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Driven by artificial intelligence technology, chatbots have begun to play an important customer service role in the online retail environment. This study aims to explore how conversational styles improve the interaction experience between consumers and chatbots in different social crowding environments, and the moderating role of product categories is considered.

Three studies are conducted to understand the influences of conversational styles, social crowding and product categories on consumer acceptance, assessed using situational experiments and questions.

In a low social crowding environment, consumers prefer chatbots with a social-oriented (vs. task-oriented) conversational style, while in a high social crowding environment, consumers prefer a task-oriented (vs. social-oriented) conversational style, and warmth and competence mediate these effects. The moderating effect of product categories is supported.

This study expands the application of the stereotype content model to improve the interaction experience level between consumers and chatbots in online retail. The findings can provide managerial suggestions for retailers to select a chatbot's conversational style and promote a more continuous interaction between consumers and chatbots.

Tourism via virtual reality (VR) technology has become an interesting option for consumers to “travel.” The best approaches to optimizing the VR tourism environment, improving the interactive experience of tourists and encouraging tourists to adopt VR are not yet fully understood. This study explores the willingness of tourists to adopt VR tourism from the dual aspects, richness and dynamics, of virtual social cues.

To examine the effects of richness (multiple vs. few cues) and dynamic (changeable vs. static cues) on consumers' willingness to adopt VR tourism, three virtual tourism scenes were designed and presented by head-mounted displays. The data were collected for participants in the VR laboratory and tested by ANOVA and partial least squares–structural equation modeling.

Virtual social cues can generate mental imagery through interactivity, vividness and parasocial interactions, thus increasing the consumer's likelihood of adopting VR tourism. It was also found that imagination moderates mental imagery and adoption intention. When the consumer's imagination is stronger, their mental imagery stimulates a stronger willingness to adopt VR tourism.

The authors innovatively utilize concepts of parasocial interaction and mental imagery and discuss the various influences and mediation mechanisms of social cue characteristics on consumers' adoption of VR tourism. The conclusions may provide new insights for VR tourism managers and tourism scholars.

Promoting the adoption of digital payments by the elderly plays an important role in the development of the digital economy. The purpose of this study is to build an extended theory of planned behavior (TPB) model to predict the elderly's intention to pay for digital services under COVID-19 epidemic constraints.

Based on the extended TPB model, 320 qualified participants were recruited on the network. The structural equation model was tested using the SmartPLS3.3 tool, and the moderation effects were tested through SPSS26 and the Process macro.

The results showed that the three dimensions of TPB theory, the basic elements (perceived value and perceived risk), and the external environment (COVID-19 pandemic) were important factors that influence the elderly users' intention to adopt digital payments. Further research found that motivation factors (personal innovativeness, intergenerational support, and social support) can positively moderate these effects.

The results of the study provide a further explanation for understanding the willingness of elderly people to adopt digital payments during the COVID-19 pandemic and bring inspiration to system developers and social managers to reduce the risk of COVID-19 pandemic and increase the share of digital payments for this category.

This paper used the extended TPB theory to construct a fundamental environmental motivation (FEM) framework for understanding the main influencing factors of elderly users' intention to adopt digital payments during the COVID-19 pandemic.

The purpose of this study is to explore mitigation measures for cash flow interruption during the epidemic and provide decision support to ensure the regular operation and robustness of the supply chain (SC).

Considering the scenarios of production capacity and demand disruption during the epidemic, the authors adopt system dynamics (SD) to construct a three-echelon SC financial system consisting of a core manufacturer, a capital-constrained retailer and the customer. In different interruption scenarios, through the decision adjustments of stakeholders, the differences in performance are compared to explore solutions for SC robust optimization.

The results show that partial credit guarantee (PCG) could solve cash flow interruption and maintain the regular operation of the SC. During epidemic, with the product price increases, the revenue of stakeholders and the robustness are generally negatively correlated. But when the manufacturer's production capacity is fully interrupted, increasing product price is the right decision for the retailer and could simultaneously promote performance and robustness.

This paper primarily focuses on the PCG under the cash flow interruption caused by epidemics. The authors adopt the supply chain finance (SCF) theory and SD method to supplement and expand existing research on interruption management of SC. It is a pioneering study to explore the robustness of the SC financial system under disruptions.