Decoding the Trends and Progress of Artificial Intelligence in E-commerce Over the Last Decade

Ihwana As'ad

Abstract


Through process improvement, growth acceleration, and business landscape transformation, artificial intelligence (AI) has transformed online businesses and accelerated digital transformation. The purpose of this study is to presents a conceptual overview of artificial intelligence (AI) in E-commerce. Potential research themes, explored through content analysis and visualization techniques, offer deeper understanding of the knowledge landscape in this field. This study utilized VOSviewer and R-bibliometrix to conduct data analysis and network visualization the scientific output of 811 research articles form Scopus, WoS and PubMed database from 2000 to 2024, including the number of publications, countries, journal, citations, authors, and keywords. The results of this research show that China and USA emerges as the country with the significant contributions to the development of research related to artificial intelligence in e-commerce, which is dominated by affiliations from Zhejiang University. In the analysis of the relationship between topics, two clusters were obtained, the most dominant topics with keyword “human” and “neural network”. Neural networks are included in AI algorithms that has characteristics similar to the human brain and have the ability to operate more efficiently and profitably in e-commerce. Researchers will gain important insights into the current landscape, as well as collaborative frameworks to suggest directions for future research.

Keywords


artificial intelligence; bibliometrics analysis; e-commerce; scopus database

Full Text:

PDF

References


H. Dissanayake, O. Manta, A. Iddagoda, and M. Palazzo, “AI applications in business: Trends and insights using bibliometric analysis,” Int. J. Manag. Educ., vol. 22, no. 3, p. 101075, 2024, doi: 10.1016/j.ijme.2024.101075.

A. Valencia-Arias, H. Uribe-Bedoya, J. D. González-Ruiz, G. S. Santos, and E. C. Ramírez, “Artificial intelligence and recommender systems in e-commerce. Trends and research agenda,” Intell. Syst. with Appl., vol. 24, p. 200435, 2024, doi: 10.1016/j.iswa.2024.200435.

G. Fortin, “85% of companies will fail at AI integration-Here’s how to succeed,” Salesfloor. [Online]. Available: https://salesfloor.net/85-of-companies-will-fail-at-ai-integration-heres-how-to-succeed/

M. B. Kalıpçı, E. K. Şimşek, and R. Eren, “Decoding the trends and the emerging research directions of E-commerce and tourism in the light of resource dependence theory: A bibliometric analysis,” Heliyon, vol. 10, no. 6, p. e28076, 2024, doi: 10.1016/j.heliyon.2024.e28076.

E. Labib, “Artificial intelligence in marketing: Exploring current and future trends,” Cogent Bus. Manag., vol. 11, no. 1, p. 2348728, 2024, doi: 10.1080/23311975.2024.2348728.

P. Chugh and V. Jain, “Artificial intelligence (AI) empowerment in E-commerce: A bibliometric Voyage,” NMIMS Manag. Rev., vol. 32, no. 3, pp. 159–173, 2024, doi: 10.1177/09711023241303621.

S. Park and K. Lee, “Examining the impact of E-commerce growth on the spatial distribution of fashion and beauty stores in Seoul,” Sustain., vol. 13, no. 9, pp. 1–20, 2021, doi: 10.3390/su13095185.

R. E. Bawack, S. F. Wamba, K. D. A. Carillo, and S. Akter, Artificial intelligence in E Commerce : a bibliometric study and literature review. Springer Berlin Heidelberg, 2022. doi: 10.1007/s12525-022-00537-z.

C. Wang et al., “An empirical evaluation of technology acceptance model for artificial intelligence in E-commerce,” Heliyon, vol. 9, no. 8, p. e18349, 2023, doi: 10.1016/j.heliyon.2023.e18349.

B. (Kevin) Chae and G. Goh, “Digital entrepreneurs in artificial intelligence and data analytics: Who are they?,” J. Open Innov. Technol. Mark. Complex., vol. 6, no. 3, pp. 1–15, 2020, doi: 10.3390/JOITMC6030056.

I. Boukrouh and A. Azmani, “Artificial intelligence applications in E-ommerce: A bibliometric study from 1995 to 2023 ising merged data sources,” Int. J. Prof. Bus. Rev., vol. 9, no. 4, pp. 1–25, 2024, doi: 10.26668/businessreview/2024.v9i4.4537.

M. R. Awal and M. S. Chowdhury, “Threat or prospect? Exploring the impact of digital entrepreneurs’ artificial intelligence perception and intention to adopt blockchain technology on the achievement of SDGs,” Heliyon, vol. 10, no. 13, pp. 1–14, 2024, doi: 10.1016/j.heliyon.2024.e33853.

