參考文獻 |
Bahdanau, D., Cho, K., & Bengio, Y. (2014). Neural machine translation by jointly learning to align and translate. arXiv preprint arXiv:1409.0473.
Bai, T., Zou, L., Zhao, W. X., Du, P., Liu, W., Nie, J.-Y., & Wen, J.-R. (2019). CTrec: A long-short demands evolution model for continuous-time recommendation. Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval,
Buckinx, W., & Van den Poel, D. (2003). Predicting online purchasing behavior.
Chen, S. C., & Dhillon, G. S. (2003). Interpreting dimensions of consumer trust in e-commerce. Information technology and management, 4, 303-318.
Cheng, L.-C., Huang, Y.-H., & Wu, M.-E. (2018). Applied attention-based LSTM neural networks in stock prediction. 2018 IEEE International Conference on Big Data (Big Data),
Chiu, C.-M., Hsu, M.-H., Lai, H., & Chang, C.-M. (2012). Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems, 53(4), 835-845.
Chiu, C. M., Chang, C. C., Cheng, H. L., & Fang, Y. H. (2009). Determinants of customer repurchase intention in online shopping. Online information review, 33(4), 761-784.
Chong, B., Yang, Z., & Wong, M. (2003). Asymmetrical impact of trustworthiness attributes on trust, perceived value and purchase intention: a conceptual framework for cross-cultural study on consumer perception of online auction. Proceedings of the 5th international conference on Electronic commerce,
Chu, Y., Yang, H.-K., & Peng, W.-C. (2019). Predicting online user purchase behavior based on browsing history. 2019 IEEE 35th international conference on data engineering workshops (ICDEW),
Cirqueira, D., Hofer, M., Nedbal, D., Helfert, M., & Bezbradica, M. (2020). Customer purchase behavior prediction in e-commerce: A conceptual framework and research agenda. New Frontiers in Mining Complex Patterns: 8th International Workshop, NFMCP 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers,
Dick, A. S., & Basu, K. (1994). Customer loyalty: toward an integrated conceptual framework. Journal of the academy of marketing science, 22, 99-113.
Doney, P. M., & Cannon, J. P. (1997). An examination of the nature of trust in buyer–seller relationships. Journal of marketing, 61(2), 35-51.
Fang, H., Zhang, D., Shu, Y., & Guo, G. (2020). Deep learning for sequential recommendation: Algorithms, influential factors, and evaluations. ACM Transactions on Information Systems (TOIS), 39(1), 1-42.
Gefen, D., & Straub, D. W. (2004). Consumer trust in B2C e-Commerce and the importance of social presence: experiments in e-Products and e-Services. Omega, 32(6), 407-424.
Guo, L., Hua, L., Jia, R., Zhao, B., Wang, X., & Cui, B. (2019). Buying or browsing?: Predicting real-time purchasing intent using attention-based deep network with multiple behavior. Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining,
Guo, Y., Cheng, Z., Nie, L., Wang, Y., Ma, J., & Kankanhalli, M. (2019). Attentive long short-term preference modeling for personalized product search. ACM Transactions on Information Systems (TOIS), 37(2), 1-27.
Hochreiter, S., & Schmidhuber, J. (1997). Long short-term memory. Neural computation, 9(8), 1735-1780.
Huang, J., Zhao, W. X., Dou, H., Wen, J.-R., & Chang, E. Y. (2018). Improving sequential recommendation with knowledge-enhanced memory networks. The 41st international ACM SIGIR conference on research & development in information retrieval,
Jarvenpaa, S. L., Knoll, K., & Leidner, D. E. (1998). Is anybody out there? Antecedents of trust in global virtual teams. Journal of management information systems, 14(4), 29-64.
Kim, J., Ji, H., Oh, S., Hwang, S., Park, E., & del Pobil, A. P. (2021). A deep hybrid learning model for customer repurchase behavior. Journal of Retailing and Consumer Services, 59, 102381.
Ko, Y. H., Hsu, P. Y., Cheng, M. S., Jheng, Y. R., & Luo, Z. C. (2019). Customer retention prediction with CNN. Data Mining and Big Data: 4th International Conference, DMBD 2019, Chiang Mai, Thailand, July 26–30, 2019, Proceedings 4,
Komiak, S. X., & Benbasat, I. (2004). Understanding customer trust in agent-mediated electronic commerce, web-mediated electronic commerce, and traditional commerce. Information technology and management, 5, 181-207.
Lee, H. I., Choi, I. Y., Moon, H. S., & Kim, J. K. (2020). A multi-period product recommender system in online food market based on recurrent neural networks. Sustainability, 12(3), 969.
Leecharoen, B., Butcher, K., & Chomvilailuk, R. (2014). Examining the association between customer satisfaction and repurchase behavior in fashion retailing. International Journal of Business Tourism and Applied Sciences, 2(1), 57-68.
Lewicki, R. J., & Bunker, B. B. (1996). Developing and maintaining trust in work relationships. Trust in organizations: Frontiers of theory and research, 114, 139.
