中国集装箱港口企业生产率测度研究
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摘要
经济发展推动我国集装箱港口的迅猛发展,未来10年将是我国由集装箱“大港”迈进“强港”的关键性时期。但我国港口粗放型发展方式不利于港口实力的增强。因此,打造集装箱强国,必须注重集装箱港口的集约化发展,提高港口生产率,依靠效率提升促进集装箱港口竞争力提升,实现集装箱大国到强国的转变。
论文采用差分自回归移动平均模型(Autoregressive Integrated Moving Average, ARIMA),预测我国集装箱港口发展规模,思考集装箱港口规模的增长对港口生产率提出的挑战,运用随机前沿生产函数(Stochastic Frontier Approach, SFA)和数据包络方法(Data Envelopment Analysis, DEA),测度我国沿海内地主要集装箱港口企业生产率,包括技术效率、随机前沿生产函数下的全要素生产率增长及其构成、Malmquist指数下的全要素生产率增长及其构成;探讨全要素生产率增长的变化以及区域性全要素生产率的波动;研究影响技术效率的外生性因素。主要体现在:
①提出基于超越对数生产函数的中国集装箱港口企业全要素生产率增长测度模型,研究投入要素对生产率的影响程度和影响方向,揭示中国集装箱港口企业全要素生产率(Total Factor Productivity,TFP)增长及其构成波动特点;并将我国沿海、内陆集装箱港口企业划分为五大区域,探讨区域全要素生产率组成的波动和地区差距。研究结果显示:
1)我国集装箱港口企业全要素增长率大都呈现增长趋势,集装箱港口业全要素增长明显。其中,技术进步变化稳定增长;技术效率改进明显;规模效率增长变化幅度平缓,规模经济性保持在稳定状态;资源配置效率变化呈现出负增长状态,优化资源配置势在必行。2)集装箱港口企业区域性全要素生产率组成差异较为明显。五大区域平均技术进步率增长较小;但区域技术效率改进变化趋势相同,平均增幅均在10%以上,区域规模效率变化除长三角区域为下降趋势外,其他区域呈现波动状态,无明显上升或下降趋势。3)资本各投入要素中,设备对集装箱港口企业效率提升影响积极,代表港口基础设施建设的泊位数却呈现较强消极影响作用;研究结果也首次显示劳务工人对提升港口企业生产率影响积极,而在职员工却表现出消极影响。
②提出基于数据包络分析的中国集装箱港口企业生产率测度模型,重点研究中国集装箱港口企业投入余量和现有条件下最优产出。得出如下结论:
1)我国集装箱港口企业生产一方面产出不足,另一方面是规模过剩,资源浪费现象普遍,而且企业技术效率个体差异较大,投入产出效率极为不平衡。2)各集装箱港口企业样本期间DEA-Malmquist全要素生产率变化指数及其分解结果显示,集装箱港口行业Malmquist全要素生产率增长大于1,平均增长14.9%,改善主要源于集装箱港口综合技术效率的提升。
③提出基于随机生产函数的中国集装箱港口企业内部管控效率损失模型和外部经济环境效率损失模型,研究港口企业所有权变化、生产规模、区域经济环境等外生性因素对生产率的影响。研究结果显示:
1)外部资金的介入引起集装箱港口企业股权结构变化,对技术效率表现为积极正向影响。外资与合资港口技术效率明显高于地方国有属性港口。同时集装箱港口企业外部资金增长速度低于技术效率提升的速度,港口企业技术效率和外部资金介入之间存在着U型反转结构。2)规模差异带来的效率差异明显,规模较大的港口企业有着较好的技术效率;3)专科以上专业技术人才对效率的推动作用没有得到展现,主要原因是集装箱港口现有人力资源的知识水平远远不能满足现实和未来港口发展的需求,其次港口存在着不同程度的冗员现象,不利于企业高效率提升生产效率。4)区域经济的增长明显促进集装箱规模扩大,但并不直接推动技术效率的提升。5)港口所在城市第三产业占比的提高不仅能有效提升集装箱港口企业技术效率,对于集装箱吞吐量的增加也表现出极强的促进作用。
综合以上分析,为推动我国集装箱港口企业全要素生产率的增长、提升技术效率,做大做强集装箱港口业,提出引进海内外战略投资者,深化集装箱港口企业产权管理;合理确定集装箱港口规模,促进集装箱港口科学发展;加强技术改造和信息化建设,促进技术进步;加强港口人才培养,提升人才效能;加快港口资源整合,充分发挥港口群体优势等对策建议。
Economic development promotes the rapid expansion of China's container terminals, the next 10 years will be the critical period when container stride from the "large port" into the "strong port". However, extensive development mode make against the strength of China's port. Therefore, to enhance container strength, the intensive development must be focused on and productivity must be increased, depending on promoting efficiency to achieve changes.
