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Internal employees of firms are a reliable source of information for potential job seekers. However, few studies have focused on why internal employees actively recommend their firms. Based on the social exchange theory, this study aims to construct a chain mediation model using perceived challenge stress and employee experience as mediators to explore how leadership empowerment behavior affects employee referrals.

Bootstrap repeated sampling analysis was conducted on a sample of 307 employees collected through two-time points.

Leadership empowerment behavior is positively related to employee referrals; perceived challenge stress and employee experience mediate the effect of leadership empowerment behavior on employee referrals, respectively; in addition, perceived challenge stress and employee experience play a chain mediating role between leadership empowerment behavior and employee referrals.

The findings can help provide insight into the drivers of employee referrals and can effectively guide organization reputation management.

This study aims to investigate the multiple influence paths or underlying mechanisms of entrepreneurial leadership (EL) on adaptive innovation from the perspectives of organizational learning and resource management, drawing on complex adaptive system theory.

With a questionnaire survey of 317 senior and middle managers from different firms in China, structural equation modeling was used to test the hypothesized conceptual model, and bootstrapping method was employed to examine the multiple mediating effects.

Results indicate that EL has a significant and positive effect on adaptive innovation. This relationship is partially mediated through exploitative learning, exploratory learning, resource bricolage and boundary-spanning integration, respectively. The impact of EL on adaptive innovation is also sequentially transmitted through exploitative learning and resource bricolage or exploratory learning and boundary-spanning integration.

Adaptive innovation has become a firm competition strategy to cope with dynamic changes in current uncertain environment where EL can play its effectiveness to engage firms in such innovation activities. However, the question of why and how EL drives adaptive innovation has yet to be discussed. This study highlights the innovation effectiveness of EL and the triggering process of adaptive innovation, and contributes to several countermeasures for firms to implement leadership and innovation practices responding to uncertain environment.

The purpose of this paper is to propose a type of hybrid bearing lubricated with supercritical carbon dioxide (S-CO₂) and to investigate the stiffness and damping characteristics of the bearing under hydrostatic status.

Established a test rig for radial bearings lubricated with S-CO₂ and used it to measure the dynamic coefficients by recording the relative and absolute displacements of bearing. Test bearing is mounted on a nonrotating, stiff shaft. Using static loading experiments to obtain structural stiffness. The dynamic coefficient regularities of the test bearing under hydrostatic status were revealed through dynamic loading experiments.

Experiment results indicate that test bearing displayed increased stiffness when subjected to high excitation frequencies and low excitation forces, as well as elevated damping when exposed to low excitation frequencies and low excitation forces. Additionally, an increase in either environmental pressure or hydrostatic recess pressure can elevate the dynamic coefficient. The effect of temperature on the dynamic coefficient is more pronounced around the critical temperature of S-CO₂.

Designed a type of hybrid bearing for use in the Brayton cycle that is lubricated with S-CO₂ and uses hydrostatic lubrication during start-stop and hydrodynamic lubrication during high-speed operation. The hybrid bearing reduces the wear and friction power consumption of gas bearing. However, few experimental analyses have been conducted by researchers in this field.

This paper aims to explore the effects of normative and hedonic motivations on continuous knowledge contribution, and how past contribution experience moderates the effects of the motivations on continuous knowledge contribution.

Based on goal-framing theory, the present study proposes a comprehensive theoretical model by integrating normative and hedonic motivations, past contribution experience and continuous knowledge contribution. The data for virtual community members' activities were collected using the Python Scrapy crawler. Logit regression was used to validate the integrative model.

The results show that both normative motivation (reflected by generalized reciprocity and social learning) and hedonic motivation (reflected by peer recognition and online attractiveness) are positively associated with continuous knowledge contribution. Moreover, these effects are found to be significantly influenced by members' past knowledge contribution experience. Specifically, the results suggest that past knowledge contribution experience undermines the influence of generalized reciprocity on continuous knowledge contribution but strengthens the effect of peer recognition and online attractiveness.

Although the emerging literature on continuous knowledge contribution mainly focuses on motivations as antecedents that promote continuous knowledge contribution, most of these studies assume that the relationship between motivating mechanisms and continuous knowledge contribution does not change over time. The study is one of the initial studies to examine whether and how the influence of multiple motivations evolves relative to levels of past contribution experience.

