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Current multi-source image fusion methods frequently overlook the issue of detailed features when employing deep learning technology, resulting in inadequate target feature information. In real-world mission scenarios, such as military information acquisition or medical image enhancement, the prominence of target feature information is of paramount importance. To address these challenges, this paper introduces a novel infrared-visible light fusion model.

Leveraging the foundational architecture of the traditional DenseFuse model, this paper optimizes the backbone network structure and incorporates a Unique Feature Encoder (UFE) to meticulously extract the distinctive features inherent in the two images. Furthermore, it integrates the Convolutional Block Attention Module (CBAM) and the Squeeze and Excitation Network (SE) to enhance and replace the original spatial and channel attention mechanisms.

Compared to other methods such as IFCNN, NestFuse, DenseFuse, etc., the values of entropy, standard deviation, and mutual information index of the method presented in this paper can reach 6.9985, 82.6652, and 13.6022, respectively, which are significantly improved compared with other methods.

This paper presents a UFEFusion framework that synergizes with the CBAM attention mechanism to markedly augment the extraction of detailed features relative to other methods. Moreover, the framework adeptly extracts and amplifies unique features from disparate images, thereby elevating the overall feature representation capability.

This paper aims to examine the antecedents and performance outcomes of proactive and reactive knowledge-sharing behaviour. Specifically, it investigates from the employee’s perspective how human resource management, with the system of human resource (HR) practices and work climate, influences proactive and reactive knowledge-sharing behaviours via the employees’ interest-based motivation.

For the main hypotheses, a moderated mediation model was tested using survey-based data from 400 employees from Poland and structural equation modelling analyses. Next, the authors used data from 143 employee supervisor dyads (subsample data) to test the employee performance outcomes of knowledge sharing.

The results show that commitment-based HR practices are positively related to knowledge-sharing behaviour via autonomous motivation when employees perceive a cooperative climate in the workplace. Furthermore, there are motivational and outcome differences between sharing knowledge reactively and proactively. External motivation is detrimental to reactive knowledge sharing, while introjected motivation is positively related to proactive knowledge sharing. Next, while proactive knowledge-sharing is related to better performance, reactive knowledge-sharing has no performance implications for employees.

From the managerial perspective, this study suggests that to facilitate knowledge sharing, managers should align the implementation of commitment-based HR practices with a cooperative climate in the work environment.

By differentiating proactive and reactive knowledge-sharing behaviour and examining the contingent role of cooperative psychological climate, the study explains the mixed results of external and introjected motivation to share knowledge. This study also provides more specific results on the performance outcomes of knowledge givers, showing that performance effects should not be taken for granted.

This paper aims to address the gaps in current research by exploring how blockchain technology influences corporate green innovation.

This study investigates the potential of blockchain technology to stimulate the green innovation of companies using the difference-in-difference model with a panel data set of 1,803 Chinese listed companies from 2012 to 2019.

The application of blockchain significantly increases the number of green invention patents obtained by companies but has no significant impact on green utility model patents, that is, blockchain applications improve the quality rather than the quantity of green innovation. The role of blockchain in promoting green innovation is particularly pronounced in state-owned enterprises, non-heavily polluting industries and older companies. The use of blockchain technology helps reduce sales costs and boosts research and development investments, thereby encouraging green innovation. Additionally, a company’s internal control quality plays a moderating effect.

Firstly, previous research on blockchain has primarily centered on its relationship with supply chain management. This article empirically tests the impact of blockchain applications on the green innovation of companies using the DID method. Secondly, current studies mainly explore the influencing factors on green invention patents. This article examines the impact of blockchain applications on both green invention patents and green utility model patents and identifies distinct influencing effects. Finally, this article introduces the internal control mechanism of enterprises into the DID model and explores the potential impact of the quality of internal control on the relationship between blockchain and green innovation.

This study identifies a methodology to explore the issues of enterprise innovation ecosystem health (EIEH).

