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AI-powered digital human avatar influencer (DHAI) is a digitally created character with a human-like appearance and noteworthy social media presence. They mimic human behavior through form, behavior and emotional realism. However, there have been varied viewpoints in the literature about the effect of DHAI realism on consumer response. Therefore, this study aims to examine the effect of form, behavioral and emotional realism on consumer engagement and parasocial relationships that further affect attachment toward DHAI and brand, with the moderating effect of content authenticity.

Using a cross-sectional design, 426 respondents in India were asked to visit the Instagram page of a specific DHAI identified through a pretest study. The authors used the Smart PLS 4.0 version to examine the hypotheses.

Accordingly, based on the social presence theory, the findings of the quantitative study indicated that DHAI’s form, behavioral and emotional realism positively influence customers’ engagement with DHAI, but only the behavior and emotional realism of DHAI positively affect the parasocial relationship. Further, perceived DHAI’s content authenticity moderates the effect of DHAI engagement and parasocial relationship on DHAI sentimental attachment.

This study provides novel and practical insights for developing DHAI by considering realism characteristics for enhanced customer engagement, parasocial relationship and attachment toward DHAI and brands.

This study aims to discover the impact of the interaction between learning performance (as behavioral realism) and realistic appearance (as form realism) of AI-powered software robots on user trust. The study also aims to reveal how and why the interaction happens, especially from the dual processing perspective of affective and cognitive human responses.

We adopted an experimental research methodology in a movie recommendation system environment where machine learning-based recommendations are widely used. We conducted a 3 × 2 factorial design experimentation based on the three levels of learning performance (low, mid and high) and two levels of realistic appearance (caricature avatar and digital human). We used ANCOVA and the PROCESS Macro to analyze our models.

Our results confirm that learning performance (intelligence) is a critical factor influencing user trust in software robots, and this intelligence–trust relationship is influenced by their realistic appearance. Our results further reveal that there are two significant intermediating mechanisms, i.e. affective and cognitive user responses, and that the intelligence–appearance interaction effect on trust is explained especially by the affective response mechanism.

This study provides valuable implications for creating optimal learning performance and realistic appearance that can lead to trust in various settings where AI-powered software robots are utilized.

This study has sveral contributions to the literature. First, in addition to the well-recognized factor of anthropomorphic characteristics, this study investigates another critical behavioral factor of AI-powered robots (learning performance as intelligence characteristics) and the intriguing interaction between the two realism factors. Second, drawing upon the mediated moderation perspective, the study proposes a novice perspective on how and why the two realism factors can build user trust (the underlying mechanisms).

This paper aims to explore customers’ pro-environmental behaviors (PEBs) adopted at hotels that implement green practices. A method to examine the gap between self-reported and actual PEBs is presented.

The empirical study is divided in two parts. The first one comprised a survey questionnaire administered to 136 customers who stayed in Portuguese hotels (Sample 1). The second one consisted of 495 in-room consumer PEBs observations (Sample 2). A method was developed to compare self-reported and actual PEBs, combining the answers given to the questionnaire and the observed PEBs implemented by customers during their stay. The aggregate observations of in-room consumer’s PEBs enabled the development of an index to assess the actual PEBs (ACTUALPEBI). This index was then compared with the self-reported PEB index (REPORTEDPEBI).

The majority of guests indicated adopting environmentally friendly practices while at the hotel, and 50% of REPORTEDPEBI rank similarly to ACTUALPEBI.

Understanding and measuring both actual and reported PEBs of guests offers valuable insights for hotel managers and marketers. This information can be used to target specific consumer segments with green marketing campaigns and develop educational programs that effectively encourage guest participation in hotel sustainability efforts. While the survey participants were international, the research itself was limited to hotels in Portugal. Therefore, future research should involve more participants and be conducted across different countries.

