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Despite the burgeoning popularity of virtual gifting in live streaming, research lacks an in-depth understanding of the drivers behind this behavior. Using para-social relationship (PSR), this study aims to capture viewers’ lively social feelings toward the streamer as the key factor leading to the purchase behavior of virtual gifts. It also aims to establish a theoretical link between PSR and viewers’ holistic experience in live streaming as captured by cognitive absorption and aims to investigates the role of technological features (i.e. viewer–streamer and viewer–viewer interactivity, streamer-level and viewer-level deep profiling and design aesthetics) in shaping viewers’ experience.

Based on 433 survey responses, this study employs a combination of structural equation modeling and neural networks to offer valuable insights into the relationships between the technological environment, viewer experience and viewer behavior.

Our results highlight the salience of PSR in promoting the purchase of virtual gifts through cognitive absorption and the importance of the technological environment in eliciting the viewer experience. This study sheds light on the development of PSR in a technological environment and its relationship with cognitive absorption.

By applying PSR to conceptualize viewers’ perceived connection with the streamer, this study extends the research on purchase behavior in the non-shopping context by providing an enlightened understanding of virtual gift purchase behavior in live streaming. Moreover, by theoretically linking PSR with cognitive absorption, virtual gift purchase and technological features of live streaming, it enriches the theory of PSR and bridges the gap between the design practice of supporting the IT infrastructure of live streaming and research.

The purpose of this paper is to investigate what factors can affect people’s continuous watching and consumption intentions in live streaming.

This research conducted a mixed-methods study. The semi-structured interview was deployed to develop a research model and a live streaming typology. A survey was then used for quantitative assessment of the research model. Survey data were analyzed using partial least squares-structural equation modeling.

The results suggest that sex and humor appeals, social status display and interactivity play considerable roles in the viewer’s behavioral intentions in live streaming and their effects vary across different live streaming types.

This research is conducted in the Chinese context. Future research can test the research model in other cultural contexts. This study can also be extended by incorporating the roles of viewer gender and price sensitivity in the future.

This study provides managerial insights into how live streaming platforms and streamers can improve their popularity and profitability.

The paper introduces a novel form of social media and a new business model. It illustrates what will affect people’s behavioral intentions in such a new context.

Charitable crowdfunding features are embedded in social media platforms to encourage pro-social behaviors. Although such new practice allows practitioners to leverage the power of a highly connected crowd, accomplishing the fundraising goal is still a challenge. This study seeks to understand what drives the donation intention in charitable crowdfunding features on social media platforms by examining the roles of social experience, empathy and personal impulsiveness.

A survey questionnaire was distributed to social media users in China to collect data. A total of 206 valid responses were analyzed using structural equation modeling to test the proposed hypotheses.

The results showed that empathy mediates interaction with the fundraiser and perceived proximity with the donatee on a user's donation intention. We also found that social influence on social media platforms positively influences empathy and donation intention. In addition, personal impulsiveness was found to moderate the relationship between empathy and donation intention.

This study contributes to existing literature and practices. It identifies three dimensions of social experience and examines their effects on donation intention, providing insights into the charitable crowdfunding features on social media. Moreover, this study extends the understanding to empathy by delineating its mediating role in the relationship between social experience and donation intention and examining how personal impulsiveness moderates the effect of empathy on donation intention. Furthermore, this study provides valuable insights for practitioners to craft strategies to stimulate pro-social behaviors and increase donations.

The purpose of this paper is to investigate the effects of trust in service and structural assurance on the continuance intention of FinTech services, and the roles of technical factors (i.e. situational normality and system quality) and social factors (i.e. herding and subjective norm) in developing trust in service and structural assurance. YuEbao is selected as the subject as it is a representative example of FinTech services in China.

A survey questionnaire was deployed and a ten-point sliding scale with two-decimal points was applied to improve the accuracy of the questionnaire. Partial least squares structural equation modeling was used to analyze the data.

Trust in service and structural assurance can encourage continuance intention of FinTech service. System quality, situational normality and subjective norm can boost the development of trust in service. Both herding and subjective norm can affect structural assurance significantly.

