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An in-depth analysis and prediction study of consumer buying behavior for digital marketing

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Oct 09, 2024

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Tong, H. L., Quiroz, J. C., Kocaballi, A. B., Fat, S. C. M., Dao, K. P., Gehringer, H., ... & Laranjo, L. (2021). Personalized mobile technologies for lifestyle behavior change: a systematic review, meta-analysis, and meta-regression. Preventive medicine, 148, 106532. Search in Google Scholar

Chouk, I., & Mani, Z. (2019). Factors for and against resistance to smart services: role of consumer lifestyle and ecosystem related variables. Journal of Services Marketing, 33(4), 449-462. Search in Google Scholar

Wu, L., Zhang, F., Chang, S. J., & Zhang, Z. (2021). How do the internet technological developments shift the consumption pattern of paper products? Evidence from China. Technology in Society, 67, 101731. Search in Google Scholar

Antonović, D. (2021). The Effectiveness of Digital Marketing Tools on Buying Behavior Across Generations and Devices. Webster University. Search in Google Scholar

Halim, V. U., Benson-Eluwa, V., & Madu, J. E. (2024). DIGITAL MARKETING AND BUYING BEHAVIOUR OF CONSUMERS OF ONLINE PRODUCTS IN ABIA STATE NIGERIA. British International Journal of Business and Marketing Research, 7(3), 18-46. Search in Google Scholar

Müller, J. M., Pommeranz, B., Weisser, J., & Voigt, K. I. (2018). Digital, Social Media, and Mobile Marketing in industrial buying: Still in need of customer segmentation? Empirical evidence from Poland and Germany. Industrial Marketing Management, 73, 70-83. Search in Google Scholar

Akter, S., Motamarri, S., Hani, U., Shams, R., Fernando, M., Babu, M. M., & Shen, K. N. (2020). Building dynamic service analytics capabilities for the digital marketplace. Journal of Business Research, 118, 177-188. Search in Google Scholar

Bala, M., & Verma, D. (2018). A critical review of digital marketing. M. Bala, D. Verma (2018). A Critical Review of Digital Marketing. International Journal of Management, IT & Engineering, 8(10), 321-339. Search in Google Scholar

Sibarani, H. J. (2021). Digital Marketing Implementation on Development and Prospective Digital Business (case Study on Marketplace in Indonesia). Malaysian E Commerce Journal, 5(2), 64-68. Search in Google Scholar

Chaudhuri, N., Gupta, G., Vamsi, V., & Bose, I. (2021). On the platform but will they buy? Predicting customers’ purchase behavior using deep learning. Decision Support Systems, 149, 113622. Search in Google Scholar

Cirqueira, D., Hofer, M., Nedbal, D., Helfert, M., & Bezbradica, M. (2019, September). Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda. In International workshop on new frontiers in mining complex patterns (pp. 119-136). Cham: Springer International Publishing. Search in Google Scholar

Romanenko, N., Sharma, K., & Verma, S. (2024). Prediction of financial customer buying behavior based on machine learning. Journal of Artificial Intelligence General science (JAIGS) ISSN: 3006-4023, 5(1), 125-131. Search in Google Scholar

Miklosik, A., Kuchta, M., Evans, N., & Zak, S. (2019). Towards the adoption of machine learning-based analytical tools in digital marketing. Ieee Access, 7, 85705-85718. Search in Google Scholar

Joshi, R., Gupte, R., & Saravanan, P. (2018). A random forest approach for predicting online buying behavior of Indian customers. Theoretical Economics Letters, 8(03), 448. Search in Google Scholar

Waheed, A., & Jianhua, Y. (2018). Achieving consumers’ attention through emerging technologies: The linkage between e-marketing and consumers’ exploratory buying behavior tendencies. Baltic journal of management, 13(2), 209-235. Search in Google Scholar

Syaputra, D. Y. (2021). The concept of marketplace marketing strategy as application of marketing 4.0. Budapest International Research and Critics Institute-Journal (BIRCI-Journal), 4(3), 6100-6110. Search in Google Scholar

Ziakis, C., & Vlachopoulou, M. (2023). Artificial intelligence in digital marketing: Insights from a comprehensive review. Information, 14(12), 664. Search in Google Scholar

Babalola, H. B., Lateef, S. A., & Zekeri, A. A. (2020). New trends of intelligent e-marketing and consumer buying behaviour: a study of selected universities in Osun State, Nigeria. Jurnal Aplikasi Manajemen, Ekonomi Dan Bisnis, 5(1), 14-25. Search in Google Scholar

Sriram, V. P., Shaikh, A. A., Sumana, B. K., Kumar, A., Dhiman, V., & Naved, M. (2022, June). Consumer Behaviour on Digital Marketing Platforms—Specifically in Terms of Consumer Loyalty Using Machine Learning. In Proceedings of Second International Conference in Mechanical and Energy Technology: ICMET 2021, India (pp. 377-386). Singapore: Springer Nature Singapore. Search in Google Scholar

Mukhtar, S., Mohan, A. C., & Chandra, D. (2023). Exploring the influence of digital marketing on consumer behavior and loyalty. International Journal of Research-Granthaalayah, 11(9), 1-18. Search in Google Scholar

Dhivya, R., Shinde, G., Bandgar, B. M., Velu, C. M., Sade, A., & Sucharitha, Y. (2022). An Analysis Of Consumer Electronics Products To Determine The Impact Of Digital Marketing On Customer Purchasing Behaviour. Journal of Positive School Psychology, 6986-6995. Search in Google Scholar

JūratĖ ŠaltytĖ Benth, Fred Espen Benth & Espen Rostrup Nakstad. (2024). Nearly Instantaneous Time-Varying Reproduction Number for Contagious Diseases-a Direct Approach Based on Nonlinear Regression. Journal of computational biology : a journal of computational molecular cell biology. Search in Google Scholar

Shaomin Li, Xiaofei Sun & Kangning Wang. (2024). Distributed statistical learning algorithm for nonlinear regression with autoregressive errors. Pattern Recognition110551-. Search in Google Scholar

Quan Jiale, Yan Binbin, Sang Xinzhu, Zhong Chongli, Li Hui, Qin Xiujuan... & Zhang Huming. (2023). Multi-Depth Computer-Generated Hologram Based on Stochastic Gradient Descent Algorithm with Weighted Complex Loss Function and Masked Diffraction. Micromachines(3),605-605. Search in Google Scholar

Cheng XianFu, Yao YanQing, Zhang Liying, Liu Ao & Li Zhoujun. (2022). An improved stochastic gradient descent algorithm based on Rényi differential privacy. International Journal of Intelligent Systems(12),10694-10714. Search in Google Scholar

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