Identifying Determinants of Branch Performances in <scp>A</scp>gricultural <scp>B</scp>ank of <scp>C</scp>hina: A Spatial Econometric Approach

Liu, Yicheng; Yang, Wen; Mai, Chao-Cheng

doi:10.1111/twec.12194

Cited by 3 publications

(3 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…They have strong purchasing power when it comes to agricultural machinery. Therefore, the level of economic development makes the largest contribution to the improvement in the AEL [21]. The basis for the operation of agricultural machinery is the land resource.…”

Section: Discussionmentioning

confidence: 99%

“…In addition to factors such as regional economic development, land resources, as well as policy and environment, the AML in a country depends on the improvement of its AEL [7,18]. The factors affecting the AEL have also been studied in existing literature [1,[19][20][21][22]. Liu and Tian [1] found that the level of economic development is the most important factor affecting the AEL in China, followed by the scale of farmland management and the agricultural planting structure.…”

mentioning

confidence: 99%

“…The dependent variable is also set to a single indicator, due to the limitations of the methods used. For example, one can use the total power of agricultural machinery per laborer or use the total power of agricultural machinery to express the AEL [15,21], or use the weighted averages of 0.4, 0.3, and 0.3 to indicate the ploughing, seeding, and harvesting mechanization levels, respectively [24]. Such practices cannot fully reflect the AEL and AML.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Study on Factors Affecting the Agricultural Mechanization Level in China Based on Structural Equation Modeling

Wei

Zhu

et al. 2018

Sustainability

View full text Add to dashboard Cite

The subsidy policy for the purchase of agricultural machinery and China's Agricultural Mechanization Promotion Law have been implemented since 1998 and 2004, respectively. The goal of the policy and the law is to improve the agricultural mechanization level (AML) in China. Policymakers expect that the AML could be increased by improving the agricultural equipment level (AEL). The AML in China is affected by many factors. However, only a few studies have investigated the effects of the AEL on the AML. To fill this gap, we built an integrative conceptual framework and estimated a corresponding structural equation model (SEM) using the relevant data collected from 30 provinces (cities and districts) in mainland China. The relevant data cover the years from 2001 to 2014. There are six factors in our framework, including AEL, level of economic development, land resource endowment, benefit factors, policy and environmental factors, and demographic factors. The results showed that the AEL had the greatest impact on the AML. The level of economic development, the demographic factors, and the benefit factors not only directly affected China's AML but also indirectly affected the AML through the AEL. Meanwhile, land resource endowment and policy and environmental factors had only an indirect effect on the AEL. This report can be used to inform the government that the improvement of the AEL is one of the important ways to achieve the comprehensive mechanization of China's agriculture, that the agricultural machinery purchase subsidies must still be enhanced and that the enforcement of China's Agricultural Mechanization Promotion Law must still be strengthened.Sustainability 2019, 11, 51 2 of 16 rural laborer, and low farmer income levels [3]. These conditions effectively prevent China from following the development path of using large-scale agricultural machinery, like that purchased by farmers in European and American countries. Correspondingly, China cannot follow the path of using small-scale agricultural machinery with higher value, like that purchased by Japanese and Korean farmers. With the development of agricultural mechanization, however, China has explored its own road to mechanization.China's agriculture has experienced a large expansion of machine investments by farmers and machine rental services provided by specialized agents, which has contributed to the mechanization of agricultural production [4][5][6]. Previous literature on the agricultural mechanization in China has concluded that the agricultural mechanization has increased the grain yield and ensured food security in China [7][8][9]. At present, the agricultural mechanization in China is in the transition period from whole process mechanization to comprehensive mechanization [10]. The development of agricultural mechanization was consistent with China's new-type urbanization [11]. Because of the continuous advancement of China's urbanization process and the massive transfer of rural labor, China's agriculture is developing toward a reliance on more mac...

show abstract

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Study on Factors Affecting the Agricultural Mechanization Level in China Based on Structural Equation Modeling

Wei

Zhu

et al. 2018

Sustainability

View full text Add to dashboard Cite

show abstract

Spatial autocorrelation patterns among US commercial banks: before, during and after the subprime mortgage crisis

Parnes

2022

Applied Economics

View full text Add to dashboard Cite

Investigation of the factors driving engineering insurance consumption in China’s construction industry: a hybrid approach

Zhou,

Wang,

Gong

2024

ECAM

View full text Add to dashboard Cite

PurposeGiven the increasing importance of engineering insurance, it is still unclear which specific factors can enhance the role of engineering insurance as a risk transfer tool. This study aims to propose a hybrid approach to identify and analyze the key determinants influencing the consumption of engineering insurance in mainland China.Design/methodology/approachThe empirical analysis utilizes provincial data from mainland China from 2008 to 2019. The research framework is a novel amalgamation of the generalized method of moments (GMM) model, the quantile regression (QR) technique and the random forest (RF) algorithm. This innovative hybrid approach provides a comprehensive exploration of the driving factors while also allowing for an examination across different quantiles of insurance consumption.FindingsThe study identifies several driving factors that significantly impact engineering insurance consumption. Income, financial development, inflation, price, risk aversion, market structure and the social security system have a positive and significant influence on engineering insurance consumption. However, urbanization exhibits a negative and significant effect on the consumption of engineering insurance. QR techniques reveal variations in the effects of these driving factors across different levels of engineering insurance consumption.Originality/valueThis study extends the research on insurance consumption to the domain of the engineering business, making theoretical and practical contributions. The findings enrich the knowledge of insurance consumption by identifying the driving factors specific to engineering insurance for the first time. The research framework provides a novel and useful tool for examining the determinants of insurance consumption. Furthermore, the study offers insights into the engineering insurance market and its implications for policymakers and market participants.

show abstract

Identifying Determinants of Branch Performances in Agricultural Bank of China: A Spatial Econometric Approach

Abstract: We would like to thank the associate editor Eden Yu and two anonymous referees for helpful comments and suggestions.

Cited by 3 publications

References 37 publications

Study on Factors Affecting the Agricultural Mechanization Level in China Based on Structural Equation Modeling

Study on Factors Affecting the Agricultural Mechanization Level in China Based on Structural Equation Modeling

Spatial autocorrelation patterns among US commercial banks: before, during and after the subprime mortgage crisis

Investigation of the factors driving engineering insurance consumption in China’s construction industry: a hybrid approach

Contact Info

Product

Resources

About