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Virtual reality (VR) offers unprecedented immersion and interactivity in education, and working and learning from home have become the norm during the COVID-19 pandemic. This study empirically investigated the factors affecting the use of a VR online learning system (VROLS).

To explore factors affecting users’ continuance behavioral intentions toward using VROLSs, a research framework was formed comprising factors that constitute benefits (i.e. pull factors) and costs (i.e. push factors); these factors included perceived value, flow and social influence. The data for this study were collected via online survey questionnaires. A total of 307 valid responses were used to examine the hypotheses in the research model, employing structural equation modeling (SEM) techniques.

Perceived value, flow experience and the number of peers using VR primarily affect the decision to adopt a VROLS. The pull factors of spatial presence, entertainment and service compatibility, along with the push factors of complexity and visual fatigue, affect perceived value. Therefore, we conclude that perceived value is a primary factor positively influencing both flow experience and the decision to adopt the service.

This study contributes to a theoretical understanding of factors that explain users’ intention to use VROLSs.

This paper aims to analyse how both Lin’s birthplace identity and his Christian identity contributed to his fruitful public career and to ascertain which identity became the most significant.

Archival research is the main method used in this paper. The most important archives drawn from are the Daniel Tse Collection in the Special Collection and Archives of the Hong Kong Baptist University Library. Oral history has also been used in this paper to uncover more material that has not yet been discussed in existing scholarly works.

This paper argues that although Lin’s birthplace identity and social networks helped him to start his business career in Nam Pak Hong and develop into a leader in the local Chaozhou communities, these factors were insufficient to his becoming a respectable member of the Chinese elite in post-war Hong Kong. He became well known not because of his leading position in local Chaozhou communities or any great achievement he had obtained in business but because of his contribution to the development of Christian education. These achievements earned him a reputation as a “Christian educator”. Thus Lin’s Christian identity became more important than his birthplace identity in contributing to his successful public career.

This paper has value in showing how Christian influences interacted with various cultural factors in early Hong Kong. It also offers insights into Lin’s life and motivations as well as the history of the institutions he contributed to/founded. It not only furthers our understanding of the Chinese Christian business elite in early Hong Kong but also provides us with insights when further studying this group of people in other British colonies in Asia.

The purpose of this study is to propose an integrated model based on expectation–confirmation model (ECM), flow theory and human–organization–technology fit framework to examine whether human, organizational and technology factors as antecedents to medical professionals' beliefs can affect their continuance intention of the cloud-based e-learning system.

Sample data for this study were collected from medical professionals at five hospitals in Taiwan. A total of 500 questionnaires were distributed, and 368 (73.6%) useable questionnaires were analyzed using structural equation modeling in this study.

Synthetically speaking, human, organizational and technology factors, as antecedents to medical professionals' continuance intention of the cloud-based e-learning system have been examined, and the results strongly support the research model with all hypothesized links being significant.

Particularly, it is worth mentioning that the application of capturing both ECM and flow theory for completely explaining three types of factors (i.e. human, organizational and technology factors) as external variables to medical professionals' cloud-based e-learning continuance intention is well documented, that is, information systems (IS) and nonIS determinants are simultaneously evaluated, and extrinsic and intrinsic motivators are both taken into consideration in this study's theoretical development of medical professionals' cloud-based e-learning continuance intention to acquire a more comprehensive and robust analysis.

According to expectation–confirmation model (ECM) and task-technology fit (TTF) model, the purpose of this paper is to examine the role of TTF in students’ cloud-based e-learning continuance and evaluate whether TTF affects students’ perceived impact on learning of the cloud-based e-learning system within the educational institution.

Sample data for this study were collected from students enrolled in a comprehensive university in Taiwan. A total of 500 questionnaires were distributed in the campus, and 391 (78.2 percent) usable questionnaires were analyzed using structural equation modeling in this study.

This study’s results verified that both task characteristics and technology characteristics affected students’ perceived TTF, which significantly contributed to their perceived usefulness, confirmation and satisfaction with the cloud-based e-learning system, and these in turn directly or indirectly led to their continuance intention of the system and perceived impact on learning; essentially, the results strongly supported the research model integrating ECM and TTF model via positioning key constructs as the drivers with all hypothesized links being significant.

This study contributes to an understanding of the TTF in explaining students’ cloud-based e-learning continuance that is difficult to explain with only their utilitarian perception of the cloud-based e-learning system, and further places considerably more emphasis upon students’ perceived impact on learning greatly driven by their TTF in the system. Thus, this study’s empirical evidence on incorporating ECM and TTF model can shed light on the outcome for cloud-based e-learning continuance and enhance better understanding of a richer post-adoption model.

The purpose of this paper is to observe consumers’ attitudes toward and intentions to purchase green products on social media and to explore the relationships among social media marketing, perceived consumer effectiveness (PCE), product knowledge, subjective norms, perceived behavioral control, price consciousness and attitudes toward and intentions to purchase green products. In addition, this research attempts to further understand these relationships in different consumer groups.

A questionnaire survey method was used to collect data from consumers in China. The Amos 22.0 software package was used to conduct the data analysis.