T. Kollmann, L. Kleine-Stegemann, K. de Cruppe, and C. Then-Bergh, “Eras of digital entrepreneurship: Connecting the past, present, and future,” Bus. Inf. Syst. Eng., vol. 64, no. 1, pp. 15–31, 2022, doi: 10.1007/s12599-021-00728-6.

I. As’ad, M. Alwi, B. Anitasari, A. A. J. Sinlae, F. Nugroho, and K. Anwar, “The implementation of E-commerce for micro, small and medium enterprises (MSMEs) in Covid 19 pandemic era,” Proc. Int. Conf. Soc. Econ. Business, Educ. (ICSEBE 2021), vol. 205, pp. 42–45, 2022, doi: 10.2991/aebmr.k.220107.009.

S. S. S. Solórzano et al., “Acceptance of artificial intelligence and its effect on entrepreneurial intention in foreign trade students: A mirror analysis,” J. Innov. Entrep., vol. 13, no. 1, pp. 1–20, 2024, doi: 10.1186/s13731-024-00412-5.

H. N. Bui and C. D. Duong, “ChatGPT adoption in entrepreneurship and digital entrepreneurial intention: A moderated mediation model of technostress and digital entrepreneurial self-efficacy,” Equilibrium. Q. J. Econ. Econ. Policy, vol. 19, no. 2, pp. 391–428, 2024, doi: 10.24136/eq.3074.

K. N. Aliyah and Z. D. Rizqiana, “The implementation of AI and immersive technology in E-commerce: The role of customer engagement as a mediating variable,” Relev. J. Manag. Bus., vol. 7, no. 1, pp. 50–63, 2024, doi: 10.22515/relevance.v7i1.9124.

S. Aljarboa, “Factors influencing the adoption of artificial intelligence in e-commerce by small and medium-sized enterprises,” Int. J. Inf. Manag. Data Insights, vol. 4, no. 2, p. 100285, 2024, doi: 10.1016/j.jjimei.2024.100285.

R. E. Bawack, S. F. Wamba, K. D. A. Carillo, and S. Akter, Artificial intelligence in E-commerce: A bibliometric study and literature review, vol. 32, no. 1. Springer Berlin Heidelberg, 2022. doi: 10.1007/s12525-022-00537-z.

L. Lobschat et al., “Corporate digital responsibility,” J. Bus. Res., vol. 122, pp. 875–888, 2021, doi: 10.1016/j.jbusres.2019.10.006.

T. Handra, N. P. L. Santoso, O. Wilson, and T. Ramadhan, “The implementation of artificial intelligence in electronic commerce,” Creat. Commun. Innov. Technol. J., vol. 703 LNNS, no. 2, pp. 497–504, 2023, doi: 10.33050/ccit.v17i2.3167.

L. Sulastri, “The role of artificial intelligence in enhancing customer experience: A case study of global E-commerce platforms,” Int. J. Sci. Soc., vol. 5, no. 3, pp. 451–469, 2023, doi: 10.54783/ijsoc.v5i3.1257.

M. Madanchian, “The impact of artificial intelligence marketing on E-commerce sales,” Systems, vol. 12, no. 10, pp. 1–20, 2024, doi: 10.3390/systems12100429.

A. Hidayat, H. Susilowati, and A. Miranti, “Utilizing AI for predicting demand and managing supply chains in E-commerce organizations,” JMI J. Manag. Informatics, vol. 3, no. 2, pp. 250–266, 2024, doi: 10.51903/jmi.v3i2.32.

F. O. Usman, N. L. Eyo-Udo, E. A. Etukudoh, B. Odonkor, C. V. Ibeh, and A. Adegbola, “A critical review of AI-driven strategies for entrepreneurial success,” Int. J. Manag. Entrep. Res., vol. 6, no. 1, pp. 200–215, 2024, doi: 10.51594/ijmer.v6i.748.

R. H. Tsiotsou and A. Boukis, “In-home service consumption: A systematic review, integrative framework and future research agenda,” J. Bus. Res., vol. 145, pp. 49–64, 2022, doi: 10.1016/j.jbusres.2022.02.050.

W. M. Lim, T. Rasul, S. Kumar, and M. Ala, “Past, present, and future of customer engagement,” J. Bus. Res., vol. 140, pp. 439–458, 2022, doi: 10.1016/j.jbusres.2021.11.014.

J. R. Jena, S. K. Biswal, R. R. Panigrahi, and A. K. Shrivastava, “Investigating the potential areas in artificial intelligence and financial innovation : A bibliometric analysis,” J. Scientometr. Res., vol. 13, no. 1, pp. 71–80, 2024, doi: 10.5530/jscires.13.1.6.

