Path Analysis Using Structural Equation Modelling (SEM) to Examine the Moderation of Product Knowledge in the Effects of and Perceived Risk, Environmental Consciousness, and Subjective Norm on Purchase Intention
DOI:
https://doi.org/10.57125/FEL.2024.03.25.01Keywords:
Structural Equation Modelling, Path Analysis, Purchase Intention, Perceived Risk, Environmental Consciousness, Subjective Norm, Product KnowledgeAbstract
The objective of this research was to enhance the comprehension of consumer behaviour by exploring how purchase intentions are influenced by perceived risk, environmental consciousness, and subjective norms, which together create a complex interplay. SEM and PLS, focusing on the moderating role of product knowledge were employed in the study. While consumer marketing has well-established models, business marketing lacks similar references. This study contributes to the academic discourse and provides practical insights for organizations as they adapt to evolving customer preferences. The research technique included the evaluation of the measurement model via the use of reflective indicators, as well as the assessment of convergent and discriminant validity. Using bootstrapping, the structural model was then tested through the hypothesis testing, as well as the overall model quality and fit were evaluated using R square, Q square, F square, and SRMR. The results indicated that subjective norms played a more dominant role than perceived risk and environmental awareness in the context of purchase intention. However, the interaction between these factors and product knowledge did not significantly impact the purchase intention. The product knowledge is in-depth knowledge about the products marketed by a company. In this research, the product knowledge was a moderating variable, where the moderating variable could strengthen or weaken the independent variable. The R square value illustrated a high overall effect of exogenous/endogenous variables on purchase intention. The research contributes to the literature by bridging gaps in SEM application, shedding light on the complexities of consumer behaviour in business marketing, and advocating for a nuanced understanding of PLS-SEM's dual purpose. The findings offer valuable insights for researchers and practitioners in navigating the intricate landscape of consumer decision-making.
References
Albers, S. (2010). Energy-efficient algorithms. Communications of the ACM, 53(5), 86–96. https://www.doi.org/10.1145/1735223.1735245
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Asmin. (2002). Penerapan path analysis menurut penempatan urutan variabel dalam penelitian [The application of path analysis according to the placement of variable order in research]. Presisi: Jurnal Penelitian dan Evaluasi Pendidikan, 1(2).
Bangun, C. S., Suhara, T., & Husin, H. (2023). Penerapan teori planned behavior dan perceived value pada online purchase behavior [Application of the theory of planned behavior and perceived value in online purchase behavior]. Technomedia Journal, 8(1SP), 123–134. https://doi.org/10.33050/tmj.v8i1SP.2074
Chen, Y. S., & Chang, C. H. (2012). Enhance green purchase intentions: The roles of green perceived value, green perceived risk, and green trust. Management Decision, 50(3), 502–520. https://doi.org/10.1108/00251741211216250
Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In G. A. Marcoulides (Ed.), Methodology for business and management. Modern methods for business research (pp. 295–336). Mahwah: Lawrence Erlbaum Associates Publishers.
Davvetas, V., Diamantopoulos, A., Zaefarian, G., & Sichtmann, C. (2020). Ten basic questions about structural equations modeling you should know the answers to – But perhaps you don’t. Industrial Marketing Management, 90, 252–263. https://doi.org/10.1016/j.indmarman.2020.07.016
Denis, D., & Legerski, J. (2006). Causal modeling and the origins of path analysis. Theory & Science, 7(1), 2–10. https://theoryandscience.icaap.org/content/vol7.1/denis.html
Gärling, A., & Thøgersen, J. (2001). Marketing of electric vehicles. Business Strategy and the Environment, 10(1), 53–65. https://doi.org/10.1002/1099-0836(200101/02)10:1%3C53::AID-BSE270%3E3.0.CO;2-E
Ghozali, I., & Latan, H. (2015). Partial least squares konsep, teknik dan aplikasi menggunakan program SmartPLS 3.0 untuk penelitian empiris [Partial least squares concept, technique, and application using the SmartPLS 3.0 program for empirical research]. Semarang: Badan Penerbit UNDIP.
Gregor, S. (2006). The nature of theory in information systems. MIS Quarterly, 30(3), 611–642. https://doi.org/10.2307/25148742
Guenther, M., & Guenther, P. (2021). The complex firm financial effects of customer satisfaction improvements. International Journal of Research in Marketing, 38(3), 639–662. https://doi.org/10.1016/j.ijresmar.2020.10.003
Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152. https://doi.org/10.2753/MTP1069-6679190202
Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Cham : Springer. https://doi.org/10.1007/978-3-030-80519-7
Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., & Thiele, K. O. (2017). Mirror, mirror on the wall: a comparative evaluation of composite-based structural equation modeling methods. Journal of the Academy of Marketing Science, 45, 616–632. https://doi.org/10.1007/s11747-017-0517-x
Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). New York, NY: Guilford Press.
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(2009), 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014
Henseler, J., & Sarstedt, M. (2013). Goodness-of-fit indices for partial least squares path modeling. Computational Statistics, 28(2), 565–580. https://doi.org/10.1007/s00180-012-0317-1
Huang, X., & Ge, J. (2019). Electric vehicle development in Beijing: An analysis of consumer purchase intention. Journal of Cleaner Production, 216, 361–372. https://doi.org/10.1016/j.jclepro.2019.01.231
Jia, J., Shi, B., Che, F., & Zhang, H. (2020). Predicting the regional adoption of electric vehicle (EV) with comprehensive models. IEEE Access, 8, 147275–147285. https://doi.org/10.1109/ACCESS.2020.3014851
Jiang, Q., Wei, W., Guan, X., & Yang, D. (2021). What increases consumers’ purchase intention of battery electric vehicles from Chinese electric vehicle start-ups? Taking Nio as an example. World Electric Vehicle Journal, 12(2), Article 71. https://doi.org/10.3390/wevj12020071
Joreskog, K. G., & Wold, H. O. A. (1982). The ML and PLS techniques for modeling with latent variables: Historical and comparative aspects. In Systems under indirect observation: Causality, structure, prediction. Part I (pp. 263–270). Amsterdam: North-Holland Publ.