This paper had pondered the challenge which was proposed to the port productivity based on the container scale growth's ARIMA (0,1,0) autoregressive moving average forecast model. At the same time, productivity of Chinese main container terminals had been estimated by utilizing SFA and DEA method, include technical efficiency, total factor productivity(TFP) and its’composing, Malmquist-index- total factor productivity(TFP) and its’composing. TFP changes as well as regional TFP fluctuation were discussed and technical efficiency of exogenous factors was still studied in this paper. The details were as following:
①Total factor productivity measure model including four input variables was put forward with the aid of stochastic front production (TFP) model in order to research inputs factors’s influencing degree and direction, and the characteristics of TFP changes and fluctuations in China's container terminals. At the same time, the fluctuations in the composition of the regional TFP as well as local disparity were discussed. The results showed that:
1) TFP presented rising tendency in China's container ports. thereinto, technology advancement increased steadily; improvement of technical efficiency was obvious; scale efficiency SEC changed gently; economic scale maintained at the steady state; resource allocation efficiency showed negative growth. 2) Regional diversity of TFP composition was obvious. The average technology advancement growth in five regions was low, but the change tendency of region technology efficiency improvement was the same, the average increased range was above 10%. In addition to Yangtze River Delta region of scale efficiency change is downtrend, other regions fluctuated. 3) For each investment factor, equipment was positive to efficiency promotion of container terminals, the following was labor workers, while serving staff demonstrated negative impact. Berths presented the strongly negative effect. The large-scale infrastructural facilities had manifested the resources waste and the efficiency sacrifice to a certain extent.
②With the aid of the data envelope analysis, The measure model of productivity change of container terminals were brought forward, primarily research the input slacks and optimal output in China's container terminals. The following conclusions were arrived:
1) The measurement results based on DEA-CCR model showed that individual difference of technical efficiency was obvious in Container Terminal Company, and input-output efficiency was extremely imbalance. The measure results of cross-section data in 2007 indicated that production output was insufficiency while the scale was surplus and the waste of resources was common. 2) Container’s TPF change index of DEA-Malmquist in sample period and decomposition results showed that, technical efficiency, technological progress and scale efficiency changes were characterized by fluctuations, while the overall made positive contribution to TPF productivity promotion. Malmquist TFP of port industry was greater than 1, the average growth was about 14.9%, improvement mainly stem from the promotion of synthesis technology efficiency. Malmquist TFP of Five regional ports presented growth condition, regional container port operations were in the process of continuous improvement, which the improvement of Bohai and Yangtze River Delta region were relatively prominent.
③China's container terminals inner management efficiency loss model and outer economy entironment efficiency loss model based on stochastic front production function were put forward, and discussed incidence and direction which exogenous factors to technical efficiency. Study conclusion:
1) Involvement of external capital caused the structure changes of stocks in container port. It manifested a positive influence to technical efficiency. Technical efficiency of foreign investment and joint venture terminal was significantly higher than the local state-owned terminals. Rate of external funding growth was lower than that of technical efficiency, there was U-inverted structure between the technology efficiency and involvement of external funding. 2) Differences in efficiency caused by differences in size were obvious, and bigger terminal had better technical efficiency. 3)Professional and technical personnel in promoting the efficiency had not been demonstrated. The primary reason was that existing level of knowledge of human resources cannot satisfy the demand of reality and the future development, followed there were varying degrees of redundancy, which is not conducive to increase the production efficiency. 4) Regional economic growth promoted container scale significantly while not promoting enhancement of technical efficiency directly. 5) Increased proportion of tertiary industry in Port city can not only improve the technical efficiency of container, also displayed a strong role for promoting container throughput.
