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Purpose: Generative artificial intelligence (GenAI) has progressed in its ability and has seen explosive growth in adoption. However, the consumer's perspective on its use, particularly in specific scenarios such as financial advice, is unclear. This research develops a model of how to build trust in the advice given by GenAI when answering financial questions. Design/methodology/approach: The model is tested with survey data using structural equation modelling (SEM) and multi-group analysis (MGA). The MGA compares two scenarios, one where the consumer makes a specific question and one where a vague question is made. Findings: This research identifies that building trust for consumers is different when they ask a specific financial question in comparison to a vague one. Humanness has a different effect in the two scenarios. When a financial question is specific, human-like interaction does not strengthen trust, while (1) when a question is vague, humanness builds trust. The four ways to build trust in both scenarios are (2) human oversight and being in the loop, (3) transparency and control, (4) accuracy and usefulness and finally (5) ease of use and support. Originality/value: This research contributes to a better understanding of the consumer's perspective when using GenAI for financial questions and highlights the importance of understanding GenAI in specific contexts from specific stakeholders.

While short videos bring a lot of information and happiness to users, they also occupy users time and short videos gradually change peoples living habits. This paper studies the negative effects and negative emotions of users caused by using short video platforms, as well as the users intention to continue using the short video platform when they have negative emotions. Therefore, this study uses flow theory and illusion of control theory to construct a research hypothesis model and preliminarily confirms six influencing factors, and uses sequential mixed research method to conduct quantitative and qualitative research. The results show that users use of short video platforms will have negative emotions and negative emotions will affect users intention to continue to use short video platforms. This study expands the breadth and depth of research on short videos and enriches the research of negative emotions on the intention to continue using human computer interaction software. Additionally, illusion of control theory is introduced into the field of human computer interaction for the first time, which enriches the application scenarios of control illusion theory., Comment: Electronic Commerce Research and Applications (2023)

Artificial intelligence based chatbots have brought unprecedented business potential. This study aims to explore consumers trust and response to a text-based chatbot in ecommerce, involving the moderating effects of task complexity and chatbot identity disclosure. A survey method with 299 useable responses was conducted in this research. This study adopted the ordinary least squares regression to test the hypotheses. First, the consumers perception of both the empathy and friendliness of the chatbot positively impacts their trust in it. Second, task complexity negatively moderates the relationship between friendliness and consumers trust. Third, disclosure of the text based chatbot negatively moderates the relationship between empathy and consumers trust, while it positively moderates the relationship between friendliness and consumers trust. Fourth, consumers trust in the chatbot increases their reliance on the chatbot and decreases their resistance to the chatbot in future interactions. Adopting the stimulus organism response framework, this study provides important insights on consumers perception and response to the text-based chatbot. The findings of this research also make suggestions that can increase consumers positive responses to text based chatbots. Extant studies have investigated the effects of automated bots attributes on consumers perceptions. However, the boundary conditions of these effects are largely ignored. This research is one of the first attempts to provide a deep understanding of consumers responses to a chatbot., Comment: Internet Research (2021)

Ransomware attack effectiveness has increased causing far reaching consequences that are not fully understood. The ability to disrupt core services, the global reach, extended duration, and the repetition has increased their ability to harm organizations. One aspect that needs to be understood better is the effect on the user. The user in the current environment is exposed to new technologies that might be adopted, but there are also habits of using existing systems. The habits have developed over time with trust increasing in the organization in contact directly and the institutions supporting it. This research explores whether the global, extended, and repeated RW attacks reduce the trust and inertia sufficiently to change long-held habits in using information systems. The model tested measures the effect of the RW attack on the e-commerce status quo to evaluate if it is significant enough to overcome the users resistance to change., Comment: International Journal of Information Systems in the Service Sector (2022)

This paper offers an overview of collaborative consumption (CC), the related business models (BM), the value added (VA) from the consumer's perspective and the role of trust. CC is expanding but it is unclear what opportunities it offers and what the challenges will be. This research evaluates the current CC BMs and identifies 13 ways they add value from the consumer's perspective. This research further explores whether CC BMs fall into two categories in terms of what the consumer values. In the first category, the CC BMs require a low level of trust while in the second category of CC BMs a higher level of trust is necessary. It was found that 13 VA by CC BMs could be grouped into personal interest, communal interest and trust building. It is important for organisations to acknowledge how their CC BM relates to these dimensions.

On the one hand, a growing amount of research discusses support for improving online collaborative learning quality, and many indicators are focused to assess its success. On the other hand, thinkLets for designing reputable and valuable collaborative processes have been developed for more than ten years. However, few studies try to apply thinkLets to online collaborative learning. This paper introduces thinkLets to online collaborative learning and experimentally tests its effectiveness with participants' responses on their satisfaction. Yield Shift Theory (YST), a causal theory explaining inner satisfaction, is adopted. In the experiment, 113 students from Universities in Beijing, China are chosen as a sample. They were divided into two groups, collaborating online in a simulated class. Then, YST in student groups under online collaborative learning is validated, a comparison study of online collaborative learning with and without thinkLets is implemented, and the satisfaction response of participants are analyzed. As a result of this comparison, YST is proved applicable in this context, and satisfaction is higher in online collaborative learning with thinkLets.

Central Bank Digital Currencies (CBDCs) have been implemented by only a handful of countries, but they are being explored by many more. CBDCs are digital currencies issued and backed by a central bank. Consumer trust can encourage or discourage the adoption of this currency, which is also a payment system and a technology. This research attempts to understand consumer trust in CBDCs so that the development and adoption stages are more effective and satisfying for all the stakeholders.