Description
A performance appraisal is a systematic and periodic process that assesses an individual employee’s job performance and productivity in relation to certain pre-established criteria and organizational objectives.
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Proceedings of the 7th International Conference on Innovation & Management
Research on Performance Evaluation about Investment and Financing Pattern of Urban Infrastructure
Zou Huining, Shen Lei, Tong Teng School of Economics, Wuhan University of Technology,Wuhan, P.R.China, 430070 (E-mail: [email protected], [email protected], [email protected])
Abstract Starting from the analysis of characteristics of urban infrastructure, this paper analyzes the selection factors of its investment and financing pattern. From the perspective of the whole city, the paper establishes synthesis performance appraisal model of the pattern with Analytical Hierarchy Process (AHP). The empirical study is then done on Shanghai, Tianjin, and Kunming in China and the paper takes these three cities to measure the rationality and profitability of the pattern selection. Therefore, by the comprehensive performance evaluation system of its investment and financing mode with a city as a unit can help the urban managers to find the most suitable pattern for the development of urbanization. Key words Urban infrastructure; Investment and financing pattern; Performance appraisal; Analytical Hierarchy Process
1 Introduction
The situation of urban infrastructure is an important support of urban development and civilization level. What’s more, it is also the material conditions of the city’s economic and social development. Since the 80s of the 20th century, the urbanization trend is accelerating and urban infrastructure features and supply is increasingly inadequate with the country’s rapid economic development. Governments have increased investment in urban infrastructure construction. However, the urban infrastructure facility is a complex systematic project, which in certain ways directly or indirectly involved in the city’s production process. Compared with general products and services, it has some special economic characteristics such as natural monopoly, non-competition and exclusive in consumption, and the high concentration in cost, making the project difficult to attract a large number of private capitals. It is difficult to complete even in developed countries with only government finance. To deal with the problem of funds insufficient, governments have introduced competitive mechanism to make the composition of investment and Financing colorful. At the same time, they have broadened the investment and financing channels and optimized the capital structure. The innovation of urban infrastructure’s investment and financing pattern has also been realized by diversifying the modes of investment and financing and improving the efficiency of capital allocation and operation etc.. In all these patterns, BOT, TOT, PPP, and ABS are the most widely used. However, the innovation is a dynamic and diversified progress of choosing which affected not only by the external factors such as financing environment and the area’s general economic environment, but also by the micro factors as technical level and management capacity. For urban managers, only complete grasp the influence effects of mode selection which affected by various factors and have comprehensive performance evaluation on the existing model, they can find the most suitable pattern for the development of urbanization. To this end, many scholars at home and abroad also carried out the corresponding research. Charnes, Cooper and Hodes (1978) carried on evaluation and measurement on supply efficiency of public goods by using data envelopment analysis (DEA). It expands the theory of production frontier. Domestic researches are more focused on the economic effect evaluation of the application of a single project‘s investment and financing models. Fewer researches are done from the prospective of the whole city with consideration of rationality and profitability of the pattern chosen. In china, the city’s infrastructure construction is often one of the major tasks for local governments, whose investment and financing mode needs to be unified arranged and selected by the government. Therefore, it is necessary to establish a comprehensive Performance Evaluation System of its investment and financing mode with a city as a unit.