In conclusion, in order to promote China's container port TFP growth, improve technical efficiency, and enhance container port industry, some suggestions such as Promote enterprise property management in container port, introduce overseas strategic investors; strengthen internal management, focus on the effective use of inputs optimize human resource; and plan and develop orderly, conduct resources integration were put forward.
论文采用差分自回归移动平均模型(Autoregressive Integrated Moving Average, ARIMA),预测我国集装箱港口发展规模,思考集装箱港口规模的增长对港口生产率提出的挑战,运用随机前沿生产函数(Stochastic Frontier Approach, SFA)和数据包络方法(Data Envelopment Analysis, DEA),测度我国沿海内地主要集装箱港口企业生产率,包括技术效率、随机前沿生产函数下的全要素生产率增长及其构成、Malmquist指数下的全要素生产率增长及其构成;探讨全要素生产率增长的变化以及区域性全要素生产率的波动;研究影响技术效率的外生性因素。主要体现在:
①提出基于超越对数生产函数的中国集装箱港口企业全要素生产率增长测度模型,研究投入要素对生产率的影响程度和影响方向,揭示中国集装箱港口企业全要素生产率(Total Factor Productivity,TFP)增长及其构成波动特点;并将我国沿海、内陆集装箱港口企业划分为五大区域,探讨区域全要素生产率组成的波动和地区差距。研究结果显示:
1)我国集装箱港口企业全要素增长率大都呈现增长趋势,集装箱港口业全要素增长明显。其中,技术进步变化稳定增长;技术效率改进明显;规模效率增长变化幅度平缓,规模经济性保持在稳定状态;资源配置效率变化呈现出负增长状态,优化资源配置势在必行。2)集装箱港口企业区域性全要素生产率组成差异较为明显。五大区域平均技术进步率增长较小;但区域技术效率改进变化趋势相同,平均增幅均在10%以上,区域规模效率变化除长三角区域为下降趋势外,其他区域呈现波动状态,无明显上升或下降趋势。3)资本各投入要素中,设备对集装箱港口企业效率提升影响积极,代表港口基础设施建设的泊位数却呈现较强消极影响作用;研究结果也首次显示劳务工人对提升港口企业生产率影响积极,而在职员工却表现出消极影响。
②提出基于数据包络分析的中国集装箱港口企业生产率测度模型,重点研究中国集装箱港口企业投入余量和现有条件下最优产出。得出如下结论:
1)我国集装箱港口企业生产一方面产出不足,另一方面是规模过剩,资源浪费现象普遍,而且企业技术效率个体差异较大,投入产出效率极为不平衡。2)各集装箱港口企业样本期间DEA-Malmquist全要素生产率变化指数及其分解结果显示,集装箱港口行业Malmquist全要素生产率增长大于1,平均增长14.9%,改善主要源于集装箱港口综合技术效率的提升。
③提出基于随机生产函数的中国集装箱港口企业内部管控效率损失模型和外部经济环境效率损失模型,研究港口企业所有权变化、生产规模、区域经济环境等外生性因素对生产率的影响。研究结果显示:
1)外部资金的介入引起集装箱港口企业股权结构变化,对技术效率表现为积极正向影响。外资与合资港口技术效率明显高于地方国有属性港口。同时集装箱港口企业外部资金增长速度低于技术效率提升的速度,港口企业技术效率和外部资金介入之间存在着U型反转结构。2)规模差异带来的效率差异明显,规模较大的港口企业有着较好的技术效率;3)专科以上专业技术人才对效率的推动作用没有得到展现,主要原因是集装箱港口现有人力资源的知识水平远远不能满足现实和未来港口发展的需求,其次港口存在着不同程度的冗员现象,不利于企业高效率提升生产效率。4)区域经济的增长明显促进集装箱规模扩大,但并不直接推动技术效率的提升。5)港口所在城市第三产业占比的提高不仅能有效提升集装箱港口企业技术效率,对于集装箱吞吐量的增加也表现出极强的促进作用。
综合以上分析,为推动我国集装箱港口企业全要素生产率的增长、提升技术效率,做大做强集装箱港口业,提出引进海内外战略投资者,深化集装箱港口企业产权管理;合理确定集装箱港口规模,促进集装箱港口科学发展;加强技术改造和信息化建设,促进技术进步;加强港口人才培养,提升人才效能;加快港口资源整合,充分发挥港口群体优势等对策建议。
Economic development promotes the rapid expansion of China's container terminals, the next 10 years will be the critical period when container stride from the "large port" into the "strong port". However, extensive development mode make against the strength of China's port. Therefore, to enhance container strength, the intensive development must be focused on and productivity must be increased, depending on promoting efficiency to achieve changes.
