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Journal articles on the topic 'E-commerce Personalization'

Author: Grafiati

Published: 5 June 2025

Last updated: 16 July 2025

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1

Vavliakis, Konstantinos N., George Katsikopoulos, and Andreas L. Symeonidis. "E-commerce Personalization with Elasticsearch." Procedia Computer Science 151 (2019): 1128–33. http://dx.doi.org/10.1016/j.procs.2019.04.160.

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Tarmizi and Lidiana. "Enhancing User Experience in E-commerce through Personalization Algorithms A Study on Information System Design." Journal Informatic, Education and Management (JIEM) 6, no. 1 (2024): 24–28. http://dx.doi.org/10.61992/jiem.v6i1.59.

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This research aims to improve user experience in e-commerce through the use of personalization algorithms in information system design. The research methods used involve literature analysis, prototype development, and user testing. Literature analysis was conducted to understand the concept of personalization, relevant algorithms, and factors influencing user experience in e-commerce. Based on this understanding, a prototype e-commerce information system with personalization features was implemented. User testing is carried out to collect data about user experiences before and after implementi

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Thakur, Dr Kachan. "Emotion-Driven Personalization in E-Commerce." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–7. https://doi.org/10.55041/isjem03364.

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Abstract: By incorporating emotional intelligence into online shopping experiences, emotion-driven personalization in e-commerce is a huge change in how companies interact with their customers. Personalization methods that have been used for a long time mostly use behavioral data, like browsing history, purchase patterns, and demographic data. But they often don't take into account the complex emotions that affect how people make decisions. With technologies like AI, machine learning, facial recognition, sentiment analysis, and biometric feedback, emotion-driven personalization tries to close

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Mariia, Bulycheva. "Personalization in E-Commerce: Optimizing Recommendations for Multimodal Content." American Journal of Applied Sciences 07, no. 05 (2025): 57–65. https://doi.org/10.37547/tajas/volume07issue05-06.

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This article examines modern approaches to the personalization of multimodal content in e-commerce, driven by the growing complexity of user requests and the evident need to adapt recommendations to diverse data formats and content modality. The relevance of this topic is underscored by the increasing volume of information associated with the article, including text, images, video, and audio, which necessitates the application of specialized methods for precise customization and improved personalization. The purpose of the study is to develop original proposals for optimizing recommendation al

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Mandagie, Wenny Candra, and Robert Kristaung. "The power of AI personalization: Mediated moderation in social & e-commerce." Jurnal Manajemen dan Pemasaran Jasa 18, no. 1 (2025): 35–58. https://doi.org/10.25105/v18i1.21587.

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This study investigates the impact of AI-driven personalization on key customer outcomes within Indonesia's e-commerce landscape. It examines how personalization influences customer engagement, trust, perceived relevance, customer experience, and purchase frequency. While prior studies have extensively explored AI personalization, limited research has examined its mediated moderation effects on customer behavior in emerging e-commerce markets, particularly in Indonesia. This study addresses the gap by analyzing the moderating effect of education level and the mediating role of perceived releva

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Schubert, Petra, and Uwe Leimstoll. "Personalization of E-Commerce Applications in SMEs." Journal of Electronic Commerce in Organizations 2, no. 3 (2004): 21–39. http://dx.doi.org/10.4018/jeco.2004070102.

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Jinyoung Hwang. "E-commerce and Consumer Behavior." GSC Advanced Research and Reviews 19, no. 3 (2024): 361–71. http://dx.doi.org/10.30574/gscarr.2024.19.3.0139.

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The research investigates consumer behavior within e-commerce, focusing on the factors influencing online purchasing decisions and strategies to enhance customer engagement and loyalty. The study explores psychological, social, and technological elements that shape online behaviors, including personalization, trust-building mechanisms, and user experience optimization. Employing a mixed-methods approach, it examines how e-commerce businesses leverage data analytics, marketing strategies, and customer feedback to adapt to evolving consumer preferences. Special attention is given to the impact o

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Maduwinarti, Ayun, Nugraha Kusbianto, and I. G. N. Andhika Mahendra. "The influence of customer personalization on customer satisfaction, engagement, and loyalty Indonesian E-commerce in the digital age." International Journal of Innovative Research and Scientific Studies 8, no. 3 (2025): 1904–14. https://doi.org/10.53894/ijirss.v8i3.6900.

