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As less is known about how internal communication can influence employees’ whistleblowing intention, this study aims to explore how participatory communication, organizational listening and organizational responsiveness influence employees’ external whistleblowing intention.

An online survey was conducted with 657 employees across various industries in the United States.

The results revealed that participatory communication, organizational listening and organizational responsiveness can fulfill the organization’s relational contract with their employees. As a communication-charged outcome, the fulfillment of employees’ relational psychological contract is associated with a lower intention to blow the whistle externally.

This study is among the first to examine internal communication strategies, namely, participatory communication, organizational listening and organizational responsiveness, as the antecedents of employees’ relational psychological contract and external whistleblowing intention.

The success of public–private partnership (PPP) projects is highly correlated to the successful management of risks encountered during the operation phase. PPP projects are especially exposed to risk due to the long operation period over which revenues need to be generated to recoup substantial initial investment and operational running costs. Despite the critical impact of risk exposure, limited research has been specifically undertaken on the matter of operational risk management. This study seeks to address this oversight by identifying and evaluating operational risk management strategies for PPPs.

Vulnerability theory is the theoretical lens used, with context drawn from Chinese PPP projects. Based on the data collected from expert interviews and questionnaires, 28 operational risk management strategies are identified. A fuzzy synthetic method is employed to analyze the effectiveness of the 28 strategies.

The findings reveal that providing an exit mechanism clause into the contract, establishing a comprehensive performance evaluation mechanism and developing a clear compensation mechanism are the top three effective strategies. This study also reveals that risk mitigation approaches that reduce vulnerability prove more effective than attempts to reduce external threats. Specifically, strategies aimed at managing contract, political, technical and financial risk are the most effective.

The findings of this study extend current knowledge regarding the risk management of PPP projects. They also offer a reference by which practitioners may select effective operational risk management pathways and thereby, galvanize the sustainable development of PPPs.

This article aims to develop and validate a theoretical model via survey data to identify the affordances and challenges influencing metaverse adoption. We specifically examine the impact of immersion on users' adoption decisions and identify which affordances predict this immersion. Additionally, this paper assesses the importance of perceived risks in users' decision-making processes regarding future metaverse engagement.

Using regression models applied to 198 survey responses, we tested our proposed model. To deepen our insights, we also conducted a qualitative analysis.

The findings confirm that users' perceptions of immersion and perceived risks are critical determinants in adoption decisions. Social presence, influenced by factors such as ubiquity and interoperability, emerges as a key component of immersion. From the qualitative data, we identified two potential strategies to enhance metaverse immersion: technical improvements and offline device-assisted strategies.

Our study contributes to the literature on information systems (IS) adoption and provides practical insights for practitioners on crucial considerations in metaverse design.

The COVID-19 pandemic and the corresponding control measures have harmed the mental health of professionals working in the construction industry. Existing research has also indicated that demographic characteristics are leading variables causing differences in individual’s perceptions on mental health and psychosocial hazardous factors. Combining these, this research aims to compare the differences and similarities of the perceived mental health outcomes and psychosocial hazards among construction professionals with different demographic characteristics during the pandemic.

Using a questionnaire survey, data were collected from 531 construction professionals working in Chinese construction companies, which were analyzed quantitatively using mean score comparative analysis, Mann–Whitney U test and Kruskal–Wallis H test, as well as Spearman’s correlation analysis.

The results indicate that construction professionals with different ages, years of working experience and positions are exposed to different psychosocial hazards, resulting in different mental health conditions during the pandemic. Age and years of working experience are also strong predictors of the level of depression and anxiety experienced by construction professionals; that is, mental ill health tends to decrease with the increase of age and experience. Male department/unit heads, working in a company office environment for a private company and aged 31–40 years old with 11–20 years of working experience, tend to have the best mental health condition. In contrast, psychosocial hazards are more likely to produce the most serious impact on male site-based construction professionals working for a state-owned company, either with less than one year of working experience or in a senior management position.

Despite the significant contribution of the construction industry to the global economy, the differences and similarities of the mental health outcomes and psychosocial hazards among construction professionals with different demographic characteristics during the pandemic remain unknown. This research, therefore, reveals the mental health outcomes and psychosocial hazard impacts among different types of construction professionals during the pandemic. Specifically, this research unveils the important personal characteristics which are closely associated with poor mental health and the stronger impacts of psychosocial hazards on the mental health of construction professionals during the pandemic. The results are valuable for governments and construction companies to formulate targeted mental health intervention strategies during future public health emergencies.

Market evaluation of products is the basis for product innovation, yet traditional expert-based evaluation methods are highly dependent on the specialization of experts. There exist a lot of weak expert-generated texts on the Internet of their own subjective evaluations of products. Analyzing these texts can indirectly extract the opinions of weak experts and transform them into decision-support information that assists product designers in understanding the market.

In social networks, a subset of users, termed “weak experts”, possess specialized knowledge and frequently share their product experiences online. This study introduces a comparative opinion mining framework that leverages the insights of “weak experts” to analyze user opinions.