This paper had pondered the challenge which was proposed to the port productivity based on the container scale growth's ARIMA (0,1,0) autoregressive moving average forecast model. At the same time, productivity of Chinese main container terminals had been estimated by utilizing SFA and DEA method, include technical efficiency, total factor productivity(TFP) and its’composing, Malmquist-index- total factor productivity(TFP) and its’composing. TFP changes as well as regional TFP fluctuation were discussed and technical efficiency of exogenous factors was still studied in this paper. The details were as following:
①Total factor productivity measure model including four input variables was put forward with the aid of stochastic front production (TFP) model in order to research inputs factors’s influencing degree and direction, and the characteristics of TFP changes and fluctuations in China's container terminals. At the same time, the fluctuations in the composition of the regional TFP as well as local disparity were discussed. The results showed that:
1) TFP presented rising tendency in China's container ports. thereinto, technology advancement increased steadily; improvement of technical efficiency was obvious; scale efficiency SEC changed gently; economic scale maintained at the steady state; resource allocation efficiency showed negative growth. 2) Regional diversity of TFP composition was obvious. The average technology advancement growth in five regions was low, but the change tendency of region technology efficiency improvement was the same, the average increased range was above 10%. In addition to Yangtze River Delta region of scale efficiency change is downtrend, other regions fluctuated. 3) For each investment factor, equipment was positive to efficiency promotion of container terminals, the following was labor workers, while serving staff demonstrated negative impact. Berths presented the strongly negative effect. The large-scale infrastructural facilities had manifested the resources waste and the efficiency sacrifice to a certain extent.
②With the aid of the data envelope analysis, The measure model of productivity change of container terminals were brought forward, primarily research the input slacks and optimal output in China's container terminals. The following conclusions were arrived:
1) The measurement results based on DEA-CCR model showed that individual difference of technical efficiency was obvious in Container Terminal Company, and input-output efficiency was extremely imbalance. The measure results of cross-section data in 2007 indicated that production output was insufficiency while the scale was surplus and the waste of resources was common. 2) Container’s TPF change index of DEA-Malmquist in sample period and decomposition results showed that, technical efficiency, technological progress and scale efficiency changes were characterized by fluctuations, while the overall made positive contribution to TPF productivity promotion. Malmquist TFP of port industry was greater than 1, the average growth was about 14.9%, improvement mainly stem from the promotion of synthesis technology efficiency. Malmquist TFP of Five regional ports presented growth condition, regional container port operations were in the process of continuous improvement, which the improvement of Bohai and Yangtze River Delta region were relatively prominent.
③China's container terminals inner management efficiency loss model and outer economy entironment efficiency loss model based on stochastic front production function were put forward, and discussed incidence and direction which exogenous factors to technical efficiency. Study conclusion:
1) Involvement of external capital caused the structure changes of stocks in container port. It manifested a positive influence to technical efficiency. Technical efficiency of foreign investment and joint venture terminal was significantly higher than the local state-owned terminals. Rate of external funding growth was lower than that of technical efficiency, there was U-inverted structure between the technology efficiency and involvement of external funding. 2) Differences in efficiency caused by differences in size were obvious, and bigger terminal had better technical efficiency. 3)Professional and technical personnel in promoting the efficiency had not been demonstrated. The primary reason was that existing level of knowledge of human resources cannot satisfy the demand of reality and the future development, followed there were varying degrees of redundancy, which is not conducive to increase the production efficiency. 4) Regional economic growth promoted container scale significantly while not promoting enhancement of technical efficiency directly. 5) Increased proportion of tertiary industry in Port city can not only improve the technical efficiency of container, also displayed a strong role for promoting container throughput.
In conclusion, in order to promote China's container port TFP growth, improve technical efficiency, and enhance container port industry, some suggestions such as Promote enterprise property management in container port, introduce overseas strategic investors; strengthen internal management, focus on the effective use of inputs optimize human resource; and plan and develop orderly, conduct resources integration were put forward.
引文
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