食品生产企业质量安全分类监管研究
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摘要
食品生产企业是食品质量安全的第一责任人。过去我国的食品质量安全监管以统一监管为主,强调监管标准、内容、方法和程序的一致性。由于企业数量较少,总体水平较低,统一监管取得了良好的成效。然而近年来,我国食品生产企业增长迅速,不同的企业其产品质量安全和信用等级差异很大,监管难度各不相同；与此同时,监管人员数量非常有限,监管资源严重不匹配,人民群众日益增长的食品质量安全需求与政府监管保障能力之间的矛盾十分突出。如果继续沿用传统的统一监管的模式,必然会分散监管资源,降低监管效果和效率,不能有效控制食品生产企业质量安全风险,最终造成产品质量无法得到保障。因此,应用分类监管的理念和方法对食品生产企业进行监管应运而生。
如何从质量安全监管的角度,评价食品生产企业的质量安全状况,针对不同的食品生产企业采取差异化监管措施,是食品生产企业分类监管的核心。本文旨在为我国食品质量安全监管提供一个新的理论和制度框架。政府监管部门基于食品生产企业分类体系和模型,可以实现对食品生产企业质量安全状况的科学、客观评价,根据不同产品的风险级别,采取不同的监管措施,提高监管效果和效率,预防和控制食品生产企业质量安全风险,从而实现监管手段从“经验判断和定性分析”向“指标管理和定量监控”转变。
本文围绕“为何要进行分类监管”和“如何进行分类监管”两个核心问题,分别从理论和实践两个层面进行研究阐述,而“如何分类监管”又包含两个方面的内容：一是如何分类；二是如何实施。本文首先对分类监管进行理论研究,包括一般理论、消费者效用与均衡视角以及风险管理与激励相容视角；然后建立分类方法,包括遴选并细化分类要素,确定指标特性,对指标进行赋值,采用定性与定量相结合的方法,构建分类指标体系,对体系合理性进行评价；在此基础上,建立食品生产企业分类模型,进行试点应用,对企业类型进行预测,再对指标体系进行修正和优化；最后就如何组织实施分类监管提出建议。
研究结果表明,不论是从经济学还是管理学的角度,分类监管较之统一监管能够更有效的控制企业风险、减少资源投入而且优化监管效果；通过借鉴瑞士洛桑国际管理学院(IMD)国际竞争力指标体系,设计的食品生产企业分类评价指标体系具有较好的合理性,基于Ordinal Logistic回归建立的食品生产企业分类模型较为有效,预测结果较为准确；分类监管是对现有产品质量安全监管制度的创新和完善,通过分类监管可以很好地将现有监督措施串联起来,从而形成一套集生产许可、质量认证、监督抽查和产品召回等为一体的综合监管制度体系。
本文的创新之处主要有三点：
第一,从质量安全监管的视角研究食品生产企业分类,遴选分类要素。既考虑与国际接轨又考虑适合我国的国情,本文提出分类要素应涵盖风险管理和技术创新两大方面。一方面,食品生产企业分类体系的构成要素首先应以能够评价企业质量安全风险为核心,基于对国内外企业质量安全风险评价方法的分析,将产品质量、质量管理、资源配置和企业责任纳入分类要素。另一方面,基于我国的国情,为了鼓励企业提高核心竞争力并争创标杆企业,纳入技术创新水平这一要素,以便更加全面和前瞻性的对企业进行分类。因此,本研究将企业分类要素划分为5个：企业责任、质量管理、资源配置、产品质量、技术创新。
第二,设计与评价食品生产企业分类指标体系。分类指标体系的构建采用定性与定量相结合的方法；鉴于食品生产企业分类是一个多目标决策的过程(督促企业履行产品质量安全主体责任,降低和防范企业产品质量风险以及监管责任风险,提高产品质量监管效能,引导和促进企业实施以质取胜),同时本文构建的评价指标是多级的,其中又含有多个定性指标的情况,为了减少评价体系的主观性,提高分类方法的可操作性、易于推广性以及适用性,并确保搜集数据资料具有可行性,本研究主要借鉴IMD的国际竞争力指标体系的赋值方法,即采用三级指标均等分配权重的方法,各个三级指标均为10分,不对一级和二级指标进行主观评分。此方法的优点是可以避免各因素权重确定过程中的主观干扰。体系合理性评价包括定性与定量评价,定性评价主要采用地方调研和征求专家意见的方法,定量评价主要应用统计学方法,对指标体系的信度、效度和稳定性进行分析。
第三,建立食品生产企业分类模型并进行应用。由于分类指标体系包含多个定量指标,而且企业类型分为多种,因此本文选择应用Logistic回归中的顺序(Ordinal)回归,建立食品生产企业分类模型,并选择内蒙古自治区的企业进行试点应用,对企业类型进行预测,并对指标体系进行修正。结果表明,模型的拟合度较好,预测准确率为97.6%,且修正后体系的合理性有了较大幅度的提高。
Food production enterprises are the first person responsible for food quality and safety. In the past, China's food quality and safety was dominated by uniform regulation, which emphasizes consistency in standards, contents, approaches and processes. Uniform regulation worked well with a small number of enterprises at a low level. However in recent years, with the rapid growth of food production enterprises, the quality and safety, and credit rating of enterprises vary differently, leading to varying regulatory difficulty. At the same time, serious shortage of regulatory resources, especially limited regulatory staff, makes the conflicts between the growing demand for food quality and safety and the government's regulatory capacity even more prominent. Inefficient use of regulatory resources caused inevitably by the traditional pattern of uniform regulation will lead to poor regulatory effectiveness in food production quality and safety control, ultimately causing unguaranteed product quality. Therefore, this is how the concepts and methods of classification regulation on food production enterprises came into being.
