar] [CrossRef]
  13. Morgan, R.M.; Hunt, S.D. The commitment-trust theory of relationship marketing. Journal of marketing 1994, 58, 20–38. [Google Scholar] [CrossRef]
  14. Orzan, G.; Platon, O.E.; Stefănescu, C.D.; Orzan, M. Conceptual model regarding the influency of social media marketing communication on brand trust, brand affect and brand loyalty. Economic Computation & Economic Cybernetics Studies & Research. 2016, 50.
  15. Gültekin, B.; KİLİC, S.I. Repurchasing an Environmental Related Crisis Experienced Automobile Brand: An Examination in the Context of Environmental Consciousness, Brand Trust, Brand Affect, and Resistance to Negative Information. Sosyoekonomi 2022, 30, 241–260. [Google Scholar] [CrossRef]
  16. Parasuraman, A.B.; Zeithaml, V.A.; Berry, L. SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality 1988, 64, 12–40. [CrossRef]
  17. Andaleeb, S.S.; Basu, A.K. Technical complexity and consumer knowledge as moderators of service quality evaluation in the automobile service industry. Journal of retailing 1994, 70, 367–381. [Google Scholar] [CrossRef]
  18. Chai, J.C.; Malhotra, N.K.; Alpert, F. A two-dimensional model of trust–value–loyalty in service relationships. Journal of retailing and consumer services 2015, 26, 23–31. [Google Scholar] [CrossRef]
  19. Vacas de Carvalho, L.; Azar, S.L.; Machado, J.C. Bridging the gap between brand gender and brand loyalty on social media: Exploring the mediating effects. Journal of Marketing Management 2020, 36, 1125–1152. [Google Scholar] [CrossRef]
  20. Ahmed, Q.M.; Raziq, M.M.; Ahmed, S. The role of social media marketing and brand consciousness in building brand loyalty. GMJACS 2018, 8, 12. [Google Scholar]
  21. Karjaluoto, H.; Munnukka, J.; Kiuru, K. Brand love and positive word of mouth: the moderating effects of experience and price. Journal of Product & Brand Management 2016, 25, 527–537. [CrossRef]
  22. Homburg, C.; Koschate, N.; Hoyer, W.D. Do satisfied customers really pay more? A study of the relationship between customer satisfaction and willingness to pay. Journal of marketing 2005, 69, 84–96. [Google Scholar] [CrossRef]
  23. Huang, C.C. The impacts of brand experiences on brand loyalty: mediators of brand love and trust. Management Decision 2017, 55, 915–934. [Google Scholar] [CrossRef]
  24. Bairrada, C.M.; Coelho, A.; Lizanets, V. The impact of brand personality on consumer behavior: the role of brand love. Journal of Fashion Marketing and Management: An International Journal 2019, 23, 30–47. [Google Scholar] [CrossRef]
  25. Dwivedi, A.; Nayeem, T.; Murshed, F. Brand experience and consumers’ willingness-to-pay (WTP) a price premium: Mediating role of brand credibility and perceived uniqueness. Journal of Retailing and Consumer Services 2018, 44, 100–107. [Google Scholar] [CrossRef]
  26. Research and Markets. (2023). Jordan Automotive Market: Size, Share, Outlook. Retrieved from https://www.researchandmarkets.com/reports/5713278/jordan-automotive-market-size-share-outlook#.
  27. Molina-Azorin, J.F.; Guetterman, T.C. Special Issues on Mixed Methods Research: Expanding the Use of Mixed Methods in Disciplines. Journal of Mixed Methods Research 2023, 17, 234–242. [Google Scholar] [CrossRef]
  28. Martí-Parreño, J.; Galbis-Córdova, A.; Currás-Pérez, R. Teachers’ beliefs about gamification and competencies development: A concept mapping approach. Innovations in education and teaching international 2021, 58, 84–94. [Google Scholar] [CrossRef]
  29. Kane, M.; Trochim, W.M. Concept mapping for planning and evaluation. Sage Publications, Inc; 2007.
  30. Sørensen, F.; Fuglsang, L.; Sundbo, J.; Jensen, J.F. Tourism practices and experience value creation: The case of a themed attraction restaurant. Tourist Studies 2020, 20, 271–297. [Google Scholar] [CrossRef]
  31. Royo-Vela, M.; Casamassima, P. The influence of belonging to virtual brand communities on consumers’ affective commitment, satisfaction and word-of-mouth advertising: The ZARA case. Online Information Review 2011, 35, 517–542. [Google Scholar] [CrossRef]
  32. Murillo-Zegarra, M.; Ruiz-Mafe, C.; Sanz-Blas, S. The effects of mobile advertising alerts and perceived value on continuance intention for branded mobile apps. Sustainability 2020, 12, 6753. [Google Scholar] [CrossRef]