In this work, the authors used reversible addition-fragmentation transfer (RAFT) polymerization to develop a new cationic acrylate modified epoxy resin emulsion for water-borne inkjet which have the advantages of both polyacrylate and epoxy resin. The emulsion was successfully used in the canvas coating for inkjet printing. This paper aims to contribute to the development of novel cationic emulsions for inkjet printing industry.

In this work, the epoxy acrylate was synthesized from RAFT agent and epoxy resin firstly. Cationic macromolecular emulsifier was prepared by RAFT polymerization, using 2,2’-Azobisisobutyronitrile as initiator, 2-(dimethylamino)ethyl methacrylate and styrene as monomer, which was directly used to prepare the emulsion. The influences of the amount of 2-(dimethylamino)ethyl methacrylate on particle size, zeta potential and water contact angle were studied. Finally, the cationic emulsion was used to print images by inkjet printing.

The emulsion has the smallest particle size, the highest potential and the highest water contact angle when the DM content is 13 Wt.%. The transmission electron microscopy analysis reveals the latex particles is core-shell sphere with the diameters in the range 120–200 nm. The emulsion was successfully used in the canvas coating for inkjet printing. This work will contribute to the development of novel cationic emulsions for inkjet printing industry.

The emulsion was successfully used in the canvas coating for inkjet printing. This work will contribute to the development of novel cationic emulsions for inkjet printing industry.

Driven by the dual-carbon target and the widespread digital transformation, leveraging digital technology (DT) to facilitate sustainable, green and high-quality development in heavy-polluting industries has emerged as a pivotal and timely research focus. However, existing studies diverge in their perspectives on whether DT’s impact on green innovation is synergistic or leads to a crowding-out effect. In pursuit of optimizing the synergy between DT and green innovation, this paper aims to investigate the mechanisms that can be harnessed to render DT a more constructive force in advancing green innovation.

Drawing from the theoretical framework of resource orchestration, the authors offer a comprehensive elucidation of how DT intricately influences the green innovation efficiency of enterprises. Given the intricate interplay within the synergistic relationship between DT and green innovation, the authors use the fuzzy-set qualitative comparative analysis method to explore diverse configurations of antecedent conditions leading to optimal solutions. This approach transcends conventional linear thinking to provide a more nuanced understanding of the complex dynamics involved.

The findings reveal that antecedent configurations fostering high green innovation efficiency actually differ across various stages. First, there are three distinct configuration patterns that can enhance the green technology research and development (R&D) efficiency of enterprises, namely, digitally driven resource integration (RI), digitally driven resource synergy (RSy) and high resource orchestration capability. Then, the authors also identify three configuration patterns that can bolster the high green achievement transfer efficiency of enterprises, including a digitally optimized resource portfolio, digitally driven RSy and efficient RI. The findings not only contribute to advancing the resource orchestration theory in the digital ecosystem but also provide empirical evidence and practical insights to support the sustainable development of green innovation.

The findings can offer valuable insights for enterprise managers, providing decision-making guidance on effectively harnessing the innovation-driven value of internal and external resources through resource restructuring, bundling and leveraging, whether with or without the support of DT.

The research findings contribute to heavy-polluting enterprises addressing the paradoxical tensions between digital transformation and resource constraints under environmental regulatory pressures. It aims to facilitate the simultaneous achievement of environmental and commercial success by enhancing their green innovation capabilities, ultimately leading to sustainability across profit and the environment.

Compared with previous literature, this research introduces a distinctive theoretical perspective, the resource orchestration view, to shed light on the paradoxical relationship on resource-occupancy between DT application and green innovation. It unveils the “black box” of how digitalization impacts green innovation efficiency from a more dynamic resource-based perspective. While most studies regard green innovation activities as a whole, this study delves into the impact of digitalization on green innovation within the distinct realms of green technology R&D and green achievement transfer, taking into account a two-stage value chain perspective. Finally, in contrast to previous literature that predominantly analyzes influence mechanisms through linear impact, the authors use configuration analysis to intricately unravel the complex influences arising from various combinatorial relationships of digitalization and resource orchestration behaviors on green innovation efficiency.