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Enterprise Information Systems Volume 15, 2021 - Issue 10
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Mining analysis of customer perceived value of online customisation experience under social commerce

Xiangzhi Bua Business School, Shantou University, Shantou, China;b Guangdong-Taiwan Enterprise Cooperation Research Institute, Shantou University, Shantou, ChinaView further author information
,
Zhoucheng Huanga Business School, Shantou University, Shantou, ChinaView further author information
&
Quanwu Zhaoc School of Economics and Business Administration, Chongqing University, Chongqing, China;d Chongqing Key Laboratory of Logistics, Chongqing University, Chongqing, ChinaCorrespondence[email protected]
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Pages 1658-1682 | Received 22 Mar 2020, Accepted 20 Feb 2021, Published online: 04 Mar 2021

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Read on this site (3)

Ruiqing Sun, Ying Kei Tse & Xiaohong Liu. (2023) An empirical investigation of electronic word-of-mouth: product recall and crisis response strategy in social media. Enterprise Information Systems 17:12.
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Li Xinwei, Ying Kei Tse & Fernando Fastoso. (2023) Unleashing the power of social media data in business decision making: an exploratory study. Enterprise Information Systems 0:0.
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Xiaoting Dai, Jie Zhang & Victor Chang. (2023) Impacts of social networks in an agent-based artificial stock market. Enterprise Information Systems 17:5.
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Articles from other publishers (4)

Van-Ho Nguyen & Thanh Ho. (2023) Analysing online customer experience in hotel sector using dynamic topic modelling and net promoter score. Journal of Hospitality and Tourism Technology 14:2, pages 258-277.
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Dhananjay Bapat & Rahul Khandelwal. (2022) Antecedents and consequences of consumer hope for digital payment apps services. Journal of Services Marketing 37:1, pages 110-127.
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Saeedeh Poormoosa Abkenar, Iman Raeesi Vanani, Babak Sohrabi & Amir Manian. (2022) Social Commerce Mobile Application Enhancement: a hybrid text clustering - topic modeling business model analysis. Electronic Commerce Research.
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Ming K. Lim, Yan Li & Xinyu Song. (2021) Exploring customer satisfaction in cold chain logistics using a text mining approach. Industrial Management & Data Systems 121:12, pages 2426-2449.
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