First, this study constructs the indicator system of EIEH based on the research objective; second, the dynamic vertical projection method (DVPM) and entropy weight method are proposed to analyze the status and influencing factors of EIEH; finally, the future development of EIEH is analyzed using GM (1,1).

In terms of methodology, the DVPM can effectively analyze EIEH, which can not only analyze the development status and potential of EIEH every year but also analyze the comprehensive state of EIEH for many years. In terms of practice, the value and grade of EIEH in China have been gradually increasing from 2016 to 2020, but the overall development is unbalanced, and five key factors affecting EIEH have been identified. The EIEH in China is predicted to steadily grow from 2021 to 2025.

The analytical method employed in this study can effectively analyze EIEH, which provides a new analytical perspective for the evaluation of EIEH and enriches the research content of the enterprise innovation ecosystem (EIE). By analyzing the results, we can gain a comprehensive understanding of the state of different EIEs, enabling each EIE to design tailored remedial measures to enhance EIEH and achieve sustainable development.

The purpose of this study is to investigate the impact of servant leadership on frugal innovation through the mediating role of corporate social responsibility to employees.

This study used a quantitative research method and structural equation modeling to test hypotheses in the proposed research model based on a sample of 325 Vietnamese firms.

The research findings indicated that five dimensions of servant leadership including empowerment, humility, standing back, stewardship and authenticity are positively related to frugal innovation. Moreover, corporate social responsibility to employees partially mediates the connections between five servant leadership’s dimensions and frugal innovation.

This study provides important insights and a novel approach for leaders of Vietnamese small and medium-sized firms to improve their firms’ frugal innovation capability through leadership practice and corporate social responsibility to employees.

This study significantly fills research gaps in the literature and advances the understanding of how servant leadership promotes corporate social responsibility to employees to improve frugal innovation.

The Industry 4.0 (I4.0) revolution originated in developed countries and has now been promoted worldwide as a powerful tool for improving productivity. However, adopting I4.0 technologies poses significant challenges, especially for emerging economies that are far from the I4.0 frontier. In the context of emerging economies, this paper aims to explore the impact of adopting I4.0 technologies on firms’ total factor productivity (TFP) and its mediation channels.

Using panel data for 2,928 firms in China’s manufacturing industry during the period 2010–2022, this study adopts fixed effects regression model to test the theoretical hypotheses. Endogeneity issues are addressed by the instrumental variable approach and propensity score matching.

The results show that adopting I4.0 technologies can significantly improve emerging economy firms’ TFP, and this effect is achieved by promoting technological innovation and alleviating financial constraints. Furthermore, the findings indicate a heterogeneity in the effects of I4.0 technology adoption. When top managers are long-term oriented, firms are state-owned, industry competition pressure is low or regional manufacturing innovation capability is strong, the positive impact of I4.0 on TFP is weakened.

This paper is one of the first attempts to offer empirical evidence about whether and how the adoption of I4.0 technologies boosts TFP growth among firms in emerging economies. The study expands on the organizational performance consequences of I4.0 adoption and provides implications for decision-makers in developing countries in implementing I4.0.

The purpose of this study is to contribute to empirical research on individual ambidexterity drivers. This paper analyzes the relationships between inclusive leadership, team knowledge acquisition, team knowledge sharing, digital tools usage and individual ambidexterity.

This study conducted a questionnaire survey of high-tech and manufacturing enterprises in China and obtained 75 leader questionnaires and 365 employee questionnaires. The hypotheses were tested using hierarchical and cross-level regressions.

The research indicates that inclusive leadership improves team knowledge acquisition and sharing. However, only team knowledge sharing significantly boosts individual ambidexterity, and not team knowledge acquisition. Thus, inclusive leadership fosters individual ambidexterity primarily through team knowledge sharing. Digital tools usage strengthens the impact of inclusive leadership on team knowledge sharing, thereby intensifying its effect on individual ambidexterity. However, digital tools usage weakens the effect of inclusive leadership on team knowledge acquisition.