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In the rapidly evolving landscape of Indonesian e-commerce, this research explores the intricate dynamics between customer personalization and its impact on customer loyalty. Positioned within a burgeoning market projected to exceed USD 95 billion by 2025, the study addresses the competitive challenges faced by e-commerce enterprises in retaining customers. Leveraging personalized content and interactions, the research delves into the mediating roles of customer engagement and customer satisfaction in shaping customer loyalty. Employing a quantitative approach, the research collected data thro

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Upasana, Das. "AI Powered Consumer Behavior in e-Commerce." International Journal of Contemporary Research in Multidisciplinary 3, no. 4 (2024): 01–13. https://doi.org/10.5281/zenodo.12679257.

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As the e-commerce industry continues to evolve, artificial intelligence (AI) has emerged as a powerful tool for understanding and influencing consumer behavior. This review explores the convergence of e-commerce and consumer behavior, emphasizing the significant influence of AI-driven personalization on market trends. AI-powered technologies have the ability to analyze vast amounts of data in real-time, providing valuable insights into consumer preferences, shopping patterns, and decision-making processes. By leveraging AI algorithms, e-commerce retailers can personalize the shopping experienc

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Bello, Binaebi Gloria, Ganiyu Bolawale Omotoye, Azeez Jason Kess-Momoh, Sunday Tubokirifuruar Tula, and Andrew Ifesinachi Daraojimba. "ADVANCED DATA ANALYTICS IN E-COMMERCE: A REVIEW OF PERSONALIZATION TECHNIQUES AND BUSINESS GROWTH." Business, Organizations and Society 2, no. 1 (2024): 32–39. https://doi.org/10.26480/bosoc.01.2024.32.39.

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The rapid evolution of e-commerce platforms has intensified the need for effective data analytics strategies to enhance user experiences and drive business growth. This paper presents a comprehensive review of advanced data analytics techniques employed in the realm of e-commerce, with a specific focus on personalized strategies. The objective is to understand how personalization techniques contribute to business growth and customer satisfaction. The review encompasses a diverse range of personalization methods, including collaborative filtering, content-based filtering, and hybrid approaches.

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Johan Reimon Batmetan, Trudi Komansilan, and Sondy C Kumajas. "A Conceptual Framework for e-Commerce Personalization in Small Medium Enterprise’s." Technium: Romanian Journal of Applied Sciences and Technology 16 (October 29, 2023): 83–91. http://dx.doi.org/10.47577/technium.v16i.9964.

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Information overload on e-commerce sites or applications makes users spend more resources than they should. Buyers should be able to use it according to their own habits, needs, wants and beliefs. Personalization of e-commerce is a solution that can be used to overcome this problem. In this paper, the researcher creates a framework for personalizing e-commerce, especially for small and medium enterprises. This framework consists of the customer behavior assumption, technology requirement and business assumption. The customer behavior assumption contains an approach to the habits/nature of the

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Researcher. "THE IMPACT AND BENEFITS OF E-COMMERCE PERSONALIZATION: A TECHNICAL ANALYSIS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 1291–301. https://doi.org/10.5281/zenodo.14400809.

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E-commerce personalization has emerged as a transformative force in digital retail, fundamentally reshaping how businesses interact with customers. This comprehensive article examines the multifaceted impact of personalization technologies on business performance, customer engagement, and operational efficiency. The article explores how advanced personalization strategies drive revenue growth, enhance customer lifetime value, and improve marketing effectiveness across various retail sectors. The article demonstrates how personalization has become a critical differentiator in competitive m

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Setyawan, Abdur Rochman Tri. "Implementasi artificial intelligence marketing pada E-commerce : personalisasi konten rekomendasi serta dampaknya terhadap purchase intention." Fair Value: Jurnal Ilmiah Akuntansi dan Keuangan 4, no. 12 (2022): 5385–92. http://dx.doi.org/10.32670/fairvalue.v4i12.2039.

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The digital transformation that has now penetrated into business activities has encouraged the emergence of online buying and selling platforms, or what we often know as e-commerce. E-commerce was made because people wanted to buy and sell things online in a way that was easy for both buyers and sellers. This study aims to determine the impact of artificial intelligence on purchase intention in e-commerce. The variables tested are the influence of perceived usefulness, perceived ease of use, and attitude toward personalization on purchase intention on Shopee e-commerce. The sampling method in

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Ya, Luo. "The Comparison of Personalization Recommendation for E-Commerce." Physics Procedia 25 (2012): 475–78. http://dx.doi.org/10.1016/j.phpro.2012.03.113.

