The Impact of Product Description, Product Photo, Rating, and Review on Purchase Intention in E-commerce
DOI:
https://doi.org/10.58229/jcsam.v1i2.100Keywords:
e-commerce, product description, product photo, rating & review, purchase intentionAbstract
The Covid-19 pandemic in the last 3 years has strengthened E-commerce growth, making online shopping the new norm due to restricted offline activities. To aid buyers and sellers in conducting transactions in E-commerce, E-commerce platforms have introduced features like product descriptions, product photos, ratings, and reviews. These features have created a competitive landscape, benefiting sellers who can use them effectively. Nevertheless, many sellers still struggle to optimize these features and market their products effectively to buyers. Failure to optimize these features correctly restricts the marketing strategy's effectiveness and puts sellers at risk for unanticipated difficulties that may be prevented by determining the various effects of these features on customers’ purchase intentions. Therefore, this research aims to analyze the impact of product descriptions, product photos, and ratings & reviews on customers' purchase intention in E-commerce. A quantitative approach is used in this study, where the data is analyzed through descriptive statistics and PLS-SEM. The result of this study suggested that all three features of product description, product photo, and rating & review significantly and positively influence purchase intention in E-commerce. In addition, the author also found that moderation of perceived trust significantly affects product description and rating & review on purchase intention, while the moderation of perceived risk only significantly affects rating & review on purchase intention. The finding of this research is expected to give insights to E-commerce sellers on optimizing the features in E-commerce to increase the customers’ purchase intention.
References
Abiad, A. et al. (2020) ‘The economic impact of the COVID-19 outbreak on developing Asia’, ADB Briefs. doi:10.22617/brf200096.
Battha, M. and Zina, F. (2022) The impact of Online Reviews and Influencers on Customers' Purchasing Intention [Preprint]. Available at: http://www.diva-portal.org/smash/get/diva2:1663364/FULLTEXT01.pdf
Becker, J.-M., Ringle, C.M. and Sarstedt, M. (2018) ‘Estimating moderating effects in PLS-SEM and PLSC-SEM: Interaction term generation*data treatment’, Journal of Applied Structural Equation Modeling, 2(2), pp. 1–21. doi:10.47263/jasem.2(2)01.
BPS Kota Bandung (2020) Penduduk Menurut Kelompok Umur dan Jenis Kelamin (Jiwa), 2018-2020, Badan Pusat Statistik Kota bandung. Available at: https://bandungkota.bps.go.id/indicator/12/103/1/penduduk-menurut-kelompok-umur-dan-jenis-kelamin.html
Chang, K.-C. et al. (2019) Effect of tangibilization cues on consumer purchase intention in the social media context: Regulatory Focus Perspective and the moderating role of Perceived Trust’, Telematics and Informatics, 44, p. 101265. doi:10.1016/j.tele.2019.101265.
Cohen, J. (1988) Statistical Power Analysis for the behavioral sciences. Hillsdale, NJ: L. Erlbaum Associates.
Finstad, K. (2010) Response Interpolation and Scale Sensitivity: Evidence Against 5-Point Scales.
Galhotra, B. and Dewan, A. (no date) Impact of COVID-19 on digital platforms and change in E-commerce shopping trends. ResearchGate.
GOZUKARA, E., OZYER, Y. and KOCOGLU, I. (2014) ‘The moderating effects of perceived use and perceived risk in online shopping’, Journal of Global Strategic Management, 2(8), pp. 67–67. doi:10.20460/jgsm.2014815643.
Hair, J.F. et al. (2019) ‘When to use and how to report the results of PLS-SEM’, European Business Review, 31(1), pp. 2–24. doi:10.1108/ebr-11-2018-0203.
Halima, M.H. et al. (2021) ‘Impact of online crisis response strategies on online purchase intention: The roles of online brand attitude and brand perceived usefulness’, SAGE Open, 11(1), p. 215824402110038. doi:10.1177/21582440211003872.
Hidayat, A. (2021) PLS SEM: Pengukuran kecocokan model (Inner Model Dan Outer Model), Uji Statistik. Available at: https://www.statistikian.com/2018/08/pls-sem-pengukuran-kecocokan-model-inner-dan-outer.html
ITU (2021) Facts and figures 2021. Available at: https://www.itu.int/itu-d/reports/statistics/2021/11/15/internet-use/
Kock, N. (2016) ‘Hypothesis testing with confidence intervals and P values in PLS-sem’, International Journal of e-Collaboration, 12(3), pp. 1–6. doi:10.4018/ijec.2016070101.
Kotler, P. (2017) Principle of Marketing: An Asian perspective. Harlow: Pearson Education Limited.
