Large Language Models (LLMs) are increasingly used in decision-making scenarios that involve risk assessment, yet their alignment with human economic rationality remains unclear.In this study, we investigate whether LLMs exhibit risk preferences consistent with human expectations across different personas.Specifically, we propose an evaluation metric called Risk Disparity Score (RDS) and assess whether LLM-generated responses reflect appropriate levels of risk aversion or riskseeking behavior based on individual's persona.Our results reveal that while LLMs make reasonable decisions in simplified, personalized risk contexts, their performance declines in more complex economic decision-making tasks.To address this, we test whether current state-of-art alignment methods such as Direct Preference Optimization(DPO) and In Context Learning(ICL) can enhance LLM adherence to persona-specific risk preferences.We find DPO can improve the economic rationality of LLMs in loss-related parameters, offering a step toward more human-aligned AI decision-making.

Abstract This article examines the determinants of service quality and continuance intention of online services. We proposed and empirically tested a model with both service and technology characteristics as the main drivers of service quality and subsequent continuance intention of eTax, an electronic government (eGovernment) service that enables citizens to file their taxes online. Our data were collected via a two‐stage longitudinal online survey of 518 participants before and after they made use of the eTax service in Hong Kong. The results showed that both service characteristics (i.e., security and convenience) and one of the technology characteristics (i.e., perceived usefulness, but not perceived ease of use) were the key determinants of service quality. Another interesting and important finding that runs counter to the vast body of empirical evidence on predicting intention is that perceived usefulness was not the strongest predictor of continuance intention but rather service quality was. To provide a richer picture of these relationships, we also conducted a post‐hoc analysis of the effects of service and technology characteristics on the individual dimensions of service quality and their subsequent impact on continuance intention and found assurance and reliability to be the only significant predictors of continuance intention. We present implications for research and practice related to online services.

Abstract Prior research on Web animation typically focuses on banner ads, where the findings suggest that users are capable of ignoring the animation when performing online tasks. Research on non‐banner‐ads animation (e.g., animation applied to the main content of an e‐commerce Web site), however, is relatively scarce with inconclusive results. We propose that the effects of non‐banner‐ads animation are moderated by task type and the Web user's experience with the animation. Drawing upon divided attention theories, especially the central capacity theory, this research investigates the effects of non‐banner‐ads animation on Web users' clicking behavior, task performance, and perceptions through an online shopping experiment. The results show that non‐banner‐ads animation does attract Web users' attention, with the animated item more likely to be clicked first and also more likely to be purchased when users are performing browsing tasks. Meanwhile, Web users' task performance and perceptions are negatively affected in the presence of animation. Moreover, the negative effects of animation on task performance are greater in browsing tasks than in searching tasks. Finally, experience can help Web users to reduce the distraction from animation and is more effective when users are engaged in searching tasks than when they are engaged in browsing tasks.

While previous studies on buy-it-now (BIN) auctions focus on the impact of BIN format on economic performances, our study focuses on factors that affect the level of use of BIN auctions by sellers. We propose a conceptual model where culture and product categories are two important factors on the level of use of BIN auctions. Our empirical investigation shows that the level of use of BIN auctions can be explained by the Hofstede Cultural Dimensions. While power distance brings a positive impact, uncertainty avoidance and individualism bring negative impacts on the level of use of BIN auctions by sellers of different countries. Our result also shows that the level of use of BIN auctions by sellers increases with the ease of judging product quality. Our results provide valuable insights for marketplace operators to refine their business strategies and market mechanisms for expanding their businesses to overseas markets.

From a student's perspective, technology-assisted learning provides convenient access to interactive contents in a hyperlinked multimedia environment that allows increased control over the pace and timing of the presented material. Previous research examining different aspects of technology-assisted learning has found equivocal results concerning its effectiveness and outcomes. We extend prior studies by conducting a longitudinal field experiment to compare technology-assisted with face-to-face learning for students' learning of English. Our comparative investigation focuses on learning effectiveness, perceived course learnability, learning-community support, and learning satisfaction. In addition, we analyze the effects of different learning styles in moderating the effectiveness of and satisfaction with technology-assisted learning. Overall, our results show significantly greater learning effectiveness with technology-assisted learning than with conventional face-to-face learning. Learning style has noticeable influences on the effectiveness and outcomes of technology-assisted learning. We also observe an apparently important interaction effect with the medium for delivery, which may partially explain the equivocal results of previous research.

Personalization agents are incorporated in many Web sites to tailor content and interfaces for individual users. In contrast to the proliferation of personalized Web services worldwide, empirical research on the effects of Web personalization is scant. How does exposure to personalized offers affect subsequent product consideration and choice outcome? Drawing on literature in human-computer interaction (HCI) and user behavior, this research examines the effect of three major elements of Web personalization strategies on users' information processing through different decision-making stages: personalized content quality, feature overlapping among alternatives, and personalized message framing. These elements can be manipulated by a firm during implemention of its personalization strategy. A study using a personalized ringtone download Web site was conducted. The findings provide empirical evidence of the effects of Web personalization. In particular, when users are forming their consideration sets, the agents can play a role in helping users discover new products or generate demand for unfamiliar products. Once a decision has been made, however, the personalization agent's persuasive effects diminish. These results establish that the role of personalization agents changes at different stages of users' decision-making process.