Research On Quality&Safety Classification Regulation Of Food Production Enterprises

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.