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Nasution, Umar Hamdan
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Fundamental Models of Digital Stimulus on Consumer Purchasing Decisions: Implications For AI-Based Marketing Strategies and The Digital Economy Nasution, Umar Hamdan; Zahri, Cut; Rahman, M. Arif
Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies Vol. 1 (2025)
Publisher : CV Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/cessmuds.v1.11

Abstract

This research aims to develop a fundamental model that links digital stimulus to consumer purchasing decisions, with AI-based marketing strategies as a moderator variable. The development of digital technology has revolutionized consumer behavior in the purchase decision-making process. Digital stimuli, such as personalized advertising, artificial intelligence-based interactions (including chatbots and virtual assistants), automated product recommendations, and interactive UI/UX designs, are increasingly influencing consumer preferences. However, research that comprehensively examines the relationship between digital stimulus, AI-based marketing strategies, and purchasing decisions is still limited, especially in Indonesia. The novelty of this research lies in the integration of consumer behavior analysis with machine learning approaches to validate prediction models of purchase decisions. The method employed was a survey of 420 active digital consumers, followed by Partial Least Squares Structural Equation Modeling (PLS-SEM) analysis and algorithmic validation using Random Forest and Gradient Boosting. The results show that personalized advertising and UI/UX design have a significant positive effect on purchase intent, which is further the primary determinant of purchase decisions. Machine learning-based pricing strategies have been demonstrated to enhance the effectiveness of personalized advertising. At the same time, AI interactions, product recommendations, sentiment analysis, and customer engagement moderation are not significant. Algorithmic validation confirms a very high prediction accuracy (96.9%–98.3%), indicating that the model reliably maps the behavior patterns of digital consumers. Theoretically, this study enriches the literature on digital consumer behavior while providing practical recommendations for e-commerce to optimize ad personalization, enhance UI/UX design, and leverage AI-based pricing strategies. The implications of this research are also relevant for regulators in strengthening ethical policies and developing the national digital economy ecosystem
Co-Authors Ahmad, Ikhwanul Al Firah, Al Firah Andika Andika Arif Rahman Arneta, Yaumi Arfah Noor Aurel, Nurul Bobby Hartanto Cittaro, Michael Cut Zahri, Cut Dewi Wahyuni Fandi Iskandar Sopang Fasyah, Shakira Firah, Al Harun Harun Hasbi, Roqy Herlia, Herlia Idris Idris Iskandar, Eddy Iwanda, Muya Syaroh Junaidi, Listya Devi Kartika Pratiwi Khairuni, Lila Lubis, Mhd Ridho Akbar Lumban Tobing, Maria Magdalena Nasution, Roni Ngatemin, Ngatemin Nurjannah Nurjannah Pratama, Rizki Purba, Rakhmawati Rabitha, Nurul Rahim, Rani Rahman, M. Arif Rahman, Muhammad Arif Rahmat Darmawan, Rahmat Ramadani, Anisa Fitri Riswandi, Sofi Sahnan Rangkuti Sarah Nasution Siahaan, Rumiris Simarmata, Devi Risda Sinaga, Kariaman Sinurat, Mangasi Siregar, Lukman Hakim Sopang, Fandi Iksandar Sopang, Fandi Iskandar Suardi, Suardi Syamsurizal - - syauqi, teuku Tampubolon, Ayu Azari Victor Victor Zhaki, Ahmad Zulkarnaen, Mierna Zulkarnain, Mierna