JTAER, Vol. 18, Pages 1257-1282: “Customer Reviews or Vlogger Reviews?” The Impact of Cross-Platform UGC on the Sales of Experiential Products on E-Commerce Platforms

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030064

Authors: Yiwu Jia Haolin Feng Xin Wang Michelle Alvarado

User-generated content (UGC) from e-commerce platforms and third-party platforms can impact customer-perceived risk and influence product sales in online stores. However, the understanding of UGC from which platform type yields a stronger effect on product sales and how the effects interact across the platforms remains limited. This limitation arises from the complexity of consumer purchasing behavior and information processing, as well as the heterogeneity of UGC features across different platforms and the uncertainty surrounding causal relationships. This study constructs a novel cross-platform framework using the elaboration likelihood model (ELM) to investigate the underlying mechanism of how cross-platform UGC affects online sales of experiential products. Additionally, it examines the mediating effect of purchase intention in the relationship between cross-platform UGC and product sales, as well as the moderating effect of product price. Taking the e-commerce platform Tmall and third-party platform Bilibili as a cross-platform example, we analyzed customer reviews on Tmall and vlogger reviews on Bilibili for 300 cosmetic products, using text sentiment analysis and multiple regression. Results show that the number of product evaluations from third-party platforms positively impacts sales, but this impact is weaker compared to the influence of UGC originating from e-commerce platforms on sales. The underlying mechanism refers to the process by which UGC on an e-commerce platform directly impacts sales and also influences sales through purchase intention. In contrast, UGC on third-party platforms only influences sales through purchase intention. Furthermore, the product price has no significant moderating effect on the positive relationship between review length and sales. This study provides a cross-platform UGC research framework that can guide effective cross-platform marketing management by shedding light on the role of UGC in reducing customer-perceived risk and its impact on online sales of experiential products.

JTAER, Vol. 18, Pages 1238-1256: Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030063

Authors: Yunho Maeng Choong C. Lee Haejung Yun

Although the market for Head-Mounted Display Virtual Reality (HMD VR) devices has been growing along with the metaverse trend, the product has not been as widespread as initially expected. As each user has different purposes for use and prefers different features, various factors are expected to influence customer evaluations. Therefore, the present study aims to: (1) analyze customer reviews of hands-on HMD VR devices, provided with new user experience (UX), using text mining, and artificial neural network techniques; (2) comprehensively examine variables that affect user evaluations of VR devices; and (3) suggest major implications for the future development of VR devices. The research procedure consisted of four steps. First, customer reviews on HMD VR devices were collected from Amazon.com. Second, candidate variables were selected based on a literature review, and sentiment scores were extracted. Third, variables were determined through topic modeling, in-depth interviews, and a review of previous studies. Fourth, an artificial neural network analysis was performed by setting customer evaluation as a dependent variable, and the influence of each variable was checked through feature importance. The results indicate that feature importance can be derived from variables, and actionable implications can be identified, unlike in general sentiment analysis.

JTAER, Vol. 18, Pages 1217-1237: Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030062

Authors: Jorge de Andrés-Sánchez Jaume Gené-Albesa

Conversational robots powered by artificial intelligence (AI) are intensively implemented in the insurance industry. This paper aims to determine the current level of acceptance among consumers regarding the use of conversational robots for interacting with insurers and seeks to identify the factors that influence individuals’ behavioral intention to engage with chatbots. To explain behavioral intention, we tested a structural equation model based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model. It was supposed that behavioral intention is influenced by performance expectancy, effort expectancy, social influence, and trust, and by the moderating effect of insurance literacy on performance expectancy and effort expectancy. The study reveals a significant overall rejection of robotic technology among respondents. The technology acceptance model tested demonstrates a strong ability to fit the data, explaining nearly 70% of the variance in behavioral intention. Social influence emerges as the most influential variable in explaining the intention to use conversational robots. Furthermore, effort expectancy and trust significantly impact behavioral intention in a positive manner. For chatbots to gain acceptance as a technology, it is crucial to enhance their usability, establish trust, and increase social acceptance among users.

JTAER, Vol. 18, Pages 1196-1216: How Streamers Foster Consumer Stickiness in Live Streaming Sales

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030061

Authors: Yongbing Jiao Emine Sarigöllü Liguo Lou Baotao Huang

Streamers play a critical role in fostering consumer stickiness in live streaming sales. Thus, it is necessary to make clear the mechanism of how streamers influence consumer stickiness. Based upon the theories of social support, social identification and consumer stickiness, this study investigates the effects of consumers’ perceived emotional support, informational support, financial support, affectionate support and social network support from streamers on consumer–streamer identification, which in turn affects consumer–streamer stickiness and consumer–brand stickiness in live streaming sales settings. Based on the structural equation modeling analysis of 280 online questionnaires, using the software of Smart PLS 3.0, the results demonstrate that perceived emotional support, perceived informational support, perceived financial support and perceived affectionate support enhance consumer–streamer identification, thereby enhancing consumer–streamer stickiness and consumer–brand stickiness, and thus, consumer–streamer stickiness also enhances consumer–brand stickiness. This study not only extends the theories of live streaming sales, but also provides practical implications for enterprises’ improving consumer–streamer stickiness and consumer–brand stickiness in live streaming sales.

JTAER, Vol. 18, Pages 1177-1195: Pricing Game Models of Hybrid Channel Supply Chain: A Strategic Consumer Behavior Perspective

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030060

Authors: Xuelong Zhang Yufei Li Jianhua Zhu Xuequan Zhou

The current sales model combining online and offline channels meets the diverse requirements of consumers. However, consumers’ inter-channel switching behavior and strategic behavior also pose significant challenges to pricing decisions in the hybrid channel. Using game theory and consumer utility theory, a retailer-driven pricing model is developed to study the optimal pricing problem for each channel in a mixed-channel supply chain considering the characteristics of channel competition and the waiting behavior of strategic consumers. Study results show there is a negative correlation between the proportion of strategic consumers and the optimal pricing and profit of each channel, and as the proportion of strategic consumers rises, the optimal pricing and profit of manufacturers and retailers all trend downward. Incorporating strategic consumers into the pricing model will assist the supply chain in elucidating the behavior of consumer heterogeneity during various decision-making periods and in making reasonable pricing decisions. Effective guiding strategies, such as pre-discount and purchase restrictions, can reduce the profit loss caused by strategic consumer behavior. The optimal combination of pre-announcement discount and strategic consumer ratio can generate the greatest profit for retailers and the supply chain.

JTAER, Vol. 18, Pages 1157-1176: Strata Fee Management in Condominiums via Smart Contracts

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030059

Authors: Liam Scholte Rui Wang Kwok Keung Chung Michal Aibin

Condominiums and similar properties use a stratum to manage daily operations, and owners fund it through strata fees. While existing strata fee management systems may be able to handle such funds, such systems could be more inherently transparent. It is possible to leverage the digital ledger from blockchain networks and smart contracts to build a fully transparent strata fee management system. This paper proposes designing a strata fee management system based on a smart contract in the Ethereum network. Both strata corporations and homeowners can interact with the smart contract to execute common procedures such as paying strata fees and handling expenses. Using smart contracts for strata fee management, it is believed that the chance of fraud by strata corporations is lowered compared to other systems.