Kristiana, R., & Aqmala, D. (2023). The influence of environmental awareness, environmental awareness, product knowledge and willingness to pay on the interest in purchasing eco-friendly products at "The body shop" in Semarang city. E-Bisnis : Jurnal Ilmiah Ekonomi Dan Bisnis, 16(2), 422–436. https://doi.org/10.51903/e-bisnis.v16i2.1427
Kusumawati, A. ., & Tiarawati, M. . (2022). Pengaruh green perceived risk dan green packaging terhadap green purchase intention pada produk skincare avoskin: Studi pada konsumen terhadap niat beli produk avoskin [The influence of green perceived risk and green packaging on green purchase intention for avoskin skincare products: A study on consumer attitudes towards purchasing avoskin products]. Sibatik Journal: Jurnal Ilmiah Bidang Sosial, Ekonomi, Budaya, Teknologi, Dan Pendidikan, 1(10), 2071–2084. https://doi.org/10.54443/sibatik.v1i10.305
Lashari, Z. A., Ko, J., & Jang, J. (2021). Consumers’ intention to purchase electric vehicles: Influences of user attitude and perception. Sustainability, 13(12), Article 6778. https://doi.org/10.3390/su13126778
Li, C. C. (1975). Path analysis – A primer. The Boxwood Press.
Martínez‐López, F. J., Gázquez‐Abad, J. C., & Sousa, C. M. (2013). Structural equation modelling in marketing and business research: Critical issues and practical recommendations. European Journal of Marketing, 47(1/2), 115–152. https://doi.org/10.1108/03090561311285484
McDonald, R. P. (1996). Path analysis with composite variables. Multivariate Behavioral Research, 31(2), 239–270. https://doi.org/10.1207/s15327906mbr3102_5
Pradeep, V. H., Amshala, V. T., & Kadali, B. R. (2021). Does perceived technology and knowledge of maintenance influence purchase intention of BEVs. Transportation Research Part D: Transport and Environment, 93, Article 102759. https://doi.org/10.1016/j.trd.2021.102759
Rithmaya, C. L. (2016). Pengaruh kemudahan penggunaan, kemanfaatan, sikap, risiko dan fitur layanan terhadap minat ulang nasabah bank BCA dalam menggunakan initernet banking [The influence of ease of use, utility, attitude, risk, and service features on the repeat interest of BCA bank customers in using internet banking]. Jurnal Riset Ekonomi dan Manajemen, 16(1), 160–177. http://dx.doi.org/10.17970/jrem.16.160110.ID
Sarstedt, M., Hair, J. F., Nitzl, C., Ringle, C. M., & Howard, M. C. (2020). Beyond a tandem analysis of SEM and PROCESS: Use of PLS-SEM for mediation analyses!. International Journal of Market Research, 62(3), 288–299. https://doi.org/10.1177/1470785320915686
Sarstedt, M., Hair, J. F., & Ringle, C. M. (2022a). “PLS-SEM: Indeed a silver bullet” – Retrospective observations and recent advances. Journal of Marketing Theory and Practice, 31(3), 261–275. https://doi.org/10.1080/10696679.2022.2056488
Sarstedt, M., Radomir, L., Moisescu, O. I., & Ringle, C. M. (2022b). Latent class analysis in PLS-SEM: A review and recommendations for future applications. Journal of Business Research, 138, 398–407. https://doi.org/10.1016/j.jbusres.2021.08.051
Sudaryono, S. (2011). Aplikasi analisis (Path Analysis) berdasarkan urutan penempatan variabel dalam penelitian [Application of analysis (Path Analysis) based on the order of variable placement in research]. Jurnal Pendidikan dan Kebudayaan, 17(4), 391–403. https://doi.org/10.24832/jpnk.v17i4.36
Tanuwijaya, A., & Balqiah, T. E. (2022). Enhancing purchase intention of electric vehicle: Implementing theory of planned behavior and green purchase behavior. In Proceeding of the 6th International conference on family business and entrepreneurship (pp. 369–383). http://e-journal.president.ac.id/presunivojs/index.php/ICFBE/article/view/3793/1218
Walker, J. K., Jeger, M., & Kopecki, D. (2013). The role of perceived abilities, subjective norm and intentions in entrepreneurial activity. The Journal of Entrepreneurship, 22(2), 181–202. https://doi.org/10.1177/0971355713490621
Wedayanti, N. P. A. A., & Giantari, I. G. A. K. (2016). Peran pendidikan kewirausahaan dalam memediasi pengaruh norma subyektif terhadap niat berwirausaha [The role of entrepreneurial education in mediating the influence of subjective norms on entrepreneurial intention] [Unpublished doctoral dissertation]. Udayana University.
Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20, 557–585.
Wright, S. (1934). The method of path coefficients. The Annals of Mathematical Statistics, 5(3), 161–215. https://www.jstor.org/stable/2957502
Yamin, S. (2022). Olah data statistik: SmartPLS 3, SMARTPLS 4, AMOS & STATA. Depok: PT Dewangga Energi Internasional.
Yeniaras, V., Kaya, I., & Dayan, M. (2020). Mixed effects of business and political ties in planning flexibility: Insights from Turkey. Industrial Marketing Management, 87, 208–224. https://doi.org/10.1016/j.indmarman.2020.01.002
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 authors
This work is licensed under a Creative Commons Attribution 4.0 International License.
