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Prefabricated building has emerged as a hallmark of modern construction industrialization and a pivotal driver of industrial upgrading. In this new building type, the supply of high-quality prefabricated components plays a crucial role in ensuring project quality, cost-effectiveness and on-time completion. Consequently, selecting the optimum suppliers for these components is vital. This study provides valuable insights for construction enterprises, guiding them in the optimal selection of prefabricated component suppliers and thereby contributing to the sustainable development of the construction industry.

The entropy weight method is used to integrate and rank 19 commonly used evaluation indices, forming a supplier evaluation system from the enterprises perspective. Subsequently, the VIKOR multi-attribute decision model, combined with a comprehensive evaluation method based on cloud modeling, is applied to identify the most suitable suppliers through case study.

The findings emphasized that product quality, particularly the component compliance rate, is paramount in supplier selection. Additionally, companies should prioritize cost management and fundamental supplier capabilities, such as transportation efficiency and operational flexibility, while fostering strong partnerships with high-quality suppliers. Furthermore, all stakeholders need to enhance the supply chain’s responsiveness and adaptability, ensuring these improvements are achieved without strict cost controls.

This study minimizes the influence of subjective biases from decision-makers’ by integrating quantitative and qualitative analysis methods, thereby enhancing the comprehensiveness and accuracy of evaluations. By effectively addressing the fuzziness and uncertainty inherent in evaluation data, it establishes a robust system for selecting prefabricated building suppliers. This approach offers reliable and practical decision support, providing theoretical backing for enterprises in choosing prefabricated component suppliers and promoting the sustainable development of the prefabricated construction industry.

The surge of social media as a pivotal platform for individuals to access travel-related information has become increasingly significant. Drawing upon social-technical theory and weak tie theory, this study aims to delve into the antecedents and moderating variables shaping impulsive travel intentions within social media.

Data were collected from 696 Chinese social media users and travelers and analyzed using partial least squares structural equation modeling (PLS-SEM).

The findings indicate that information quality and social network interaction significantly influence spatial presence, thereby increasing users’ impulsive travel intentions. The moderating roles of tie strength and face consciousness are confirmed. For travelers with strong ties, their spatial presence is impacted more by social network interaction. Conversely, for individuals with weak ties, spatial presence is more influenced by information quality. In addition, travelers with heightened face consciousness exhibit a diminished susceptibility to the influence of spatial presence on their travel intentions compared to those with lower face consciousness.

The study endeavors to extend the application of the social-technical theory in the domain of tourism social media marketing by examining the interplay of technological and social attributes on impulsive travel intention. It integrates weak tie theory into the socio-technical perspective, emphasizing the importance of weak ties in the social media environment and their influence on travel behavior. In addition, this study introduces face consciousness to the mechanism, seeking to broaden the research scope and capture the nuances of specific cultural contexts. The insights contribute valuable knowledge for destinations and tourism companies to optimize social media marketing.

社交媒体作为个人获取旅行相关信息的重要平台, 其影响力日益显著。本研究基于社会技术理论和弱关系理论, 探讨社交媒体中塑造冲动旅行意图的前因和调节变量。

本研究收集了696名中国社交媒体用户和旅行者的数据, 并采用偏最小二乘法结构方程建模（PLS-SEM）进行分析。

研究结果表明, 信息质量和社交网络互动显著影响空间存在感, 从而增强用户的冲动旅行意图。研究确认了关系强度和面子意识的调节作用。对于有强关系的旅行者来说, 社交网络互动对他们的空间存在感影响更大。相反, 对于有弱关系的个体, 信息质量对空间存在感的影响更为显著。此外, 面子意识较强的旅行者在空间存在感对其旅行意图的影响上表现出更低的敏感性, 相较于面子意识较低的个体。

本研究旨在扩展社会技术理论在旅游社交媒体营销领域的应用, 通过考察技术属性与社会属性对冲动旅行意图的相互作用。研究将弱关系理论融入社会技术视角, 强调了社交媒体环境中弱关系的重要性及其对旅行行为的影响。此外, 本研究引入了面子意识的机制, 旨在拓宽研究范围, 捕捉特定文化背景下的细微差异。研究结果为旅游目的地和公司优化社交媒体营销提供了宝贵的知识。

Precise temperature measurements are crucial for understanding Earth’s energy balance and for accurately predicting future climate change. Therefore, atmospheric temperature observations using radiosonde sensors require enhanced accuracy, targeting measurements with a precision of 0.1 K or better.

First, temperature errors of radiosonde sensors were simulated using computational fluid dynamics (CFD) from sea level up to an altitude of 32 km. These simulations accounted for a range of environmental factors, including solar radiation intensity, solar radiation angle, air velocity and altitude (air density). A neural network algorithm was then applied to learn and model the CFD-derived temperature errors. Based on this, a temperature error correction algorithm for radiosonde sensors was developed.