2 Model Construction
2.1 Ideology of performance rating index system The performance of Urban Infrastructure Investment and Financing Patterns are ultimately reflected in the contribution level of investment and financing on urban development. Therefore, the
Proceedings of the 7th International Conference on Innovation & Management
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performance evaluation model build in this paper includes two levels. First, a comprehensive and well-bedded evaluation system of urban infrastructure development level is established according to the characteristics of urbanization development in China on the basis of AHP and fuzzy comprehensive evaluation method. Then, per capita urban infrastructure investment situation and changes in development level of the urban infrastructure within a period of time are investigated to make judgment on the performance of the mode by using longitudinal evaluation mode. 2.2 System design of evaluation indexes on urban infrastructure development level 2.2.1 Classification and composition Divide the assessment system of urban infrastructure development into hardware environment and software environment those two categories according to the requirements which urban development has on infrastructure environment. The main concern and analysis of hardware environment is the indicators which can direct reflect the quality life of residents and urban infrastructure development. It is used to determine the supply capacity of the city’s infrastructure including the indicators of urban road traffic urban energy, urban communications and urban water supply and drainage those four categories. The soft environment paid more attention on the factors such as the external environment affecting urban infrastructure construction, comfort level of residential living environment, and the sustainable level of urban development. It can be divided into two categories which are the indicators of urban external environment and urban sanitation. On this basis of above, we selected 19 three-level indicators to form the development level indicator system of the investment and financing pattern combining the characteristics of urban infrastructure development. (See Table 1) What’s sure is that many indicators can be used to measure the development level of urban infrastructure and different stages of development and different regions can be adjusted according to actual situation. 2.2.2 Weight assignment of evaluation indexes
Table 1 First-level indexes Evaluation Indexes System of Urban Infrastructure Development Level Second-level indexes Third-level indexes
Indicator
Indicator Evaluation indexes of urban road traffic system
Indicator Road area per citizen The number of cars owned by citizen Rail transportation conditions Urban gas popularization rate The ability of urban distribution network to change electricity Energy consumption per unit of GDP Telephone penetration rate Internet penetration rate Per capita water quantity Water supply capacity Urban water penetration rate Drain pipe density Urban economic development level Financial ecological environment City green coverage rate Urban sewage treatment MSW processing ability Waste harmless treatment rate The number of public toilets people have
Urban hard environmental system
Evaluation indexes of urban energy resources Evaluation indexes of urban communication system Evaluation indexes of urban water drainage system
Evaluation indexes of external environment Urban soft environmental system
Evaluation indexes of environmental health system
(1) Determine factor set of assessment According to the established assessment system, we further determined the factor set of assessment, which is V = { f1 , f 2 L f n } = (Urban Hard Environment Indicators, Urban Soft Environment Indicators).
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The primary estimation index fi representing the affected factors, and f i = f i1 , f i 2 ,L f ij , , where i = 1,2 ... n, n is the number of primary index. j is the number of secondary index included in primary index fi, j = 1,2 ... m. We then get m factors’ matrix eigen value of n evaluation index.
{
}
? F1 ? ? f11 L fim ? ? M ?=? M O M ? F =? ? ? ? ?f L f ? ? ? F nm ? ? n ? ? n1
?1?
(2) Determine weights set of index Use the basic principles of AHP, combine with the structure of evaluation index system and judge the relatively important degree of all indicators using expert scoring method, we assessed the weight of all indicators according to the range of relative importance values provided in the table. F is target value, fi is assessment factor?fi?F(i=1,2,…n). wij is the weight between observation fi and fj. And the numeric areas of wij shown in table 2.
Table 2 Numerical Value of the Relative Importance Index
fi and fj are equally important wij 1
fi slightly important than f j 3
fi important than fj 5
2?4 represented the median of 1?3?3?5?If fi and fj comparability wij, the comparison of fj and fi have 1/wij
In order to ensure the typicality and rationality of the data, we did dispersion degree measurement on each of the weight indicators to determine the need for a second round investigation and get the hierarchical matrix of evaluation index system. Then underway normalized processing and consistency checking on the matrix W gotten above using AHP methods, to generate the weights of all levels, where
?W11 L W1m ? ? W =? ?M O M ? ? ?Wn1 L Wnm ? ?
The judgment matrix meets:
?2?
0 ? wij ? 5 i ? j
wij = 1 i = j wij + w ji = 1 i ? j
Here the unit eigenvector corresponding to the biggest eigenvalue of the judgment matrix can be obtained by integration method. That is , add each line of Matrix firstly and we get:
? = ? in =1 ?ij (i = 1, 2L n)
Then underway normalized processing on vector ? j = (?1 L?n ) ?
(3)
Pj =
?
