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Based on affective events theory, this study explores the cross-level effect of team reflexivity on employee innovative behaviors. Specifically, the authors examine the mediating effects of affective and normative commitment on this relationship, as well as the moderating effects of benevolent leadership.

The authors surveyed 341 employees and their direct supervisors in 74 work units and utilized multilevel path analysis to test a model of cross-level moderated mediation.

The study analysis results suggest that team reflexivity significantly contributes to employee innovative behavior. Both affective commitment and normative commitment mediate this relationship. Benevolent leadership not only enhances the relationship between team reflexivity and affective/normative commitment, but also reinforces the linkage of team reflexivity→affective commitment→employee innovative behavior.

The current study suggests that organizations should invest more in promoting team reflexivity and benevolent leadership in workplace. Furthermore, managers need to develop appropriate employees training programs and pay more attention to employees' work and personal lives. They need to make efforts to enhance employees' affective and normative commitment, thereby facilitating their innovative behavior.

This research identifies affective commitment and normative commitment as key mediators that link team reflexivity to employee innovative behavior and reveals the moderating role of benevolent leadership in the process.

Based on social information processing (SIP) theory, this study explores the cross-level effect of high-involvement work practices (HIWPs) on employee innovative behavior by studying the mediating role of self-reflection/rumination and the moderating role of transactive memory system (TMS).

This study collects data from 452 employees and their direct supervisors in 94 work units, and tests a cross-level moderated mediation model using multilevel path analysis.

The results suggest that HIWPs significantly contribute to employee innovative behavior. Both self-reflection and self-rumination mediate the above relationship. TMS not only positively moderates the relationship between HIWPs and self-reflection, but also reinforces the linkage of HIWPs. →self-reflection→employee innovative behavior. Furthermore, TMS negatively moderates the relationship between HIWPs and self-rumination, and attenuates the mediating effect of self-rumination.

The study suggests that enterprises should invest more in promoting HIWPs and TMS in the workplace. Furthermore, managers should provide employees training programs to enhance their self-reflection, as well as lower self-rumination, in order to facilitate employee innovative behavior.

This research identifies self-reflection and self-rumination as key mediators that link HIWPs to employee innovative behavior and reveals the moderating role of TMS in the process.

This study aims to introduce a three-hole cooling unit to improve downstream cooling performance by jet interaction and coalescence at a lower manufacture cost.

A new three-hole cooling unit is proposed. Reynolds-averaged Navier–Stokes (RANS) simulation is performed in the present study. The CFD package ANSYS CFX is used to predict film-cooling effectiveness and flow fields.

The results show that, at pitch ratio P/D = 3, Case 4 configuration with a round hole upstream and two trenched holes downstream can obtain a high cooling performance at a lower manufacture cost, especially at the higher turbulence. Considering the effect of increased pitch ratio, Case 6 configurations of three staggered trenched holes show a superior downstream cooling performance than Case 4 configurations. Case 6 configurations have the potential of achieving a high cooling performance with a reduced number of holes and less coolant flow.

The application of these cooling units in the turbine passage will be conducted in the future. The more detailed flow field will be simulated by large eddy simulation in the following research.

The round and trenched cooling holes have been proved to be achievable in the manufacture. This combined three-hole cooling unit will give the opportunity to increase turbine inlet temperature further.

Both cooling performance and practical manufacture are taken into account. This cooling scheme will give a superior surface protection on the hot components.

Because of indeterminateness of the environment and delay of the communication, deep space spacecraft is required to be autonomous. Planning technology is studied in order to realize the spacecraft autonomy. First, a multi‐agent planning system (MAPS) based on temporal constraint satisfaction is proposed for concurrency and distribution of spacecraft system. Second, timeline concept is used to describe simultaneous activity, continue time, resource and temporal constraints. Third, for every planning agent in the MAPS, its layered architecture is designed and planning algorithm based on the temporal constraint satisfaction is given in detail. Finally, taking some key subsystems of deep space explorer as an example, the prototype system of MAPS is implemented. The results show that with the communication and cooperation of the planning agents, the MAPS is able to produce complete plan for explorer mission quickly under the complex constraints of time and resource.

