The advancement in digital technologies has led to an explosive information phenomenon, particularly in Internet shopping. This paper attempts to examine the trust element in the current pervasive use of the recommendation system for product promotion effectiveness. Owing to the nature of high-volume online consumers and the nonexistence of the online consumer sampling frame, sampling weight adjustment approach was utilised for ensuring sample representativeness. Additionally, the responses collected were further analysed according to gender for a holistic understanding of the trust element. A cross-sectional quantitative research approach was adopted. Specifically, snowball sampling method was used to collect responses from online consumers. The findings revealed that benevolence, integrity, and competence trust are found to be positively associated with product promotion effectiveness. Competence trust recorded a large effect size followed by benevolence and integrity trust. Both male and female consumers shown different degrees of trust level. The findings provide practical implications for online merchants. They were suggested to focus on enhancing online consumers’ trust level and capitalize on competence trust for effective product promotion. They should also recognize the gender differences in the trust level for product promotion effectiveness when they are promoting gender-based products and services.

/pdf/advancing-on-weighted-pls-sem-in-examining-the-trust-based-13xvvbt4m1.pdf

Advancing on weighted PLS-SEM in examining the trust-based recommendation system in pioneering product promotion effectiveness.

“Take it or leave it?”: Evidence on cultural differences affecting return behaviour for Gen Z

In the Web2.0 era, user-generated content (UGC) provides a valuable source of data to aid in understanding consumers and driving intelligent business. Text mining techniques, such as semantic analysis and sentiment analysis, help to extract meaningful information embedded in UGC. However, research on text mining of UGC for e-commerce business applications involves interdisciplinary knowledge, and few studies have systematically summarized the research framework and application directions of related research in this field. First, based on e-commerce practice, in this study, we derive a general framework to summarize the mainstream research in this field. Second, widely used text mining techniques are introduced, including semantic and sentiment analysis. Furthermore, we analyze the development status of semantic analysis in terms of text representation and semantic understanding. Then, the definition, development, and technical classification of sentiment analysis techniques are introduced. Third, we discuss mainstream directions of text mining for business applications, ranging from high-quality UGC detection and consumer profiling, to product enhancement and marketing. Finally, research gaps with respect to these efforts are emphasized, and suggestions are provided for future work. We also provide prospective directions for future research.

/pdf/text-mining-of-user-generated-content-ugc-for-business-2hcpg478.pdf

Text Mining of User-Generated Content (UGC) for Business Applications in E-Commerce: A Systematic Review

Comprehensive helpfulness of online reviews: A dynamic strategy for ranking reviews by intrinsic and extrinsic helpfulness

ABSTRACT Under information asymmetry, electronic word of mouth (eWOM) is crucial to understanding customer experience in peer-to-peer (P2P) accommodation. However, the topics of what dimensions are included in eWOM and how these dimensions determine sales performance from a contingency perspective remain starkly underinvestigated. Drawing upon trust transfer theory and signaling theory, we identify two eWOM dimensions (i.e., listing-based eWOM and host-based eWOM) and examine their interactions with price and responsiveness on sales performance. Using objective data from Xiaozhu.com, a leading accommodation-sharing platform in China, we apply machine learning algorithms and economic analysis to illustrate customer behavior. Our results indicate that the valence of listing-based eWOM and that of host-based eWOM are positively associated with sales performance. Compared with listing-based eWOM, host-based eWOM exerts a more decisive influence on sales performance. Notably, the relationship between the valence of listing-based eWOM (host-based eWOM) and sales performance is weakened (strengthened) by listing price (host’s responsiveness). These findings provide helpful managerial insights for service strategies and policy actions to improve the accommodation-sharing economy.

How Electronic Word of Mouth Matters in Peer-to-Peer Accommodation: The Role of Price and Responsiveness

Online consumer reviews (OCRs) can function as a venue for digital collaboration among various stakeholders to better meet  collaborate in consumer needs. The sheer volume of OCRs, however, has pos...

Personalized Ranking of Online Reviews Based on Consumer Preferences in Product Features

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Personalized Ranking of Online Reviews Based on Consumer Preferences in Product Features