Enlightenment of Big Data Thinking on the Construction of Scientific Research Performance Evaluation System for Humanities Teachers in Local Universities

Author(s):  
Ermi Zhang ◽  
Wanbing Shi
2020 ◽  
Author(s):  
Nadia Sanee ◽  
Leila Nemati-Anaraki ◽  
Shahram Sedghi ◽  
Abdolreza Noroozi Chakoli

Abstract In this qualitative study, the trends analysis based on scoping review and interview used to identify the driving forces affecting the future of research performance evaluation. MAXQDA version 10 and thematic analysis were used to analyze the interviews and documents. The social trends included the research social impact, the social development of society, increasing researchers’ awareness of the research evaluation importance, lack of research culture in society, the gender gap in society, and employing human resources. The technological trends were the development of information and communication technology, scientometric indicators, and open science. The economic trends and driving forces included not emphasize on the oil economy merely, research grant, economic evaluation of research, and research budget. The environmental trends and driving forces were increased emphasis on green information, using the green environment components in research institutes, and a favorable organizational environment. The political trends and driving factors included scientific diplomacy, a country's domestic policy, war and political sanctions, research performance evaluation system, optimal research policy, and increased research collaboration. The results showed that various social, technological, economic, environmental, and political factors and indicators must be included and normalized in the national and international research performance evaluation system.


SAGE Open ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 215824401990125 ◽  
Author(s):  
Guangchao Charles Feng

China’s scientific achievement has received considerable international attention due to a large amount of research and development (R&D) spending. This article aims to study the performance of China’s R&D expenditures (in the form of research funding) by examining the research performance of individual researchers based on bibliometric measures. This study concludes that research practice is not merely determined by capital possessed. Besides, international collaboration primarily accounts for research performance of scholars, whereas research funding and publishing in Chinese-based journals do not impact research performance significantly.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Honglin Fu

This paper uses a multidimensional big data matrix model to optimize the analysis and conduct a systematic construction of the enterprise performance evaluation system. The adoption of new research methods and perspectives to promote the study of the use of performance information is of great significance to achieve the effectiveness, science, and sustainability of corporate performance management. To solve the problem of objectivity and scientificity of performance information use, this part attempts to analyze performance information use from the perspective of the multidimensional big data matrix, focusing on the techniques and methods in the process of promoting performance information use from the multidimensional big data matrix and tries to construct a system model of enterprise performance information use from two dimensions: the use of performance information sources and the use of performance information results. Based on multiple theoretical hypotheses, a theoretical and empirical basis is provided for the division of demand dimensions of enterprise performance evaluation system. Through social capital theory, three dimensions of network social capital, cognitive social capital, and structural social capital are hypothesized, and the logistic regression method is applied for empirical study. The results show that these three dimensions have significant effects on the knowledge demand of enterprise performance evaluation systems. It is verified that the multidimensional big data matrix can enhance the quality of performance information sources and improve the objectivity of performance information. In the performance information source use dimension, the analysis verified that the collection and preprocessing technology of big data can realize the automation, real-time, and diversification of information collection and preprocessing, and enhance the objectivity of performance information. Big data helps to improve the quality and effectiveness of performance information results use. In the dimension of using performance information results, the distributed computing and analysis processing technology of big data can assist the decision support system, and the use of information can be shifted from micromanagement to decision support, to realize the scientific use of performance information and improve the quality of enterprise management decisions.


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