Understanding and measuring both actual and reported PEBs of guests offers valuable insights for hotel managers and marketers. This information can be used to target specific consumer segments with green marketing campaigns and develop educational programs that effectively encourage guest participation in hotel sustainability efforts.

This study proposes an alternative method for analyzing customers’ PEBs by observing actual PEBs during their stay and comparing them to self-reported PEBs, thereby reducing answer biases.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This paper aims to identify and report the differential effects of activity control and capability control on role stressors, which subsequently affect salespeople’s job satisfaction and sales performance.

Drawing on job demands-resources (JD-R) theory, the authors defined active control and customer demandingness as the job demands and capability control as the job resource, and designed their relationship with role stressors, which are indicated as role ambiguity, role conflict and role overload. The authors enrolled a sample of 223 industrial salespeople from pharmaceutical companies. After collecting the data, the authors used structural equation modeling using AMOS to test and estimate causal relationships along with a two-step approach to examine the interaction effect. The authors have also tested the simple slope of two-way interactions. All of the measured variables were identical to those used in previous studies.

The study findings indicate that behavior-based control can be counterproductive. Reducing activity control can decrease role stress, increase job satisfaction and improve job performance; increasing capability control, however, can reduce role stress and increase job satisfaction and performance. It is also important to acknowledge the external environment of the sales context in which behavior-based control is most effective: whereas high customer demandingness and capability control are related to reduced role stress, high customer demandingness and activity control are related to increased role stress.

Sales managers should recognize that different control management regimes reinforce or mitigate salespeople’s job stressors and outcomes under specific conditions (i.e. work environments marked by higher or lower customer demandingness).

Drawing on JD-R theory, the research shows that a behavior control (i.e. activity control and capability control) has differential, and even opposite, psychological consequences.

Drawing on the attribution theory, this study re-examined the effect of supervisor-subordinate guanxi (SSG) on counterproductive work behaviors (CWBs) by highlighting the critical moderating role of job self-efficacy and the mediating role of psychological entitlement, with the aim of revealing the potential drawbacks of SSG.

Three-wave matched data were collected from 434 employees working in China. The authors adopted path analysis in Mplus 7.4 to test the hypotheses proposed in this study.

The results suggested that among subordinates with high job self-efficacy, SSG triggers psychological entitlement, which subsequently leads to CWBs.

This research challenges the prevailing consensus regarding the beneficial effects of SSG on subordinate management from the social exchange theory perspective by revealing when and why high-quality SSG can also engender subordinates’ psychological entitlement and subsequent CWBs. By doing so, this study provides a more dialectical view of the impact of establishing high-quality SSG in human resource management.

Virtual idols have entered the golden period as the main form of future digital people. However, existing studies only focus on a single idol type and partial role relationships related to virtual idols, lacking synthesized insights. To address these gaps, this paper summarizes different types of virtual idols and all role relationships to achieve a comprehensive literature review.

Based on the business ecosystem theory, this paper constructs a business role ecosystem framework for virtual idols from the two subsystems of value co-creation and value realization.

Firstly, we extract common characteristics and the generalized definition applicable to diverse idol types. Secondly, we find that there are commonalities and differences in the significant characteristics of virtual idols in different application fields. Thirdly, literature in the value co-creation subsystem mainly focuses on co-creation mechanisms in the role relationship between idols and demanders (RRID). A few focus on virtual idols’ constructions in the role relationship between producers and idols (RRPI) and co-creation phenomena in the role relationship between demanders and producers (RRDP). Finally, literature in the value realization subsystem mainly focuses on consumer attitudes and realization mechanisms in RRID. A few focus on realization phenomena in the role relationship between producers and tripartite enterprises (RRPT) and RRPI.

This paper points out future implementing directions of industry practitioners, gives strategies to promote economic value realizations and emphasizes the importance of cultural communication.

This paper discusses the existing theoretical gaps and possible future research directions regarding characteristics, applications and role relationships.

