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Peer-to-Peer Accommodation Service (P2PAS) has emerged as a novel paradigm that enables consumers to book temporary accommodation through P2PAS platforms (online transaction), and then reside in hosts' rooms (offline consumption). Due to potential variance in performance and conflict of interest between hosts and platforms, consumers may differ in their trust perceptions of the two parties, which in turn affects consumers' continuous usage of P2PAS. To this end, the authors endeavor to unravel the effect of consumers' trust incongruence on continuance intention, and to further elucidate the moderating influence of transaction and consumption risks on this relationship. This paper aims to discuss the aforementioned objectives.

This study collected data through an online survey of 408 P2PAS consumers. Polynomial modeling and response surface analysis were conducted to validate the hypothesized relationships.

Response surface analysis reveals that trust incongruence did not significantly affect consumers' continuance intention. However, continuance intention would be greater when TP was higher than TH compared with when TH was higher than TP. Furthermore, the analytical results suggest that trust incongruence exerts greater negative effect on continuance intention when transaction and consumption risks were high.

First, the study marks a paradigm shift in conceptualizing the incongruence between TP and TH as a determinant of consumers' continuance intention toward P2PAS. Second, the authors derive a typology of risks that is contextualized to P2PAS. Finally, the authors establish transaction and consumption risks as boundary conditions influencing the effects of trust incongruence on consumers' continuance intention toward P2PAS.

This paper studies the optimal decision-making and coordination problem of a dual-channel fresh agricultural product (FAP) supply chain. The purpose is to analyze the impact of information sharing on optimal decisions and propose a coordination mechanism to encourage supply chain members to share information.

The two-echelon dual-channel FAP supply chain includes a manufacturer and a retailer. By using the Stackelberg game theory and the backward induction method, the optimal decisions are obtained under information symmetry and asymmetry and the coordination contract is designed.

The results show that supply chain members should comprehensively evaluate the specific situation of product attributes, coefficient of freshness-keeping cost and network operating costs to make decisions. Asymmetric information can exacerbate the deviation of optimal decisions among supply chain members and information sharing is always beneficial to manufacturers but not to retailers. The improved revenue-sharing and cost-sharing contract is an effective coordination mechanism.

The conclusions can provide theoretical guidance for supply chain managers to deal with information asymmetry and improve the competitiveness of the supply chain.

This paper combines the three characteristics that are most closely related to the reality of supply chains, including horizontal and vertical competition of different channels, the perishable characteristics of FAPs and the uncertainty generated by asymmetric demand information.

This paper aims to understand Chinese tourists’ changing shopping experience in Macao. In scrutinizing reviews posted in the pre-COVID and during COVID eras, the study has identified changing patterns in Chinese tourists’ shopping experiences, including increased leisure components while shopping, decreased luxury pursuits and an improved overall leisure and shopping experience because of decreased prices in accommodation and a less crowded retail and leisure environment. An emergent opportunity to provide “retail-tainment” experience is discussed.

The purpose of this paper is to introduce an improved system identification method for small unmanned helicopters combining adaptive ant colony optimization algorithm and Levy’s method and to solve the problem of low model prediction accuracy caused by low-frequency domain curve fitting in the small unmanned helicopter frequency domain parameter identification method.

This method uses the Levy method to obtain the initial parameters of the fitting model, uses the global optimization characteristics of the adaptive ant colony algorithm and the advantages of avoiding the “premature” phenomenon to optimize the initial parameters and finally obtains a small unmanned helicopter through computational optimization Kinetic models under lateral channel and longitudinal channel.

The algorithm is verified by flight test data. The verification results show that the established dynamic model has high identification accuracy and can accurately reflect the dynamic characteristics of small unmanned helicopter flight.

This paper presents a novel and improved frequency domain identification method for small unmanned helicopters. Compared with the conventional method, this method improves the identification accuracy and reduces the identification error.