Analysis of Customer Feedback for an e-Commerce Application Based on Artificial Neural Networks
Abstract
With the rise of the Internet, e-commerce platforms have become one of the primary shopping channels for consumers. Establishing an efficient and intelligent customer service system is a crucial challenge for these platforms. This research aims to analyze how the interactivity of e-commerce applications and customer feedback from online shopping experiences can influence consumer loyalty and the likelihood of repurchase. To evaluate customer loyalty, we utilize an artificial neural network, which is processed using the SPSS application. The findings indicate that the relationship between interactivity, consumer feedback, and loyalty has a confidence level of 85.4%. A relationship between variables is considered strong if the R-squared value is above 50%, while a value below 50% indicates a weaker relationship.
Downloads
References
“View of Analisis Online Customer Review Dan Seller Reputation Terhadap Keputusan Belanja Online Dimasa Pandemi Covid-19.” https://www.yrpipku.com/journal/index.php/msej/article/view/612/514 (accessed Jan. 28, 2024).
D. Aprillita and D. H. Perkasa, “PENGARUH PANDEMIK COVID-19 TERHADAP DAYA BELI MASYARAKAT UNTUK SEKTOR ONLINE RETAIL,” J. Bisnis, Ekon. Manajemen, dan Kewirausahaan , vol. 1, no. 1, pp. 14–19, May 2021, doi: https://doi.org/10.52909/JBEMK.V1I1.23.
“View of Research Methodology for Analysis of E-Commerce User Activity Based on User Interest using Web Usage Mining.” https://journals.itb.ac.id/index.php/jictra/article/view/1921/3253 (accessed Nov. 12, 2024).
“View of Investigating the Effect of m-Commerce Application’s Functional and Non-Functional Attributes on Usability and Continuance Intention.” https://journals.itb.ac.id/index.php/jictra/article/view/22365/6661 (accessed Nov. 12, 2024).
C. Li and Y. Zhang, “Construction of Intelligent Customer Service System on E-Commerce Platform and Its Impact on User Experience,” 2023 Int. Conf. Network, Multimed. Inf. Technol. NMITCON 2023, 2023, doi: https://doi.org/10.1109/NMITCON58196.2023.10276323.
Y. Christian and Y. Utama, “Issues and determinant factors of customer feedback on e-commerce (e-marketplace),” Proc. 2021 Int. Conf. Inf. Manag. Technol. ICIMTech 2021, pp. 234–239, Aug. 2021, doi: https://doi.org/10.1109/ICIMTECH53080.2021.9535075.
X. Deng, “Big data technology and ethics considerations in customer behavior and customer feedback mining,” Proc. - 2017 IEEE Int. Conf. Big Data, Big Data 2017, vol. 2018-January, pp. 3924–3927, Jul. 2017, doi: https://doi.org/10.1109/BIGDATA.2017.8258399.
S. G. Hasson, J. Piorkowski, and I. McCulloh, “Social media as a main source of customer feedback – Alternative to customer satisfaction surveys,” Proc. 2019 IEEE/ACM Int. Conf. Adv. Soc. Networks Anal. Mining, ASONAM 2019, pp. 829–832, Aug. 2019, doi: https://doi.org/10.1145/3341161.3345642.
W. L. Army, A. Nugroho, S. Anita, and S. Sarah, “The Customer Engagement Effect on Customer Loyalty (Case Study: Marketplace Retailer),” J. Cahaya Mandalika ISSN 2721-4796, vol. 5, no. 1, pp. 379–389, Mar. 2024, doi: https://doi.org/10.36312/JCM.V5I1.2686.
V. Arghashi and C. A. Yuksel, “Interactivity, Inspiration, and Perceived Usefulness! How retailers’ AR-apps improve consumer engagement through flow,” J. Retail. Consum. Serv., vol. 64, p. 102756, Jan. 2022, doi: https://doi.org/10.1016/J.JRETCONSER.2021.102756.
C. Orús, S. Ibáñez-Sánchez, and C. Flavián, “Enhancing the customer experience with virtual and augmented reality: The impact of content and device type,” Int. J. Hosp. Manag., vol. 98, p. 103019, Sep. 2021, doi: https://doi.org/10.1016/J.IJHM.2021.103019.
O. Petit, C. Velasco, and C. Spence, “Digital Sensory Marketing: Integrating New Technologies Into Multisensory Online Experience,” J. Interact. Mark., vol. 45, pp. 42–61, Feb. 2019, doi: https://doi.org/10.1016/J.INTMAR.2018.07.004.
