The effect of website quality, social media marketing, and personal selling on brand equity through brand loyalty: A study of B2B customers of PT gaya makmur tractors

Authors

  • Jimmy Fernando Pangaribuan Universitas Bina Nusantara, Indonesia
  • Dita Maharani Universitas Bina Nusantara, Indonesia
  • Amia Luthfia Universitas Bina Nusantara, Indonesia

DOI:

https://doi.org/10.58524/jasme.v6i1.1112

Keywords:

Brand equity, Brand loyalty, Personal selling, Social media marketing, Website quality

Abstract

Background: The rapid expansion of digital communication technologies has fundamentally transformed marketing practices in business-to-business (B2B) industries. Despite this shift, the effectiveness of integrating digital channels with interpersonal communication in shaping long-term brand value remains insufficiently explained, particularly within complex industrial markets such as heavy equipment distribution. Existing studies tend to examine website quality, social media marketing, and personal selling in isolation, leaving a critical gap in understanding their combined influence and underlying relational mechanisms.

Aims: This study aims to analyze the integrated effects of website quality, social media marketing, and personal selling on brand equity through brand loyalty, while clarifying the mediating role of relational commitment in a B2B context.

Method: A quantitative explanatory approach was employed using Structural Equation Modeling–Partial Least Squares (SEM-PLS). Data were collected from 302 B2B customers of PT Gaya Makmur Tractors through a structured questionnaire, and analyzed to evaluate both direct and indirect relationships among constructs.

Results: The findings demonstrate that all three communication channels significantly influence brand loyalty and brand equity. Social media marketing exhibits the strongest direct effect on brand equity, followed by personal selling and website quality. Furthermore, brand loyalty acts as a partial mediator, indicating that communication effectiveness operates through both immediate perception and sustained relational engagement.

Conclusion: This study advances the understanding of B2B marketing by positioning brand loyalty as a central relational mechanism within an integrated communication system. The results suggest that brand value in industrial markets is not solely driven by information quality or promotional intensity, but by the ability to align digital credibility with personalized interaction to foster long-term commitment. From a practical standpoint, firms are encouraged to develop coordinated communication strategies that balance digital presence and interpersonal engagement as part of a unified decision-support system. This approach not only strengthens competitive positioning but also enhances the sustainability of customer relationships, offering a more holistic pathway for optimizing brand equity in complex B2B environments.

References

Ahmad, F., Mustafa, K., Hamid, S. A. R., Khawaja, K. F., Zada, S., Jamil, S., Qaisar, M. N., Vega-Muñoz, A., Contreras-Barraza, N., & Anwer, N. (2022). Online Customer Experience Leads to Loyalty via Customer Engagement: Moderating Role of Value Co-creation. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.897851

Batra, S. (2024). Exploring the application of PLS-SEM in construction management research: A bibliometric and meta-analysis approach. Engineering, Construction and Architectural Management, 32(4), 2697–2727. https://doi.org/10.1108/ECAM-04-2023-0316

Bhagat, S., & Kim, D. J. (2023). Examining users’ news sharing behaviour on social media: Role of perception of online civic engagement and dual social influences. Behaviour & Information Technology, 42(8), 1194–1215. https://doi.org/10.1080/0144929X.2022.2066019

Carlson, J., Rahman, S. M., Rahman, M. M., Wyllie, J., & Voola, R. (2021). Engaging Gen Y Customers in Online Brand Communities: A Cross-National Assessment. International Journal of Information Management, 56. https://doi.org/10.1016/j.ijinfomgt.2020.102252

Cheung, G. W., Cooper-Thomas, H. D., Lau, R. S., & Wang, L. C. (2024). Reporting reliability, convergent and discriminant validity with structural equation modeling: A review and best-practice recommendations. Asia Pacific Journal of Management, 41(2), 745–783. https://doi.org/10.1007/s10490-023-09871-y

DİRSEHAN, T., & HENSELER, J. (2023). Modeling indices using partial least squares: How to determine the optimum weights? Quality & Quantity, 57(4), 521–535. https://doi.org/10.1007/s11135-022-01515-5

Hair, J., & Alamer, A. (2022). Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example. Research Methods in Applied Linguistics, 1(3), 100027. https://doi.org/10.1016/j.rmal.2022.100027

International Tourism, Hospitality and Gastronomy Congress, ITHGC 2022. (2025). Lecture Notes in Networks and Systems, 1451 LNNS.

