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This paper aims to investigate how chief executive officer (CEO) responsible leadership impacts corporate social responsibility (CSR) and organization performance by considering diverse organizational climates (including ethical, service and initiative climates) as mediators and CEO founder status as a moderator.

This study analyzed survey data from 212 service organizations in China with structural equation modeling.

The results clearly established that CEO responsible leadership played a crucial role in augmenting both CSR and organization performance by shaping positive organizational climates. Notably, CEO responsible leadership significantly fostered ethical, service and initiative climates. Furthermore, an ethical climate promoted CSR and organization performance, whereas service and initiative climates specifically enhanced organization performance. Additionally, responsible CEOs with founder status exhibited a higher propensity for enhancing ethical, service and initiative climates within service organizations.

Service organizations should take measures to build CEO responsible leadership, especially for CEOs with founder status. Furthermore, service organizations should motivate employees to reach consensus on ethical conducts, superior service and proactive approach to work.

First, the findings on CEO responsible leadership’s effects on CSR and organization performance extend the research on responsible leadership outcomes. Second, this paper adds to responsible leadership literature through exploring the mediating effects of ethical, service and initiative climates. Finally, the finding on the moderating role of founder CEOs offers a novel perspective regarding the boundary condition of the effects of CEO responsible leadership.

The purpose of this paper is to explore the effecting mechanism of relational embeddedness on technological innovation performance in the context of China.

By probing into the related theories and five exploratory case studies of Chinese manufacturing firms, this paper establishes a conceptual model about the effects of relational embeddedness on technological innovation performance and proposes nine hypotheses. The authors then investigate 228 Chinese manufacturing firms by questionnaires, and testify the hypotheses and conceptual model by structural equation modeling.

Chinese firm's relational embeddedness in the international manufacturing network has a positive effect on its technological innovation performance through explorative learning. Specifically, trust, information sharing and joint problem solving are beneficial to new knowledge acquisition and application, and then to the improvement of technological innovation performance.

This paper mainly focuses on bilateral relations among firms, regardless of the influence of network structure. Future research can extend to multilateral relations as well.

The paper builds up linkages among theories of network resources, organizational learning and technological innovation to open the black‐box of how relational embeddedness acts on technological innovation. It is a supplement to the existing research on inter‐firm network theories in developing countries.

Copula modeling enables the analysis of multivariate count data that has previously required imposition of potentially undesirable correlation restrictions or has limited attention to models with only a few outcomes. This article presents a method for analyzing correlated counts that is appealing because it retains well-known marginal distributions for each response while simultaneously allowing for flexible correlations among the outcomes. The proposed framework extends the applicability of the method to settings with high-dimensional outcomes and provides an efficient simulation method to generate the correlation matrix in a single step. Another open problem that is tackled is that of model comparison. In particular, the article presents techniques for estimating marginal likelihoods and Bayes factors in copula models. The methodology is implemented in a study of the joint behavior of four categories of US technology patents. The results reveal that patent counts exhibit high levels of correlation among categories and that joint modeling is crucial for eliciting the interactions among these variables.

The purpose of this study is to investigate the heat resistance and heat-resistant oxygen aging of 4-nitrophthalonitrile-etherified cardanol-phenol-formaldehyde (PPCF) to further use and develop the resin as the matrix resin of high-temperature resistant adhesives and coatings.

PPCF resin was synthesized by 4-nitrophthalonitrile and cardanol-phenol-formaldehyde (PCF). The structures of PPCF and PCF were investigated by Fourier transform infrared, differential scanning calorimetry and proton nuclear magnetic resonance. In addition, the heat resistance and processability of PPCF and PCF resins were studied by dynamic mechanical analysis, thermogravimetric analysis, scanning electronic microscopy (SEM), X-ray diffraction (XRD) techniques and rheological studies.

The results reveal that PPCF forms a cross-linked network at a lower temperature. PPCF resin has excellent resistance under thermal aging in an air atmosphere and that it still had a certain residual weight after aging at 500°C for 2 h, whereas the PCF resin is completely decomposed.

4-Nitrophthalonitrile was introduced into PCF resin, and XRD and SEM were used to investigate the high temperature residual carbon rate and heat-resistant oxygen aging properties of PPCF and PCF resins.

The purpose of this study was to investigate the microstructural evolution and hydrolytic stability of poly(phenylborosiloxane) (PPhBS) to further use and develop the oligomers as heat-resistant modifiers.

PPhBS was synthesized by direct co-condensation of boric acid (BA) and phenyltriethoxysilane (PTEOS). The structural evolution of PPhBS at high temperature was investigated by Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), differential thermal analysis (DTA), in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and 29Si nuclear magnetic resonance (NMR) spectroscopy. In addition, the change in the morphology of the PPhBS powder was examined to demonstrate the evolution of the chemical bonds, and the hydrolytic stability of PPhBS was investigated by a combination of X-ray diffraction (XRD) analysis, measurement of the mass loss in water and FTIR spectroscopy.

