Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability
It is important to understand factors affecting the perceived online review helpfulness as it helps solve the problem of information overload in online shopping. Moreover, it is also crucial to explore the factors’ relative importance in predicting review helpfulness in order to effectively detect p...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2017
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| Online Access: | https://eprints.nottingham.ac.uk/52602/ |
| _version_ | 1848798765164527616 |
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| author | Li, Boying Hou, Fangfang Guan, Zhengzhi Chong, Alain Yee-Loong Pu, Xiaodie |
| author_facet | Li, Boying Hou, Fangfang Guan, Zhengzhi Chong, Alain Yee-Loong Pu, Xiaodie |
| author_sort | Li, Boying |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | It is important to understand factors affecting the perceived online review helpfulness as it helps solve the problem of information overload in online shopping. Moreover, it is also crucial to explore the factors’ relative importance in predicting review helpfulness in order to effectively detect potential helpful reviews before they exert influences. Applying Elaboration Likelihood Model (ELM), this study first investigates the effects of central cues (review subjectivity and elaborateness) and peripheral cues (reviewer rank) on review helpfulness with readability as a moderator. Second, it also explores their relative predicting power using the machine learning technique. ELM is tested in online context and the results are compared between experience and search goods. Our results provide evidence that for both types of products review subjectivity can play a more significant role when the content readability is high. Furthermore, this study reveals that the dominant predictor is varied for different product types. |
| first_indexed | 2025-11-14T20:24:58Z |
| format | Conference or Workshop Item |
| id | nottingham-52602 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:24:58Z |
| publishDate | 2017 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-526022020-05-04T18:55:48Z https://eprints.nottingham.ac.uk/52602/ Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability Li, Boying Hou, Fangfang Guan, Zhengzhi Chong, Alain Yee-Loong Pu, Xiaodie It is important to understand factors affecting the perceived online review helpfulness as it helps solve the problem of information overload in online shopping. Moreover, it is also crucial to explore the factors’ relative importance in predicting review helpfulness in order to effectively detect potential helpful reviews before they exert influences. Applying Elaboration Likelihood Model (ELM), this study first investigates the effects of central cues (review subjectivity and elaborateness) and peripheral cues (reviewer rank) on review helpfulness with readability as a moderator. Second, it also explores their relative predicting power using the machine learning technique. ELM is tested in online context and the results are compared between experience and search goods. Our results provide evidence that for both types of products review subjectivity can play a more significant role when the content readability is high. Furthermore, this study reveals that the dominant predictor is varied for different product types. 2017-07-16 Conference or Workshop Item NonPeerReviewed Li, Boying, Hou, Fangfang, Guan, Zhengzhi, Chong, Alain Yee-Loong and Pu, Xiaodie (2017) Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability. In: 21st Pacific Asia Conference on Information Systems (PACIS 2017), 16-20 July, 2017, Langkawi, Malaysia. Review helpfulness; Elaboration Likelihood Model (ELM); readability; search goods; experience goods http://aisel.aisnet.org/pacis2017/257/ |
| spellingShingle | Review helpfulness; Elaboration Likelihood Model (ELM); readability; search goods; experience goods Li, Boying Hou, Fangfang Guan, Zhengzhi Chong, Alain Yee-Loong Pu, Xiaodie Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability |
| title | Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability |
| title_full | Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability |
| title_fullStr | Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability |
| title_full_unstemmed | Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability |
| title_short | Evaluating online review helpfulness based on Elaboration Likelihood Model: the moderating role of readability |
| title_sort | evaluating online review helpfulness based on elaboration likelihood model: the moderating role of readability |
| topic | Review helpfulness; Elaboration Likelihood Model (ELM); readability; search goods; experience goods |
| url | https://eprints.nottingham.ac.uk/52602/ https://eprints.nottingham.ac.uk/52602/ |