Evaluation of Agricultural Extension Service for Sustainable Agricultural Development Using a Hybrid Entropy and TOPSIS Method

Wang, Zhiguo; Wang, Junbin; Guo-ping, Zhang; Wang, Zhixiong

doi:10.3390/su13010347

Cited by 35 publications

(22 citation statements)

References 62 publications

(72 reference statements)

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“…Teixeira et al (2021) used Entropy to determine the weights of various constructs/criteria and support the AHP [ 22 ]. Wang et al (2021) used an Entropy and TOPSIS mixed method to evaluate agricultural extension service for sustainable agricultural development [ 44 ]. The TOPSIS method was be applied for ranking, while the Entropy method was used to determine the weight with good stability [ 44 ].…”

Section: Literature Reviewmentioning

confidence: 99%

“…Wang et al (2021) used an Entropy and TOPSIS mixed method to evaluate agricultural extension service for sustainable agricultural development [ 44 ]. The TOPSIS method was be applied for ranking, while the Entropy method was used to determine the weight with good stability [ 44 ]. Wei et al (2021) used the Entropy and AHP methods for karst collapse susceptibility assessment, which used AHP to build the structure model according to experts’ judgment [ 45 ].…”

Section: Literature Reviewmentioning

confidence: 99%

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A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement

Zhang

Yan

et al. 2022

PLoS ONE

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Background As the world’s largest coal producer, China was accounted for about 46% of global coal production. Among present coal mining risks, methane gas (called gas in this paper) explosion or ignition in an underground mine remains ever-present. Although many techniques have been used, gas accidents associated with the complex elements of underground gassy mines need more robust monitoring or warning systems to identify risks. This paper aimed to determine which single method between the PCA and Entropy methods better establishes a responsive weighted indexing measurement to improve coal mining safety. Methods Qualitative and quantitative mixed research methodologies were adopted for this research, including analysis of two case studies, correlation analysis, and comparative analysis. The literature reviewed the most-used multi-criteria decision making (MCDM) methods, including subjective methods and objective methods. The advantages and disadvantages of each MCDM method were briefly discussed. One more round literature review was conducted to search publications between 2017 and 2019 in CNKI. Followed two case studies, correlation analysis and comparative analysis were then conducted. Research ethics was approved by the Shanxi Coking Coal Group Research Committee. Results The literature searched a total of 25,831publications and found that the PCA method was the predominant method adopted, and the Entropy method was the second most widely adopted method. Two weighting methods were compared using two case studies. For the comparative analysis of Case Study 1, the PCA method appeared to be more responsive than the Entropy. For Case Study 2, the Entropy method is more responsive than the PCA. As a result, both methods were adopted for different cases in the case study mine and finally deployed for user acceptance testing on 5 November 2020. Conclusions The findings and suggestions were provided as further scopes for further research. This research indicated that no single method could be adopted as the better option for establishing indexing measurement in all cases. The practical implication suggests that comparative analysis should always be conducted on each case and determine the appropriate weighting method to the relevant case. This research recommended that the PCA method was a dimension reduction technique that could be handy for identifying the critical variables or factors and effectively used in hazard, risk, and emergency assessment. The PCA method might also be well-applied for developing predicting and forecasting systems as it was sensitive to outliers. The Entropy method might be suitable for all the cases requiring the MCDM. There is also a need to conduct further research to probe the causal reasons why the PCA and Entropy methods were applied to each case and not the other way round. This research found that the Entropy method provides higher accuracy than the PCA method. This research also found that the Entropy method demonstrated to assess the weights of the higher dimension dataset was higher sensitivity than the lower dimensions. Finally, the comprehensive analysis indicates a need to explore a more responsive method for establishing a weighted indexing measurement for warning applications in hazard, risk, and emergency assessments.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement

Zhang

Yan

et al. 2022

PLoS ONE

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“…Furthermore, Latruffe et al (2016) and Tomich et al (2004) believe that sustainable development indicators can be classified from three main dimensions, namely environment, economy, and society. Wang, Wang et al (2021) introduce the dimension of agricultural extension service on the basis of environment, economy, and society to comprehensively evaluate the sustainable development of AIPs. However, it is necessary to identify and evaluate the key factors influencing the sustainable development of AIPs in China.…”

