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The purpose of this paper is to analyze manufacturers' production decisions and governments' low-carbon policies in the context of influencer spillover effects.

This paper investigates the impact of the social influencer spillover effect on manufacturers' production decisions when they collaborate with intermediary platforms to sell products through marketplace or reseller modes. Game theory and static numerical comparison are used to analyze our models.

Firstly, under low-carbon policies, the spillover effect does not always benefit manufacturer profits and changes non-monotonically with an increasing spillover effect. Secondly, in cases where there are both a carbon emission constraint and a spillover effect present, if either the manufacturer or intermediary platform holds a strong position, then marketplace mode benefits manufacturer profits. Thirdly, regardless of business mode used when environmental damage coefficient is high for products; government should implement cap-and-trade regulation to optimize social welfare while reducing manufacturers’ carbon emissions.

This study offers theoretical and practical research support to assist manufacturers in optimizing production decisions for compliance with carbon emission limits, enhancing profits through the development of effective influencer marketing strategies, and providing strategies to mitigate carbon emissions and enhance social welfare while sustaining manufacturing activities.

This paper addresses the limitations of prior research by examining how the social influencer spillover effect influences manufacturers' business mode choices under government low-carbon policies and analyzing the social welfare of different carbon emission restrictions when such spillovers occur. Our findings provide valuable insights for manufacturers in selecting optimal marketing strategies and business modes and decision-makers in implementing effective regulations.

Cyberbullying is a globally pervasive problem and not novel in academia. Previous studies mainly focussed on the features, consequences and technological management of cyberbullying. However, most of the studies took cyberbullying examples in the West, and some issues still need to be addressed in the Chinese context. Thus, this study investigates how participants use cyberbullying words and why they use them in that particular way in China.

This study uses content analysis to summarise the typical features of cyberbullying words, revealing a positive relationship between cyberbullying words and sentimental expressions. This paper also uses the questionnaire (N = 705) to explore the prevalence of cyberbullying among Chinese Internet users and to compare the gender differences in the cognition of cyberbullying words and involvement in cyberbullying, in line with the social cognitive theory.

This study stated that people prefer repetitively using offensive words to achieve cyberbullying goals. Interestingly, this study does not find obvious gender differences in cyberbullying roles and cyberbullying language use. However, it explained the relationship between cognition and the use of cyberbullying words from a gender perspective.

Theoretically, this study expands cyberbullying studies into a new cultural environment, pointing to a novel term, “imbalanced relation,” for exploring cyberbullying behaviours. This study highlights the significance of technology and education in detecting and preventing cyberbullying, suggesting that educators and social media platforms can directly predict and prevent cyberbullying through textual perspectives and individuals' cognition of cyberbullying.

This study aims to examine cyberbullying linguistic and emotional features and individual differences in cyberbullying behaviour in a high-context culture like China. Its values include comparing the differences between cyberbullying in China and cyberbullying in the West from the linguistic and cultural directions and reconsidering the “power imbalance” feature of cyberbullying.

In an era marked by heightened geopolitical uncertainties, such as international conflicts and economic instability, the dynamics of energy markets assume paramount importance. Our study delves into this complex backdrop, focusing on the intricate interplay the between traditional and emerging energy sectors.

This study analyzes the interconnections among green financial assets, renewable energy markets, the geopolitical risk index and cryptocurrency carbon emissions from December 19, 2017 to February 15, 2023. We investigate these relationships using a novel time-frequency connectedness approach and machine learning methodology.

Our findings reveal that green energy stocks, except the PBW, exhibit the highest net transmission of volatility, followed by COAL. In contrast, CARBON emerges as the primary net recipient of volatility, followed by fuel energy assets. The frequency decomposition results also indicate that the long-term components serve as the primary source of directional volatility spillover, suggesting that volatility transmission among green stocks and energy assets tends to occur over a more extended period. The SHapley additive exPlanations (SHAP) results show that the green and fuel energy markets are negatively connected with geopolitical risks (GPRs). The results obtained through the SHAP analysis confirm the novel time-varying parameter vector autoregressive (TVP-VAR) frequency connectedness findings. The CARBON and PBW markets consistently experience spillover shocks from other markets in short and long-term horizons. The role of crude oil as a receiver or transmitter of shocks varies over time.

