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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.

The authors integrate prior research and propose a comprehensive three-factor model. The study combines individual and situational factors and proposes a socialized factor.

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.

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.

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.

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.

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.

This study adopts self-determination theory and stimulus-organism-response framework to develop a model that explores the motivations of such donors by considering their self-determination needs and extrinsic and intrinsic motivations.

Based on online survey data collected from 436 crowdfunding donors in China, this study follows a structural equation modeling analysis to test hypotheses.

The results indicate that perceived ease of use, perceived self-efficacy and social connection have positive effects on the donation intentions of backers through a combination of extrinsic and intrinsic motivations.

The findings shed light on various extrinsic and intrinsic motivations advancing knowledge of individual fund motivation in donation-based crowdfunding and provide guidelines for the development of donation-based crowdfunding theory and practice.

The metaverse enables users to create their own avatars in a shared virtual space, giving rise to a new avatar personality that differs from their real-self personality. The aim of this research is to explore how users' real-self and avatar personalities may affect their behavioral engagement and satisfaction in the metaverse context.

This research applies self-discrepancy theory to investigate how the big five traits of both real-self and avatar personalities influence users' engagement and satisfaction in the metaverse. The present research employed a mixed-methods approach, beginning with a qualitative study to identify prevalent personality cues among users on metaverse social media platforms. Subsequently, a quantitative study was conducted to further validate the findings of the qualitative study.

The results indicated that avatar personality scored higher than the real-self personality in the dimensions of openness, conscientiousness and extraversion, while scored lower in the dimensions of agreeableness and neuroticism. Both real-self and avatar personality traits positively influenced metaverse satisfaction via behavioral engagement in the metaverse. Notably, avatar personality traits had a stronger impact on behavioral engagement compared to real-self personality traits, which further influence metaverse satisfaction.

The present study offers practical insights for metaverse developers and managers to enhance user satisfaction by focusing on users’ big five traits of both real-self and avatar personality. It suggests implementing personalized tools, organizing personality-based social activities and other initiatives to encourage user’s behavioral engagement and ultimately enhance metaverse satisfaction.

Unlike existing research that concentrates on a single facet of personality traits, this research employs a mixed-methods approach to conceptualize users' real-self personality and avatar personality, further exploring their impacts on metaverse satisfaction.

People's socializing behavior in social networking services (SNS) presents dramatically different features, forming differentiated online social interaction patterns (DOSIP) in SNS. This study aims to explore the relationships between users' multidimensional psychological needs and multiple social interaction patterns in SNS.

Based on Maslow's hierarchy of needs and use and gratifications (U&G) theory, the authors develop the research model to examine the effects of psychological needs on DOSIP. A survey is used to collect the data of SNS users' social interaction. The authors adopt structural equation modeling–neural network (SEM-NN) integrated method to examine the research model.

Need to belong, need for self-esteem, need for social contact, need for emotional expression, need for cognition, and need for external-esteem have significant influences on both active and passive social interactions respectively.

Based on the categorization of DOSIP into six types in terms of the level of activity and disclosure of social interaction, the authors construct an integrated research model of multidimensional psychological needs to multiple social interaction patterns, and validate the antecedents of DOSIP from the perspective of psychological needs.

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.

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.

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.

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.

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.

As retailers have increasingly embraced an omnichannel retailing strategy, explaining and predicting the helpfulness of online review should consider both online-based and offline-based reviews. The paper aims to discuss this issue.

Based on the signaling theory, this study intends to examine the impacts of review-related and reviewer-related signals on review helpfulness in the context of omnichannel retailing. The proposed research model and corresponding hypotheses were tested by using negative binomial regression.

The results shown that both review-related (review rating and review sentiment strength) and reviewer-related (reviewer real name and reviewer expertise) signals positively affect review helpfulness. Contrary to the authors’ expectations, review length negatively affects review helpfulness. Specifically, when the review submitted from an omnichannel retailer’s offline channel, the positive impacts of reviewer real name on review helpfulness will be stronger, and the positive impacts of reviewer expertise on review helpfulness will be weaker.

Unlike many previous studies tend to explore the antecedents of review helpfulness in a single-channel setting, the study examined the factors that affect review helpfulness in an omnichannel retailing context.

