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Cheng J, Song T, Liu Z, Zhou L, Sun D. RETRACTED ARTICLE: Artificial intelligence technology based on deep learning in digestive endoscopy imaging diagnosis. PERSONAL AND UBIQUITOUS COMPUTING 2023; 27:845-850. [DOI: 10.1007/s00779-021-01532-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Accepted: 01/28/2021] [Indexed: 08/30/2023]
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Ogiela U, Snášel V. Predictive intelligence in evaluation of visual perception thresholds for visual pattern recognition and understanding. Inf Process Manag 2022. [DOI: 10.1016/j.ipm.2022.102865] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Mallavarapu T, Cranfill L, Kim EH, Parizi RM, Morris J, Son J. A federated approach for fine-grained classification of fashion apparel. MACHINE LEARNING WITH APPLICATIONS 2021. [DOI: 10.1016/j.mlwa.2021.100118] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
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Li Z, Yuan J, Du B, Hu J, Yuan W, Palladini L, Yu B, Zhou Y. Customer Behavior on Purchasing Channels of Sustainable Customized Garment With Perceived Value and Product Involvement. Front Psychol 2021; 11:588512. [PMID: 33408664 PMCID: PMC7779488 DOI: 10.3389/fpsyg.2020.588512] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 11/24/2020] [Indexed: 11/28/2022] Open
Abstract
Online shopping for customized garments has become the fastest-growing field of the Chinese eBusiness market. Most consumers not only limit themselves to buying standardized garments but also want to buy garments customized to their preferences. This phenomenon has pushed the fashion textile and apparel industry to change its supply chain operations to meet the customization demand. Besides, the fashion textile and apparel industry also want to study how different channel factors will affect consumers' perceived value and further influence consumers' purchasing decisions. We initiated this study and empirically tested more than 200 experienced consumers. This study collaborated with a fashion textile and apparel company that aims to implement customized product lines soon. Based on the perceived value theory and risk management theory, we investigated whether product involvement and channel identification on supply chain design will affects potential customized product consumers' purchasing decisions. The findings reveal that channel recognition affects consumer decisions by having a positive impact on their perceived value. The perceived risk and shopping channel involvement of consumers have a negative impact on their perceived values and channel selections. In addition, product involvement has a moderating effect on the relationship between channel's perceived risk, perceived values, and channel selections as well.
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Affiliation(s)
- Zhenfang Li
- School of Business, Ningbo University, Ningbo, China
| | - Jia Yuan
- School of Business, Ningbo University, Ningbo, China
| | - Bisheng Du
- School of Business, Ningbo University, Ningbo, China.,Center for Collaborative Innovation on Port Trading Cooperation and Development, Ningbo University, Ningbo, China
| | - Junhao Hu
- School of Business, Ningbo University, Ningbo, China
| | - Wenwen Yuan
- School of Business, Ningbo University, Ningbo, China
| | - Lorenzo Palladini
- Department of Management, Faculty of Law, Economics and Finance, Luxembourg University, Luxembourg City, Luxembourg
| | - Bing Yu
- School of Business, Ningbo University, Ningbo, China
| | - Yan Zhou
- School of Business, Ningbo University, Ningbo, China.,Center for Collaborative Innovation on Port Trading Cooperation and Development, Ningbo University, Ningbo, China
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Context-Controlled Topic-Aware Neural Response Generation for Open-Domain Dialog Systems. Inf Process Manag 2021. [DOI: 10.1016/j.ipm.2020.102392] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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