?j
n i =1
?i
(i = 1, 2,L n)
(4)
Where P?P1, P2, …Pn?are the weight sets desired. Then calculate the biggest eigenvalue ?max of the judgment matrix, we get the consistency index C.I. ?C.I.= ?max-n)/(n-1). According to the average random index R.I. of judgment matrixes with different
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order, we calculate the consistency ratio C.R.?C.R.=C.I./R.I.?and at last realize the consistency test of the matrixes. When C.R.?0.10, the judgment matrix meet the consistency and when C.R.>0.10, the relatively important value need to be amended till it meets the consistency demand. 2.2.3 Establish criteria of data evaluation and grade classification First of all, the way of non-dimensional points is used to divide the sub-system development level of urban infrastructure into four grades—good, fair, general and poor. Here, 80 to 100 points indicates that the urban infrastructure development which represents by the index is good. It can fully meet community needs and provide quality services for residents. 50 to 80 points says that the urban infrastructure development can fully meet the needs of production and residents’ life well, but it has further optimized space in relation to urban development needs. 20 to 50 points indicates that the urban infrastructure development lags behind, which would constrain urbanization if not to transform. 0 to 20 points means that the level of urban infrastructure development lagged far behind, which has already caused great damage to people's daily lives and need to be improved immediately. Secondly, we determine the critical value of grading index. To determine and measure the critical value of urban infrastructure’s development level, the paper compiled the original data of 19 relevant indicators from 1990 to 2008. Based on the reference of average level and target value of international cities whose related indicators developed, and combined with the China's current urbanization development level and regional differences with consideration of the research results which has done by other experts and scholars, this paper at last determined the evaluation criteria and classification threshold of the measurement indicators in current empirical evaluation system. Then, we get the comprehensive weight and the evaluation criteria of the 19 indicators in the urban infrastructure development listed in Table 3. Combined with the indicators weight given above, we can get the comprehensive evaluation value of a city’s infrastructure development level V as follows:
V = ? in=1?i × f i (i = 1, 2K n)
?5?
Where V is the comprehensive value of urban infrastructure development, ?i and fi are the comprehensive weight and the evaluation value of the indicator i respectively. Obviously, a higher comprehensive value indicates a better urban infrastructure development.
·364· Table 3
Proceedings of the 7th International Conference on Innovation & Management
Evaluation Index System Weight and Index Critical Value of Urban Infrastructure Construction
First-level indexes Indicator Weight
Second-level indexes Indicator Urban road traffic Weight
Third-level indexes Indicator Road area per citizen Weight 0.199 0.455 0.346 0.297 0.540 0.163 0.500 0.500 0.423 0.227 0.123 0.227 0.5 0.5 0.317 0.317 0.189 0.103 0.074 80?100
?15 ?20 ?8
Grade value and critical value 50?80 10?15 15?20 6?8 85?95 1.8-1.6 0.65-0.85 1100-1350 200-400 200-250 1.5?1.8 90?95 8-10 1.8?3 0.5?0.8 40%?60% 65%?80% 70%?85% 0.15?0.2 3.8?4.3 20?50 5?10 10?15 4?6 70?85 1.6-1.3 0.85-1 500-1100 100-200 150-200 1.2?1.5 80?90 6-8 1?1.8 0.2?50 20%?40% 50%?65% 55%?70% 0.10?0.15 3.3?3.8 0?20
?5
0.423
The number of cars owned by citizen Rail transportation conditions Urban gas popularization rate
<10
?4 ?70 ?1.3 ?1 ?500 ?100 ?150 ?1.2 ?80 ?6 ?1 ?0.2 ?20% ?50% ? 55% ?0.10 ?3.3
95% 2.2-1.8
?0.65 ?1350 ?400 ?250
Urban energy resources Urban physic environment system 0.7 Urban communication system
0.227
The ability of urban distribution network to change electricity Energy consumption per unit of GDP
0.123
Telephone penetration rate Internet penetration rate Per capita water quantity
Urban water drainage system
0.227
Water supply capacity Urban water penetration rate Drain pipe density
1.8?2 95?100
?10 ?3 ?0.8 ?60% ?80% ?85% ?0.2 ?4.3
External environment Urban soft environment system
0.3
Urban economic development level Financial ecological environment City green coverage rate
0.3 Environmental health system 0.7
Urban sewage treatment MSW processing ability Waste harmless treatment rate The number of public toilets people have
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2.3 Model establishment of performance evaluation on urban infrastructure investment and financing Construction of urban infrastructure is a long process. In order to scientifically evaluate the performance of the urban infrastructure investment and financing mode, we have to investigate that whether level of urban infrastructure development matches the increase value of investment and financing scale of the city within a period of time. If in a certain period of time the growth rate of urban infrastructure development is higher than the growth rate of investment for urban infrastructure, then the choice of investment and financing mode is more suitable for the development of the city with a higher performance level. Shall use the formula said:
Pt ,t + k =
(Vt + k ? Vt ) / Vt ? It +k I ? ?I ? = t ?/? t ? ? ? Rt + k Rt ? ? Rt ?
