Supportive Leadership and Post-Adoption Use of MOOCs

Ahmed, Fawad; Faraz, Naveed Ahmad; Ahmad, Nisar; Iqbal, Muhammad Khalid

doi:10.4018/joeuc.308813

Cited by 8 publications

(3 citation statements)

References 96 publications

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“…This study is based on Memmel, the research indicators of Memmel et al (2015) and Zhirui (2021), and the research methods of Yuan and Yang (2020), Niu and Ling (2021), Wang and Wang (2021) , Dai (2018), Ahmed et al (2022), Wang (2020), Zhao andLi (2019), andTong et al (2019). Yang et al (2022) uses AHP and expert judgment to determine whether the seven attribute indicators of loan term, mortgage guarantee, loan interest rate, loan amount, repayment method, bad debt amount, and overdue days have the greatest impact on the borrower's repayment status, that is, the main factors affecting credit risk.…”

Section: Classification Of Datamentioning

confidence: 99%

Empirical Test of Credit Risk Assessment of Microfinance Companies Based on BP Neural Network

2023

International Journal of Information Technologies and Systems Approach

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In recent years, the chaos of internet finance has occurred frequently, especially P2P, with high risks. As a kind of financial innovation, small loan companies are challenging to avoid alone, and the issue of credit risk is also highly valued. This study selects the loan records of a small loan company (a daily loan record from September 1, 2016 to July 1, 2021 has seven indicators, each of which has 21299 data). It uses MATLAB programming to test the correctness of risk indicator selection and the accuracy of BP neural network classification and identification results. This study obtains the corresponding risk value. According to the corresponding risk value, the newly applied loans are classified, that is, rated, to verify the effectiveness and applicability of this method. Therefore, BP neural network has strong applicability, generalization ability, and portability and is an effective method for small loan companies to guide credit risk assessment.

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Section: Classification Of Datamentioning

confidence: 99%

Empirical Test of Credit Risk Assessment of Microfinance Companies Based on BP Neural Network

2023

International Journal of Information Technologies and Systems Approach

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“…The enterprise system is a crucial component of management that plays a deciding role in resource allocation. Good HR practices positively impact employees' perspectives on using technology, thus encouraging their innovative behavior (Ahmed et al, 2022). Low-efficiency systems would bring about supply and demand disruption, severe lag, utility failure, and other undesirable outcomes.…”

Section: Introductionmentioning

confidence: 99%

Differential Effects of Renqing and System on Employee Work Quality

Xie

Ngan

et al. 2023

Journal of Organizational and End User Computing

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This article investigates how Renqing and the system affect employees' work quality in Chinese culture. The leader-employee matching questionnaires were gathered using data from businesses in China's Beijing, Shanghai, Guangdong, Jiangxi, and Yunnan provinces. The article then uses an empirical analytic method to analyze the data. It uses SPSS25.0 software to process data. The results indicate that the three dimensions of emotion relationship, resource relationship, and norm relationship have an equal impact on the quality of work enjoyment; the system has no substantial effect on employees' work quality, but it regulates the impact of Renqing on work quality. If a Chinese company wants employees that produce high-quality work, the article's conclusions suggest that Renqing should be considered. In the meantime, the company should increase its efforts to improve the efficiency of its system.

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“…Consider engineering bidding documents as an example. The relevant information involved in the international bidding process is shown in Figure 1 (Ahmed et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Design of a Structured Parsing Model for Corporate Bidding Documents Based on Bi-LSTM and Conditional Random Field (CRF)

Zhang

Chen

et al. 2023

International Journal of Information Technologies and Systems Approach

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International projects are often realized through the bidding process, but the existence of information exchange barriers in different countries leads to a complex and tedious bidding process. In this paper, the authors study the complex problem of reading bidding documents, combine the artificial intelligence to analyze them in a structured way, and realize the intelligent analysis of bidding documents. Firstly, through the CRF model, the structured analysis of the tender document is carried out according to the title of the tender document, and the extraction of quoted price, technology and commercial part is realized. Secondly, the detailed analysis of quoted price and technology is completed using the Bi-LSTM method, and the main five key feature extraction and analysis are completed. Finally, based on the CRF-Bi-LSTM method, the actual test is carried out, and the correlation coefficient is as high as 0.965. The results show that the structured parsing model proposed has good application prospects.

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Supportive Leadership and Post-Adoption Use of MOOCs

Cited by 8 publications

References 96 publications

Empirical Test of Credit Risk Assessment of Microfinance Companies Based on BP Neural Network

Empirical Test of Credit Risk Assessment of Microfinance Companies Based on BP Neural Network

Differential Effects of Renqing and System on Employee Work Quality

Design of a Structured Parsing Model for Corporate Bidding Documents Based on Bi-LSTM and Conditional Random Field (CRF)

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