An automotive product case study demonstrates that evaluations based on weak expert insights offer managerial insights with a 99.4% improvement in timeliness over traditional expert analyses. Furthermore, in the few-shot sentiment analysis module, with only 10% of the sample, the precision loss is just 1.59%. In addition, the quantitative module of specialization weighting balances low-specialization expert opinions and boosts the weight of high-specialization weak expert views. This new framework offers a valuable tool for companies in product innovation and market strategy development.

This study introduces a novel approach to opinion mining by focusing on the underutilized insights of weak experts. It combines few-shot sentiment analysis with specialization weighting and AHP, offering a comprehensive and efficient tool for product evaluation and market analysis.

This study aims to explore the impact of mobile learning on educating Iranian adult neo-literates within courses held by Iranian Literacy Movement Organization.

A concurrent mixed-methods design was used to investigate to what extent the adult neo-literates in Shiraz, Iran, were ready to use mobile phones in their courses. The qualitative section involved merging and summarizing basic themes into organizing themes. The themes were then integrated to create a single global theme.

The results showed that the participants were ready to embrace m-learning. Instrumentality was the most influential factor contributing to neo-literates’ readiness for m-learning. Findings also showed that from learners’ standpoint, mobile phones presented some unique features, enabling them to integrate elements from both distance and face-to-face courses. They also believed that mobile phones or other information and communications technology gadgets provided better opportunities for learning, although they fall short of fully replacing human instructors.

The limitations of the study were the participants’ limited familiarity with the research procedure and the impossibility of holding joint gatherings at specific locations.

This applied study helps the literacy movement to take strong steps toward creating an educational environment that guarantees learning anytime and anywhere for its learners.

This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?

This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.

The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.

This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.

The construction industry is experiencing digital transformation, which is also defined as intelligent construction. With the rise of intelligent construction, job characteristics are changing rapidly. Current knowledge about job competencies required by intelligent construction is lacking. Therefore, the aim of this paper is to explore job competencies related to intelligent construction by text mining recruitment information. It is expected to reveal the trend of talent development for the intelligent construction industry.

A total of 375 job advertisements regarding the demanding professionals and industrial workers related to intelligent construction were collected and analyzed to reveal the demands of the current labor market. Different job posts related to intelligent construction were classified into 11 categories. Job competencies were extracted and analyzed using the latent Dirichlet allocation (LDA) model, frequency–inverse document frequency (TF-IDF) algorithm and k-means cluster analysis method. The text mining results identified 10 job competencies.

Currently, there was a high demand for high-tech talents in the labor market related to intelligent construction. Those high-tech job posts, such as software engineers and R&D staff, required digital technology, R&D skills, electrical automation knowledge and programming capability. Current employees demanding for intelligent construction are expected to be capable of both using information technology and having a general knowledge of the construction industry.

Through text mining of current job advertisements, the overall demand for compound talents in the labor market of intelligent construction were explored. The results provide empirical reference for personnel training and talent cultivation in the development of intelligent construction. Higher educational institutions, human resources professionals, as well as experts that are already employed or aspire to be employed in intelligent construction companies, would benefit from the results of our analysis.

Rhetorical figures are frequently used in English-Chinese advertisement translation, but their impact on consumers is an under-studied issue. This research aims to explore Chinese consumers’ perception of two categories of rhetorical figures in bilingual advertising, namely schemes and tropes, via an eye-tracking experiment.

It takes rhyme and antithesis as representative examples of schemes and takes metaphor as an example of tropes. Eighty-six native Chinese speakers with satisfactory English proficiency participated in the experiment. Thirty English slogans without rhetorical figures were selected for the experiment. Two parallel Chinese versions were prepared, one with rhetorical figures and the other without. Participants were randomly assigned to read the English version and one Chinese version.

Data analyses show that the translations with rhetorical figures generally involve higher fixation duration or count, smaller saccade amplitude and higher subjective ratings. In particular, the impact of metaphor is more prominent than that of rhymes and antitheses. Still, English texts receive higher ratings than Chinese translations except for cases where metaphors are used in translations.

The results suggest that incorporating rhetorical figures particularly tropes into Chinese translations is effective in increasing Chinese consumers’ attention and processing depth and to present English advertisements together with Chinese translations can be helpful for affecting their attitude.

It applies the eye-tracking approach to explore Chinese consumers’ perception of rhetorical figures. It provides empirical evidence for the effectiveness of tropes.

The motivation of value co-creation among the multi-actor in sharing economy was an important topic in interactive marketing communication research. This study investigated how customer gratitude expression leads to value co-creation of PSPs in the sharing economy, and also investigates the moderating effect of platform benevolent climate.

A three-wave field survey (Study 1) and two experiments (Studies 2 and 3) were given to respondents with sharing economy practitioners.

First, customer gratitude expression positively influenced PSP's perceived meaningful work, which in turn enhanced their value co-creation intention. Second, PSP's perceived platform benevolent climate moderated the relationship between customer gratitude expression and PSP's perceived meaningful work.

Prior research discussed PSPs' value co-creation intention mainly from the perspective of platforms and PSPs, but few considered customer-PSP interaction perspective. This study revealed how customer gratitude expression influences PSP's value co-creation intention in highly interactive digital business context, examined the boundary condition of gratitude expression, and extended the application scenarios of social information processing theory.