Experimental results demonstrated that the average absolute error between the measured temperature errors and the values corrected using the algorithm was 0.019 K, with a root mean square error of 0.018 K and a correlation coefficient of 0.99. These findings suggest that the temperature error correction algorithm effectively reduces measurement errors to approximately 0.05 K.

The widespread adoption of this technology can impact various aspects of society, including enhancing the overall quality of meteorological observation networks and providing more accurate meteorological data support for multiple fields, such as agriculture, disaster early warning, and public health.

This study focuses on developing a correction algorithm for radiation-induced errors in sounding temperature sensors by integrating CFD with neural network algorithm. This approach aims to enhance the accuracy of temperature observations from sounding sensors, minimizing biases caused by solar radiation. The improved precision in temperature measurements will contribute to more reliable historical temperature data, thereby supporting research in climate change by providing accurate datasets for long-term climate analysis.

This study aims to propose a moderated mediation model to investigate the moderating effects of environmental, social and governance (ESG) performance on the relationship between inefficient investment and firm performance and the mediating effect of firms that participate in institutional research on the relationship between investment efficiency and performance. This study also analyses the heterogeneity of the corporate nature, intensity of industrial research and development (R&D), industrial competition and regional marketization.

This study uses a panel data fixed-effects model to conduct a regression analysis of 1,918 Chinese listed firms from 2016 to 2020. A Fisher’s permutation test is used to examine the differences between state-owned and nonstate-owned firms.

Inefficient investment negatively impacts corporate performance and higher ESG performance exacerbates this effect by attracting more institutional research which reveals more problems. State-owned enterprises perform significantly better than nonstate-owned enterprises in terms of ESG transformation. Industrial R&D intensity, competition and regional marketization also mitigate the negative effects of inefficient investment on corporate performance.

This study suggests that companies should consider inefficient investments that arise from agency issues in corporate ESG transformation. In addition, state-owned enterprises in ESG transformation should take the lead to achieve sustainable development more efficiently. China should balance regional marketization, encourage enterprises to increase R&D intensity, reduce industry concentration, encourage healthy competition and prevent market monopolies.

This study combines the agency and stakeholder theories to reveal how inefficient investments that arise from agency issues inhibit value creation in ESG initiatives.

Little is established about the mechanism through which employee voice is connected to employee mental health. Drawing from social exchange theory, this study examines how employee engagement practices are associated with employee voice, which further influences employee mental health. In addition, the study includes parallel mediation and examines whether perceived interpersonal justice (PIJ) and empathetic leadership (EL) mediate the relationship between employee engagement practices and employee voice.

Three time-lagged surveys of 457 employees in the Indian information technology (IT) sector were accomplished.

As hypothesised, employee engagement practices have a positive influence on employee voice. Secondly, employee voice has a positive influence on the employee’s mental health. PIJ and EL were also found to be significant parallel mediators for the relationship among employee engagement practices and employee voice.

This study displays the positive influence of employee engagement practices on employee voice. Further, the employee’s voice influences the employee’s mental health. Therefore, it suggests means for improving its pervasiveness in an organisation.

This research paper is an important contribution as it is one of the few studies examining the role of PIJ and EL as parallel mediators of employee engagement practices and employee voice. It also answers repeated calls for more research on employee mental health in the IT sector.

This paper aims to focus on the reliability of Sn15Bi–xAg and Sn15Bi–xCu solder joints during isothermal aging.

The effects of Ag or Cu additions on the microstructure, interfacial metallic compound layer and shear strength of Sn–15Bi (Sn15Bi) based solder joints during were investigated. The effects of Ag or Cu additions on the microstructure and tensile properties of Sn15Bi-based bulk solders were also investigated to provide a comprehensive analysis. The interfacial morphology and microstructure were observed by scanning electron microscopy and the composition in the structure was examined by energy dispersive spectrometer. The shear tests were carried out on the as-soldered and as-aged joints using a ball shear tester.

The results revealed that by adding Ag or Cu, the microstructure of Sn15Bi solder can be refined. Ag addition increased the tensile strength of Sn15Bi solder but had little effect on elongation. However, Cu addition decreased the tensile strength and elongation of Sn15Bi solder. For solder joints, Ag addition increased the shear strength and toughness of Sn15Bi/Cu joints but Cu addition decreased the shear strength and toughness of Sn15Bi/Cu joints.

The authors can potentially provide a replacement for Sn40Pb traditional solder with Sn15Bi solder by alloying Ag or Cu due to its lower cost and similar melting point as Sn–Pb solder.

