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Yin Jian-zhong

Bio: Yin Jian-zhong is an academic researcher from Hunan City University. The author has contributed to research in topics: Financing cost & Internal financing. The author has an hindex of 1, co-authored 4 publications receiving 4 citations.

Papers
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Proceedings ArticleDOI
14 Jun 2015
TL;DR: In this article, a comprehensive fuzzy evaluation model of SMEs is established by fuzzy evaluation method in order to evaluate the overall SMEs' overall financing efficiency, which will provide guidance for SMEs to make financing decisions.
Abstract: The financing efficiency evaluation of small and medium-sized enterprises (SME) is fuzzy. The comprehensive fuzzy evaluation model of SMEs will be established by fuzzy evaluation method in this paper. The financing efficiency of such five different kinds of financing methods as internal financing, financing of stocking and bond, bank loan and private lending of SMEs will be analyzed in the terms of financing cost, fund utilization rate, financing risk, freedom degree of financing body and market maturity, and companies' overall financing efficiency will be accordingly analyzed, which will provide guidance for SMEs to make financing decisions.

3 citations

Journal Article
TL;DR: In this article, the difference between the internal and external financing of private enterprises is compared and analyzed from six aspects, such as financing cost, and evaluate their whole financing efficiency synthetically in order to provide a direction for the private enterprises to make financing decisions.
Abstract: Taking different development stages of private enterprises as a clue,the writer compares and analyzes the difference between the internal financing,the creditor’s rights financing and stakeholder’s right financing from six aspects,such as financing cost,and evaluates their whole financing efficiency synthetically in order to provide a direction for the private enterprises to make financing decisions.

1 citations

Proceedings ArticleDOI
01 Nov 2016
TL;DR: Wang et al. as mentioned in this paper adopted normative analysis, descriptive statistics analysis and multivariate linear regression analysis method, uses Stata14.0 measuring software, and selects 797 listed manufacturing companies’ financial data in Shanghai and Shenzhen between 2010 and 2014, to study the influence of debt maturity, debt source on company performance.
Abstract: To achieve the research aim of optimizing the debt financing structure, and enhancing company performance, this paper adopts normative analysis, descriptive statistics analysis and multivariate linear regression analysis method, uses Stata14.0 measuring software, and selects 797 listed manufacturing companies’ financial data in Shanghai and Shenzhen between 2010 and 2014, to study the influence of debt maturity, debt source on company performance. The research results show that the listed manufacturing companies’ debt financing structure is unreasonable. It relies heavily on current debt whose debt sources are mainly bank loans and commercial credit. Current debt or non-current debt, bank loan, commercial credit, or bonds payable all have negative correlation with company performance. Therefore they are not conducive to improve company performance.

1 citations

Proceedings ArticleDOI
14 Jun 2015
TL;DR: In this article, the authors analyzed the impact of the financing structure on the profitability of listed SMEs in Hunan and found that their financing structures play a negative role in their profitability and their finance structures are irrational.
Abstract: On the basis of analyzing the financing structure and current profitability of listed SMEs in Hunan, empirical analysis of the impacts that the financing structure make on profitability of Hunan listed SMEs will be given in this paper, the results of which indicate that their financing structures play a negative role in their profitability and their financing structures are irrational

1 citations


Cited by
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Dissertation
01 Jan 2017
TL;DR: An imputation based on FCM and Particle Swarm Optimization has been developed to get better imputation values and therefore, increased the accuracy of Decision Tree classification.
Abstract: Data mining techniques are used in various industries, including database marketing, web analysis, information retrieval and bioinformatics to gain a better knowledge extraction. However, if data mining techniques are applied on real datasets, a problem that often comes up is that missing values occur in the datasets. Since the missing values may confuse the data mining process and causing the knowledge extracted unreliable, there is a need to handle the missing values. Therefore, researchers are coming out with imputation methods in the preprocessing stage. Although there are many imputation methods such as Mean, k-Nearest Neighbor (k- NN) and Fuzzy C-Means are implemented by other researchers, accuracy for the replace values is still in infancy. In this study, an imputation based on FCM and Particle Swarm Optimization (PSO) has been developed to get better imputation values. FCM has ability to cluster the data into two or more subsets with the different membership values and gives better coverage to find the correlation between the dataset. While, PSO is a swarm optimization algorithm that effectively find the optimum imputation values with less parameters to adjust. Then, FCMPSO was trained with seven artificial missing ratios from 1% to 30% for Cleveland Heart Disease dataset and real missing values in Framingham Heart Disease dataset to get the complete dataset. Then, the complete dataset was trained with Decision Tree algorithm to observe the performance in terms of accuracy. The FCMPSO results gives a better RMSE value for 30% missing ratios with 0.0237 compared to Mean, k- NN, and FCM with 0.0250, 0.0402 and 0.0249 respectively. Next, the analysis of proposed imputation on classification accuracy shows an improvement with 81.67% for Cleveland Heart Disease and 86.3% for Framingham Heart Disease compared to other imputation methods. Based on the results, the imputation values are slightly accurate compared to other imputation methods and therefore, increased the accuracy of Decision Tree classification.

