Compared with traditional charities, donation-based crowdfunding has many novel characteristics. Among the variety of factors that influence potential donors before they develop a donation intention, which are the main ones influencing the intention to donate online? The purpose of this paper is to investigate the key potential determinants of both time and money donations. This study attempts to combine the theory of planned behavior and norm activation theory with social presence theory to conceptualize and develop an integration framework to measure the donation intention. The results of the structural equation modeling, based on 350 valid questionnaire responses received from November 19 to December 19, 2018, suggest that the dependent variable of time donations is significantly affected by social presence, trust, and perceived behavioral control. As for the dependent variable of money donations, only subjective norm has an insignificant effect. The study results offer practical guidelines about the unique aspects of donation to managers of crowdfunding platform and fundraisers.

Purpose: Drawing on the technology-organization-environment (TOE) framework, this study aims to investigate determinants of performance of artificial intelligence (AI) adoption in hospitality industry during COVID-19 and identifies the relative importance of each determinant.Design/methodology/approach: A two-stage approach that integrates partial least squares structural equation modeling (PLS-SEM) with artificial neural network (ANN) is used to analyze survey data from 290 managers in the hospitality industry.Findings: The empirical results reveal that perceived AI risk, management support, innovativeness, competitive pressure and regulatory support significantly influence the performance of AI adoption. Additionally, the ANN results show that competitive pressure and management support are two of the strongest determinants.Practical implications: This research offers guidelines for hospitality managers to enhance the performance of AI adoption and presents policy-making insights to promote and support organizations to benefit from the adoption of AI technology.Originality/value: This study conceptualizes the performance of AI adoption from both process and firm levels and examines its determinants based on the TOE framework. By adopting an innovative approach combining PLS-SEM and ANN, the authors not only identify the essential performance determinants of AI adoption but also determine their relative importance.

Purpose: Online retailers widely use self-service parcel delivery as a solution to the last-mile logistics problems. The purpose of this paper is to investigate the factors that affect the consumer’s intention to use self-service parcel delivery service.Design/methodology/approach: The authors integrate prior research and propose a comprehensive three-factor model. The study combines individual and situational factors and proposes a socialized factor.Findings: This study found that location convenience, optimism, innovation, and the need for human interaction positively affect the consumer’s intention to avail of the self-service parcel delivery service. It also identifies that socialized factor positively influences the consumer’s intention to use self-service parcel delivery services.Research limitations/implications: The test results show that the explanatory power of the individual factors of the model is better than that of the situational factors. However, this does not imply that the situational factors cannot explain the consumer behavior well. Future studies should employ additional situational factors to explain the consumer behavior.Practical implications: This study offers valuable theoretical and managerial implications. Delivery service providers should concentrate on their marketing force and customize their services for consumer groups who have specific individual characteristics, such as optimism and innovation.Social implications: Strengthening service interactions in the social factor and choosing optimal locations for self-service pickup machines are also essential for the expansion of the users’ population and enhancement of service experience.Originality/value: The authors combined situational and individual factors, proposed a socialized factor, and presented the three-factor model of the consumer’s intention to use self-service parcel delivery service.

With the development of digital technologies, the use of augmented reality in the tourism sector has received increasing attention. However, the understanding of the factors influencing tourists’ post-experience intention with augmented reality devices is incomplete and there is a lack of empirical research. This study explores the impact of AR technical factors, individual factors and situational factors on users’ post-experience AR usage intention and destination revisit intention through satisfaction based on a socio-technical perspective. The survey data collected from 254 visitors who visited the Liangzhu Museum using the corresponding AR glasses were analysed, and the results showed that the novelty of the technical aspect, the technology trust of the individual aspect and the aesthetics, education and authenticity of the situational aspect influenced visitors’ AR usage intention and destination revisit intention through satisfaction. This study has an impact on future research on the application of augmented reality technology to heritage museums.