【作者】 毛帅；

【导师】 聂锐；

【作者基本信息】 中国矿业大学 ， 管理科学与工程， 2013， 博士

【摘要】 以往专家与学者对于质量与经济发展关系的研究与实践可以看出：质量提升会带来经济的增长。因此本研究就以质量发展与经济提升的关系为切入点，深度剖析两者之间到底是什么关系，从而真正揭示质量发展与经济提升的相关关系和影响度。鉴于对“质量提升”引起“经济增长”的度的表示，研究首次运用“质量贡献率”这一名词概念。在研究过程中，论文重点探讨了“质量”由哪些方面构成，和其对“经济”增长的影响度到底有多大这两个重点问题。研究首先在界定研究范围和相关研究概念综述的基础上，肯定了质量的生产力特性，并分析了它与科技进步、劳动力、资本之间的关系。所得结论为：科技进步表现为持续的质量提升，质量是包含了科技进步与管理水平提升的生产力要素。质量与劳动力、资本为三个相互独立又相辅相成的生产力要素，共同作用于经济增长。基于以上研究的佐证，论文在经典生产函数模型中加入质量因素，推导出了包括质量因素的生产函数公式。从而对质量贡献率进行测算。在构建反映质量总体水平的“城市工业产品质量指数”Q方面，本研究以全面质量管理和卓越绩效的思维构建了城市工业产品质量指数指标体系。研究所构建的城市工业产品质量指数指标体系涵盖了微观质量管理指标和宏观质量管理指标。微观质量管理层面的指标是按照“质量策划、质量控制、质量保证和质量改进”这四个质量管理的基本流程去选取的具体指标。宏观质量管理层面的指标是从政府质量管理的主要工作内容：质量安全状况监管、质量发展基础建设、质量执法情况和奖励扶持四个方面选取的。部分指标既在微观质量管理层面体现，也在宏观质量管理层面体现。由此构成的城市工业产品质量指数包括五个二级指标，二十八个三级指标、七十一个观测指标。在构建了城市工业产品质量指数指标体系的基础上，研究运用专家问卷法采集了一手数据，然后运用BP神经网络的学习算法，计算出了指标的权重，形成了完整的城市工业产品质量指数测算方法。之后，作者采集了徐州市八个区县的城市工业产品质量指数的71个观测指标数据，并计算出其相应的工业产品质量指数，然后采集相应区县的GDP、固定资产投资和劳动力数量的相关数据，再运用Eviews6.0做了实证研究。通过实证研究得出了包括质量的回归方程，并得出了质量贡献率为29.48%的研究结论。也就是说经济增长的29.48%源于工业产品质量的贡献。在回归分析的过程中，研究对八个假设分别进行了验证。通过验证的假设包括：城市工业产品质量提升与城市经济的增长呈正相关关系；城市工业产品质量提升对城市经济增长的贡献大于劳动力增长对城市经济增长的贡献；城市工业产品质量指数的二级指标——质量发展基础，与城市经济增长有着显性正相关关系；城市工业产品质量指数的二级指标——政府奖励扶持，与城市经济增长有着显性正相关关系；城市工业产品质量指数的二级指标——质量安全状况，与城市经济增长有着显性正相关关系。未通过实证检验的内容包括：城市工业产品质量提升对城市经济增长的贡献大于资本投入对城市经济增长的贡献；城市工业产品质量指数的二级指标——标准与技术水平，与城市经济增长有着显性正相关关系；城市工业产品质量指数的二级指标——政府质管执法，与城市经济增长有着显性正相关关系；这里需要说明的是，城市工业产品质量指数的两个未通过显著性检验的二级指标：标准与技术水平、政府质管执法与经济增长的正相关关系均是存在的，只是从显著性上来说有所欠缺。在计算出城市工业产品质量贡献率的基础上，研究运用统计学方法进行了城市工业产品贡献率的标杆建立与评价研究。最后，基于以上研究分析，本研究设计了一个“城市工业产品质量贡献率测度与评价管理系统”，实现了从数据采集、数据管理、指标统计与计算、地区比较与评价、报告自动生成的智能管理系统。基于此平台，不仅仅能够将本文的所有研究成果可视化，而且可以供相关质量管理部门运用。更多还原