How to evaluate the quality and safety of food production enterprises from the perspective of quality and safety regulation, and take different regulatory measures for different food production enterprises is the core of classification regulation.The dissertation aims to provide a new theoretical and institutional framework for China's food quality and safety regulation. Government regulators, based on the classification system and models of food production enterprises, can give a scientific, objective evaluation on quality and safety, and then take different regulatory measures according to different product risk levels to prevent and control risks in quality and safety, eventually changing the regulatory means from empirical judgment and qualitative analysis to index management and quantitative monitoring.
The dissertation focuses on the theoretical and practical studies on two issues: Reason for Classification Regulation and Way for Classification Regulation. The Way for Classification Regulation also contains two aspects:How to classify it and how to implement it. First, the theoretical study on classification regulation includes general theory, consumer utility and balanced perspective, as well as risk management and incentive compatibility perspective; second, the established classification method includes the selection and refinement of classification elements, identification of index characteristics, assignment of indices, establishment of a classification index system by combining qualitative and quantitative methods, evaluation on system rationality, establishment of food production enterprises classification models on this basis for pilot application, prediction on enterprise types, and correction and optimization in the index system; and last, recommendations on how to organize classification regulation are put forward in the dissertation.
The results show that, from the perspective of either economics or management, classification regulation can control enterprise risks, reduce inputs and improve regulatory effect in a more effective way than uniform regulation does. By drawing on the international competitiveness index system from Swiss business school (IMD), the classification and evaluation index system for food production enterprises is designed for rationality, and the classification model for food production enterprises is established for effectiveness as well as accurate predictions bosed on Ordinal Logistic Regression. Classification regulation, as an innovation and improvement to the existing product quality and safety regulatory system, has set up a regulatory system integrating production licensing, quality certification, supervision and checking, and product recall.
There are three main innovations in the dissertation:
First, study food production enterprises classification from the perspective of quality and safety regulation and select classification elements. Considering both international standards and national conditions, the classification elements stated in the dissertation should cover risk management and technology innovation. On one hand, the classification system for food production enterprises should take the ability to evaluate quality and safety risks as the core and the product quality, quality management, resource allocation and corporate responsibility as the elements based on the analysis on the quality and safety risk evaluation methods adopted by domestic and foreign enterprises. On the other hand, for a comprehensive and forward-looking classification, technological innovation is introduced based on national conditions to encourage enterprises to improve core competitiveness and to be benchmark enterprises. Therefore, the classification system in the dissertation consists of five elements:corporate responsibility, quality management, resource allocation, product quality, and technological innovation.
Second, design and evaluate the classification index system. A combination of qualitative and quantitative methods is employed to build up the system. Given that the food production enterprises classification is a multi-objective decision-making process (to urge enterprises to fulfill the responsibility for product quality and safety, reduce and prevent product quality and regulatory liability risks, improve product quality monitoring effectiveness, and guide and encourage enterprises to put quality first), to reduce the subjectivity of the evaluation system, improve the operability, publicity and applicability of classification, and ensure the collection of feasible data as the multi-level evaluation index system established in the dissertation contains more than one qualitative indices, the dissertation draws the assignment method from the IMD's international competitiveness index system, which uses a three-tier equal weight distribution method, with10points for all three-tier indices and no subjective ratings on tier one and two indices. This method is able to avoid subjective interference when determining the weight of each factor. System rationality is evaluated in both qualitative and quantitative ways. The former combines local research and expert opinions, and the latter analyzes system reliability, validity and stability with a statistical method.