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Mustafa Ayobami Raji, Hameedat Bukola Olodo, Timothy Tolulope Oke, Wilhelmina Afua Addy, Onyeka Chrisanctus Ofodile, and Adedoyin Tolulope Oyewole. "E-commerce and consumer behavior: A review of AI-powered personalization and market trends." GSC Advanced Research and Reviews 18, no. 3 (2024): 066–77. http://dx.doi.org/10.30574/gscarr.2024.18.3.0090.

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In the dynamic landscape of electronic commerce (e-commerce), understanding and adapting to evolving consumer behavior is critical for the sustained success of online businesses. This review delves into the intersection of e-commerce and consumer behavior, focusing on the transformative role of Artificial Intelligence (AI)-powered personalization and its impact on market trends. The advent of AI has revolutionized the way e-commerce platforms engage with and cater to individual consumer preferences. AI-powered personalization techniques leverage advanced algorithms to analyze vast datasets, en

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Mustafa, Ayobami Raji, Bukola Olodo Hameedat, Tolulope Oke Timothy, Afua Addy Wilhelmina, Chrisanctus Ofodile Onyeka, and Tolulope Oyewole Adedoyin. "E-commerce and consumer behavior: A review of AI-powered personalization and market trends." GSC Advanced Research and Reviews 18, no. 3 (2024): 066–77. https://doi.org/10.5281/zenodo.11217093.

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In the dynamic landscape of electronic commerce (e-commerce), understanding and adapting to evolving consumer behavior is critical for the sustained success of online businesses. This review delves into the intersection of e-commerce and consumer behavior, focusing on the transformative role of Artificial Intelligence (AI)-powered personalization and its impact on market trends. The advent of AI has revolutionized the way e-commerce platforms engage with and cater to individual consumer preferences. AI-powered personalization techniques leverage advanced algorithms to analyze vast datasets, en

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Mhatre, Asst.Prof. Rajavi. "E-commerce and Consumer Behaviour: A review of AI-powered personalization and market trends." International Journal of Advance and Applied Research 6, no. 25(B) (2025): 156–59. https://doi.org/10.5281/zenodo.15315551.

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<strong>Abstract:</strong> In the ever-changing world of electronic commerce (e-commerce), it is essential for online businesses to comprehend and adapt to changing consumer behaviours to achieve lasting success. This review examines the intersection of e-commerce and consumer behaviour, emphasizing the significant impact of Artificial Intelligence (AI)-enhanced personalization on market trends. The emergence of AI has transformed how e-commerce platforms interact with and meet the distinct preferences of consumers. AI-driven personalization methods utilize complex algorithms to analyse extens

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Swamy Sai Krishna Kireeti Athamakuri, Jagadeesh Thiruveedula, and Prof. (Dr) Sangeet Vashishtha. "Ethical Considerations in E-commerce Personalization: Balancing Customer Benefits with Privacy and Fairness." Universal Research Reports 12, no. 1 (2025): 167–86. https://doi.org/10.36676/urr.v12.i1.1470.

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E-commerce personalization has become a cornerstone of modern online retail, offering tailored experiences that enhance customer satisfaction and drive business growth. However, as businesses increasingly leverage customer data to personalize services, the ethical implications of such practices have become a pressing concern. This paper examines the ethical considerations in e-commerce personalization, focusing on the balance between delivering customer benefits and ensuring privacy and fairness. Key issues addressed include data privacy, the potential for discriminatory practices, the transpa

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Gupta, Tarun, and Supriya Bansal. "The AI Advantage: Assessing Personalization Effects on E-commerce Shopping Behaviors." International Journal of Science and Research (IJSR) 8, no. 8 (2019): 2313–20. http://dx.doi.org/10.21275/sr24321084709.

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Rahayu, Tri Anita, Vita Fela Wahyu Purnamasari, Muhammad Adrian Rizky, Irmawan Rahyadi, and La Mani. "Feeling Watched: A Phenomenological Exploration of Consumer Discomfort and Data Privacy Concerns in E-Commerce Personalized Email Marketing." PaperASIA 41, no. 1b (2025): 81–92. https://doi.org/10.59953/paperasia.v41i1b.313.