The results revealed that a cross-linking network was gradually formed with increasing temperature through the condensation of the residual hydroxyl groups in PPhBS, and the Si-OH and B-OH bonds remained even at a high temperature of 450°C. Furthermore, heat treatment improved the hydrolytic stability of the oligomer. The hydrolysis of the B-O-B bonds in PPhBS was reversible, whereas the Si-O-Si and Si-O-B bonds were highly resistant to hydrolysis.

The prepared PPhBS can be used as a heat-resistant modifier in adhesives, sealants, coatings and composite matrices.

Investigation of the structural evolution of a polyborosiloxane at high temperature by DRIFTS is a novel approach that avoided interference from moisture in the air. The insoluble mass fraction and the FTIR spectrum of PPhBS washed with water were used to investigate the hydrolytic stability of PPhBS.

Online employee reviews have emerged as a crucial information source for business managers to evaluate employee behavior and firm performance. The purpose of this paper is to test the relationship between employee personality traits, derived from online employee reviews and job satisfaction and turnover behavior at the individual level.

The authors apply text-mining techniques to extract personality traits from online employee reviews on Indeed.com based on the Big Five theory. They also apply a machine learning classification algorithm to demonstrate that incorporating personality traits can significantly enhance employee turnover prediction accuracy.

Personality traits such as agreeableness, conscientiousness and openness are positively associated with job satisfaction, while extraversion and neuroticism are negatively related to job satisfaction. Moreover, the impact of personality traits on overall job satisfaction is stronger for former employees than for current employees. Personality traits are significantly linked to employee turnover behavior, with a one-unit increase in the neuroticism score raising the probability of an employee becoming a former employee by 0.6%.

These findings have implications for firm managers looking to gain insights into employee online review behavior and improve firm performance. Online employee review websites are recommended to include the identified personality traits.

This study identifies employee personality traits from automated analysis of employee-generated data and verifies their relationship with employee satisfaction and employee turnover, providing new insights into the development of human resources in the era of big data.

The purpose of this study is to reveal the underlying mechanism in film formation of oil-in-water (O/W) emulsion.

This study focuses on the film forming characteristics of O/W emulsion between the surface of a steel ball and a glass disc coated with chromium. The lubricant film thicknesses of O/W emulsion with various mechanical stirring strength were discussed, which were observed by technique of relative optical interference intensity.

The authors directly observed the oil pool in the contact area, finding the size of oil pool was closely related to the film-forming ability of emulsion. Enrichment phenomenon occurs in oil pool, which was caused by phase inversion. Further investigations revealed that the emulsion is stable with strong stirring strength, resulting in a smaller oil pool size and worse film forming ability.

With the wide usage of O/W emulsion in both biological and industrial systems, the ability of emulsion film formation is considered as an important factor to evaluate the lubrication effectiveness.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-12-2022-0354/

This paper summarizes the severity of global warming, collaboration and endeavor within international government and the trend of international development for “energy-saving and emission reduction.” The Chinese government is enduring high pressure under the environment of “global warming” and “energy-saving and emission reduction” and it has made a policy for “energy-saving and emission reduction.” Based on this, we analyzed the possibility and feasibility for our logistics to “energy-saving and emission reduction,” then propose some solutions for our logistics industry to development and “energy-saving and emission reduction.”

Recognizing every worker's working status instead of only describing the existing construction activities in static images or videos as most computer vision-based approaches do; identifying workers and their activities simultaneously; establishing a connection between workers and their behaviors.

Taking a reinforcement processing area as a research case, a new method for recognizing each different worker's activity through the position relationship of objects detected by Faster R-CNN is proposed. Firstly, based on four workers and four kinds of high-frequency activities, a Faster R-CNN model is trained. Then, by inputting the video into the model, with the coordinate of the boxes at each moment, the status of each worker can be judged.

The Faster R-CNN detector shows a satisfying performance with an mAP of 0.9654; with the detected boxes, a connection between the workers and activities is established; Through this connection, the average accuracy of activity recognition reached 0.92; with the proposed method, the labor consumption of each worker can be viewed more intuitively on the visualization graphics.

With this proposed method, the visualization graphics generated will help managers to evaluate the labor consumption of each worker more intuitively. Furthermore, human resources can be allocated more efficiently according to the information obtained. It is especially suitable for some small construction scenarios, in which the recognition model can work for a long time after it is established. This is potentially beneficial for the healthy operation of the entire project, and can also have a positive indirect impact on structural health and safety.