The study highlights the important roles played by technical factors (i.e. situational normality and system quality) and social factors (i.e. herding and subjective norm) in developing the two levels of trust (i.e. trust in service and structural assurance). It also validates the influences of trust in service and structural assurance on encouraging customers’ continuance intention in the novel context of FinTech.

The findings of this study can be used by practitioners to encourage customers to continue using their FinTech services. To encourage continuance, service providers can improve the quality of their system, design the system to be aligned with customers’ using habits and show customers that their close friends are also using the service.

This study adds to the existing body of trust literature by investigating the direct effects of trust in service and structure assurance on continuance intention and how these two levels of trust are developed from technical and social aspects. It generates interesting insights into customers’ continuance behavior of FinTech services.

Retaining customers is very important for the survival of e-commerce sellers. The purpose of this paper is to investigate the roles of computer-mediated communication (CMC) tools, interactivity, trust and perceived effectiveness of e-commerce institutional mechanisms (PEEIM) in influencing customer’s repurchase intention in the Chinese online e-commerce marketplace.

The research model is empirically tested using survey data analyzed with partial least squares structural equation modeling.

This study confirms the positive relation between customer satisfaction and trust in the seller, which further contributes to repurchase intention. Results also support the positive influences of effective use of an instant messenger and feedback system on customer perceived interactivity, which helps enhance trust in the seller. PEEIM demonstrates interesting results regarding its moderating effects.

In the future, researchers can extend the study to other e-commerce platforms and take trust transfer effects and product categories into consideration.

This study highlights the importance to manage trust, PEEIM, interactivity and CMC tools in e-commerce platforms, assisting practitioners to develop appropriate business strategies and processes to retain customers.

This study extends previous investigations by integrating trust and PEEIM with interactivity and testing the model in the context of the Chinese online marketplace.

This paper aims to present a longitudinal and visualizing study using scientometric approaches to depict the historical changes in the academic community, intellectual base and research hotspots within the business domain.

Two mapping methods are used, namely, co-citation analysis and co-occurrence analysis. Both the co-citation analysis and co-occurrence analysis in this study are conducted using CiteSpace, a Java-based scientific visualization software.

This paper detects changes in academic communities in 24 business journals chosen by the University of Texas at Dallas as leading journals (UTD24) and identifies the research hotspots such as corporate governance, organizational research and capital research. Many authors and academic communities appear in two or even three periods, which indicates the lasting academic vitality of scholars in this field. This paper determines the evolution of scholars' research interests by identifying high-frequency keywords during the entire period.

This paper reveals a systematic and holistic picture of the developmental landscape of the business domain, which can provide a potential guide for future research. Furthermore, based on empirical data and knowledge visualization, the intellectual structure and evolution of the business domain can be identified more objectively.

This paper aims to present a longitudinal and visualising study using bibliometric approaches to depict the emerging trends and research hotspots within the mobile information system domain.

Publications included in the Web of Science (WoS) database for 2001–2021 are reviewed and analysed on various aspects through coauthorship, cocitation and co-occurrence analysis. The analyses are conducted using VOSViewer, a scientific visualisation software program.

Academic publications related to mobile information systems fluctuated at a low level during the initial part of the 21st century and have grown rapidly in number in the past decade. The USA and China are the leading contributors to these publications and hold dominant positions in the obtained collaboration network. Computer science, engineering and telecommunications are the top three research areas in which mainstream mobile information system research occurs. Moreover, medical informatics and health-care science services have gradually become new research hotspots.

This study provides a systematic and holistic account of the developmental landscape of the mobile information system domain. This study provides a good basis for analysing the evolution of research in mobile information systems and may serve as a potential foundation for future research.

The purpose of this paper is to focus on the operation strategy of high-performance alliance portfolios by analyzing the effect of alliance portfolios on the performance of focal firms, using post-structuralism of social network theory and contingency theory. In detail, this paper refines alliance portfolios into three dimensions, and studies the moderating role of context on the relation between alliance portfolios and firm performance.