  33. Ballester, E.; Ruiz-Mafé, C.; Rubio, N. Females’ customer engagement with eco-friendly restaurants in Instagram: the role of past visits. International Journal of Contemporary Hospitality Management 2023, 35, 2267–2288. [Google Scholar] [CrossRef]
  34. Bagozzi, R.P.; Dholakia, U.M. Antecedents and purchase consequences of customer participation in small group brand communities. International Journal of research in Marketing 2006, 23, 45–61. [Google Scholar] [CrossRef]
  35. Russell, J.A. Measures of emotion. In The measurement of emotions 1989 Jan 1 (pp. 83-111). Academic Press.
  36. Flavián, C.; Guinalíu, M.; Gurrea, R. The role played by perceived usability, satisfaction and consumer trust on website loyalty. Information & management 2006, 43, 1–4. [Google Scholar] [CrossRef]
  37. Bigne, E.; Andreu, L.; Perez, C.; Ruiz, C. Brand love is all around: loyalty behaviour, active and passive social media users. Current Issues in Tourism 2020, 23, 1613–1630. [Google Scholar] [CrossRef]
  38. Eisingerich, A.B.; Rubera, G.; Seifert, M.; Bhardwaj, G. Doing good and doing better despite negative information? :The role of corporate social responsibility in consumer resistance to negative information. Journal of Service Research 2011, 14, 60–75. [Google Scholar]
  39. Lohmöller, J.B.; Lohmöller, J.B. Predictive vs. structural modeling: Pls vs. ml. Latent variable path modeling with partial least squares. 1989,199-226.
  40. Hair Jr, J.; Page, M.; Brunsveld, N. Essentials of business research methods. Routledge; 2019 Nov 5.
  41. Ringle, C.M.; Sarstedt, M.; Sinkovics, N.; Sinkovics, R.R. A perspective on using partial least squares structural equation modelling in data articles. Data in Brief 2023, 48, 109074. [Google Scholar] [CrossRef] [PubMed]
  42. Bagozzi, R.P.; Yi, Y. On the evaluation of structural equation models. Journal of the academy of marketing science 1988, 16, 74–94. [Google Scholar] [CrossRef]
  43. Nunnally, J.C.; Bernstein, I.H. Psychometric Theory New York. NY: McGraw-Hill. 1994. [Google Scholar]
  44. Fornell, C.; Larcker, D.F. Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research 1981, 18, 39–50. [Google Scholar] [CrossRef]
  45. Goldsmith, R. The Big Five, happiness, and shopping. Journal of Retailing and Consumer Services 2016, 31, 52–61. [Google Scholar] [CrossRef]
  46. Gong, T.; Yi, Y. The effect of service quality on customer satisfaction, loyalty, and happiness in five Asian countries. Psychology & Marketing 2018, 35, 427–442. [Google Scholar]
  47. Yan, W.J.; Chiou, S.C. Dimensions of customer value for the development of digital customization in the clothing industry. Sustainability 2020, 12, 4639. [Google Scholar] [CrossRef]
  48. Aksoy, L.; Keiningham, T.L.; Buoye, A.; Lariviere, B.; Williams, L.; Wilson, I. Does loyalty span domains? Examining the relationship between consumer loyalty, other loyalties and happiness. Journal of Business Research 2015, 68, 2464–2476. [Google Scholar]
  49. Tu, Y.; Hsee, C.K. Hedonomics: On subtle yet significant determinants of happiness. Handbook of Well-being. 2018:248.
  50. Kumar, A.; Luthra, S.; Khandelwal, D.K.; Mehta, R.; Chaudhary, N.; Bhatia, S. Measuring and improving customer retention at authorised automobile workshops after free services. Journal of Retailing and Consumer Services 2017, 39, 93–102. [Google Scholar] [CrossRef]
  51. Srivastava, M.; Kaul, D. Exploring the link between customer experience–loyalty–consumer spend. Journal of Retailing and Consumer Services 2016, 31, 277–286. [Google Scholar] [CrossRef]
  52. Jiang, W.; Lü, Y.; Liu, Y.; Gao, W. Ecosystem service value of the Qinghai-Tibet Plateau significantly increased during 25 years. Ecosystem services 2020, 44, 101146. [Google Scholar] [CrossRef]
  53. Turgut & Gultekin, 2015 Turgut, M.U.; Gultekin, B. The critical role of brand love in clothing brands. Journal of Business Economics and Finance. 2015, 4.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
Prerpints.org logo

Preprints.org is a free preprint server supported by MDPI in Basel, Switzerland.

facebook logotwitter logolinkedin logo
MDPI Initiatives
Important Links
Subscribe

Disclaimer

Terms of Use

Privacy Policy

© 2024 MDPI (Basel, Switzerland) unless otherwise stated