Jo, H., & Park, D.-H. (2023). Mechanisms for successful management of enterprise resource planning from user information processing and system quality perspective. Scientific Reports, 13(1), 12678. https://doi.org/10.1038/s41598-023-39787-y

Khalufi, N. A. M., Sheikh, R. A., Khan, S. M. F. A., & Onn, C. W. (2025). Evaluating the Impact of Sustainability Practices on Customer Relationship Quality: An SEM-PLS Approach to Align with SDG. Sustainability, 17(2). https://doi.org/10.3390/su17020798

Krisprimandoyo, D. A., Sufa, S. A., Wardani, D. T., & Widiyanto, S. (2024). Exploring the Relationship between Social Media Engagement, Customer Reviews, and Brand Perceptions: A Comprehensive Study in Retail Industry. International Journal of Business, Law, and Education, 5(2), 1584–1591. https://doi.org/10.56442/ijble.v5i2.597

Marlinda, L., Rusiyati, S., Adi, W. T., Maisyaroh, Komarudin, R., & Salim, A. (2018). Selection of factors affecting women’s loyalty in buying goods in indonesian e-marketplaces using the profile machine method. Journal of Theoretical and Applied Information Technology, 97(8), 2166–2178.

Moran, M. B., Heley, K., Baldwin, K., Xiao, C., Lin, V., & Pierce, J. P. (2019). Selling tobacco: A comprehensive analysis of the U.S. tobacco advertising landscape. Addictive Behaviors, 96, 100–109. https://doi.org/10.1016/j.addbeh.2019.04.024

Ofori, E. K., Aram, S. A., Saalidong, B. M., Gyimah, J., Niyonzima, P., Mintah, C., & Ahakwa, I. (2023). Exploring new antecedent metrics for safety performance in Ghana’s oil and gas industry using partial least squares structural equation modelling (PLS-SEM). Resources Policy, 81, 103368. https://doi.org/10.1016/j.resourpol.2023.103368

Park, H., & Kim, Y.-K. (2014). The role of social network websites in the consumer-brand relationship. Journal of Retailing and Consumer Services, 21(4), 460–467. https://doi.org/10.1016/j.jretconser.2014.03.011

Prakoesw, C. R. S., Hidayah, N., & Dewi, A. (2022). A Scoping Review of Research on Brand Image, Marketing Mix, Patient Hospital Satisfaction, And Loyalty in Indonesia. Res Militaris, 12(2), 964–983.

Pumjaroen, J. (2025). Forecasting Economic Cycles with Time Series PLS-SEM: Evaluating Reflective vs. Formative Specification of PCA-Derived Indicators. Journal of Business Cycle Research, 21(2), 237–260. https://doi.org/10.1007/s41549-025-00116-z

Radzi, A. R., Rahman, R. A., & Almutairi, S. (2022). Modeling COVID-19 Impacts and Response Strategies in the Construction Industry: PLS–SEM Approach. International Journal of Environmental Research and Public Health, 19(9). https://doi.org/10.3390/ijerph19095326

Subhaktiyasa, P. G. (2024). PLS-SEM for Multivariate Analysis: A Practical Guide to Educational Research using SmartPLS. EduLine: Journal of Education and Learning Innovation, 4(3), 353–365. https://doi.org/10.35877/454RI.eduline2861

Teepapal, T. (2025). AI-driven personalization: Unraveling consumer perceptions in social media engagement. Computers in Human Behavior, 165, 108549. https://doi.org/10.1016/j.chb.2024.108549

Ting, L., & Ahn, J. (2023). Understanding the roles of interaction and trust in formation of loyalty toward customer-to-customer (C2C) platforms. Asia Pacific Journal of Marketing and Logistics, 35(10), 2565–2581. https://doi.org/10.1108/APJML-12-2022-1072

U-on, V., Wantanee, K., & Torthienchai, N. (2025). Trust as a mediator between brand experience and loyalty: evidence from student engagement through digital communication and institutional systems in Thai universities. Scientific Culture, 11(4), 51. https://doi.org/10.5281/zenodo.11042505

Vaithilingam, S., Ong, C. S., Moisescu, O. I., & Nair, M. S. (2024). Robustness checks in PLS-SEM: A review of recent practices and recommendations for future applications in business research. Journal of Business Research, 173, 114465. https://doi.org/10.1016/j.jbusres.2023.114465

Wang, S., Cheah, J.-H., Wong, C. Y., & Ramayah, T. (2023). Progress in partial least squares structural equation modeling use in logistics and supply chain management in the last decade: A structured literature review. International Journal of Physical Distribution & Logistics Management, 54(7–8), 673–704. https://doi.org/10.1108/IJPDLM-06-2023-0200

Wasan, P. (2017). Managing technologies for consumer engagement. In V. Jauhari (Ed.), Hospitality Marketing and Consumer Behavior: Creating Memorable Experiences (pp. 261–289). Apple Academic Press. https://doi.org/10.1201/9781315366227

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Published

2026-03-28