The empirical results suggest that attitude, subjective norms and perceived behavioral control positively affect purchase intentions, while price consciousness negatively affects purchase intentions. Product knowledge positively affects consumers’ attitudes and purchase intentions, and PCE positively affects consumers’ attitudes. As expected, social media marketing positively affects subjective norms, product knowledge and PCE and negatively affects price consciousness. However, there is no significant relationship between PCE and purchase intentions. According to the results of multigroup structural equation modeling analysis, the effects differ significantly among different consumer groups.

This study enriches the research about the factors that influence consumers’ purchases of green products in emerging countries in the social media marketing context.

The purpose of this paper is to examine the roles of task-technology fit (TTF), learning-technology fit (LTF) and cognitive absorption (CA) in determining medical professionals’ cloud-based electronic learning (e-learning) system continuance intention and performance outcomes and evaluate whether medical professionals’ perceived impact on learning can affect their perceived impact on tasks within medical institutions.

Sample data for this study were collected from medical professionals at six hospitals in Taiwan. A total of 600 questionnaires were distributed, and 373 (62.2%) usable questionnaires were analyzed using structural equation modeling in this study.

In this study, medical professionals’ perceived TTF and LTF as antecedents to their cloud-based e-learning continuance intention and performance outcomes were validated, and medical professionals’ perceived impact on learning had a positive effect on their perceived impact on tasks. Synthetically speaking, this study’s results strongly support the research model with all hypothesized links being significant.

It is particularly worth mentioning that this study introduces a new construct, “LTF,” to conceptualize, define and measure it, and further contributes to the application of capturing both expectation–confirmation model and CA (i.e. an intrinsic motivator) for completely explaining medical professionals’ perceived TTF and LTF as external variables to their cloud-based e-learning continuance intention and performance outcomes.

Contextual cues have become a hot research topic in the field of mobile consumer behavior, owing to the continuous rise of digital marketing. However, the complex online shopping scene makes it challenging to directly identify the association between the characteristics of contextual cues and consumer behavior. Presently, few studies have only systematically extracted and refined the types and characteristics of contextual cues. The purpose of this study is to explore the types and mechanisms of contextual cues in online shopping scenarios.

This study uses the word2vec algorithm, grounded theory and co-occurrence cluster method, along with online shopping word-of-mouth (WOM) text and consumer behavior theory, in order to explore different types of contextual cues and its efficiency from 5,619 comment corpus.

This study puts forward the following conclusions. (1) From the perspective of online shopping, contextual cues comprise aesthetic perception cues, value perception cues, trust-dependent cues, time perception cues, memory attention cues, spatial perception cues, attribute cues and relationship cues. (2) Based on the online shopping scenarios, contextual cues and their interaction effects exert an effect on consumer satisfaction, recommendation, purchase and return behavior.

The study conclusions are helpful to further reveal the deep association between contextual cues and consumer behavior in the process of online shopping, thus providing practical and theoretical enlightenment for enterprises to not only effectively reshape the scene but also promote the consumers' active purchase behavior.

Although crowdsourcing has gained significant attention and is being used by numerous companies to develop new products and solve practical issues, the performance of crowdsourcing is not optimistic. The purpose of this paper is to develop a validated risk profile of crowdsourcing and investigate the relationships among different types of risks and those between risks and performance in crowdsourcing.

Based on the quantitative data collected from 136 crowdsourcing participants in China, two dimensions (i.e. social system and technical system risks) and five sub-dimensions (i.e. crowdsourcer, relationship, crowdsourcee, complexity, and requirement) of crowdsourcing risks are developed and validated. A theoretical model that integrates crowdsourcing risks and performance is developed. The technique of partial least squares is employed to assess the measurement model and test the hypotheses.

The empirical evidence determines the positive association of social system risks with technical system risks, which in turn negatively affect crowdsourcing performance. Specifically, relationship risk is positively affected by crowdsourcer and crowdsourcee risks, and these risks positively affect requirement and complexity risks. However, requirement and complexity risks negatively affect crowdsourcing performance.

This study explores the interrelationship between various risks and the relationship between risk and performance in the context of crowdsourcing by integrating risk-based view with socio-technical theory. Systematic but different risk mitigation strategies should be designed in crowdsourcing to manage risks and enhance performance.

The purpose of this paper is to assess the influence mechanism of the word-of-mouth reputation of influencers.

This study explored word-of-mouth reputation from four characteristics of information source of influencers: credibility, professionalism, interactivity and attractiveness. The grounded theory was used to extract the characteristic indicators of influencers and used questionnaire surveys to obtain 218 valid samples. The fuzzy-set qualitative comparative analysis (fsQCA) was used for the configuration analysis.

The results revealed the following: (1) a causal asymmetric correlation exists between the driving mechanism of high word-of-mouth reputation and non-high word-of-mouth reputation; (2) influencers matching high word-of-mouth reputation comprises potential, developmental and almighty types, whereas live streaming influencer matching non-high word-of-mouth reputation comprises elementary and groping types; and (3) all factors must be combined to play a role, and neutral permutations of two solutions were found among the three overall solutions to attain high word-of-mouth reputation; (4) the combination of high user activity and high exposure is the core configuration that results in high word-of-mouth reputation.

This study provides recommendation for consumers, live streamers, brand and e-commerce platform on how to promote the sustainable and healthy development of influencer marketing.

This study focused on elucidating how the characteristics of information source affect the word-of-mouth reputation of influencers and have a reference value for the research on word-of-mouth reputation in the context of live commerce.