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Despite widespread use of virtual streamers, academic research on this subject remains limited. This study aims to explore the mechanisms by which consumer perceptions of virtual streamers influence consumer purchase intentions.

We used partial least squares structural equation modeling to analyze validated online survey data from 414 consumers watching virtual streamers.

Consumer perceptions of virtual streamers (perceived competence, perceived interaction quality and perceived warmth) promote the establishment of transactional psychological contract and relational psychological contract between consumers and virtual streamers, which further affects consumers’ purchase intention.

This study enriches the research on virtual streamers, facilitates their adoption and introduces the psychological contract into a new research context by revealing the formation of the psychological contract from the perspective of virtual streamers. Moreover, this study provides a new understanding of the relationship between disembodied artificial intelligence and consumers.

Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.

This study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.

Results show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.

This study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.

This study aims to identify a value co-creation framework for live streaming through tourism scenes (LStTS). It also clarifies the value attributes of LStTS and makes an empirical test.

The study used a mixed-method approach. In Study 1, a total of 12,216 pieces of viewers’ comments and ten web news reports were coded and analyzed employing a grounded theory approach. In Study 2, data were collected from 587 Douyin e-commerce users. Exploratory factor analysis and partial least squares structural equation modeling were used to test the value co-creation framework of LStTS.

In Study 1, six value attributes in three categories were identified based on a content analysis of viewers’ comments. In Study 2, a three-order factorial model of value co-creation in LStTS was identified and tested.

Our study is limited by the preponderance of female respondents in the sample and the unique nature of the research context.

Merchants and streamers should consider whether there is a fit between the merchandise and the tourism scene when selecting the tourism scene for live streaming marketing; they can select novel and beautiful natural tourism scenes to attract viewers. Detailed and comprehensive product information should be provided in the process of live streaming marketing and sharing with consumers.

The novelty of our study lies in the provision of a new value co-creation framework in LStTS, which offers a theoretical basis for analyzing the value of the tourism scene in live streaming marketing.

This study investigates how perceived political corruption, a generally overlooked corruption type, relates to firms' new product development (NPD) through perceived regulatory obstacles. It also examines firms' perceptions of business association support in this relationship, considering these associations' potential support for NPD.

This study conducted an empirical analysis of 1,663 firms in Turkey, a country noted for a history of legislative corruption, and in which there are strong business associations. Drawing the data from the World Bank's 2019 Enterprise Surveys Dataset, this study tested the hypotheses via the two-stage factor score regression method.

This study finds that perceived political corruption significantly relates to NPD negatively through perceived regulatory obstacles. It also finds that the perceived support of business associations to NPD is significantly greater when firms perceive regulatory obstacles but only slight political corruption.

As far as political corruption is concerned, this study reveals that corruption can also be the cause of regulatory obstacles, expanding the common view of corruption as a means of overcoming regulatory obstacles to NPD. In addition, it introduces the role of business associations in this relationship by revealing their support to NPD for different levels of perceived political corruption and regulatory obstacles.

This study aims to comprehensively examine the transitions in household livelihood strategies within rural China, including the underlying processes, drivers and outcomes.

This study uses two waves (2010 and 2018) of longitudinal data from the China Family Panel Studies (CFPS), employing latent cluster analysis, regression models and cumulative distribution function within a dynamic household livelihood strategy framework.

The results show that (1) households’ livelihood strategies can be categorized into four distinct types, i.e. agricultural dominated, agricultural dominated with non-agricultural supplementation, non-agricultural dominated with agricultural supplementation and employment oriented. (2) During 2010–2018, approximately 60% of households underwent transitions in their livelihoods, encompassing both upward and downward trajectories, with a prevalence of upward transitions. (3) Various forms of livelihood capital significantly contribute to upward transitions, while the availability of land resources and exposure to shocks impede the potential for upward mobility. (4) The transition towards non-agricultural livelihood strategies by households leads to a notable enhancement in their livelihood welfare.

In the context of urbanization, industrialization and globalization, rural areas in China are undergoing a gradual socioeconomic transformation, which has also led to changes in rural households’ livelihood strategies. Nevertheless, a dearth of empirical investigation exists regarding the dynamics of rural households’ livelihood strategies, the determinants behind such transitions and the resulting outcomes on their livelihoods. A comprehensive understanding of livelihood transitions can provide valuable insights for policymakers in their endeavors to promote rural revitalization in China.

Based on the nationwide representative datasets in China, it examines the micro-level livelihood transitions of rural households within the broader context of socioeconomic transformation that presents both opportunities and challenges, as well as vulnerable contexts, shaped by various government policies. This exploration would offer valuable theoretical and empirical evidence to advance our understanding of the process, driver and outcome of rural households’ livelihood transition in developing countries.

The construction industry has embraced building information modelling (BIM) as a practical methodology towards digitalisation. However, critics believe BIM has reached a plateau in addressing distinctive construction challenges. As a result, literature has seen an increase in the development and use of BIM-based plugins. Overall, the plugins have been critical in delivering custom-built solutions to longstanding construction challenges. The purpose of this study is to empirically investigate this trend and the potential barriers undermining the wider development of BIM plugins, by that contributing to a stimulating research topic and a growing knowledge gap.

Methodologically, this study used a quantitative approach to collect data through a carefully designed questionnaire. This study achieved a sample size of 39 experts who have been involved in developing, experimenting and publishing BIM-based plugins for specific construction activities.