?6?
Where Pt,t+k indicates the investment and financing pattern performance of a city’s urban infrastructure from year t to t+k ; Vt+k?Vt represents the composite scores of this city ‘s infrastructure development level at year t+k and t respectively ; It+k?It indicates the amount of investment put into urban infrastructure at year t+k and t respectively; Rt+k?Rt states the Average population of urban resident at the year t+k and t respectively.
3 Empirical Analyses
China’s vast territory and distinguish between big cities makes the role of the same kind of investment and financing modes in different urban infrastructure construction different. Obviously, it is not scientific and objectively if only uses the data of one city to reflect the performance problems. Therefore, this paper chose Shanghai, Tianjin and Kunming, these three typical cities to make an empirical analysis. Among these three cities, Shanghai is an international metropolis, whose economic strength, financial resources are rich, and has a rapid development of urbanization. Tianjin city is one of the traditional industrialization whose urbanization development is rapid in recent years, while Kunming is located in southwestern China whose geographical environment is complex and economic strength is relatively backward. It is on behalf of the western underdeveloped region of the city. In terms of time, the years from 2004 to 2008 in China is the peak of urbanization development, and at that time the urban infrastructure investment and financing mode innovations are emerge in an endless stream. This paper will select the related data about urban infrastructure development and performance in 2004 and 2008 respectively in Shanghai, Tianjin and Kunming, and evaluate the investment and financing mode in this period, in order to find the existing problems in Chinese urban infrastructure construction and the way to innovation. This original data comes from “China statistical yearbook”, “China urban statistical yearbook” “Shanghai statistical yearbook”, “Tianjin statistical yearbook” and “Kunming statistical yearbook” respectively in 2005 and 2009 etc. Due to the reasons of statistical data of individual phenomenon inevitably default, this study will use the calculation of sample the default value as the "imaginary value”. Through calculation we can get the urban infrastructure development synthetically score in Shanghai, Tianjin, and Kunming city, seen in Table4. According to the formula of 5 calculated the performance of urban infrastructure investment and financing mode in 2004-2008 in Shanghai Tianjin and Kunming, the result came out that Shanghai is 0.065, while Tianjin and Kunming are 0.2714 and 0.070 respectively.
4 Results Analysis
Underway empirical analysis on urban infrastructure investment and financing patterns of Shanghai, Tianjin and Kunming these three cities, which has different scale and are in three different stages of economic growth using performance evaluation model we found Shanghai is best developed. It is due to the substantial wealth, economic power and financial ecological environment (inside it its urban financial ecological environment index scores is 100 points) which Shanghai have. However, the level of performance in Shanghai is not high as concerns to the 5 years from 2004 to 2008 because of the soaring population. The indicators such as number of private owned cars, City power substation capacity and Per capita water consumption for residential use don’t have obviously improvement. Increasing in
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Proceedings of the 7th International Conference on Innovation & Management
investment fund scale failed to make great improvement in urban infrastructure construction also indicates that there exist problem of wasting fund in the process of construction. Although the overall development level of urban infrastructure construction of Tianjin is slightly lower than that of Shanghai, its performance of urban infrastructure investment and financing pattern is the best in these three cities. Its contribution reached 27.14%, which shows that Tianjin choice a suitable investment and financing mode for their urban infrastructure. Comparatively speaking, the development level of Kunming is the lowest, which is only 48.20 % in year 2008. It is closely related to its external economic environment. Kunming is located in the southwest of China, whose traffic is relatively isolated and financial ecological environment comparatively lag behind. It is difficult to obtain other social capital input for its urban infrastructure construction program except the government financial support. Therefore, the performance level of current financing mode in Kunming is difficult to meet the development needs, which need further mercerization reform and attract non-governmental funds into the market, so as to supplement the shortage of financial capital.