Chatbots have been explored as a novel approach to enhancing consumer engagement by delivering more enjoyable, personalized services. This research aims to investigate the mechanism through which anthropomorphic elements of chatbots influence consumers' intentions to use the technology.

This research introduces five key concepts framed through the “computers-are-social-actors” (CASA) paradigm: form realism (FR), behavioral realism (BR), cognitive trust (CT), entertainment (EM) and chatbot usage intention (CUI). An online questionnaire garnered 280 responses from China and 207 responses from Indonesia. Data collection employed a combination of purposive and snowball sampling techniques. This research utilized structural equation modeling through the analysis of moment structures (AMOS) 27 software to test the hypotheses.

(1) FR positively predicts CT and EM, (2) FR negatively predicts CUI, (3) BR positively predicts CT and EM, (4) BR positively predicts CUI and (5) Both CT and EM mediate the relationship between FR and CUI, as well as between BR and CUI.

This research enriches the current literature on interactive marketing by exploring how the anthropomorphic features of chatbots enhance consumers' intentions to use such technology. It pioneers the exploration of CT and EM as mediating factors in the relationship between chatbot anthropomorphism and consumer behavioral intention. Moreover, this research makes a methodological contribution by developing and validating new measurement scales for measuring chatbot anthropomorphic elements.

The purpose of this study is to comprehensively evaluate the impact of the prefabrication rate on greenhouse gas (GHG) emissions and sustainability in prefabricated construction. In addition, it aims to identify the optimal prefabrication rate threshold that can promote the transformation of the construction industry toward more environmentally friendly practices.

This study uses an interdisciplinary methodology that combines emergy analysis with an extended input-output model to develop a GHG emission accounting model tailored for prefabricated buildings. The model assesses various construction schemes based on different rates of prefabrication and uses the emergy phase diagram from ecological economics to quantify the sustainability of these schemes.

This study indicates that within a prefabrication rate threshold of 61.27%–71.08%, a 5% increase in the prefabrication rate can significantly reduce emissions by approximately 36,800 kg CO₂(e). However, emissions begin to rise when the prefabrication rate exceeds this threshold. The case analysis identifies steel, concrete and electricity as the primary sources of GHG emissions, suggesting strategies for optimizing their usage and promoting the adoption of clean energy.

This study represents a novel tool for assessing the environmental impact and sustainability of prefabricated buildings. It offers scientific guidance for the construction industry’s environmental protection and sustainable development strategies, thereby contributing to a transition toward more environmentally friendly practices.

The application of galvanized steel is widespread across industries due to its protective zinc coating that protects against atmospheric corrosion. However, previous studies have primarily focused on long-term corrosion rates rather than the full-scale corrosion behavior of the zinc. This paper aims to study the full-scale corrosion evolution of galvanic steel under simulated marine atmospheric environment using real-time EIS measurement.

Electrochemical impedance spectroscopy (EIS) provides an advanced method in monitoring such behavior. Therefore, the EIS method has been used to conduct a comprehensive investigation on the corrosion behavior of galvanic steel in a full-time manner.

The results indicate that the corrosion process of galvanic steel can be divided into three stages: an initial stage with an increased corrosion rate, a subsequent stage with a reduced corrosion rate, and finally a third stage with the lowest and constant corrosion rate. The evolution of corrosion resistance is closely related to changes in composition and structure of the patina layer. In the initial stage, galvanized steel undergoes the formation of soluble ZnCl₂ and needle-like Zn₅(OH)₈Cl₂·H₂O, which promotes the generation and maintenance of an electrolyte layer, consequently leading to an increase in corrosion rate. With prolonged corrosion time, there is a continuous accumulation of Zn₅(OH)₈Cl₂·H₂O within the patina layer, which reduces the content of soluble components and promotes the development of a denser inner layer, thus enhancing corrosion resistance.

This work holds significance in the monitoring of corrosion, understanding the evolution of corrosion and predicting the lifespan of galvanized steel.