Kotler, P. and Armstrong, G. (2012) Principles Of Marketing 14th Edition. Essex, England: Pearson Education Limited.
Kripesh, A.S., Prabhu, H.M. and Sriram, K.V. (2020) ‘An empirical study on the effect of product information and perceived usefulness on purchase intention during online shopping in India’, International Journal of Business Innovation and Research, 21(4), p. 509. doi:10.1504/ijbir.2020.105982.
Kumar Raja, D.R. and Pushpa, S. (2017) “Feature level review table generation for e-commerce websites to produce qualitative rating of the products,” Future Computing and Informatics Journal, 2(2), pp. 118–124. Available at: https://doi.org/10.1016/j.fcij.2017.09.002.
Li, G. et al. (2021) ‘How do environmental values impact green product purchase intention? the moderating role of Green Trust’, Environmental Science and Pollution Research, 28(33), pp. 46020–46034. doi:10.1007/s11356-021-13946-y.
Li, X., Wang, M. and Chen, Y. (2014) THE IMPACT OF PRODUCT PHOTO ON ONLINE CONSUMER PURCHASE INTENTION: AN IMAGE-PROCESSING ENABLED EMPIRICAL STUDY.
Li, X., Wang, M. and Chen, Y. (2014) THE IMPACT OF PRODUCT PHOTO ON ONLINE CONSUMER PURCHASE INTENTION: AN IMAGE-PROCESSING ENABLED EMPIRICAL STUDY.
Meiryani, Dr. (2021) Memahami Koefisien Jalur (path coefficients) Dalam Smart Pls, Accounting. Available at: https://accounting.binus.ac.id/2021/08/12/memahami-koefisien-jalur-path-coefficients-dalam-smart-pls/
Memon, M.A. et al. (2020) ‘Sample Size For Survey Research: Review and recommendations’, Journal of Applied Structural Equation Modeling, 4(2), pp. i–xx. doi:10.47263/jasem.4(2)01.
Mensah, I.K. (2019) ‘Exploring the moderating effect of perceived usefulness on the adoption of E-Government Services’, International Journal of Electronic Government Research, 15(1), pp. 17–35. doi:10.4018/ijegr.2019010102.
Ng, W.K., Yan, G. and Lim, E.-P. (2000) “Heterogeneous product description in Electronic Commerce,” ACM SIGecom Exchanges, 1(1), pp. 7–13. Available at: https://doi.org/10.1145/844302.844305.
Park, D.-H., Lee, J. and Han, I. (2007) ‘The effect of online consumer reviews on consumer purchasing intention: The moderating role of involvement’, International Journal of Electronic Commerce, 11(4), pp. 125–148. doi:10.2753/jec1086-4415110405.
Pavlou, P.A. (2003) ‘Consumer acceptance of Electronic Commerce: Integrating Trust and Risk with the technology acceptance model’, International Journal of Electronic Commerce, 7(3), pp. 101–134. doi:10.1080/10864415.2003.11044275.
Qalati, S.A. et al. (2021) ‘Effects of perceived service quality, website quality, and reputation on purchase intention: The mediating and moderating roles of trust and perceived risk in online shopping’, Cogent Business & Management, 8(1). doi:10.1080/23311975.2020.1869363.
Rainie, L., Keeter, S. and Perrin, A. (2019) Trust and distrust in America, Pew Research Center - U.S. Politics & Policy. Available at: https://www.pewresearch.org/politics/2019/07/22/trust-and-distrust-in-america/
Rigdon, E.E. (2012) ‘Rethinking partial least squares path modeling: In praise of simple methods’, Long Range Planning, 45(5–6), pp. 341–358. doi:10.1016/j.lrp.2012.09.010.
Shaw, N. (2014) ‘The mediating influence of trust in the adoption of the Mobile Wallet’, Journal of Retailing and Consumer Services, 21(4), pp. 449–459. doi:10.1016/j.jretconser.2014.03.008.
Shmueli, G. and Koppius, O.R. (2011) ‘Predictive analytics in information systems research’, MIS Quarterly, 35(3), p. 553. doi:10.2307/23042796.
Steckler, A. et al. (1992) ‘Toward integrating qualitative and quantitative methods: An introduction’, Health Education Quarterly, 19(1), pp. 1–8. doi:10.1177/109019819201900101.
Zhang, J., Zheng, W. and Wang, S. (2020) “The study of the effect of online review on Purchase Behavior,” International Journal of Crowd Science, 4(1), pp. 73–86. Available at: https://doi.org/10.1108/ijcs-10-2019-0027.
Zhang, Y. et al. (2011) ‘Repurchase intention in B2C e-commerce—a relationship quality perspective’, Information & Management, 48(6), pp. 192–200. doi:10.1016/j.im.2011.05.003.