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Personalized email marketing is common in e-commerce to boost engagement and conversions. However, most studies have been quantitative, lacking insights into consumers’ subjective experiences. Privacy-personalization paradox, where consumers appreciate relevant content but feel discomfort over perceived invasiveness, highlights the need for a qualitative understanding of consumer emotions and perceptions. Addressing this gap, this research explores consumer responses to personalized email marketing, focusing on privacy concerns and preferences for data control. Using a phenomenological approac

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Nagarajan. "AI-Driven E-Commerce Optimization in Customer Acquisition: Enhancing E-Commerce Frontends with Artificial Intelligence." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 12, no. 4 (2024): 1–6. https://doi.org/10.5281/zenodo.15084406.

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The rapid growth of e-commerce has led to an increased reliance on artificial intelligence (AI) to optimize customer acquisition, user engagement, and conversion rates. AI-driven web frontends have transformed the way businesses approach search engine optimization (SEO), Google Shopping integration, and user experience (UX) improvements to enhance online visibility and customer retention. This paper explores the role of machine learning, predictive analytics, and AI-driven automation in streamlining the customer journey, improving personalization, and increasing conversion rates. By analy

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Zareena, Noorbasha, and Tarakeswara Rao Balaga. "Enhancing e-commerce personalization with review-based adaptive feature matching: a real-time approach." IAES International Journal of Artificial Intelligence (IJ-AI) 14, no. 3 (2025): 2178. https://doi.org/10.11591/ijai.v14.i3.pp2178-2184.

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The widespread evolution of e-commerce platforms necessitates advanced personalization techniques to enhance user experience and satisfaction. Our paper introduces the review-based adaptive feature matching (R-AFM) algorithm, an innovative approach to real-time personalization in e-commerce settings. Leveraging the rich data from user reviews and product metadata available in the Amazon product review dataset, R-AFM dynamically adapts to user preferences and behaviors through a sophisticated feature matching process. The methodology encompasses data collection, feature extraction, user prefere

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Ali, Chreesk Sabah M., and Subhi R. M. Zeebaree. "Personalization in Digital Marketing: Leveraging Machine Learning for E-Commerce." Asian Journal of Research in Computer Science 18, no. 3 (2025): 105–29. https://doi.org/10.9734/ajrcos/2025/v18i3582.

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In the era of digital transformation, machine learning (ML) techniques have revolutionized personalized marketing, enabling businesses to enhance customer engagement through data-driven strategies. This paper presents a systematic review of ML applications in digital marketing and e-commerce, focusing on customer segmentation, recommendation systems, and targeted advertising. Specifically, it explores the role of collaborative filtering, deep learning, reinforcement learning, and hybrid AI models in improving personalization and predictive analytics. The findings indicate that deep learning-ba

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Saxena, Ms Ishita. "An Analysis on Digital Advertising and Its Effect on E-Commerce." International Scientific Journal of Engineering and Management 04, no. 06 (2025): 1–9. https://doi.org/10.55041/isjem04209.

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ABSTRACT: The rise of digital advertising has transformed the e-commerce landscape, reshaping how consumers engage with products and make purchasing decisions. This study investigates the impact of digital advertising on consumer trust, engagement, and buying behavior, using primary data collected from 85 respondents. A mixed-method approach was employed to assess consumer exposure to various ad formats, including social media, search engine, and platform-based advertisements. The findings reveal that while digital ads are widely encountered—especially on platforms like Instagram, YouTube, and

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Kaptein, Maurits, and Petri Parvinen. "Advancing E-Commerce Personalization: Process Framework and Case Study." International Journal of Electronic Commerce 19, no. 3 (2015): 7–33. http://dx.doi.org/10.1080/10864415.2015.1000216.

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Prakash Dangi, Divya Saini, Dakshita Choudhary. "AI for Personalization in E-commerce and Recommendation System." Tuijin Jishu/Journal of Propulsion Technology 44, no. 1 (2023): 122–30. http://dx.doi.org/10.52783/tjjpt.v44.i1.2217.