Based on experiential learning theory (ELT), this study explores the cross-level effect of team reflexivity on employee innovative behavior. The authors especially focus on the mediating effect of individual intellectual capital (IIC) and the moderating effect of empowering leadership on the relationship between the two constructs.

This study collects data from 76 work units, which include 362 employees and their direct supervisors. A cross-level moderated mediation model was tested by using multilevel path analysis.

The results show that team reflexivity significantly contributes to employee innovative behavior. IIC mediates the above relationship. Empowering leadership not only positively moderates the relationship between team reflexivity and IIC but also reinforces the linkage of team reflexivity → IIC → employee innovative behavior.

The study suggests that organizations should invest more in promoting team reflexivity and empowering leadership in the workplace. Furthermore, managers should make members aware of the importance of IIC for employee innovative behavior. They need to make efforts to enhance IIC via internal communication channels or open discussions, which facilitate IIC and employee innovative behavior.

This research tests the relationship between team reflexivity and employee innovative behavior and identifies IIC as a key mediator that links team reflexivity to employee innovative behavior. It also highlights the moderating role of empowering leadership in the process.

Despite the implementation of the “land for social security” scheme to compensate for land expropriation in rural China, the distribution of social security benefits varies widely both between and within provinces. Why do local officials offer pension compensation in addition to cash payments to some landless farmers and not to others? Using in-depth interviews and survey data, I find that certain attributes of collective demands may signal a threat to social stability, prompting government concessions in the form of welfare benefits. Particularly, among the dispossessed farmers who have engaged in petitions, those who petitioned to higher-level officials were found to be more likely to receive pension benefits than those who have participated in claim-making with a bigger crowd. I propose that in the administrative hierarchy system of cadre evaluation, local officials may perceive public visits and petitions to higher levels of government as more threatening to their career prospects. Moreover, the dilemma between compensation and stability maintenance may also enable local officials to condone strategic targeting rather than collective gathering.

This study investigates the influence of social trust on the attainment of corporate environmental, social and governance (ESG) objectives.

This study conducts panel regression analysis on a distinctive dataset for 2009–2017 on Chinese firms.

The analysis reveals a significant positive association between social trust and firm-level ESG practices. Moreover, the impact of social trust on shaping ESG outcomes is further amplified by factors such as economic growth, corporate governance standards and institutional quality. This relationship remains statistically positive when the authors employ alternative measures and methodologies, such as the instrumental variables, propensity score matching and difference-in-differences approaches. Notably, the results of heterogeneity tests indicate that the Trust–ESG nexus is more prominent for state-owned enterprises and firms with substantial market capitalization, superior profitability and higher leverage.

This study expands the comprehension of the determinants of ESG and underscores the influential role of social trust as an informal institution in enhancing a firm's ESG performance.

By analyzing the mechanisms by which rural infrastructure resilience (RIR) impacted population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

This study considered 213 administrative villages in Longxi County in the Longzhong loess hilly region as the evaluation unit. Based on the construction of a multidimensional RIR evaluation system, the spatial spillover effect of RIR on population loss was determined using the spatial Durbin model (SDM).

The average resilience of each subsystem of rural infrastructure in Longxi County was low, and there were large differences in the spatial distribution. The mean RIR index value was 0.2258, with obvious spatial directivity and agglomeration characteristics. The population loss index of Longxi County had a value of 0.1759, with 26.29 of villages having a high loss level. The population loss was relatively serious and was correlated with the spatial distribution of RIR. The villages with larger RIR index values had lower population loss. The RIR had a significant spatial spillover effect on population loss. Productive infrastructure resilience and living infrastructure resilience (LIR) had negative spillover effects on population loss, and social service infrastructure resilience (SSIR) had a positive spillover effect on population loss.

By analyzing the mechanisms by which RIR impacted on population loss in Longxi County, this study proposes measures to improve RIR, which provides a practical reference for realizing China's rural revitalization strategy, besides providing ideas for alleviating population loss in similar regions around the world.

Effectively predicting research and development project portfolio benefit (R&D PPB) could assist organizations in monitoring the execution of research and development project portfolio (R&D PP). However, due to the uncertainty and complexity of R&D PPB, current research remains lacking a valid R&D PPB prediction tool. Therefore, an R&D PPB prediction model is proposed via a backpropagation neural network (BPNN).