J. Wu, Z. Wang, and L. Huang, “The interaction effect between online trust and Web site interactivity on highest purchasing price,” Int. Conf. Manag. Serv. Sci. MASS 2011, 2011, doi: https://doi.org/10.1109/ICMSS.2011.5998972.
S. A. A. Rajon and M. M. Rahman, “On the impact of virtual environment in trust building: E-commerce perspective,” 2013 16th Int. Conf. Comput. Inf. Technol. ICCIT 2013, pp. 224–229, Dec. 2014, doi: https://doi.org/10.1109/ICCITECHN.2014.6997329.
J. Coughlan, R. D. Macredie, and N. Patel, “Evaluating the effectiveness of customers’ communication experiences with online retailers - A study of e-mortgages,” Interact. Comput., vol. 19, no. 1, pp. 83–95, 2007, doi: https://doi.org/10.1016/J.INTCOM.2006.06.003.
Y. Gongan and L. Qi, “Exploring the effects of interactivity on consumer trust in e-retailing,” 2008 Int. Conf. Wirel. Commun. Netw. Mob. Comput. WiCOM 2008, 2008, doi: https://doi.org/10.1109/WICOM.2008.2154.
K. M. Boer, “Interaktivitas sebagai Strategi Mediated Communication pada Fans Pages Starbucks Coffee Indonesia,” J. ILMU Komun., vol. 10, no. 2, Dec. 2013, doi: https://doi.org/10.24002/JIK.V10I2.348.
G. van Noort, H. A. M. Voorveld, and E. A. van Reijmersdal, “Interactivity in Brand Web Sites: Cognitive, Affective, and Behavioral Responses Explained by Consumers’ Online Flow Experience,” J. Interact. Mark., vol. 26, no. 4, pp. 223–234, Nov. 2012, doi: https://doi.org/10.1016/j.intmar.2011.11.002.
A. Iswaratama, “The Role of Virtual Communities in Encouraging Social Interaction in the Digital Era,” Hist. J. Hist. Soc. Sci., vol. 3, no. 1, pp. 51–61, Mar. 2024, doi: https://doi.org/10.58355/HISTORICAL.V3I1.100.
M. Suryani, N. N. Adawiyah, and E. B. Syahputri, “Pengaruh Harga dan Online Customer Review Terhadap Keputusan Pembelian di E-Commerce Sociolla Pada Masa Pandemi Covid-19,” Formosa J. Multidiscip. Res., vol. 1, no. 1, pp. 49–74, May 2022, doi: https://doi.org/10.55927/FJMR.V1I1.416.
W. Rusdiyanto and S. Suranti, “ANALISIS PENGARUH KUALITAS PELAYANAN PADA LOYALITAS PELANGGAN DENGAN KEPUASAN PELANGGAN SEBAGAI VARIABEL MEDIASI,” Efisiensi Kaji. Ilmu Adm., vol. 18, no. 1, pp. 15–28, May 2021, doi: https://doi.org/10.21831/EFISIENSI.V18I1.37406.
V. A. Zeithaml, L. L. Berry, and A. Parasuraman, “The behavioral consequences of service quality,” J. Mark., vol. 60, no. 2, pp. 31–46, 1996, doi: https://doi.org/10.2307/1251929.
S. Molinillo, R. Aguilar-Illescas, R. Anaya-Sánchez, and F. Liébana-Cabanillas, “Social commerce website design, perceived value and loyalty behavior intentions: The moderating roles of gender, age and frequency of use,” J. Retail. Consum. Serv., vol. 63, p. 102404, Nov. 2021, doi: https://doi.org/10.1016/J.JRETCONSER.2020.102404.
Y. K. Lee, S. H. Kim, M. K. Seo, and S. K. Hight, “Market orientation and business performance: Evidence from franchising industry,” Int. J. Hosp. Manag., vol. 44, pp. 28–37, Jan. 2015, doi: https://doi.org/10.1016/J.IJHM.2014.09.008.
“(PDF) A Customer Loyalty Model for E-Service Context.” https://www.researchgate.net/publication/220437600_A_Customer_Loyalty_Model_for_E-Service_Context (accessed Nov. 12, 2024).