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E-commеrcе has bеcomе a crucial part of our daily livеs, offеring consumеrs a divеrsе sеlеction of products and sеrvicеs. With thе growth of thе е-commеrcе industry, thе task of connеcting consumеrs with products that match thеir individual prеfеrеncеs has bеcomе morе complеx. To tacklе this challеngе, artificial intеlligеncе (AI) has еmеrgеd as a powеrful tool for еnhancing pеrsonalization and rеcommеndation systеms in е-commеrcе. This rеsеarch papеr dеlvеs into thе rеalm of AI-drivеn pеrsonalization and rеcommеndation systеms, providing a comprеhеnsivе еxploration of thеir applications, mеth

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Kumar, Ashish, Kakali Chatterjee, and Ashish Singh. "Energy-Efficient Secure Architecture For Personalization E-Commerce WSN." IEEE Transactions on Consumer Electronics 70, no. 4 (2024): 6901–8. https://doi.org/10.1109/tce.2024.3424574.

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Abdullah, Mohamad Fariz, Muhamad Azman Ibrahim, Azlin Zanariah Bahtar, and Noor Rita Mohamad Khan. "Conceptualizing the Implications of Artificial Intelligence (AI) Tools and Personalization Marketing on Consumer Purchase Intention: Insights from the Malaysian E-Commerce Market." Information Management and Business Review 16, no. 3S(I)a (2024): 430–36. http://dx.doi.org/10.22610/imbr.v16i3s(i)a.4145.

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Artificial intelligence (AI) has emerged as a powerful tool, enabling online retailers to offer highly personalized shopping experiences tailored to individual preferences and behaviors. As e-commerce continues to grow in Malaysia, understanding the influence of AI and personalization marketing on consumer purchase intentions has become increasingly important for businesses seeking to remain competitive. However, the rapid adoption of AI also raises concerns about data privacy, ethical AI usage, and compliance with emerging data protection regulations, such as Malaysia’s Personal Data Protecti

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Oualid, Cheriet, Douha Selma, and Bouali Soufyane. "The Impact of Content Personalization on Customer Engagement and Market Risks of E-Stores." Financial Markets, Institutions and Risks 8, no. 3 (2024): 37–56. http://dx.doi.org/10.61093/fmir.8(3).37-56.2024.

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This article examines the impact of content personalization on customer engagement in the Algerian e-commerce sector. By analyzing data from 70 e-commerce stores operating in Algeria between January 12, 2023, and October 10, 2023, the study highlights the importance of personalization strategies in enhancing customer experiences and driving sales. The research employs a mixed-method approach, combining quantitative data analysis of website metrics with qualitative insights from customer surveys, to provide a comprehensive understanding of the effectiveness of personalization. The findings reve

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Agrawal, Mr Pankaj, Mr Parth Panchal, and Mr Nakul Lohar. "Enhancing Personalization in E-Commerce: A Comparative Analysis of Recommendation System Models." International Journal of Research Publication and Reviews 6, no. 3 (2025): 7523–26. https://doi.org/10.55248/gengpi.6.0325.12136.

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Harsha Koundinya Cheruku. "Data Privacy in E-commerce: Balancing Personalization with Customer Trust." Journal of Computer Science and Technology Studies 7, no. 5 (2025): 680–87. https://doi.org/10.32996/jcsts.2025.7.5.75.

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The evolving landscape of e-commerce has created a complex intersection between personalization and privacy, necessitating a delicate balance between enhanced user experience and data protection. This comprehensive exploration delves into the fundamental aspects of data privacy in digital retail, examining how organizations can implement effective personalization strategies while maintaining robust privacy standards. The discussion encompasses critical elements including data minimization practices, consent management frameworks, and transparency initiatives that foster consumer trust. The imp

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Hayrapetyan, David R., and Syuzi H. Darbinyan. "The role of personalization in influencing digital trust and impulse buying in e-commerce." Theoretical and Experimental Psychology 18, no. 2 (2025): 120–37. https://doi.org/10.11621/tep-25-15.

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Background. In the context of the rapid growth of digital commerce and active implementation of artificial intelligence (AI) in marketing practices, personalization turns to be one of the key strategies for interacting with consumers. In the context of e-commerce personalization is considered as individualized product recommendations, price offers and advertising messages based on the user data and AI algorithms. This transforms consumers behavior, increasing their engagement, but at the same time boosting the risks of manipulative influence. In this regard, it seems relevant to analyze how pe

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Celestin, Mbonigaba. "AI-Driven Personalization: Revolutionizing E-commerce with Blockchain and IoT Collaboration." Randwick International of Social Science Journal 6, no. 2 (2025): 104–15. https://doi.org/10.47175/rissj.v6i2.1147.