Section: Literature Reviewmentioning

confidence: 99%

Drivers of the Sustainable Development of Agro-industrial Parks: Evidence from Jiangsu Province, China

Wang

2022

SAGE Open

Self Cite

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The agro-industrial park (AIP) is developing rapidly all over the world and their industrial ecological characteristics have extensively promoted the development of the agricultural industry. However, academia and industry still lack a complete evaluation system to guide the sustainable development of AIPs. This study constructs a sustainable development evaluation system of the AIP that includes four parts of economic, social, technical, and sustainable criteria. Then, a multi-criteria decision-making (MCDM) method is employed for quantitative analysis based on a primary survey dataset; that is, the decision-making trial and evaluation laboratory (DEMATEL). In addition, a secondary dataset of 153 national AIPs in China from 2012 to 2014 is taken as a case study. The results of the DEMATEL analysis reveal some interesting findings. First, economic criteria still play an essential role in the sustainable development of AIP, and it is affected by almost all causal factors, which in turn affect most of the influencing factors. Second, there is no significant causal relationship between the criteria criterion and other criteria. Last, the case study reveals that the level of sustainable development of AIP in economically developed areas is significantly higher than the national average. The results of this study can also provide managers and policy planners with support for the sustainable management of AIP.

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“…After the Second World War, due to the blind pursuit of the efficiency of agricultural industrialization, agricultural development continued to suffer from problems such as overproduction, biodiversity and loss of soil fertility [20]. Modern agriculture must meet new challenges, such as producing healthy food, adapting to climate change [21], while meeting the needs of a growing population [22] protecting natural resources and protecting landscapes [21]. Scholars began to carry out a series of studies on sustainable agricultural development in response to this issue.…”

Section: Research On the Sustainable Development Of Agriculturementioning

confidence: 99%

“…Nadaraia (2021) identified 47 indexes that can be used to assess the sustainability of plantation agricultural systems [29]. Wang et al (2021) analyzed the sustainable development of agriculture from the three dimensions of environment, society and economy, identified the main factors affecting the sustainable development of agriculture, and proposed improvement measures and management suggestions to reduce obstacles to sustainable agricultural development and improve Sustainable Agriculture Practice [22].…”

Section: Research On the Sustainable Development Of Agriculturementioning

confidence: 99%

Analysis on the Temporal and Spatial Features of the Coupling and Coordination of Industrialization and Agricultural Green Development in China during 1990–2019

Guo

Pan

et al. 2021

IJERPH

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In the past 30 years, China’s industrialization level has developed rapidly, and agricultural green development (AGD) is facing severe challenges. The research on the temporal and spatial features of the coupling and coordination of industrialization and agricultural green development is a key issue to promote the sustainable development of agriculture. This paper takes China’s industrialization and AGD level as the research object, and uses panel data from 31 provinces in China from 1990 to 2019 to construct an evaluation index system for industrialization and AGD. This paper uses the coupling coordination degree model and spatial autocorrelation analysis method to calculate, test and analyze the temporal and spatial features of the coupling coordination level of industrialization and AGD. The results show that: this paper compares the industrialization and AGD levels during the study period and finds that China’s industrialization development level is on the rise as a whole, and the AGD level shows a downward trend first and then rises later. Through the horizontal comparison of different regions, this paper finds that there is a large regional imbalance in the level of industrialization and AGD. The coupling and coordination level of industrialization and AGD has always been primary. From the time point of view, coupling coordination degree shows a trend of first decline and then rise. From a spatial point of view, coupling coordination degree varies greatly among provinces, with the eastern, central and western regions decreasing successively. The level of coupling coordination has obvious positive autocorrelation in spatial distribution, and presents significant spatial agglomeration characteristics in space. The research results can provide a theoretical basis for regionally differentiated governance of the coordinated development of industrialization and AGD, and promote coordinated development.

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Evaluation of Agricultural Extension Service for Sustainable Agricultural Development Using a Hybrid Entropy and TOPSIS Method

Cited by 35 publications

References 62 publications

A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement

A comparative analysis of the principal component analysis and entropy weight methods to establish the indexing measurement

Drivers of the Sustainable Development of Agro-industrial Parks: Evidence from Jiangsu Province, China

Analysis on the Temporal and Spatial Features of the Coupling and Coordination of Industrialization and Agricultural Green Development in China during 1990–2019

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