The R&D PPB prediction model is constructed via a refined immune genetic algorithm coupling backpropagation neural network (RIGA-BPNN). Firstly, considering the characteristics of R&D PP, benefit evaluation criteria are identified. Secondly, the benefit criteria values are derived as input variables to the model via trapezoidal fuzzy numbers, and then the R&D PPB value is determined as the output variable through the CRITIC method. Thirdly, a refined immune genetic algorithm (RIGA) is designed to optimize BPNN by enhancing polyfitness, crossover and mutation probabilities. Lastly, the R&D PPB prediction model is constructed via the RIGA-BPNN, followed by training and testing.

The accuracy of the R&D PPB prediction model stands at 99.26%. In addition, the comparative experiment results indicate that the proposed model surpasses BPNN and the immune genetic algorithm coupling backpropagation neural network (IGA-BPNN) in both convergence speed and accuracy, showcasing superior performance in R&D PPB prediction. This study enriches the R&D PPB predicting methodology by providing managers with an effective benefits management tool.

The research implications of this study encompass three aspects. First, this study provides a profound insight into R&D PPB prediction and enriches the research in PP fields. Secondly, during the construction of the R&D PPB prediction model, the utilization of the composite system synergy model for quantifying synergy contributes to a comprehensive understanding of intricate interactions among benefits. Lastly, in this research, a RIGA is proposed for optimizing the BPNN to efficiently predict R&D PPB.

This study carries threefold implications for the practice of R&D PPM. To begin with, the approach proposed serves as an effective tool for managers to predict R&D PPB. Then, the model excels in efficiency and flexibility. Furthermore, the proposed model could be used to tackle additional challenges in R&D PPM, such as gauging the potential risk level of R&D PP.

Effective predicting of R&D PPB enables organizations to allocate their limited resources more strategically, ensuring optimal use of capital, manpower and time. By accurately predicting benefit, an organization can prioritize high-potential initiatives, thereby improving innovation efficiency and reducing the risk of failed investments. This approach not only strengthens market competitiveness but also positions organizations to adapt more effectively to changing market conditions, fostering long-term growth and sustainability in a competitive business environment.

Incorporating the characteristics of R&D PP and quantifying the synergy between benefits, this study facilitates a more insightful R&D PPB prediction. Additionally, improvements to the polyfitness, crossover and mutation probabilities of IGA are made, and the aforementioned RIGA is applied to optimize the BPNN. It significantly enhances the prediction accuracy and convergence speed of the neural network, improving the effectiveness of the R&D PPB prediction model.

Modern technologies are seen as an essential component of the fourth industrial revolution (industry 4.0) and their adoption is vital to transform the existing manufacturing system into industry 4.0-based manufacturing system. Therefore, the primary objective of this research explores the barriers of modern technology adoption and their mitigating solutions in order to align with Industry 4.0 objectives.

Barriers to adopting modern technologies and respective mitigating solutions are identified from the available literature. Further, these barriers are ranked with the help of expert opinions by using the BWM method appropriately. The identified solutions are ranked using the combined compromise solution (CoCoSo) method.

Several modern technologies and their capabilities are recognised to support the industry 4.0-based manufacturing systems. This study identifies 22 barriers to the effective adoption of modern technologies in manufacturing and 14 solutions to overcome these barriers. Change management, the high initial cost of technology and appropriate support infrastructure are the most significant barriers. The most prominent solutions to overcome the most considerable barriers are ‘supportive research, development and commercialisation environment’, ‘updated policy and effective implementation’ and ‘capacity building through training’ that are the top three solutions that need to be addressed.

The barriers and solutions of modern technology adoption are obtained through a comprehensive literature review, so there is a chance to ignore some significant barriers and their solutions. Furthermore, ranking barriers and solutions is done with expert opinion, which is not free from biases.

This identification and prioritisation of barriers will help managers to understand the barriers so they can better prepare themselves. Furthermore, the suggested solutions to overcome these barriers are helpful for the managers and could be strategically adopted through optimal resource utilisation.

This study proposes a framework to identify and analyse the significant barriers and solutions to adopting modern technologies in the manufacturing system. It might be helpful for manufacturing organisations that are willing to transform their manufacturing system into industry 4.0.