The purpose of this study is to explore the factors influencing viewers’ engagement intention in travel live streaming (TLS) from a perceived value perspective.

This study used a mixed-methods approach. In Study 1, 48 semistructured interviews were analyzed based on grounded theory and perceived value theory, and a research framework was established to investigate the impact of viewers’ engagement intentions in TLS. In Study 2, partial least squares structural equation modeling (PLS-SEM) was used to empirically validate survey data from 255 TLS viewers.

Through an analysis of the interview content, it was found that the expertise and interaction of the live streamer in TLS as well as the immersion, aesthetics and novelty of the live streaming scene are key influencing factors that affect the engagement of TLS viewers. This finding was confirmed through empirical research.

This research provides practical suggestions for live streamers, TLS platforms and local government to increase viewer engagement. Specifically, it provides methods and directions for the individual improvement of live streamers, further promotes the development and construction of the platform and underscores the importance of government initiatives in policy support and regulatory framework development.

This study focuses on the less-researched field of TLS. Using a mixed-methods approach combining interviews and PLS-SEM, this study explores the key factors that affect the engagement of TLS viewers based on the characteristics of live streamers and live streaming scenes.

This study aims to explore how specific cues with new manifestations (i.e. herding message and price discount information) and customer cognitive style influence attention allocation and purchase intention.

To empirically validate the research hypotheses, an eye-tracking experiment with a 2 × 2 × 2 mixed design was conducted on a sample of 44 participants recruited from a university in China. Repeated measures analysis of variance was employed for data analysis.

The results show that herding message and price discount information play different roles in viewers' attention and have an interactive effect on attention. Moreover, individual cognitive styles moderate the impact of herding message on attention allocation. Still, two cues positively affect customer purchase intention.

This study guides future research by applying cue utilization theory to investigate the effects of two cues in live streaming. Findings offer practical implications for how live streaming cues affect viewers' attention allocation and purchase intention.

The aim of this study is to investigate how social media users' experience of seeking emergency information affects their engagement intention toward emergency information with a reciprocity framework integrated with information adoption model.

Drawing on reciprocity theory, indebtedness theory, and information adoption model, an integrative research model is developed. This study employs a questionnaire survey to collect data of 325 social media users in China. Structural equation modeling analyses are conducted to test the proposed theoretical model.

Social media users' experience of seeking emergency information has a strong effect on their perceived information usefulness and indebtedness, while perceived information usefulness further influences community norm, indebtedness, and engagement intention. The authors also found that perceived information usefulness mediates the relationships between experience of seeking emergency information and community norm/indebtedness.

This study offers a new perspective to explain social media users' engagement intention in the diffusion of emergency information. This study contributes to the literature by extending the theoretical framework of reciprocity and applying it to the context of emergency information diffusion. The findings of this study could benefit the practitioners who wish to leverage social media tools for emergency response purposes.

Attracted by tremendous market opportunities of mobile business, many web services providers have started to expand their web services from traditional PC-based environment into the mobile-based environment. However, success in the web services cannot guarantee the success in the mobile services. The purpose of this paper is to identify factors that influence consumer evaluation and use of mobile shopping services in a web-mobile service extension context.

Based on categorization theory, this paper focusses on the role of integration and consistency between web and mobile services. A research model was created and empirically tested on data collected from 298 mobile shopping users in China.

The structural equation modeling analysis indicates that evaluation of source (web service quality) positively affect evaluation of target (perceived mobile service quality and flow in mobile services). The study also found that the relationships between source and target (perceived integration and perceived consistency) play an important role in determining evaluation of the target, which in turn shapes intention to use mobile services.

The survey is based on mobile shopping consumers. Caution is required in any effort to generalize the findings to other research contexts. Factors influencing a consumer's extension or adoption decisions in regard to different mobile services may not be the same, or the degree of influence may differ. Continued studies can test and compare our findings in different mobile services contexts.

The results of the findings provide specific methods for managing the process of web-mobile service extension. The results also indicate the importance of perceived consistency in shaping consumers’ evaluation of the extended mobile services in practical environments.

The present study extends the categorization theory to a multi-channel context and examines mobile services adoption from a cross-environment perspective. It considers evaluation of source, evaluation of target, and the relationships between source and target, which enriches the innovation adoption literature by providing a holistic insight into the evaluation and use of mobile services.