Green financial assets and clean energy play significant roles in the financial markets and reduce geopolitical risk. Our study employs a time-frequency connectedness approach to assess the interconnections among four markets' families: fuel, renewable energy, green stocks and carbon markets. We utilize the novel TVP-VAR approach, which allows for flexibility and enables us to measure net pairwise connectedness in both short and long-term horizons.

The global market for cloud gaming is growing rapidly. How gamers evaluate the service quality of this emerging form of cloud service has become a critical issue for both researchers and practitioners. Building on the literature on service quality and software as a service, this study develops and validates a gamer-centric measurement instrument for cloud gaming service quality.

A three-step measurement instrument development process, including item generation, scale development and instrument testing, was adopted to conceptualize and operationalize cloud gaming service quality.

Cloud gaming service quality consists of two second-order constructs of support service quality and technical service quality with seven first-order dimensions, namely rapport, responsiveness, reliability, compatibility, ubiquity, smoothness and comprehensiveness. The instrument exhibits desirable psychometric properties.

Practitioners can use this new measurement instrument to evaluate gamers' perceptions toward their service and to identify areas for improvement.

This study contributes to the service quality literature by utilizing qualitative and quantitative approaches to develop and validate a new measurement instrument of service quality in the context of cloud gaming and by identifying new dimensions (compatibility, ubiquity, smoothness and comprehensiveness) specific to it.

This study aims to reveal how chief executive officer (CEO) transformational leadership affects business model innovation (BMI) by exploring the serial mediating role of top management team (TMT) collective energy and behavioral integration and the moderating role of TMT-CEO value congruence.

The sample of 520 TMT members from 127 enterprises in North China was collected through a two-wave questionnaire survey. Hierarchical regression and bootstrapping were used to test the hypothetical relationships proposed in this study.

The results indicate that TMT collective energy and behavioral integration play a serial mediation role between CEO transformational leadership and BMI. TMT-CEO value congruence positively moderates the relationship between CEO transformational leadership and TMT collective energy as well as the serial mediation effect.

The results suggest that CEOs can stimulate TMT collective energy by demonstrating transformational leadership behaviors, thereby promoting TMT behavioral integration and ultimately achieving BMI. In addition, to enhance the effectiveness of CEO transformational leadership, enterprises should take measures to ensure that TMT members hold values that are consistent with those of CEOs.

Based on social cognitive theory, the mediating mechanism and boundary conditions of CEO transformational leadership that affect BMI are revealed by this study, thus opening the “black box” of the relationship between the two. It also supplements research on the role of TMT among the antecedents of BMI.

The purpose of this paper is to study the effect of vapor assembly sequence and assembly temperature on the corrosion protection of the complex silane films Al alloy. The performance and application range of silane films are enhanced.

The complex silane films were successfully prepared on the surface of aluminum alloy using via vapor phase assembly of 1,2,3-benzotriazole (BTA) and dodecyltrimethoxysilanes (DTMS). The protection of the assembly films against corrosion of Al alloy is investigated by the electrochemical measurements and the alkaline solution accelerated corrosion test. Thickness and hydrophobicity of the complex films are studied using ellipsometric spectroscopy and contact angle tests.

It shows that the anti-corrosion ability of the complex films is overall superior to that of the single-component assembled films. DTMS-BTA films have larger thickness and best anti-corrosion ability. The alkyl chains in DTMS have better compatibility with BTA molecules. The rigid BTA molecule can permeate into the long alkyl chain of DTMS as fillers and improve the barrier properties of the complex films.