Qscore of the Evaluation Index System on Urban Infrastructure Development Level in City Shanghai, Tianjin and Kunming from2004 to 2008 City Shanghai Tianjin Kunming Year 2004 2008 2004 2008 2004 2008 Urban infrastructure development index 62.06 67.63 39.73 58.37 41.83 48.20 1.Urban hardware environment System index 52.89 60.56 35.28 56.74 37.70 45.31 (1)Urban road traffic system index 68.15 68.37 22.32 60.96 53.73 44.73 Urban road traffic system index 81.00 89.40 45.8 70.34 20.12 61.10 Number of private owned cars index 38.30 35.12 24.2 45.8 99.36 63.98 Rail transport situation index 100 100 6.35 75.5 13.05 10 (2)City energy and power Systems index 39.15 47.02 38.51 45.34 26.71 37.65 City gas penetration index 100 100 94 100 57.23 92.48 City power substation capacity index 12.31 11.24 15.38 15.38 17.08 14.46 Unit GDP energy consumption index 17.17 69 14 45 3 14.46 (3)Urban communication system index 87.68 100 51.45 70.38 23.73 81.84 Telephone penetration index 88.56 100 39.85 52.76 38.25 63.68 Internet penetration index 86.8 100 63.05 88 9.2 100 (4)Urban water supply and drainage system index 23.42 46.22 57.46 63.86 31.93 41.39 Per capita water consumption index 9.87 18.13 6 17.24 8.93 7.47 Water supply capacity index 19 62 91 95 74 100 Urban water coverage index 92 99 94 100 63.80 98 Drainage channels density index 15.93 54.2 100 100 15.47 15.30 2.Urban soft environment system index 83.47 84.12 50.10 62.17 51.46 54.94 (1)Urban external environment index 100 92.70 65.38 62.5 43.63 32.75 Urban development index 100 85.4 79.75 65 49.25 24.5 Urban financial ecological environment index 100 100 51 60 38 41 (2)Urban sanitation systems index 76.39 80.44 43.55 62.03 54.82 64.45 Urban green coverage index 44.05 50.93 44.53 46.25 27 43.9 Wastewater treatment rate index 96.3 93.8 23.6 64.8 58.24 69.28 Municipal solid waste ability index 100 100 98 86 89.78 90.14 Garbage disposal rate index 97.19 98 18.95 93.50 97.85 99.34 Number of Public toilets index 40.4 75.2 20 12.79 10.18 17.64 Table 4
5 Conclusion
In short, this paper analyzed investment and financing pattern of China’s urban infrastructure with the application of performance evaluation model and investigated the rationality and profitability of the model choice in this area from the overall prospective. It provides basis for improvement of profitability level and is efficient for manager in making a timely choice of the model to advance the construction of the urban infrastructure.
References
[1] Charnes, Cooper &Hodes. Measuring the Efficiency of Decision Making Units, Eur. J. Opnl. Res. 429-444
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[2] W. Alexander Roever. Public Capital, Productive Efficiency and Convergence in Spanish Regions[J]. Review of Income and Wealth, 1998, (9): 44 [3] Cui Guo qing. Research on Financing Patterns of China’s Urban Infrastructure[D]. Tianjin: Tianjin University of Finance & Economics, 2009: 39-41 (In Chinese) [4] Guan Hui, Yang Jian. Infrastructure’s Perspective on the Research of Government Investment and Financing[J]. Theory, 2009(5) (In Chinese)
doc_143827121.pdf
A performance appraisal is a systematic and periodic process that assesses an individual employee’s job performance and productivity in relation to certain pre-established criteria and organizational objectives.
