Jun Fan, Wangyue Zhou, Xue Yang, Boying Li and Ying Xiang
Swift guanxi and trust can influence consumers’ decision making in social commerce. What factors will influence the formation of swift guanxi and trust between buyers and sellers…
Abstract
Purpose
Swift guanxi and trust can influence consumers’ decision making in social commerce. What factors will influence the formation of swift guanxi and trust between buyers and sellers in social commerce has not been clearly investigated. The purpose of this paper is to identify antecedents and impacts of swift guanxi and trust in social commerce.
Design/methodology/approach
An online questionnaire was used to collect the data, and Partial Least Squares Structural Equation Modeling was employed for data analysis. Social support and presence are introduced as the antecedents for swift guanxi and trust, leading to the repurchase intention (RI) and social sharing intention of customers.
Findings
The results indicate that social support and presence can influence swift guanxi and trust. Social support and presence are positively associated with swift guanxi and trust which further lead to RI and social sharing intention.
Practical implications
The findings can be used to guide sellers in social commerce platforms to improve their services and make good use of platform features to improve customers’ perception of presence. To attract new customers and retain old customers, sellers should also build swift guanxi and trust through the recommendation and experience sharing of previous buyers on social media.
Originality/value
This study combines social support theory and presence theory to investigate the factors that influence customers’ purchase decision and social sharing intention in the context of social commerce in China. The integration of social support theory and presence theory explains both the social and technical factors that influence swift guanxi and trust in social commerce.
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Luonan Li, Wangyue Zhou and Yuangao Chen
This study explores the effects of virtual streamer characteristics, virtual scene characteristics and streamer image-scene fit on users’ watching intention from the perspective…
Abstract
Purpose
This study explores the effects of virtual streamer characteristics, virtual scene characteristics and streamer image-scene fit on users’ watching intention from the perspective of flow experience.
Design/methodology/approach
The survey data for this study were collected from the QQ fan group of virtual streamers between November 26th 2022 and December 5th 2022. The authors survey 274 viewers who have experience of watching virtual streaming and employ the partial least squares structural equation model to test the research hypotheses.
Findings
Among the characteristics of virtual streamers, interactivity significantly influences users’ perceived enjoyment and concentration, while vividness only affects perceived enjoyment. In addition, the novelty of the virtual scene has a notable impact on users’ perceived enjoyment and concentration, whereas aesthetic appeal serves as an important indicator solely for concentration. Furthermore, the virtual streamer image-scene fit also affects users’ perceived enjoyment and concentration. Finally, perceived enjoyment and concentration equally contribute to users' watching intention.
Originality/value
This study explores the impact of virtual streamer characteristics, virtual scene characteristics and streamer image-scene fit on users’ watching intention, which enriches the research on user behavioral intention in virtual streaming. Additionally, this study attempts to combine the stimulus-organism-response (S-O-R) model and flow theory in the field of virtual streaming, expanding the research areas. Finally, this study also provides valuable insights for virtual streamers and virtual streaming platforms. By enhancing their virtual personas and optimizing their streaming strategies, virtual streamers can more effectively retain users and maintain audience engagement. Meanwhile, virtual streaming platforms can gain a deeper understanding of user preferences, enabling them to launch high-quality events that sustain user popularity. These efforts collectively contribute to the advancement of the virtual streaming industry.
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Wangyue Zhou, Jincai Dong and Wenyu Zhang
Interpersonal interaction can influence consumers’ purchase intention in social commerce (s-commerce). This paper aims to identify interpersonal interaction factors as well as the…
Abstract
Purpose
Interpersonal interaction can influence consumers’ purchase intention in social commerce (s-commerce). This paper aims to identify interpersonal interaction factors as well as the mediating effect of relationship quality between interpersonal interaction factors and consumers’ purchase intention in s-commerce.
Design/methodology/approach
This study explores new dimensions of interpersonal interaction in s-commerce by integrating interaction between consumers and online vendors and that between consumers and online recommenders in s-commerce. An online questionnaire was used to collect the data, and partial least squares structural equation modeling (PLS-SEM) was employed for data analysis.
Findings
The results indicate that interpersonal interaction factors of both online vendors and online recommenders positively affect swift guanxi and initial trust between consumers and online vendors. Swift guanxi and initial trust positively affect consumers’ purchase intention. Initial trust partially mediates between interpersonal interaction factors and purchase intention while swift guanxi does not mediate between perceived similarity of online recommenders and purchase intention.
Practical implications
The findings can be used to guide vendors in s-commerce platforms to make good use of platform features to improve interpersonal interaction. Meanwhile, s-commerce platforms should be enhanced with efficient interaction tools to help cultivate relationship quality between consumers and online vendors.
Originality/value
This study combines social exchange theory, trust transfer theory and relationship quality theory to investigate the factors that influence swift guanxi and initial trust between consumers and online vendors, which extends the study of interpersonal interaction and enriches the dimensions of relationship quality in the context of s-commerce.
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Zhenning Wang, Zhengzhi (Gordon) GUAN, Fangfang Hou, Boying Li and Wangyue Zhou
The purpose of this paper is to investigate the effects of trust in service and structural assurance on the continuance intention of FinTech services, and the roles of technical…
Abstract
Purpose
The purpose of this paper is to investigate the effects of trust in service and structural assurance on the continuance intention of FinTech services, and the roles of technical factors (i.e. situational normality and system quality) and social factors (i.e. herding and subjective norm) in developing trust in service and structural assurance. YuEbao is selected as the subject as it is a representative example of FinTech services in China.
Design/methodology/approach
A survey questionnaire was deployed and a ten-point sliding scale with two-decimal points was applied to improve the accuracy of the questionnaire. Partial least squares structural equation modeling was used to analyze the data.