Third, build and apply the classification model for food production enterprises. Because of multiple quantitative indicators and different enterprise types in the system, the dissertation chooses the ordinal regression out of logistic regression to establish the classification model and selects enterprises from the Inner Mongolia Autonomous Region for pilot applications to predict enterprise type and amend the system. The results show that the model fits well with a prediction accuracy of97.6%and rationality of the revised system has increased dramatically.
如何从质量安全监管的角度,评价食品生产企业的质量安全状况,针对不同的食品生产企业采取差异化监管措施,是食品生产企业分类监管的核心。本文旨在为我国食品质量安全监管提供一个新的理论和制度框架。政府监管部门基于食品生产企业分类体系和模型,可以实现对食品生产企业质量安全状况的科学、客观评价,根据不同产品的风险级别,采取不同的监管措施,提高监管效果和效率,预防和控制食品生产企业质量安全风险,从而实现监管手段从“经验判断和定性分析”向“指标管理和定量监控”转变。
本文围绕“为何要进行分类监管”和“如何进行分类监管”两个核心问题,分别从理论和实践两个层面进行研究阐述,而“如何分类监管”又包含两个方面的内容：一是如何分类；二是如何实施。本文首先对分类监管进行理论研究,包括一般理论、消费者效用与均衡视角以及风险管理与激励相容视角；然后建立分类方法,包括遴选并细化分类要素,确定指标特性,对指标进行赋值,采用定性与定量相结合的方法,构建分类指标体系,对体系合理性进行评价；在此基础上,建立食品生产企业分类模型,进行试点应用,对企业类型进行预测,再对指标体系进行修正和优化；最后就如何组织实施分类监管提出建议。
研究结果表明,不论是从经济学还是管理学的角度,分类监管较之统一监管能够更有效的控制企业风险、减少资源投入而且优化监管效果；通过借鉴瑞士洛桑国际管理学院(IMD)国际竞争力指标体系,设计的食品生产企业分类评价指标体系具有较好的合理性,基于Ordinal Logistic回归建立的食品生产企业分类模型较为有效,预测结果较为准确；分类监管是对现有产品质量安全监管制度的创新和完善,通过分类监管可以很好地将现有监督措施串联起来,从而形成一套集生产许可、质量认证、监督抽查和产品召回等为一体的综合监管制度体系。
本文的创新之处主要有三点：
第一,从质量安全监管的视角研究食品生产企业分类,遴选分类要素。既考虑与国际接轨又考虑适合我国的国情,本文提出分类要素应涵盖风险管理和技术创新两大方面。一方面,食品生产企业分类体系的构成要素首先应以能够评价企业质量安全风险为核心,基于对国内外企业质量安全风险评价方法的分析,将产品质量、质量管理、资源配置和企业责任纳入分类要素。另一方面,基于我国的国情,为了鼓励企业提高核心竞争力并争创标杆企业,纳入技术创新水平这一要素,以便更加全面和前瞻性的对企业进行分类。因此,本研究将企业分类要素划分为5个：企业责任、质量管理、资源配置、产品质量、技术创新。
第二,设计与评价食品生产企业分类指标体系。分类指标体系的构建采用定性与定量相结合的方法；鉴于食品生产企业分类是一个多目标决策的过程(督促企业履行产品质量安全主体责任,降低和防范企业产品质量风险以及监管责任风险,提高产品质量监管效能,引导和促进企业实施以质取胜),同时本文构建的评价指标是多级的,其中又含有多个定性指标的情况,为了减少评价体系的主观性,提高分类方法的可操作性、易于推广性以及适用性,并确保搜集数据资料具有可行性,本研究主要借鉴IMD的国际竞争力指标体系的赋值方法,即采用三级指标均等分配权重的方法,各个三级指标均为10分,不对一级和二级指标进行主观评分。此方法的优点是可以避免各因素权重确定过程中的主观干扰。体系合理性评价包括定性与定量评价,定性评价主要采用地方调研和征求专家意见的方法,定量评价主要应用统计学方法,对指标体系的信度、效度和稳定性进行分析。
第三,建立食品生产企业分类模型并进行应用。由于分类指标体系包含多个定量指标,而且企业类型分为多种,因此本文选择应用Logistic回归中的顺序(Ordinal)回归,建立食品生产企业分类模型,并选择内蒙古自治区的企业进行试点应用,对企业类型进行预测,并对指标体系进行修正。结果表明,模型的拟合度较好,预测准确率为97.6%,且修正后体系的合理性有了较大幅度的提高。
Food production enterprises are the first person responsible for food quality and safety. In the past, China's food quality and safety was dominated by uniform regulation, which emphasizes consistency in standards, contents, approaches and processes. Uniform regulation worked well with a small number of enterprises at a low level. However in recent years, with the rapid growth of food production enterprises, the quality and safety, and credit rating of enterprises vary differently, leading to varying regulatory difficulty. At the same time, serious shortage of regulatory resources, especially limited regulatory staff, makes the conflicts between the growing demand for food quality and safety and the government's regulatory capacity even more prominent. Inefficient use of regulatory resources caused inevitably by the traditional pattern of uniform regulation will lead to poor regulatory effectiveness in food production quality and safety control, ultimately causing unguaranteed product quality. Therefore, this is how the concepts and methods of classification regulation on food production enterprises came into being.