The empirical study was carried out with second-hand data gathered from Internal Revenue Service. In total, this paper gathered data from 506 focal firms in Zhejiang Province from 2001 to 2010 as the sample to test the hypotheses.

Based on the empirical results, the authors find the positive effect of relational dimension (weak alliance portfolios) and partner dimension (the diversity of partners) on performance. The effect of the former will become weaker with the increasing environmental dynamic, while the effect of the latter will become stronger. However, the structural dimension (alliance portfolios size) and relational dimension (new partners) have the negative effect on performance. And the negative effect will become stronger under high environmental dynamic. Moreover, the negative effect of non-local partners on performance becomes stronger when the environmental dynamic is high.

The paper reveals that with the industry transformation caused by “internet +,” companies have been required go beyond traditional dyadic alliance management perspective. That is to say, individual alliance relationship should be seen as a part of a much broader picture of alliance portfolio. As such, the framework may help companies to manage their alliance portfolios by matching high-performance alliance portfolios to the external environment to produce a synergistic effect (Lea et al., 2006; Tritos et al., 2013; Keith et al., 2014) taking the characteristics of the configuration of alliance portfolios into consideration.

The paper presents a model that explains the effect of three dimensions of alliance portfolios on the performance of focal firms in different contexts through empirical study. This paper also integrates post-structuralism of social network theory and contingency theory to enable the understanding on the configuration of alliance portfolios.

Rapid prototyping (RP) technology is widely used in many fields in recent years. Bone tissue engineering (TE) is an interdisciplinary field involving life sciences, engineering and materials science. Hydroxyapatite (HAp) are similar to natural bone and it has been extensively studied due to its excellent biocompatibility and osteoconductivity. This paper aims to review nanoscaled HAp-based scaffolds with high porosity fabricated by various RP methods for bone regeneration.

The review focused on the fabrication methods of HAp composite scaffolds through RP techniques. The paper summarized the evaluation of these scaffolds on the basis of their biocompatibility and biodegradability through in vitro and in vivo tests. Finally, a summary and perspectives on this active area of research are provided.

HAp composite scaffold fabricated by RP methods has been widely used in bone TE and it has been deeply studied by researchers during the past two decades. However, its brittleness and difficulty in processing have largely limited its wide application in TE. Therefore, the formability of HAp combined with biocompatible organic materials and fabrication techniques could be effectively enhanced, and it can be used in bone TE applications finally.

This review paper presented a comprehensive study of the various types of HAp composite scaffold fabricated by RP technologies and introduced their potential application in bone TE, as well as future roadmap and perspective.

The massive number of pavements and buildings coupled with the limited inspection resources, both monetary and human, to detect distresses and recommend maintenance actions lead to rapid deterioration, decreased service life, lower level of service and increased community disruption. Therefore, this paper aims at providing a state-of-the-art review of the literature with respect to deep learning techniques for detecting distress in both pavements and buildings; research advancements per asset/structure type; and future recommendations in deep learning applications for distress detection.

A critical analysis was conducted on 181 papers of deep learning-based cracks detection. A structured analysis was adopted so that major articles were analyzed according to their focus of study, used methods, findings and limitations.

The utilization of deep learning to detect pavement cracks is advanced compared to assess and evaluate the structural health of buildings. There is a need for studies that compare different convolutional neural network models to foster the development of an integrated solution that considers the data collection method. Further research is required to examine the setup, implementation and running costs, frequency of capturing data and deep learning tool. In conclusion, the future of applying deep learning algorithms in lieu of manual inspection for detecting distresses has shown promising results.

The availability of previous research and the required improvements in the proposed computational tools and models (e.g. artificial intelligence, deep learning, etc.) are triggering researchers and practitioners to enhance the distresses’ inspection process and make better use of their limited resources.

A critical and structured analysis of deep learning-based crack detection for pavement and buildings is conducted for the first time to enable novice researchers to highlight the knowledge gap in each article, as well as building a knowledge base from the findings of other research to support developing future workable solutions.