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This study investigates the transformative potential of Artificial Intelligence (AI), Blockchain, and the Internet of Things (IoT) in revolutionizing e-commerce personalization. Utilizing a qualitative methodology, it incorporates systematic literature reviews, secondary data analysis, and expert interviews. Findings reveal an 87.5% increase in customer retention rates due to AI-driven personalization from 2020 to 2024, with blockchain adoption reducing fraud cases by 80% and boosting transaction volumes by 540% over the same period. IoT integration achieved a ninefold rise in device use, driv

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Suleman, Dede, Ida Zuniarti, Sri Rusiyati, Nurzalinar Joesah, Lukman Hakim, and Raden Ati Haryati. "The Role of AI-Powered Chatbots in Enhancing Consumer Satisfaction." Golden Ratio of Mapping Idea and Literature Format 5, no. 2 (2025): 01–11. https://doi.org/10.52970/grmilf.v5i2.1430.

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This study examines the impact of AI-powered chatbots on consumer satisfaction in Indonesia's e-commerce industry. A quantitative approach was used to analyze data collected from 400 e-commerce users, focusing on key variables such as response speed, personalization, reliability, and perceived usefulness. Structural Equation Modeling (SEM) was employed to evaluate the relationships between these factors. The findings indicate that response speed and personalization significantly enhance consumer satisfaction, with personalization having the most substantial effect. Perceived usefulness mediate

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Wisnel, Wisnel, Eri Wirdianto, and Tara Cantika. "Analysis of the Effect of E-Service Quality on E-Commerce Customer Satisfaction and Loyalty." MOTIVECTION : Journal of Mechanical, Electrical and Industrial Engineering 4, no. 3 (2022): 209–22. http://dx.doi.org/10.46574/motivection.v4i3.145.

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Service quality is a determining factor for the success of an e-commerce business serving its customers, which has an impact on customer satisfaction and loyalty. Therefore, this study aims to measure the service quality of several online e-commerce market-places on customer satisfaction and loyalty in Indonesia. This study focuses on the four most visited e-commerce application providers, namely Lazada, Tokopedia, Bukalapak, and Shopee. The concept of e-servqual and the SEM-PLS analysis method are used in this study. The results show that the variables that have significant effect on customer

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Abtahi, Ahanaf Tahmid, Tashfin Shafique, Tausif Al Haque, Saleh Ahmed Jalal Siam, and Abdur Rahman. "EXPLORING CONSUMER PREFERENCES: THE SIGNIFICANCE OF PERSONALIZATION IN E-COMMERCE." Malaysian E Commerce Journal 8, no. 1 (2024): 01–07. https://doi.org/10.26480/mecj.01.2024.01.07.

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This qualitative study investigates the significance of personalized experiences within Bangladesh’s e-commerce landscape, focusing on their impact on consumer behavior, satisfaction, and loyalty. Employing qualitative methods, including in-depth interviews with 35 participants engaged in online shopping, the research explores tailored recommendations’ effectiveness and identifies challenges and potential enhancements for a more enriched user experience. The findings underscore the substantial influence of personalized recommendations, particularly those rooted in browsing history and past pur

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Miao, Jin Feng. "Design and Implementation of Personalization Recommendation System in Mobile E-Commerce." Advanced Materials Research 989-994 (July 2014): 4506–9. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.4506.

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The purpose of this paper is to basing on the design of the mobile e-commerce personalized recommender systems, presents a method of personalized recommendation product information, and makes every effort to provide effective personalized service solutions for mobile e-commerce sites.

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S, Keerthi. "Voice-Activated E-commerce: Revolutionizing Shopping Experiences with Personalization and Seamless Integration." International Journal for Research in Applied Science and Engineering Technology 12, no. 3 (2024): 2563–69. http://dx.doi.org/10.22214/ijraset.2024.59407.

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Abstract: In today's rapidly evolving landscape, voice technology has emerged as a transformative force reshaping the way consumers interact with e-commerce platforms. This exploration delves into the progression of commerce experiences facilitated by voice technology, emphasizing the integration of personalized recommendations, voice-enabled payments, and seamless compatibility with e-commerce platforms. The forefront of this evolution lies in the integration of personalized recommendations. Leveraging advanced algorithms and artificial intelligence, voice-enabled shopping assistants can prov

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Sunarmie, Sunarmie, Pamungkur Pamungkur, and Ela Elliyana. "Optimal Website Design Strategy in E-Commerce." Journal of Production, Operations Management and Economics, no. 46 (November 8, 2024): 64–76. https://doi.org/10.55529/jpome.46.64.76.