How to evaluate the quality and safety of food production enterprises from the perspective of quality and safety regulation, and take different regulatory measures for different food production enterprises is the core of classification regulation.The dissertation aims to provide a new theoretical and institutional framework for China's food quality and safety regulation. Government regulators, based on the classification system and models of food production enterprises, can give a scientific, objective evaluation on quality and safety, and then take different regulatory measures according to different product risk levels to prevent and control risks in quality and safety, eventually changing the regulatory means from empirical judgment and qualitative analysis to index management and quantitative monitoring.
The dissertation focuses on the theoretical and practical studies on two issues: Reason for Classification Regulation and Way for Classification Regulation. The Way for Classification Regulation also contains two aspects:How to classify it and how to implement it. First, the theoretical study on classification regulation includes general theory, consumer utility and balanced perspective, as well as risk management and incentive compatibility perspective; second, the established classification method includes the selection and refinement of classification elements, identification of index characteristics, assignment of indices, establishment of a classification index system by combining qualitative and quantitative methods, evaluation on system rationality, establishment of food production enterprises classification models on this basis for pilot application, prediction on enterprise types, and correction and optimization in the index system; and last, recommendations on how to organize classification regulation are put forward in the dissertation.
The results show that, from the perspective of either economics or management, classification regulation can control enterprise risks, reduce inputs and improve regulatory effect in a more effective way than uniform regulation does. By drawing on the international competitiveness index system from Swiss business school (IMD), the classification and evaluation index system for food production enterprises is designed for rationality, and the classification model for food production enterprises is established for effectiveness as well as accurate predictions bosed on Ordinal Logistic Regression. Classification regulation, as an innovation and improvement to the existing product quality and safety regulatory system, has set up a regulatory system integrating production licensing, quality certification, supervision and checking, and product recall.
There are three main innovations in the dissertation:
First, study food production enterprises classification from the perspective of quality and safety regulation and select classification elements. Considering both international standards and national conditions, the classification elements stated in the dissertation should cover risk management and technology innovation. On one hand, the classification system for food production enterprises should take the ability to evaluate quality and safety risks as the core and the product quality, quality management, resource allocation and corporate responsibility as the elements based on the analysis on the quality and safety risk evaluation methods adopted by domestic and foreign enterprises. On the other hand, for a comprehensive and forward-looking classification, technological innovation is introduced based on national conditions to encourage enterprises to improve core competitiveness and to be benchmark enterprises. Therefore, the classification system in the dissertation consists of five elements:corporate responsibility, quality management, resource allocation, product quality, and technological innovation.
Second, design and evaluate the classification index system. A combination of qualitative and quantitative methods is employed to build up the system. Given that the food production enterprises classification is a multi-objective decision-making process (to urge enterprises to fulfill the responsibility for product quality and safety, reduce and prevent product quality and regulatory liability risks, improve product quality monitoring effectiveness, and guide and encourage enterprises to put quality first), to reduce the subjectivity of the evaluation system, improve the operability, publicity and applicability of classification, and ensure the collection of feasible data as the multi-level evaluation index system established in the dissertation contains more than one qualitative indices, the dissertation draws the assignment method from the IMD's international competitiveness index system, which uses a three-tier equal weight distribution method, with10points for all three-tier indices and no subjective ratings on tier one and two indices. This method is able to avoid subjective interference when determining the weight of each factor. System rationality is evaluated in both qualitative and quantitative ways. The former combines local research and expert opinions, and the latter analyzes system reliability, validity and stability with a statistical method.
Third, build and apply the classification model for food production enterprises. Because of multiple quantitative indicators and different enterprise types in the system, the dissertation chooses the ordinal regression out of logistic regression to establish the classification model and selects enterprises from the Inner Mongolia Autonomous Region for pilot applications to predict enterprise type and amend the system. The results show that the model fits well with a prediction accuracy of97.6%and rationality of the revised system has increased dramatically.
引文
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