How effective is the fire safety education policy in China? A quantitative evaluation based on the PMC-index model

Xiong, Yachao; Zhang, Changli; Qi, Hui

doi:10.1016/j.ssci.2023.106070

Cited by 21 publications

(18 citation statements)

References 41 publications

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“…Based on these strengths, the model is clearly applicable to the energy supply policy evaluation conducted in this study. The model has also been widely used in policy evaluation, such as ecological compensation, 38,39 green development, 40,41 fire safety education 42 and fishery insurance. 43 In research on energy policy evaluation methods, most scholars apply qualitative methods; for instance, Lo 44 conducted a critical review of renewable energy and energy efficiency policies in the five areas of electricity, industry, transportation, buildings and local government in China and studied the progress and the limitations of China's formulation and implementation of these policies.…”

Section: Evolution Of Policy Evaluation Methodsmentioning

confidence: 99%

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Quantitative evaluation of China's energy supply policies in the ‘13th Five‐Year Plan’ period (2016–2020): A PMC index modelling approach incorporating text mining

Cheng,

Chen,

Lin

et al. 2024

Energy Science & Engineering

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Energy supply policy quality is an important factor that would impact national energy security. While existing research conducted policy evaluation from the lens of performance assessment, less study has been devoted to evaluating energy supply policy from the perspective of policy making. This study takes the energy supply policy documents issued by China's central government during the ‘13th Five‐Year Plan’ period (2016–2020) as the research sample, and pioneers the use of the extended policy modelling consistency (PMC) index model combined with the text mining methodology to construct a policy evaluation index system with the characteristics of the energy supply policy which conducts a more in‐depth quantitative evaluation of the energy supply policy documents. The results show that the average PMC index value of China's energy supply policies is 7.26, and the overall quality is high. The concerns of existing policies are mainly focused on reform and development planning, safety production management and project engineering construction, but there is still room for improvement in policy predictability, coordination of policy areas, clarity of policy basis and goals and comprehensiveness of policy tool combinations. Based on this, China should improve the comprehensiveness of its energy supply policy tool combinations in terms of policy design norm; strengthen policy predictability and coordination of policy areas in terms of policy implementation guarantee; and clarify the basis and goals of policies in terms of policy orientation enhancement, to provide a reference basis for the formulation and improvement of future energy supply policies and to realise the sustainable development of energy supply.

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Section: Evolution Of Policy Evaluation Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Quantitative evaluation of China's energy supply policies in the ‘13th Five‐Year Plan’ period (2016–2020): A PMC index modelling approach incorporating text mining

Cheng,

Chen,

Lin

et al. 2024

Energy Science & Engineering

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“…The first-level variables in this research were determined using classical variables, such as policy nature, as proposed by Ruiz Estrad [29]. Additionally, we incorporated improved first-level variables from previous studies [31][32][33]48,[50][51][52][53][54][55][56][57][58], as well as the results of high-frequency word summarization. The results of high-frequency word analysis and generalization were used to establish the first-level variable of policy ideas.…”

Section: Pmc-index Modelmentioning

confidence: 99%

“…Two comprehensive policies and two specialized policies are selected at each of the three stages of development. The selection criteria for the former are its representativeness and policy effectiveness [32,51,56]. For the latter, a simple random sampling method is adopted.…”

Section: Selection Of Policies To Be Evaluatedmentioning

confidence: 99%

“…Therefore, this study exploratively set up 10 primary variables and 62 secondary variables, as shown in Table 6. The primary variables are as follows: policy nature [29,51,53] (X1), policy function [56,57] (X2), policy ideas (X3), policy instrument [51,58] (X4), incentives and constraints [31,32] (X5), content evaluation [50,55,56] (X6), policy content [53,57] (X7a), functioning hierarchy [32,50,57] (X7b), participating subjects [31,33] (X8), and implementation guarantee [31,48] (X9). Each of these level 1 variables has a number of level 2 variables, as shown in Table 6.…”

Section: Variable Selection and Parameter Settingmentioning

confidence: 99%

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Quantitative Evaluation of China’s Central-Level Land Consolidation Policies in the Past Forty Years Based on the Text Analysis and PMC-Index Model

Huang,

Shen,

Zhang

et al. 2023

Land

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After nearly forty years of development, China’s land consolidation policies (CLCP) have become an important tool for promoting rural revitalization and sustainable development. However, as a major land management policy, there is still a lack of quantitative evaluation research on its text. This paper establishes an evaluation system for CLCP using text analysis and the PMC-Index model. Based on a reasonable definition of the connotation of land consolidation, this paper collects 313 related policies issued by China’s central government from 1982 to 2022, using text analysis to sort out the characteristics of issuance time, policy types, issuing institutions, and cooperation networks. By combining the outcomes of text mining with the previous research results to set evaluation indicators for the PMC-Index model, it distinguishes between comprehensive policies and specialized policies and separately evaluates them. Then, the PMC-Surface is established to clearly display the calculation results. The results show that the evaluation scores of comprehensive policies and specialized policies showed an upward trend over time. This indicates that the content of CLCP is constantly being enriched and expanded. The evaluation scores for different dimensions of comprehensive policies are relatively balanced, whereas there are significant differences in the evaluation scores of various dimensions of specialized policies. Both comprehensive policies and specialized policies have weaknesses in policy functions, incentives and constraints, and implementation guarantees, so improvements may be needed in these areas in the future. This study provides valuable insights into the advantages and disadvantages of a single land consolidation policy in China.

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How effective are WEEE policies in China? A strategy evaluation through a PMC-index model with content analysis

Wang,

Cai,

Song

et al. 2025

Environmental Impact Assessment Review

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How effective is the fire safety education policy in China? A quantitative evaluation based on the PMC-index model

Cited by 21 publications

References 41 publications

Quantitative evaluation of China's energy supply policies in the ‘13th Five‐Year Plan’ period (2016–2020): A PMC index modelling approach incorporating text mining

Quantitative evaluation of China's energy supply policies in the ‘13th Five‐Year Plan’ period (2016–2020): A PMC index modelling approach incorporating text mining

Quantitative Evaluation of China’s Central-Level Land Consolidation Policies in the Past Forty Years Based on the Text Analysis and PMC-Index Model

How effective are WEEE policies in China? A strategy evaluation through a PMC-index model with content analysis

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