·360·
Proceedings of the 7th International Conference on Innovation & Management
Research on Performance Evaluation about Investment and Financing Pattern of Urban Infrastructure
Zou Huining, Shen Lei, Tong Teng School of Economics, Wuhan University of Technology,Wuhan, P.R.China, 430070 (E-mail: [email protected], [email protected], [email protected])
Abstract Starting from the analysis of characteristics of urban infrastructure, this paper analyzes the selection factors of its investment and financing pattern. From the perspective of the whole city, the paper establishes synthesis performance appraisal model of the pattern with Analytical Hierarchy Process (AHP). The empirical study is then done on Shanghai, Tianjin, and Kunming in China and the paper takes these three cities to measure the rationality and profitability of the pattern selection. Therefore, by the comprehensive performance evaluation system of its investment and financing mode with a city as a unit can help the urban managers to find the most suitable pattern for the development of urbanization. Key words Urban infrastructure; Investment and financing pattern; Performance appraisal; Analytical Hierarchy Process
1 Introduction
The situation of urban infrastructure is an important support of urban development and civilization level. What’s more, it is also the material conditions of the city’s economic and social development. Since the 80s of the 20th century, the urbanization trend is accelerating and urban infrastructure features and supply is increasingly inadequate with the country’s rapid economic development. Governments have increased investment in urban infrastructure construction. However, the urban infrastructure facility is a complex systematic project, which in certain ways directly or indirectly involved in the city’s production process. Compared with general products and services, it has some special economic characteristics such as natural monopoly, non-competition and exclusive in consumption, and the high concentration in cost, making the project difficult to attract a large number of private capitals. It is difficult to complete even in developed countries with only government finance. To deal with the problem of funds insufficient, governments have introduced competitive mechanism to make the composition of investment and Financing colorful. At the same time, they have broadened the investment and financing channels and optimized the capital structure. The innovation of urban infrastructure’s investment and financing pattern has also been realized by diversifying the modes of investment and financing and improving the efficiency of capital allocation and operation etc.. In all these patterns, BOT, TOT, PPP, and ABS are the most widely used. However, the innovation is a dynamic and diversified progress of choosing which affected not only by the external factors such as financing environment and the area’s general economic environment, but also by the micro factors as technical level and management capacity. For urban managers, only complete grasp the influence effects of mode selection which affected by various factors and have comprehensive performance evaluation on the existing model, they can find the most suitable pattern for the development of urbanization. To this end, many scholars at home and abroad also carried out the corresponding research. Charnes, Cooper and Hodes (1978) carried on evaluation and measurement on supply efficiency of public goods by using data envelopment analysis (DEA). It expands the theory of production frontier. Domestic researches are more focused on the economic effect evaluation of the application of a single project‘s investment and financing models. Fewer researches are done from the prospective of the whole city with consideration of rationality and profitability of the pattern chosen. In china, the city’s infrastructure construction is often one of the major tasks for local governments, whose investment and financing mode needs to be unified arranged and selected by the government. Therefore, it is necessary to establish a comprehensive Performance Evaluation System of its investment and financing mode with a city as a unit.
2 Model Construction
2.1 Ideology of performance rating index system The performance of Urban Infrastructure Investment and Financing Patterns are ultimately reflected in the contribution level of investment and financing on urban development. Therefore, the
Proceedings of the 7th International Conference on Innovation & Management
·361·
performance evaluation model build in this paper includes two levels. First, a comprehensive and well-bedded evaluation system of urban infrastructure development level is established according to the characteristics of urbanization development in China on the basis of AHP and fuzzy comprehensive evaluation method. Then, per capita urban infrastructure investment situation and changes in development level of the urban infrastructure within a period of time are investigated to make judgment on the performance of the mode by using longitudinal evaluation mode. 2.2 System design of evaluation indexes on urban infrastructure development level 2.2.1 Classification and composition Divide the assessment system of urban infrastructure development into hardware environment and software environment those two categories according to the requirements which urban development has on infrastructure environment. The main