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The rapid growth of e-commerce has highlighted the importance of website design as a key factor influencing user experience and customer loyalty. Despite its critical role, many e-commerce platforms still struggle with poorly designed layouts, unintuitive navigation, and inadequate responsiveness, resulting in high bounce rates and abandoned shopping carts. This study aims to explore the specific elements of website design-such as layout, aesthetics, responsiveness, and personalization-that impact user satisfaction and loyalty. Employing a qualitative approach, the research combines expert int

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Zikry, Arief, Muhammad Bitrayoga, Siska Yulia Defitri, Akhmad Dahlan, and Nina Dwi Putriani. "Analisis Penggunaan AI dalam Keberhasilan Customer Experience Pengguna Aplikasi E-Commerce Shopee." Indo-Fintech Intellectuals: Journal of Economics and Business 4, no. 3 (2024): 766–81. http://dx.doi.org/10.54373/ifijeb.v4i3.1387.

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E-commerce has experienced rapid growth with the adoption of digital technology particularly in Southeast Asia. AI enables Shopee to provide personalized product recommendations, responsive customer service, and secure shopping experiences. This study analyzes the use of Artificial Intelligence (AI) technology in enhancing user experience on the Shopee e-commerce platform. The research employs a mixed-method approach involving 400 Shopee users in Indonesia. Product recommendation and user experience personalization both significantly increase user satisfaction. User experience personalization

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Silvester, Sinzy, and Shaji Kurain. "Dual-blend insight recommendation system for e-commerce recommendations and enhance personalization." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 2 (2024): 1181. http://dx.doi.org/10.11591/ijeecs.v34.i2.pp1181-1191.

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E-commerce, short for electronic commerce, refers to the buying and selling of goods and services over the internet. This digital transaction model has revolutionized the way businesses operate and consumers shop. In response to the burgeoning complexity of e-commerce datasets, this work addresses the need for advanced recommendation systems. This work introduces the dual-blend insight recommendation system (DIRS) model for personalized e-commerce recommendation system. The DIRS model involves dataset loading, preprocessing, and feature extraction, enabling training with recurrent neural netwo

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Ao Ting, Liang. "Risk Management and Optimization of Artificial Intelligence in E-Commerce Personalization Systems." SHS Web of Conferences 218 (2025): 02004. https://doi.org/10.1051/shsconf/202521802004.

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The economic landscape of the 21st century has been rapidly transformed by emerging technologies, particularly artificial intelligence (AI). E-commerce has become the dominant marketplace, offering consumers a highly personalized shopping experience driven by AI-powered recommendation systems. While these systems enhance efficiency and targeting, they also raise significant concerns regarding data privacy, algorithmic biases, and user experience. This paper examines the utilization of AI in e-commerce, with a focus on its impact on personalized recommendation systems. Through case studies, it

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Christian, Joshua, Febby Karissa, Boas Handoyo, and Ferdi Antonio. "The Effect of Perceived Ads Personalization Toward Online Impulse Buying Tendency with Mediating and Moderating Variables, Evidence from Indonesian Millennial E-Commerce Customers." KINERJA 25, no. 1 (2021): 103–20. http://dx.doi.org/10.24002/kinerja.v25i1.4357.

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E-commerce business grows over time and has changed retail business behavior all over the world. To expand, e-commerce uses ads personalization to study customer needs and track customer behavior. This study aims to analyze the effect of perceived ads personalization towards online impulse buying tendency. The research model hypothesized the effect of perceived ads personalization towards online impulse buying tendency. The mediating variables in this study are perceived novelty, privacy concerns, advertising value, perceived relevance, creepiness, affective reactance, and attitudes towards ad

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Judijanto, Loso, Sopyan Sopyan, and Muhamad Ammar Muhtadi. "The Effect of Data-Based Targeting, Service Personalization, and Content Quality on Consumer Loyalty in E-Commerce in Jakarta." West Science Interdisciplinary Studies 3, no. 01 (2025): 55–64. https://doi.org/10.58812/wsis.v3i01.1624.

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This study examines the influence of content quality, data-based targeting, and service personalization on consumer loyalty in Jakarta's e-commerce sector. Using a quantitative approach, data were collected from 150 respondents through a structured questionnaire and analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The results reveal that content quality exerts the strongest influence on consumer loyalty, followed by data-based targeting and service personalization. Content quality enhances customer trust and satisfaction, while data-driven targeting effectively tail

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Semenenko, Yurii. "Using artificial intelligence technologies to analyse consumer behaviour in e-commerce." Economic Analysis, no. 35(1) (2025): 475–83. https://doi.org/10.35774/econa2025.01.475.