L. Mei, N. Tang, Z. Zeng, and W. Shi, “Artificial intelligence technology in live streaming E-commerce: Analysis of driving factors of consumer purchase decisions,” Int. J. Comput. Commun. Control, vol. 20, no. 1, pp. 1–14, 2025, doi: 10.15837/ijccc.2025.1.6871.

J. Yin, X. Qiu, and Y. Wang, “The impact of AI-personalized recommendations on clicking intentions: Evidence from Chinese E-commerce,” J. Theor. Appl. Commer. Res., vol. 20, no. 1, pp. 1–21, 2025, doi: 10.3390/jtaer20010021.

X. He and Y. Liu, “Knowledge evolutionary process of Artificial intelligence in E-commerce: Main path analysis and science mapping analysis,” Expert Syst. Appl., vol. 238, p. 121801, 2024, doi: 10.1016/j.eswa.2023.121801.

S. Frioui and A. Graa, “Bibliometric Analysis of Artificial Intelligence in the Scope of E-Commerce: Trends and Progress over the Last Decade,” Manag. Econ. Rev., vol. 9, no. 1, pp. 5–24, 2024, doi: 10.24818/mer/2024.01-01.

P. Mutira, H. Yazid, Meutia, and E. Bastian, “A Bibliometrics Analysis of Management Control System,” Rev. Int. Geogr. Educ. Online, vol. 11, no. 5, pp. 2634–2649, 2021, doi: 10.48047/rigeo.11.05.160.

G. Sivertsen, R. Rousseau, and L. Zhang, “Measuring scientific contributions with modified fractional counting,” J. Informetr., vol. 13, no. 2, pp. 679–694, 2020, doi: 10.1016/j.joi.2019.03.010.

B.-Å. Lundvall and C. Rikap, “China’s catching-up in Artificial Intelligence seen as a co-evolution of Corporate and National Innovation Systems Authors,” Res. Policy, vol. 51, no. 1, pp. 1–48, 2022, doi: 10.1016/j.respol.2021.104395.

E. Ç. Akay, N. T. Y. Soydan, and B. K. Gacar, “Bibliometric analysis of the published literature on machine learning in economics and econometrics,” Soc. Netw. Anal. Min., vol. 12, no. 1, pp. 1–20, 2022, doi: 10.1007/s13278-022-00916-6.

M. I. Firmansyah, R. Myrna, and I. Widianingsih, “Analisis bibliometric dari program hibah (Bibliometric of grants program),” Shaut Al-Maktabah J. Perpustakaan, Arsip dan Dokumentasi, vol. 13, no. 2, pp. 131–144, 2021, doi: 10.37108/shaut.v13i2.565.

M. Von Zahn, S. Feuerriegel, and N. Kuehl, “The cost of fairness in AI : Evidence from E-Commerce,” Bus. Inf. Syst. Eng., vol. 64, no. 3, pp. 335–348, 2022, doi: 10.1007/s12599-021-00716-w.

F. Correia, A. M. Madureira, and J. Bernardino, “Deep Neural Networks Applied to Stock Market Sentiment Analysis,” Sensors, vol. 22, no. 4409, pp. 1–25, 2022, doi: 10.3390/ s22124409.

M. Aria and C. Cuccurullo, “bibliometrix: An R-tool for comprehensive science mapping analysis,” J. Informetr., vol. 11, no. 4, pp. 959–975, 2017, doi: 10.1016/j.joi.2017.08.007.

U. Singh, A. Saraswat, H. K. Azad, K. Abhishek, and S. Shitharth, “Towards improving e commerce customer review analysis for sentiment detection,” Sci. Rep., vol. 12, no. 21983, pp. 1–15, 2022, doi: 10.1038/s41598-022-26432-3.

J. Li, “E-Commerce fraud detection model by computer artificial intelligence data mining,” Hindawi Comput. Intell. Neurosci., vol. 2022, no. 1, pp. 1–9, 2022, doi: 10.1155/2022/8783783.

T. T. Hue and T. H. Hung, “Impact of artificial intelligence on branding: A bibliometric review and future research directions,” Humanit. Soc. Sci. Commun., vol. 12, no. 1, pp. 1–11, 2025, doi: 10.1057/s41599-025-04488-6.




DOI: http://dx.doi.org/10.30829/zero.v9i1.24423

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Publisher :
Department of Mathematics
Faculty of Science and Technology
Universitas Islam Negeri Sumatera Utara Medan
📱 WhatsApp:085270009767 (Admin Official)
SINTA 2 Google Scholar CrossRef Garuda DOAJ