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Relationship between employees' career maturity and career planning of edge computing and cloud collaboration from the perspective of organizational behavior.

ABSTRACT: A new IoT (Internet of Things) analysis platform is designed based on edge computing and cloud collaboration from the perspective of organizational behavior, to fundamentally understand the relationship between enterprise career maturity and career planning, and meet the actual needs of enterprises. The performance of the proposed model is further determined according to the characteristic of the edge near data sources, with the help of factor analysis, and through the study and analysis of relevant enterprise data. The model is finally used to analyze the relationship between enterprise career maturity and career planning through simulation experiments. The research results prove that career maturity positively affects career planning, and vocational delay of gratification plays a mediating role in career maturity and career planning. Besides, the content of career choice in career maturity is influenced by mental acuity, result acuity and loyalty. The experimental results indicate that when the load at both ends of the edge and cloud exceeds 80%, the edge delay of the IoT analysis platform based on edge computing and cloud collaboration is 10s faster than that of other models. Meanwhile, the system slowdown is reduced by 36% while the stability is increased when the IoT analysis platform analyzes data. The results of the edge-cloud collaboration scheduling scheme are similar to all scheduling to the edge end, which saves 19% of the time compared with cloud computing to the cloud end. In Optical Character Recognition and Aeneas, compared with the single edge-cloud coordination mode, the model with the Nesterov Accelerated Gradient algorithm achieves the optimal performance. Specifically, the communication delay is reduced by about 25% on average, and the communication time decreased by 61% compared with cloud computing to the edge end. This work has significant reference value for analyzing the relationship between enterprise psychology, behavior, and career planning.

SUBMITTER: Zhang R

PROVIDER: S-EPMC8494299 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Implementing the "hierarchical diagnosis and treatment" system highlights the important role of general practitioners as "residents' health gatekeepers." Still, the low level of career growth always limits the realization of their service value. Inertial thinking uses a single factor to explain the complexity of career growth in previous studies; in fact, it isn't easy to assess whether the factor is a sufficient and necessary condition for a high level of career growth. Herein, we have used a set theory perspective to analyze the mechanism of influencing high-level career growth by combining psychological and organizational factors. This research aims to analyze causal complexity relationship between these conditions and results is analyzed in detail. We choose fuzzy-set qualitative comparative analysis (fsQCA) with a sample of 407 GPs to test 5 antecedent conditional variables that can affect their career growth. The variables include professional identity, self-efficacy, achievement motivation, training mechanism, and incentive mechanism. To ensure the universality and diversity of data, the samples were selected from community medical institutions in different regions of China. The results show that three pathways can affect the high career growth of GPs, and the optimal pathway A2 is the linkage matching of high incentive mechanism, high professional identity, high achievement motivation, and high self-efficacy. At the same time, we find that professional identity plays an alternative role in the three pathways. When professional identity is at a high level, as long as achievement motivation and self-efficacy are superior, or achievement motivation, self-efficacy, and achievement motivation are superior, a high level of career growth can be achieved. We broke the shackles of previous studies that only focused on the impact of single factors on the career growth of GPs. From the perspective of set theory, we use configurational thinking to construct Influential pathways of high career growth of GPs by integrating antecedents. The results can provide effective support for improving GPs' service ability and realizing their service value to protect residents' health.

Project description:BackgroundCloud computing is an innovative paradigm that provides users with on-demand access to a shared pool of configurable computing resources such as servers, storage, and applications. Researchers claim that information technology (IT) services delivered via the cloud computing paradigm (ie, cloud computing services) provide major benefits for health care. However, due to a mismatch between our conceptual understanding of cloud computing for health care and the actual phenomenon in practice, the meaningful use of it for the health care industry cannot always be ensured. Although some studies have tried to conceptualize cloud computing or interpret this phenomenon for health care settings, they have mainly relied on its interpretation in a common context or have been heavily based on a general understanding of traditional health IT artifacts, leading to an insufficient or unspecific conceptual understanding of cloud computing for health care.ObjectiveWe aim to generate insights into the concept of cloud computing for health IT research. We propose a taxonomy that can serve as a fundamental mechanism for organizing knowledge about cloud computing services in health care organizations to gain a deepened, specific understanding of cloud computing in health care. With the taxonomy, we focus on conceptualizing the relevant properties of cloud computing for service delivery to health care organizations and highlighting their specific meanings for health care.MethodsWe employed a 2-stage approach in developing a taxonomy of cloud computing services for health care organizations. We conducted a structured literature review and 24 semistructured expert interviews in stage 1, drawing on data from theory and practice. In stage 2, we applied a systematic approach and relied on data from stage 1 to develop and evaluate the taxonomy using 14 iterations.ResultsOur taxonomy is composed of 8 dimensions and 28 characteristics that are relevant for cloud computing services in health care organizations. By applying the taxonomy to classify existing cloud computing services identified from the literature and expert interviews, which also serves as a part of the taxonomy, we identified 7 specificities of cloud computing in health care. These specificities challenge what we have learned about cloud computing in general contexts or in traditional health IT from the previous literature. The summarized specificities suggest research opportunities and exemplary research questions for future health IT research on cloud computing.ConclusionsBy relying on perspectives from a taxonomy for cloud computing services for health care organizations, this study provides a solid conceptual cornerstone for cloud computing in health care. Moreover, the identified specificities of cloud computing and the related future research opportunities will serve as a valuable roadmap to facilitate more research into cloud computing in health care.

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Relationship between employees' career maturity and career planning of edge computing and cloud collaboration from the perspective of organizational behavior.

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