First, this study addresses the call for research on ambidexterity at different levels, revealing the heterogeneous impact of team knowledge acquisition and sharing on individual ambidexterity. Second, this study developed a theoretical model to explore how leadership affects individual ambidexterity. Third, this study responds to the question that digitalization has won, but has leadership lost by investigating the role of digital tools usage in the relationship between inclusive leadership and team knowledge integration.

This study is dedicated to systematically collating the distribution and utilization circumstances of geothermal resources in China. Moreover, it endeavors to formulate a comprehensive utilization scheme for geothermal resources during the construction and operation phases of the railway, thereby furnishing robust support and valuable reference for the holistic utilization of geothermal resources along the railway corridor.

Through an in-depth analysis of the extant utilization of geothermal resources in China, it is discerned that the current utilization modalities are relatively rudimentary, bereft of rational planning and characterized by a low utilization rate. Concurrently, by integrating the practical requisites of railway construction and operation and conducting theoretical dissections, a comprehensive utilization plan for the construction and operation periods of railway is proffered.

In light of the railway’s construction and operation characteristics, geothermal utilization models are categorized. During construction, comprehensive modalities include tunnel illumination power generation, construction area heating, tunnel antifreeze using shallow geothermal energy, tunnel pavement antifreeze and construction concrete maintenance. During operation, they comprise operation tunnel antifreeze, railway roadbed antifreeze, railway switch snow melting and deicing, geothermal power station establishment and railway hot spring health tourism planning.

According to the characteristics and actual needs of railway construction and operation, it is of great significance to rationally utilize geothermal resources to promote the construction and operation of green railways.

This study intends to extend the unified theory of acceptance and use of technology (UTAUT) model by integrating perceived enjoyment as an intrinsic motivation so as to investigate factors influencing Chinese undergraduate English as a Foreign Language (EFL) students' intention to use ChatGPT for English learning.

A cross-sectional quantitative survey method research design was used in this study. Data were collected from 432 undergraduate students at two Chinese universities. The data analysis was carried out using SmartPLS 4, a computer software that employs the partial least squares structural equation modelling (PLS-SEM) technique. The analysis of the model was performed in two stages, including the assessment of reflective measurement model and structural model. The PLS predict was utilized to assess the model’s predicting power.

Findings showed that effort expectancy, performance expectancy, social influence and perceived enjoyment were positively related to Chinese undergraduate EFL learners' intention to use ChatGPT for English learning. Perceived enjoyment mediated the relationships between effort expectancy, performance expectancy, social influence and intention to use ChatGPT for English learning respectively.

Through incorporating the perceived enjoyment as an intrinsic motivation into the UTAUT model to explore factors that impact Chinese undergraduate EFL learners' intention to use ChatGPT for English learning, this study has extended the applicability of the UTAUT model and provide insights into factors affecting students' intention to utilize ChatGPT or other AI-based technologies for English learning.

Although the deployment of diverse brand capabilities is essential for business-to-business (B2B) firms to adapt to changing industrial market demands, the understanding of how brand ambidexterity (BA) influences brand performance (BP) remains limited. This study aims to investigate the importance of BA in relation to BP, analyzing the mediating effect of buyer dependence (BD) and the moderating effect of the supplier’s degree of digital use (DDU) within B2B firms.

Drawing on resource dependence theory (RDT) and the literature on BA and BD, the authors developed a theoretical research model. The authors surveyed 261 pairs of firms, including suppliers and their buyers in China. After the data were collected, the authors used partial least squares structural equation modeling to analyze the data.

The findings of the study indicate that BA significantly and positively influences BP in B2B firms. Furthermore, both buyer relationship value dependence (RVD) and switching cost dependence (SCD) mediate the relationship between supplier’s BA and BP. In addition, the supplier’s DDU positively moderates the relationship between BA and buyer RVD; however, its effect on SCD is not significant.

To the best of the authors’ knowledge, this study is among the first to reveal the underlying mechanism by which BA is leveraged by B2B firms to enhance BP. In addition, by adopting a dual supplier-buyer perspective, the findings provide valuable insights for managers seeking to understand the influence of BA on interorganizational relationships.