The findings led to the identification of the key barriers to using BIM-based plugins and the identification of the key strategies to overcome them across the three situational awareness (SA) phases. Results also suggest that the development and use of plugins are destined to increase, and the research community can now rely on the insights of this paper as a departure point to address the technological plateau in BIM-related research.

To the best of the authors’ knowledge, this is the first study to empirically identify and assess the barriers undermining the wider development of BIM-based plugins. This study contributes to theory by building on SA, by challenging existing wisdom and fostering new knowledge around strategies to overcome the evaluated barriers.

Surface quality and porosity significantly influence the structural and functional properties of the final product. This study aims to establish and explain the underlying relationships among processing parameters, top surface roughness and porosity level in additively manufactured 316L stainless steel.

A systematic variation of printing process parameters was conducted to print cubic samples based on laser power, speed and their combinations of energy density. Melt pool morphologies and dimensions, surface roughness quantified by arithmetic mean height (Sa) and porosity levels were characterized via optical confocal microscopy.

The study reveals that the laser power required to achieve optimal top surface quality increases with the volumetric energy density (VED) levels. A smooth top surface (Sa < 15 µm) or a rough surface with humps at high VEDs (VED > 133.3 J/mm³) can serve as indicators for fully dense bulk samples, while rough top surfaces resulting from melt pool discontinuity correlate with high porosity levels. Under insufficient VED, melt pool discontinuity dominates the top surface. At high VEDs, surface quality improves with increased power as mitigation of melt pool discontinuity, followed by the deterioration with hump formation.

This study reveals and summarizes the formation mechanism of dominant features on top surface features and offers a potential method to predict the porosity by observing the top surface features with consideration of processing conditions.

As artificial intelligence technology empowers service robots, they increasingly communicate with consumers in a human-like manner. This study aims to investigate the effect of service robots’ different conversational styles (competent conversational style vs. cute conversational style) on consumer service acceptance and demonstrate the moderating role of consumers’ technology anxiety.

Based on anthropomorphism theory and social presence theory, the authors conducted two scenario-based experiments (restaurant scenario and hotel scenario) to investigate this issue.

The results indicate that service robots’ conversational styles impact consumers’ willingness to accept the use of service robots through perceived social presence and positive emotion. Moreover, consumers perceived social presence and positive emotion play a serial mechanism. In addition, the effect of competent conversational style on consumers perceived social presence is less effective than that of cute conversational style. Finally, the authors demonstrate the moderating role of consumer technology anxiety in the relationship between conversational styles and perceived social presence.

To provide consumers with a positive human–robot interaction experience at the service front line, managers need to make better use of the conversational styles of service robots by comprehensively considering the characteristics of consumer technology anxiety.

This research extends the literature on service robots by integrating consumer characteristics and robots’ conversational styles. These findings highlight the effectiveness of cute conversational style in alleviating consumer technology anxiety.

Digitally driven virtual streamers are increasingly utilized in live-streaming commerce, possessing distinct advantages compared to human streamers. However, the applicable scenarios of virtual streamers are still unclear. Focusing on product attribute variances, this paper compares the livestreaming effects of virtual and human streamers to clarify the applicable scenarios for each and assist companies in strategically choosing suitable streamers.

We conducted four experiments utilizing both images and video as stimulus materials, and each experiment employed different products. To test the proposed model, a total of 1,068 valid participants were recruited, encompassing a diverse group of individuals, including undergraduates and employed workers.

The results indicate no significant difference between virtual and human streamers in increasing consumers’ purchase intention for utilitarian products. In contrast, human streamers are more effective in enhancing consumer purchase intention for hedonic products, with a mediating role of mental imagery quality. Consumers’ implicit personality variances also influence their willingness to accept virtual streamers.

This paper is the first to compare the effects of virtual and human streamers in promoting different products to enhance our comprehension of virtual streamers. Given the potential risks associated with human streamers, a comprehensive understanding of the role of virtual streamers is imperative for brands when deploying live-streaming commerce activities.

The present study aimed to explore the consequences of perceived authenticity in artificial intelligence (AI) assistants and develop a serial-mediation architecture specifying causation of loyalty in human–AI relationships. It intended to assess the predictive power of the developed model based on a training-holdout sample procedure. It further attempted to map and examine the predictors of loyalty, strengthening such relationship.

Partial least squares structural equation modeling (PLS-SEM) based on bootstrapping technique was employed to examine the higher-order effects pertaining to human–AI relational intricacies. The sample size of the study comprised of 412 AI assistant users belonging to millennial generation. PLS-Predict algorithm was used to assess the predictive power of the model, while importance-performance analysis was executed to assess the effectiveness of the predictor variables on a two-dimensional map.

A positive relationship was found between “Perceived Authenticity” and “Loyalty,” which was serially mediated by “Perceived-Quality” and “Animacy” in human–AI relational context. The construct “Loyalty” remained a significant predictor of “Emotional-Attachment” and “Word-of-Mouth.” The model possessed high predictive power. Mapping analysis delivered contradictory result, indicating “authenticity” as the most significant predictor of “loyalty,” but the least effective on performance dimension.

The findings of the study may assist marketers to understand the relevance of AI authenticity and examine the critical behavioral consequences underlying customer retention and extension strategies.

The study is pioneer to introduce a hybrid AI authenticity model and establish its predictive power in explaining the transactional and communal view of human reciprocation in human–AI relationship. It exclusively provided relative assessment of the predictors of loyalty on a two-dimensional map.