Ling, C., Zhang, T., & Chen, Y. (2019). Customer purchase intent prediction under online multi-channel promotion: A feature-combined deep learning framework. IEEE Access, 7, 112963-112976.
Liu, C.-J., Huang, T.-S., Ho, P.-T., Huang, J.-C., & Hsieh, C.-T. (2020). Machine learning-based e-commerce platform repurchase customer prediction model. Plos one, 15(12), e0243105.
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of management review, 20(3), 709-734.
McKnight, D. H., & Chervany, N. L. (2001a). Conceptualizing trust: A typology and e-commerce customer relationships model. Proceedings of the 34th Annual Hawaii International Conference on System Sciences,
McKnight, D. H., & Chervany, N. L. (2001b). What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology. International journal of electronic commerce, 6(2), 35-59.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information systems research, 13(3), 334-359.
McKnight, D. H., Cummings, L. L., & Chervany, N. L. (1998). Initial trust formation in new organizational relationships. Academy of management review, 23(3), 473-490.
Miller, A., Fisch, A., Dodge, J., Karimi, A.-H., Bordes, A., & Weston, J. (2016). Key-value memory networks for directly reading documents. arXiv preprint arXiv:1606.03126.
Mnih, V., Heess, N., & Graves, A. (2014). Recurrent models of visual attention. Advances in neural information processing systems, 27.
Niu, Z., Zhong, G., & Yu, H. (2021). A review on the attention mechanism of deep learning. Neurocomputing, 452, 48-62.
Rahim, M. A., Mushafiq, M., Khan, S., & Arain, Z. A. (2021). RFM-based repurchase behavior for customer classification and segmentation. Journal of Retailing and Consumer Services, 61, 102566.
Ran, X., Shan, Z., Fang, Y., & Lin, C. (2019). An LSTM-based method with attention mechanism for travel time prediction. Sensors, 19(4), 861.
Sako, M. (1992). Price, quality and trust: Inter-firm relations in Britain and Japan. Cambridge University Press.
Schlosser, A. E., White, T. B., & Lloyd, S. M. (2006). Converting web site visitors into buyers: how web site investment increases consumer trusting beliefs and online purchase intentions. Journal of marketing, 70(2), 133-148.
Senthilkumar, K. T., & Ponnusamy, R. (2015). Enhanced social trust computation for enriched trust based recommender system. 10, 2353-2359.
Sirdeshmukh, D., Singh, J., & Sabol, B. (2002). Consumer trust, value, and loyalty in relational exchanges. Journal of marketing, 66(1), 15-37.
Song, H. S. (2018). Deep Neural Network Models to Recommend Product Repurchase at the Right Time: A Case Study for Grocery Stores. Journal of Information Technology Applications and Management, 25(2), 73-90.
Sukhbaatar, S., Weston, J., & Fergus, R. (2015). End-to-end memory networks. Advances in neural information processing systems, 28.
Tan, F. B., & Sutherland, P. (2004). Online consumer trust: a multi-dimensional model. Journal of Electronic Commerce in Organizations (JECO), 2(3), 40-58.
Van den Poel, D., & Buckinx, W. (2005). Predicting online-purchasing behaviour. European journal of operational research, 166(2), 557-575.
Van Doren, D. C., & Smith, L. W. (1988). Teaching telemarketing in the framework of the seven steps of personal selling. Journal of Marketing Education, 10(1), 44-49.
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, Ł., & Polosukhin, I. (2017). Attention is all you need. Advances in neural information processing systems, 30.
Weston, J., Chopra, S., & Bordes, A. (2014). Memory networks. arXiv preprint arXiv:1410.3916.
Wu, J., Shi, L., Yang, L., Li, Y., Tsai, S.-B., & Zhang, Y. (2021). User value identification based on improved RFM model and k-means++ algorithm for complex data analysis. Wireless Communications and Mobile Computing, 2021, 1-8.
Xu, C., Li, Y., Li, C., Ao, X., Yang, M., & Tian, J. (2020). Interactive key-value memory-augmented attention for image paragraph captioning. Proceedings of the 28th international conference on computational linguistics,
Zhang, S., Tay, Y., Yao, L., & Sun, A. (2018). Next item recommendation with self-attention. arXiv preprint arXiv:1808.06414.
Zhang, W., & Wang, M. (2021). An improved deep forest model for prediction of e-commerce consumers’ repurchase behavior. Plos one, 16(9), e0255906.
Zhao, L., Zuo, Y., Yada, K., & Liu, M. (2021). Application of Long Short-term Memory Based Neural Network for Classification of Customer Behavior. 2021 IEEE International Conference on Systems, Man, and Cybernetics (SMC),
Zhu, C., Wang, M., & Su, C. (2022). Prediction of consumer repurchase behavior based on LSTM neural network model. International Journal of System Assurance Engineering and Management, 13(Suppl 3), 1042-1053. |