In this paper, a green and efficient method of vapor phase assembly is proposed to rust prevention during manufacture of Al alloy workpiece.

Template matching is one of the most suitable choices for full six degrees of freedom pose estimation in many practical industrial applications. However, the increasing number of templates while dealing with a wide range of viewpoint changes results in a long runtime, which may not meet the real-time requirements. This paper aims to improve matching efficiency while maintaining sample resolution and matching accuracy.

A multi-pyramid-based hierarchical template matching strategy is proposed. Three pyramids are established at the sphere subdivision, radius and in-plane rotation levels during the offline template render stage. Then, a hierarchical template matching is performed from the highest to the lowest level in each pyramid, narrowing the global search space and expanding the local search space. The initial search parameters at the top level can be determined by the preprocessing of the YOLOv3 object detection network to further improve real-time performance.

Experimental results show that this matching strategy takes only 100 ms under 100k templates without loss of accuracy, promising for real industrial applications. The authors further validated the approach by applying it to a real robot grasping task.

The matching framework in this paper improves the template matching efficiency by two orders of magnitude and is validated using a common template definition and viewpoint sampling methods. In addition, it can be easily adapted to other template definitions and viewpoint sampling methods.

The authors aim to look at the conditions under which central bank easing – and specifically the purchase of private sector securities – can/should contribute to growth, rather than fiscal policy and also ask when can the central bank’s purchase of private sector securities help supplant traditional monetary policy.

After surveying the existing literature, the authors use simple correlation of central bank private asset (stocks, bonds, etc.), interest rates, gross domestic product (GDP) growth, inflation and the extent of the functioning of domestic banking sectors (among others) to classify countries in which these purchases promote pro-growth investment.

Under the typical conditions for unconventional monetary policy, central bank purchases of private companies’ securities can promote growth in some places (like Bulgaria, the Ukraine, Georgia and Greece at the time of our writing) while hurting it in others (like in parts of Latin America and Africa in the mid-2010s). The authors find how such purchases effectively “bypass” dysfunctional banking systems and central/government local bodies fiscal spending, making the central bank the “funder of last resort” in many middle and lower income countries.

This paper tells specific central banks to ramp up – or reduce – their purchases of private sector securities. The authors identify exact jurisdictions where such “helicopter money” has led to investment in the past economic growth.

All previous work on conventional and unconventional monetary policy has looked at the way monetary policy affects investment and growth through the banking system and holding companies’ reactions constant. The authors do the opposite – looking at how companies respond, holding banking system responses constant. No one has ever looked at these private purchases (taken from a special IMF database), much less tried to argue that central banks can sometimes target investment growth much better than fiscal policy. No one has ever considered them as a funder (rather than lender) of last resort.

Online brand communities (OBCs) are important platforms to obtain consumers' ideas. The purpose of this study is to examine how peer influence and consumer contribution behavior simulate innovative behaviors in OBCs to increase idea quality.

Using a firm-hosted popular online brand community – Xiaomi Community (MIUI), the authors collected a set of data from 6567 consumers and then used structural equation modeling (SEM) and fuzzy-set qualitative comparative analysis (fsQCA) to empirically test the impact of peer influence and consumer contribution behaviors on idea quality in OBCs.

The results of this study show that both peer influence breadth and depth have a positive effect on idea adoption and peer recognition, wherein proactive contribution behavior positively mediates these relationships, and responsive contribution behavior negatively mediates the impact of peer influence breadth and peer influence depth on peer recognition. A more detailed analysis using the fsQCA method further identifies four types of antecedent configurations for better idea quality.

Based on the attention-based view and the theory of learning by feedback, this study explores the factors that affect idea quality in the context of social networks and extends the research of peer influence in the digital age. The paper helps improve our understanding of how to promote customer idea quality in OBCs.

Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.

A case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.

The results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.

This research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.

This research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.