Findings
Trust in service and structural assurance can encourage continuance intention of FinTech service. System quality, situational normality and subjective norm can boost the development of trust in service. Both herding and subjective norm can affect structural assurance significantly.
Research limitations/implications
The study highlights the important roles played by technical factors (i.e. situational normality and system quality) and social factors (i.e. herding and subjective norm) in developing the two levels of trust (i.e. trust in service and structural assurance). It also validates the influences of trust in service and structural assurance on encouraging customers’ continuance intention in the novel context of FinTech.
Practical implications
The findings of this study can be used by practitioners to encourage customers to continue using their FinTech services. To encourage continuance, service providers can improve the quality of their system, design the system to be aligned with customers’ using habits and show customers that their close friends are also using the service.
Originality/value
This study adds to the existing body of trust literature by investigating the direct effects of trust in service and structure assurance on continuance intention and how these two levels of trust are developed from technical and social aspects. It generates interesting insights into customers’ continuance behavior of FinTech services.
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Wangyue Zhou, Zayyad Tsiga, Boying Li, Shuning Zheng and Shuli Jiang
The purpose of this paper is to identify antecedents of e-finance continuance intention with Alibaba’s Yu’E Bao as an example.
Abstract
Purpose
The purpose of this paper is to identify antecedents of e-finance continuance intention with Alibaba’s Yu’E Bao as an example.
Design/methodology/approach
An online questionnaire was used to collect the data (n=293), and partial least squares structural equation modeling was employed for data analysis. Four e-finance features (perceived reputation, website quality, e-finance familiarity and situational normality) are introduced with trust acting as a moderator between the users’ satisfaction and continuance intention to use an e-finance platform.
Findings
The results find that website quality, familiarity and situational normality can influence perceived ease of use (PEOU) and perceived usefulness (PU). PEOU and PU, together with reputation, are positively associated with confirmation which further leads to satisfaction. The positive effects that satisfaction and trust have on e-finance continuance intention are confirmed, and trust is found to be a significant moderator on the relationship between satisfaction and continuance intention.
Practical implications
The findings can be used to guide e-finance providers to improve their platform design and services to retain users.
Originality/value
This study combines the theory of trust, Technology Acceptance Model and Expectations Confirmation Theory to investigate the factors that influence the continuance intention in the context of e-finance in China.
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Qinxu Ding, Ding Ding, Yue Wang, Chong Guan and Bosheng Ding
The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive…
Abstract
Purpose
The rapid rise of large language models (LLMs) has propelled them to the forefront of applications in natural language processing (NLP). This paper aims to present a comprehensive examination of the research landscape in LLMs, providing an overview of the prevailing themes and topics within this dynamic domain.
Design/methodology/approach
Drawing from an extensive corpus of 198 records published between 1996 to 2023 from the relevant academic database encompassing journal articles, books, book chapters, conference papers and selected working papers, this study delves deep into the multifaceted world of LLM research. In this study, the authors employed the BERTopic algorithm, a recent advancement in topic modeling, to conduct a comprehensive analysis of the data after it had been meticulously cleaned and preprocessed. BERTopic leverages the power of transformer-based language models like bidirectional encoder representations from transformers (BERT) to generate more meaningful and coherent topics. This approach facilitates the identification of hidden patterns within the data, enabling authors to uncover valuable insights that might otherwise have remained obscure. The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.
Findings
The analysis revealed four distinct clusters of topics in LLM research: “language and NLP”, “education and teaching”, “clinical and medical applications” and “speech and recognition techniques”. Each cluster embodies a unique aspect of LLM application and showcases the breadth of possibilities that LLM technology has to offer. In addition to presenting the research findings, this paper identifies key challenges and opportunities in the realm of LLMs. It underscores the necessity for further investigation in specific areas, including the paramount importance of addressing potential biases, transparency and explainability, data privacy and security, and responsible deployment of LLM technology.
Practical implications
This classification offers practical guidance for researchers, developers, educators, and policymakers to focus efforts and resources. The study underscores the importance of addressing challenges in LLMs, including potential biases, transparency, data privacy, and responsible deployment. Policymakers can utilize this information to shape regulations, while developers can tailor technology development based on the diverse applications identified. The findings also emphasize the need for interdisciplinary collaboration and highlight ethical considerations, providing a roadmap for navigating the complex landscape of LLM research and applications.
Originality/value
This study stands out as the first to examine the evolution of LLMs across such a long time frame and across such diversified disciplines. It provides a unique perspective on the key areas of LLM research, highlighting the breadth and depth of LLM’s evolution.
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Lifan Chen, Shengming Liu, Yue Wang and Xiaoli Hu
This study argues that leader humility is an important facilitator of team creativity. Based on social learning theory, the study explores a new mechanism that links humble leader…
Abstract
Purpose
This study argues that leader humility is an important facilitator of team creativity. Based on social learning theory, the study explores a new mechanism that links humble leader behavior to team creativity through a path of team learning.
Design/methodology/approach
Data were collected in two private-owned technology companies located in South China. The two-time survey included 77 team leaders and 310 employees. An analysis of time-lagged, multisource data was conducted.
Findings
Evidence shows that humble leader behavior promotes team learning behavior through a social learning process, with a subsequent increase in team creativity. This influence is also strengthened when leader effectiveness is high.
Practical implications
Team creativity is an important determinant of organizational success. This research shows that humble leaders can motivate team creativity by acting as a role model. In addition, this research also reminds us that humble leader behavior loses its effect if the leader is incapable.
Originality/value
This research contributes to existing literature on humble leader behavior and team creativity, especially on the mechanisms and contingency effects between these factors.