Qihua Cai

Dr. Qihua Cai

School of Business, Zhengzhou University, Zhengzhou, Henan, China
orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 January 2024 in Innovation and Green Development
Verified
Journal Article
Open access
XHXinyu Han
Xinyu Han
QCQihua Cai
Qihua Cai

8 February 2024 in Social Indicators Research
Verified
Journal Article
Closed access
PDF file
FWFang Wang
Fang Wang
XZXixi Zhang
Xixi Zhang
CYChuwen Ye
Chuwen Ye
QCQihua Cai
Qihua Cai

25 September 2024 in Frontiers in Sustainable Food Systems
Verified
Journal Article
Open access
PDF file
QCQihua Cai
Qihua Cai
XHXinyu Han
Xinyu Han
Green is the foundation of agricultural development. By leveraging modern information technology, digital village construction injects new momentum into the green growth of agriculture. Using balanced panel data from 31 provinces in China from 2011 to 2022, this paper employs the entropy approach and SBM-GML index to measure the indicators of digital village construction and agricultural green total factor productivity (AGTFP). The impacts and mechanisms of digital village construction on AGTFP are examined through fixed effect, mediating effect, and threshold models. The findings are as follows: (1) AGTFP in China shows an overall increasing trend from 2011 to 2022, with significant growth in the western region compared to the eastern and central regions. (2) Digital village construction significantly accelerates the improvement of AGTFP, a conclusion supported by robustness tests. (3) Mechanism analysis indicates that digital village construction advances AGTFP by fostering agricultural technology innovation, enhancing agricultural human capital, and improving agricultural productive services. (4) Digital village construction has a more significant impact on major grain-producing areas, economically underdeveloped areas, and northern region compared to other regions. (5) Environmental regulation acts as a threshold effect on the impact of digital village construction on AGTFP. Digital village construction substantially impacts AGTFP when environmental regulation is below the threshold, with the positive effect continuing beyond this point but at a reduced intensity.

11 July 2022 in Frontiers in Public Health
Verified
Journal Article
Open access
YZYi Zhang
Yi Zhang
QCQihua Cai
Qihua Cai
Traditional urbanization has stimulated economic growth. Meanwhile, it has damaged the natural environment. China has initiated new urbanization to resolve this dilemma. This paper aims to clarify the relationship between new urbanization and environmental pollution and prove new urbanization's superiority in containing environmental pollution. Thus, this paper adopts the static and dynamic spatial Durbin and mediating effect models to estimate the environmental pollution control mechanism of the new urbanization, using the panel data collected from 285 prefecture-level cities in China from 2003 to 2018. Findings show that: (1) Environmental pollution has time inertia and spatial spillover effect. The degree of pollution in an area is related to the environmental quality in the earlier stage and the surrounding areas. (2) The role of new urbanization in containing environmental pollution can take effect in the long run. In the short term, population urbanization can restrain the environmental pollution of both local and surrounding cities. (3) Heterogeneity analysis shows that the higher the level of environmental pollution, the greater the impact of new urbanization on environmental pollution. (4) Mediating effect test shows that technological effect and industrial structure upgrading are two important channels for new urbanization to reduce environmental pollution. (5) Threshold effect test shows that the inhibition effect of new urbanization on environmental pollution is gradually enhanced after crossing the threshold.

1 February 2016 in China Agricultural Economic Review
Verified
Journal Article
Closed access
QCQihua Cai
Qihua Cai
YZYuchun Zhu
Yuchun Zhu
QCQihui Chen
Qihui Chen
Purpose: – The purpose of this paper is to examine the roles social networks play in households’ contribution to the provision of small hydraulic facilities (SHFs) in rural China.Design/methodology/approach: – This paper adopts a sample-selection ordered probit model (Greene and Hensher, 2010) to estimate the impacts of overall social-network intensity, of the number of strong ties (relatives), and of the number of weak ties (friends), using data on 1,064 representative households collected from three provinces (Inner Mongolia, Ningxia, and Shandong).Findings: – The numbers of strong ties and weak ties both have significant impacts on households’ willingness to contribute to SHFs provision, but only the latter has a significant impact on their level of contribution. More specifically, a one standard deviation increase in the number of weak ties (i.e. friends) is associated with a 6.6 percent increase in households’ propensity of contributing more than 550 yuan and a 8.2 percent decrease in their propensity of contributing less than 100 yuan.Originality/value: – This paper is the first to examine the impacts of social networks on households’ contribution to SHFs provision in rural China. Its finding is of great policy relevance-fostering and maintaining social networks (e.g. through rural cooperatives) can significantly increase households’ contribution to public-good provision.

27 July 2018 in China Agricultural Economic Review
Verified
Journal Article
Closed access
MZMin Zhong
Min Zhong
YZYuchun Zhu
Yuchun Zhu
QCQihui Chen
Qihui Chen
LTLiu Tianjun
Liu Tianjun
QCQihua Cai
Qihua Cai
Purpose: The purpose of this paper is to examine how households’ engagement in concurrent business (CB), which is measured by the contribution of off-farm income to household income, affects the farm size–technical efficiency (TE) relationship in Northern China.Design/methodology/approach: This paper applies a stochastic frontier analysis method to analyze data on 1,006 rural households collected from four major wheat-producing provinces in Northern China, adopting a translog specification for the underlying production function.Findings: The analysis yields three findings. First, the farm size–TE relationship is inverted U-shaped for all CB engagement levels higher than 5 percent, and the most technically efficient farm size increases with the level of household CB engagement. Second, how TE varies with the level of CB engagement depends on farm size: an inverted-U relationship for relatively small farms (20μ). Finally, the overall TE score, 0.88, suggests that wheat output can be increased by 12 percent in Northern China if technical inefficiency were eliminated.Originality/value: Unlike most previous studies that examine the impacts of farm size and households’ off-farm business involvement separately, this paper examines how these two factors interact with each other.