Organizational support theory (OST) proposes that employees form a generalized perception concerning the extent to which the organization values their contributions and cares about their well-being ...(perceived organizational support, or POS). Based on hypotheses involving social exchange, attribution, and self-enhancement, we carried out a meta-analytic assessment of OST using results from 558 studies. OST was generally successful in its predictions concerning both the antecedents of POS (leadership, employee–organization context, human resource practices, and working conditions) and its consequences (employee’s orientation toward the organization and work, employee performance, and well-being). Notably, OST successfully predicted the relative magnitudes of different relationships, influences of process variables, and mediational effects. General implications of the findings for OST and research on POS are discussed.
•The two-stage RUL prediction framework is investigated in this paper.•The two-level alarm mechanism is proposed to detect FPT of each entity adaptively.•DSCN-DTAM is built for cross-domain ...prognostic with incomplete target domain data.•Double transferable attention mechanism is designed for the fined-grained transfer.•Four transfer prognostic tasks verify the effectiveness of the proposed method.
The remaining useful life (RUL) prediction provides an essential basis for improving mechanical equipment reliability. In practical application, the variant of working conditions and incomplete degradation data seriously deteriorate the performance of the prognostic models. In order to conquer this problem, a two-stage RUL prediction method is proposed for the cross-domain prognostic task with insufficient degradation data. At first, the two-level alarm mechanism is employed to detect the first predicting time (FPT) of each mechanical entity adaptively. Then, the deep separable convolutional network with the double transferable attention mechanism (DSCN-DTAM) is proposed to construct the cross-domain prognostic model. In DSCN-DTAM, multiple regularization strategies can guide the model to extract domain-invariant features, and the double transferable attention mechanism is designed to select the degradation information with high transferability. Finally, the proposed method is verified by multiple transfer prognostic tasks designed by two bearing datasets. Compared with other methods, the proposed method shows superior performance.
The world of work is changing. Communications technologies and digital platforms have enabled some types of work to be delivered from anywhere in the world by anyone with a computer and an internet ...connection. This digitally-mediated work brings jobs to parts of the world traditionally characterized by low incomes and high unemployment rates. As such, it has been touted by governments, third-sector organizations, and the private sector as a novel strategy of economic development. Drawing on a four-year study with 65 workers in South Africa, Kenya, Nigeria, Ghana and Uganda, we examine the development implications of the gig economy on labour in Africa. We offer four analytical development dimensions through which platform-based remote work impacts the lives and livelihoods of African workers, i.e. freedom, flexibility, precarity and vulnerablity. We argue that these dimensions should be understood in a continuum to better explain the working conditions and lives of workers in the gig economy.
Automatic and reliable fault diagnosis of rotating machinery cross working conditions is of practical importance. For this purpose, ensemble transfer convolutional neural networks (CNNs) driven by ...multi-channel signals are proposed in this paper. Firstly, a series of source CNNs modified with stochastic pooling and Leaky rectified linear unit (LReLU) are pre-trained using multi-channel signals. Secondly, the learned parameter knowledge of each individual source CNN is transferred to initialize the corresponding target CNN which is then fine-tuned by a few target training samples. Finally, a new decision fusion strategy is designed to flexibly fuse each individual target CNN to obtain the comprehensive result. The proposed method is used to analyze multi-channel signals measured from rotating machinery. The comparison result shows the superiorities of the proposed method over the existing deep transfer learning methods.
•CNN is modified with stochastic pooling and Leaky rectified linear unit.•Multi-channel signals are used to pre-train a series of CNNs.•Transfer CNN is constructed with parameter transfer strategy.•A new decision fusion strategy is designed based on flexible weight assignment.
...conditions such as free accommodation, free meals, and maid service, which suggest valued and respected employees, are replaced with the grudging provision of limited mileage allowance for on-call ...shifts, which suggests that employees are viewed as commodities whose long term loyalty and morale are of no consequence.
Commuting can be tiring and stressful. An unavoidable part of life for many people, it is almost always associated with negative outcomes. This study examined the implications of commuting time for ...the commitment and well-being of employees. This paper uses 'conservation of resources' theory and job demands-resources approaches to argue that employees with long commutes will be less committed and experience lower well-being. These effects are also expected to be mediated by the work-life balance of the employees and interact with the level of autonomy they perceive themselves to have. Data from the fifth European Working Conditions Survey indicate that there is a negative relationship between commuting time, commitment and well-being. Results also suggest that work-life balance mediates part of these relationships and, finally, that autonomy can act as a buffer against the effects of commuting time on both commitment and well-being.
The deregulation policies implemented in the United States and the European Union in the early 1980s brought forth a significant rise in employment in the field of logistics but at the same ...contributed to a deterioration of work conditions in the industry – a paradoxical situation largely invisible to many in the age of online shopping. In recent years, a number of cinematographers showed interest in this type of work, depicting it in documentaries. Referring to one of these films, The Weight of Dreams (Francesco Mattuzzi, 2015), this review analyses the implications of the deregulation policies over work conditions, focusing on the relation between workers and space. As seen in the film, work in the field of logistics is a struggle between the desire for an efficient movement of goods and the desires of the humans who move the goods. This translates into an ambivalence of the space they use, which on the one hand, is planned for movement, but on the other, is appropriated by users with the illusion of a sedentary life.
•A novel method called DRHRML is proposed for bearing fault diagnosis with small samples under different working conditions.•Improved sparse denoising autoencoder (ISDAE) is proposed to preprocess ...the raw vibration data.•Two novel task datasets are constructed for verifying the proposed method.
Recently, intelligent fault diagnosis has made great achievements, which has aroused growing interests in the field of bearing fault diagnosis due to its strong feature learning ability. Sufficient bearing fault samples are taken for granted in existing intelligent fault diagnosis methods generally. In practice, however, the lack of fault samples has been a knotty problem. Therefore, in this paper, a novel method called data reconstruction hierarchical recurrent meta-learning (DRHRML) is proposed for bearing fault diagnosis with small samples under different working conditions. This approach contains data reconstruction and meta-learning stages. In the data reconstruction stage, noise is reduced and the useful information hidden in the raw data is extracted. In the meta-learning stage, the proposed method is trained by a recurrent meta-learning strategy with one-shot learning way. This approach is demonstrated on the bearing fault database with 92 working conditions from Case Western Reserve University and with 56 working conditions from laboratory. Results show that the proposed method is effective for bearing intelligent fault diagnosis with small samples under different working conditions.
Objective: a hygienic assessment of working conditions and an analysis of the morbidity of aircraft workers. Materials and methods : the study was carried out on the basis of data from the Office of ...the Federal Service for Supervision of Consumer Rights Protection and Human Well-Being in the Republic of Tatarstan (Tatarstan) and the Center for Occupational Pathology Scientific and Clinical Center for Preventive Medicine of the Institute of Fundamental Medicine and Biology of the Kazan (Volga Region) Federal University. Results: hygienic monitoring of the working conditions of employees of the aviation plant showed a combined effect of harmful factors of the production environment and the labor process, corresponding to classes 3.1–3.2 in a number of professions. Among the diseases identified in employees of the enterprise, diseases of the eye and its accessory apparatus, circulatory organs and hearing predominate. According to the results of the medical examination, 6.4% of the subjects were found to have a suspicion of occupational chronic bilateral sensorineural hearing loss. Conclusions : research results indicate that there is a risk of developing occupational pathology as a result of exposure to physical factors. The employer was given recommendations to improve working conditions and preserve the health of workers.
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