Drawing on the upper echelons theory, this study focuses on how top management team (TMT) heterogeneity affects breakthrough innovations and examines how strategic decision-making logic (including causation and effectuation) moderates the relationship between TMT heterogeneity and breakthrough innovation.

By conducting an empirical test of 227 sample firms in China, the authors applied linear hierarchical regression analysis to test the hypotheses on the TMT heterogeneityinnovation relationship and the moderating roles of causation and effectuation.

The empirical tests show that TMT heterogeneity positively affects breakthrough innovation, and both causation and effectuation positively moderate the positive relationship between TMT heterogeneity and breakthrough innovation. In addition, effectuation has a stronger moderating effect on the positive correlation between TMT heterogeneity and breakthrough innovation than causation.

This study extends the upper echelons theory to explain how the characteristics of TMTs affect firm innovation. Specifically, the authors explore the TMT heterogeneity–breakthrough innovation relationship from the perspectives of information processing and core competence and reveal the boundary condition of strategic decision-making logic in the correlation between TMT heterogeneity and breakthrough innovation. In this vein, the authors contribute to the literature by untangling the internal mechanisms between TMT heterogeneity and breakthrough innovation and extending the discussion on effectuation theory from the entrepreneurship domain to the innovation field. Furthermore, the research findings can provide helpful implications for TMTs to manage breakthrough innovation effectively.

Drawing on dynamic capability theory, this study investigates how digital integration influences firms’ agility. The mediating role of organizational inertia and the moderating role of market information transparency are further examined.

Using survey data from 170 Chinese firms, this study empirically tests the proposed moderated mediation model.

The results reveal that digital integration has a direct and positive influence on agility. Furthermore, digital integration indirectly enhances agility by diminishing organizational inertia. Additionally, our results show that market information transparency mitigates the negative relationship between organizational inertia and agility but does not significantly influence the positive relationship between digital integration and agility.

This study advances the understanding of agility development. However, its cross-sectional design limits insights into causal relationships; thus, we call for longitudinal studies to explore the relationship between digital integration and agility.

This research offers valuable insights for practitioners to leverage digital integration to enhance agility by reducing organizational inertia and fostering a transparent market environment.

This study enriches the literature on agility in the era of digitalization by revealing that digital integration reduces organizational inertia, a potential barrier to a firm’s agility. We also find that market information transparency moderates the relationship between organizational inertia and agility.

The online healthcare platform (OHP) has become an essential element of the healthcare system, representing a technological shift in the job responsibilities of medical professionals. Drawing on a technology-based job demands–resources (JD-R) model, this study aims to examine how the technological characteristics of OHP affect doctors’ OHP use psychology and behavior.

This empirical study was based on a survey conducted among 423 doctors with OHP use experience. The proposed model underwent assessment through partial least squares structural equation modeling (PLS-SEM) to reveal the effects of technology-based job demands (i.e. technology-based work overload and technology-based work monitoring) and resources (i.e. perceived usefulness, facilitating conditions and IT mindfulness) on doctors’ OHP fatigue and continuance use intention.

Results suggest that technology-based work monitoring, perceived usefulness and facilitation conditions have significant impacts on doctors’ psychological and behavioral responses to using OHP, whereas technology-based work overload and IT mindfulness have a single impact on continuance use intention and fatigue of OHP.

It assists doctors, healthcare administrators, policymakers and technology developers in understanding OHPs’ technological characteristics, enabling them to harness its benefits and mitigate potential challenges. Additionally, given the self-reported cross-sectional data from China, future studies can improve generalizability and adopt experimental methods or longitudinal designs with objective data.

It extends the research on OHP by employing a technology-based JD-R model to explore work attributes and dual effects associated with OHP’s technological characteristics. It also enriches existing research by examining the role of OHP’s technological characteristics in doctors’ psychological and behavioral responses.

Agricultural science and technology (AST) often need the form of industry-university-research cooperation in successfully completing breakthrough agricultural technology innovations. Therefore, AST industry-university-research cooperation is not only the need of the AST development strategy in China but also the only way for the development of agricultural colleges and universities, agricultural scientific research institutions and agricultural enterprises. Among them, in the process of cooperative breakthrough agricultural technology innovation, the correct selection of partners is the basis for ensuring its effective operation.

Aiming at the time-series characteristics and information ambiguity of decision information in the dynamic selection process of AST industry-university-research partners, this research introduces the dynamic intuitionistic fuzzy multi-criteria decision-making method of time degree and orthogonal projection. On this basis, field theory is used to construct the cooperative innovation capability field model of the partners, and the threshold for the partners to enter or exit the system is designed to dynamically select and eliminate the partners.

Results show that this method fully considers the situation of cooperative innovation resources within the AST industry-university-research system and the resource complementarity of candidate partners.

Combined with examples from agricultural scientific research institutions, the applicability and superiority of the model are verified.