【Abstract】 Through the researches and practices on the relationship between quality andeconomic development by experts and scholars, we can find that, qualityimprovement will lead to economic growth has become a consensus. This paperstarted from a depth profile analysis on the connections between quality developmentand economic growth, then revealed the relevance between them.The two major issues studied in this paper are the structure of Quality and itsinfluence made on the Economic growth. The concept of “Quality contribution rate”is applied in this research.Firstly, based on defining the scope of the study and definition review of theresearch related, the other affirmed the productivity characteristics of quality. Then,analyzed the relationship between it and the progress of science and technology, labor,capital. The conclusions are: continuous quality improvement is the performance ofscientific and technological progress; quality is a factor of productivity, whichincluding progress in science and technology and management; quality, labor andcapital are three mutually independent but complementary factors of production, theycontribute to economic growth together. Based on the above research, author puttedthe quality factor into the classical production function model, and deduced theformula of production function including the quality factor. Then, we can calculate thequality contribution rate.In the construction of the Q index, the urban industrial product quality index,which reflects the quality level, the author built a quality index system of urbanindustrial products which based on the thoughts of total quality management andperformance excellence theory. This index system included both micro and macroquality management indicators. In the micro quality management level, indicators areselected following four issues: quality management processing and planning, qualitycontrol, quality assurance and quality improvement. In the macro quality managementlevel, indicators came from the four issues the government did on quality management:supervision and administration of quality safety, infrastructure of quality development,quality enforcement and support. Some of the indicators presents in both levels. Thereare FIVE level two indicators，TWENTY EIGHT level three indicators and SEVENTYONE observation indicators included in the thirdly level.Primary data of this study were collected by adopting expert questionnaire survey. Weights of each indicator are obtained directly from the output of learning algorithmof BP neural network. This is the measurement method of urban industrial productsquality index.Quality factors have been inducted into the review of Classical productionfunction approach in this study. A production function formula with quality factorswas deduced. The data acquisition of urban industrial product quality covered all8districts of Xuzhou city,71indicators acquired and the results were calculatedcorrespondently.The appropriate GDP, fixed assets investments and labor data were collected andintroduced into Eviews6.0. This empirical study works out a quality factors involvedregression equation and concluded the quality contribution rate was29.48%, whichmeans the certain percentage of economic growth derives from products quality.There are eight hypotheses have been tested in the regression analysis, herecomes the result: hypothesis1,3,4,6and8were verified and hypothesis2,5and7were failed the test. The detailed conclusions are as followed:Hypotheses past the test are:1. the improvement of industrial products qualityand the growth of urban economic present positive correlation;2. the improvement ofindustrial products quality contribute more than the growth of the labor force to theurban economic growth;3. Quality development infrastructure and urban economicgrowth have significant positive correlation;4. Government support and urbaneconomic growth have significant positive correlation;5. Quality security situationand urban economic growth have significant positive correlation. Indicators inhypotheses3-5are level two indicators of industrial products quality index.Hypotheses failed the test are:1. The improvement of industrial products qualitycontribute more than capital employed to the urban economic growth;2. Standardsand technical level and urban economic growth have significant positive correlation;3.Government quality enforcement and urban economic growth have significantpositive correlation. It should be noted that those two secondary level indicators(standards and technical level, government quality enforcement) and urban economicgrowth do have positive correlation but not significant enough.Based on the result of urban industrial products contribution rate, benchmarkingand evaluation research have been made by applying statistical method. Upper bound,intermediate value and lower bounds have been worked out through statisticalanalysis, therefore, the evaluating of industrial products quality contribution rate in different areas are objective.Based on the analysis above, an intelligent management system called “Urbanindustrial products quality contribution evaluating and measurement managementsystem” was designed, which including functions of data collecting, data management,indicator statistics and calculation, regional comparison and evaluating, automatesreporting. This system could visualize all the research results in this study and beoperated in quality management related department.更多还原