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Introduction. In today's digital environment, e-commerce is undergoing significant transformations under the influence of artificial intelligence (AI) technologies. The implementation of AI enables new opportunities for in-depth analysis of consumer behaviour, enhanced personalization of services, optimization of business processes, and strengthening of companies' competitiveness. At the same time, the need to explore the advantages, risks, and practical aspects of AI utilization in e-commerce is increasing. Purpose of the study. The purpose of the article is to examine the possibilities of ap

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Silvester, Sinzy, and Shaji Kurain. "Dual-blend insight recommendation system for e-commerce recommendations and enhance personalization." Indonesian Journal of Electrical Engineering and Computer Science 34, no. 2 (2024): 1181–91. https://doi.org/10.11591/ijeecs.v34.i2.pp1181-1191.

Full text

Abstract:

E-commerce, short for electronic commerce, refers to the buying and selling of goods and services over the internet. This digital transaction model has revolutionized the way businesses operate and consumers shop. In response to the burgeoning complexity of e-commerce datasets, this work addresses the need for advanced recommendation systems. This work introduces the dual-blend insight recommendation system (DIRS) model for personalized e-commerce recommendation system. The DIRS model involves dataset loading, preprocessing, and feature extraction, enabling training with recurrent neural netwo

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Aishwarya, Arvind Kshirsagar. "The Impact of Artificial Intelligence on E-commerce." International Journal of Advance and Applied Research S6, no. 16 (2025): 390–92. https://doi.org/10.5281/zenodo.15147285.

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<em>Artificial intelligence (AI) is one of the technological advancements that have redefined many industries including e-commerce. AI can be utilized in improving customer experience as well as in supply chain management, confirming that automation is crucial in contemporary e-commerce business managing. The role of AI in enhancing personalization, customer service, inventory management, fraud prevention, and in other areas will be analyzed in relation to the transformation of e-commerce. Furthermore, this paper will highlight the possible adverse effects of AI integration in e-commerce and o

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Lakshmi Kanth, Mangalagiri, Mohd Abdul Mujeeb, Manda Harshitha, et al. "Personalizing the E-Commerce – Experience: A Recommendation System." MATEC Web of Conferences 392 (2024): 01095. http://dx.doi.org/10.1051/matecconf/202439201095.

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You In the fiercely competitive landscape of the E-Commerce industry, the significance of Personalization cannot be overstated when it comes to retaining customers and bolstering revenue streams. Employing a recommendation system proves to be a highly efficacious strategy for achieving this personalization objective, as it furnishes users with pertinent product suggestions tailored to their preferences and behaviors. The focal point of this project is the development of a recommendation system tailored for an E-commerce platform, poised to elevate user experiences and amplify sales. Our method

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Jensolin Abitha Kumari J. and Preeti R. Gotmare. "Impact of Customer Perception of Value Co-Creation for Personalization in Online Shopping." International Journal of E-Business Research 18, no. 1 (2022): 1–20. http://dx.doi.org/10.4018/ijebr.309388.

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Electronic commerce firms adopt advanced technologies to provide personalization of marketing-mix with data for personalization co-created by consumers. This study explores customer's perception of value co-creation and how it impacts intention to co-create value. Customer perception of value co-creation for personalization in an e-commerce context was operationalized as second order construct comprising of fulfilment, service recovery, price perception, algorithmic fairness, personalization benefits, security, and privacy. Survey results of 638 respondents analyzed using AMOS showed that proc

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Sriwanti Belani and Rini Hadiyati. "Consumer Behavior in the E - Commerce Era." Management Studies and Business Journal (PRODUCTIVITY) 1, no. 2 (2024): 171–79. http://dx.doi.org/10.62207/4kvwfg64.

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This research investigates the relationship between factors such as accessibility, social media influence, personalization, user satisfaction, customer retention strategies, and consumer behavior in the context of e-commerce. Through a systematic literature review, the authors explore how these factors influence the way consumers search for information, evaluate options, and make purchasing decisions in an electronic commerce environment. The results show that there is a significant relationship between these factors and consumer behavior in e-commerce, with relevant implications for companies

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