2 citations

Proceedings ArticleDOI
01 Nov 2020
TL;DR: Wang et al. as mentioned in this paper analyzed the relationship between debt financing structure and company financial performance in the domestic mining industry and provided suggestions for improving the debt finance structure and financial performance.
Abstract: As an important financial decision, debt financing plays an important role in company development. In order to effectively analyze the interactive relationship between debt financing structure and company financial performance, this article takes debt financing structure as the research object and expounds the relevant theories of debt financing structure and company financial performance. Taking the domestic mining industry as an example, the corresponding economic model is established. Based on the characteristics of China's mining industry, the current situation of the debt financing structure of listed companies in the industry and the relationship between debt financing structure and finance are analyzed by using empirical analysis methods. The performance of listed mining companies. Finally, based on the empirical results, relevant conclusions are given, and suggestions for improving debt financing structure and financial performance are put forward.

1 citations

Book ChapterDOI
01 Jan 1999
TL;DR: The guidance in this chapter is applicable to financial periods ending on or after 31 December 1998 and corresponds with the effective date of the Combined Code (see chapter 7) and APB Bulletin 1998/10 Corporate governance reporting and auditors' responsibility statements as mentioned in this paper.
Abstract: The guidance in this chapter is applicable to financial periods ending on or after 31 December 1998. This corresponds with the effective date of the Combined Code (see chapter 7) and APB Bulletin 1998/10 Corporate governance reporting and auditors’ responsibility statements. This chapter addresses reporting on the annual report, preliminary announcement or interim financial statement of a listed company. It does not deal with other reports that may be required by the London Stock Exchange.

1 citations

Journal ArticleDOI
TL;DR: In this paper, the authors analyzed the venture financing of farmers losing land to urban new district construction, taking Luonan New District as an example, from the aspects of financing channels, financing scales, financing costs, financing income and financing efficiency.
Abstract: Taking Luonan New District as an example, from the aspects of financing channels, financing scales, financing costs, financing income and financing efficiency this article analyzes the venture financing of farmers losing land to urban new district construction. It is believed that internal financing plays a main part, but its proportion decreases year by year; the limitation of self-accumulation and institutional supply makes the financing demand of farmers losing land unable to be met; and internal financing efficiency is higher than external financing efficiency. Therefore, a resultant force from the farmers losing land, the government, the society and the community should be formed, so as to solve the problem of the venture financing of farmers losing land.
Proceedings ArticleDOI
05 Jan 2023
TL;DR: In this paper , the authors explored how fuzzy logic may be used in the realm of financial management and evaluated the expansion of small and medium-sized businesses using the unique fuzzy linguistic decision-making approach.
Abstract: There are numerous obstacles to the long-term success of small and medium-sized businesses as a result of rising rivalry and pervasive internal inconsistencies caused by the economy's breakneck expansion (SMEs). Because it represents both the company's current development status and its possible future prospects, a scientific evaluation of the company's capacity for sustainable growth is crucial. To make the best decisions as a group, it's helpful to employ both linguistic term sets and tentative fuzzy preference relations. E-commerce activities have been encouraged as a means to improve corporate efficiency thanks to the recent technological revolution and the growth of the digital economy. Increasing online store revenue by utilising MIS and AI is a well-established practice. That technique has grown in significance for modern corporate operations. The survival and growth of micro, small, and medium-sized businesses is an ongoing issue in every region of the world. This funding is crucial for SMEs. Machines, robots, and industrial engineering in general have greatly benefited from the application of fuzzy logic. In this chapter, we will explore how fuzzy logic may be used in the realm of financial management. As a result of globalisation, an intricate web of connections has emerged in the corporate world. This means that the elements influencing businesses' financial health are more numerous, complicated, and uncertain in a free market economy. Under the uncertain fuzzy language setting, this study presents a new method utilising a multiplicative consistency adjustment technique. Finally, The expansion of small and medium-sized businesses has been a driving force in the nation's enterprises (SMEs) will be evaluated using the unique fuzzy linguistic decision-making approach. A comparison with existing methods is done to find out what the proposed method is good for and if it can work.