D. Kurniawati and R. K. Judisseno, “PENGGUNAAN SKALA LIKERT UNTUK MENGANALISA EFEKTIVITAS REGISTRASI STAKEHOLDER MEETING: EXHIBITION INDUSTRY 2020,” Semin. Nas. Ris. Terap. Adm. Bisnis dan MICE, vol. 10, no. 1, pp. 142–152, Mar. 2022, Accessed: Jan. 28, 2024. [Online]. Available: https://prosiding-old.pnj.ac.id/index.php/snrtb/article/view/5581
Y. Zhao, Z. Xi, and L. Xu, “BP Neural Network Algorithm-based Innovation Management Model Analysis System for E-commerce Enterprises,” Proc. - 2022 Int. Conf. Artif. Intell. Things Crowdsensing, AIoTCs 2022, pp. 138–142, 2022, doi: https://doi.org/10.1109/AIOTCS58181.2022.00026.
J. Yu, “Investigation on Risk Assessment of Cross-Border E-Commerce Supply Chain Based on BP Neural Network,” 2023 Int. Conf. Network, Multimed. Inf. Technol. NMITCON 2023, 2023, doi: https://doi.org/10.1109/NMITCON58196.2023.10275982.
N. Kalaiselvi, K. R. Aravind, S. Balaguru, and V. Vijayaragul, “Retail price analytics using backpropogation neural network and sentimental analysis,” 2017 4th Int. Conf. Signal Process. Commun. Networking, ICSCN 2017, Oct. 2017, doi: https://doi.org/10.1109/ICSCN.2017.8085696.
X. Zhang, Y. Zhuang, W. Wang, and W. Pedrycz, “Online feature transformation learning for cross-domain object category recognition,” IEEE Trans. Neural Networks Learn. Syst., vol. 29, no. 7, pp. 2857–2871, Jul. 2018, doi: https://doi.org/10.1109/TNNLS.2017.2705113.
G. Wang, B. Fan, S. Xiang, and C. Pan, “Aggregating Rich Hierarchical Features for Scene Classification in Remote Sensing Imagery,” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., vol. 10, no. 9, pp. 4104–4115, Sep. 2017, doi: https://doi.org/10.1109/JSTARS.2017.2705419.
S. Neelakandan, V. Prakash, M. S. Pranavkumar, and R. Balasubramaniam, “Forecasting of E-Commerce System for Sale Prediction Using Deep Learning Modified Neural Networks,” Int. Conf. Appl. Intell. Sustain. Comput. ICAISC 2023, 2023, doi: https://doi.org/10.1109/ICAISC58445.2023.10199817.
W. Du, “Simulation of the Optimal Trader Model in E-Commerce Based on Recurrent Neural Network,” Proc. - 2023 Int. Conf. Networking, Informatics Comput. ICNETIC 2023, pp. 679–683, 2023, doi: https://doi.org/10.1109/ICNETIC59568.2023.00145.
B. D. Ripley, “Neural Networks and Related Methods for Classification,” J. R. Stat. Soc. Ser. B, vol. 56, no. 3, pp. 409–437, Sep. 1994, doi: https://doi.org/10.1111/J.2517-6161.1994.TB01990.X.
B. Cheng and D. M. Titterington, “Neural Networks: A Review from a Statistical Perspective,” https://doi.org/10.1214/ss/1177010638, vol. 9, no. 1, pp. 2–30, Feb. 1994, doi: https://doi.org/10.1214/SS/1177010638.
A. Ansari and A. Riasi, “Modelling and evaluating customer loyalty using neural networks: Evidence from startup insurance companies,” Futur. Bus. J., vol. 2, no. 1, pp. 15–30, Jun. 2016, doi: https://doi.org/10.1016/J.FBJ.2016.04.001.
A. Lörke, “Cybenko ’ s Theorem,” no. September, 2019.
K. I. Funahashi, “On the approximate realization of continuous mappings by neural networks,” Neural Networks, vol. 2, no. 3, pp. 183–192, Jan. 1989, doi: https://doi.org/10.1016/0893-6080(89)90003-8.
K. Hornik, “Approximation capabilities of multilayer feedforward networks,” Neural Networks, vol. 4, no. 2, pp. 251–257, Jan. 1991, doi: https://doi.org/10.1016/0893-6080(91)90009-T.
A. R. Gallant and H. White, “On learning the derivatives of an unknown mapping with multilayer feedforward networks,” Neural Networks, vol. 5, no. 1, pp. 129–138, Jan. 1992, doi: https://doi.org/10.1016/S0893-6080(05)80011-5.