concern and analysis of hardware environment is the indicators which can direct reflect the quality life of residents and urban infrastructure development. It is used to determine the supply capacity of the city’s infrastructure including the indicators of urban road traffic urban energy, urban communications and urban water supply and drainage those four categories. The soft environment paid more attention on the factors such as the external environment affecting urban infrastructure construction, comfort level of residential living environment, and the sustainable level of urban development. It can be divided into two categories which are the indicators of urban external environment and urban sanitation. On this basis of above, we selected 19 three-level indicators to form the development level indicator system of the investment and financing pattern combining the characteristics of urban infrastructure development. (See Table 1) What’s sure is that many indicators can be used to measure the development level of urban infrastructure and different stages of development and different regions can be adjusted according to actual situation. 2.2.2 Weight assignment of evaluation indexes
Table 1 First-level indexes Evaluation Indexes System of Urban Infrastructure Development Level Second-level indexes Third-level indexes
Indicator
Indicator Evaluation indexes of urban road traffic system
Indicator Road area per citizen The number of cars owned by citizen Rail transportation conditions Urban gas popularization rate The ability of urban distribution network to change electricity Energy consumption per unit of GDP Telephone penetration rate Internet penetration rate Per capita water quantity Water supply capacity Urban water penetration rate Drain pipe density Urban economic development level Financial ecological environment City green coverage rate Urban sewage treatment MSW processing ability Waste harmless treatment rate The number of public toilets people have
Urban hard environmental system
Evaluation indexes of urban energy resources Evaluation indexes of urban communication system Evaluation indexes of urban water drainage system
Evaluation indexes of external environment Urban soft environmental system
Evaluation indexes of environmental health system
(1) Determine factor set of assessment According to the established assessment system, we further determined the factor set of assessment, which is V = { f1 , f 2 L f n } = (Urban Hard Environment Indicators, Urban Soft Environment Indicators).
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The primary estimation index fi representing the affected factors, and f i = f i1 , f i 2 ,L f ij , , where i = 1,2 ... n, n is the number of primary index. j is the number of secondary index included in primary index fi, j = 1,2 ... m. We then get m factors’ matrix eigen value of n evaluation index.
{
}
? F1 ? ? f11 L fim ? ? M ?=? M O M ? F =? ? ? ? ?f L f ? ? ? F nm ? ? n ? ? n1
?1?
(2) Determine weights set of index Use the basic principles of AHP, combine with the structure of evaluation index system and judge the relatively important degree of all indicators using expert scoring method, we assessed the weight of all indicators according to the range of relative importance values provided in the table. F is target value, fi is assessment factor?fi?F(i=1,2,…n). wij is the weight between observation fi and fj. And the numeric areas of wij shown in table 2.
Table 2 Numerical Value of the Relative Importance Index
fi and fj are equally important wij 1
fi slightly important than f j 3
fi important than fj 5
2?4 represented the median of 1?3?3?5?If fi and fj comparability wij, the comparison of fj and fi have 1/wij
In order to ensure the typicality and rationality of the data, we did dispersion degree measurement on each of the weight indicators to determine the need for a second round investigation and get the hierarchical matrix of evaluation index system. Then underway normalized processing and consistency checking on the matrix W gotten above using AHP methods, to generate the weights of all levels, where
?W11 L W1m ? ? W =? ?M O M ? ? ?Wn1 L Wnm ? ?
The judgment matrix meets:
?2?
0 ? wij ? 5 i ? j
wij = 1 i = j wij + w ji = 1 i ? j
Here the unit eigenvector corresponding to the biggest eigenvalue of the judgment matrix can be obtained by integration method. That is , add each line of Matrix firstly and we get:
? = ? in =1 ?ij (i = 1, 2L n)
Then underway normalized processing on vector ? j = (?1 L?n ) ?
(3)
Pj =
?
?j
n i =1
?i
(i = 1, 2,L n)
(4)
Where P?P1, P2, …Pn?are the weight sets desired. Then calculate the biggest eigenvalue ?max of the judgment matrix, we get the consistency index C.I. ?C.I.= ?max-n)/(n-1). According to the average random index R.I. of judgment matrixes with different
Proceedings of the 7th International Conference on Innovation & Management
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order, we calculate the consistency ratio C.R.?C.R.=C.I./R.I.?and at last realize the consistency test of the matrixes. When C.R.?0.10, the judgment matrix meet the consistency and when C.R.>0.10, the relatively important value need to be amended till it meets the consistency demand. 2.2.3 Establish criteria of data evaluation and grade classification First of all, the way of non-dimensional points is used to divide the sub-system development level of urban infrastructure into four grades—good, fair, general and poor. Here, 80 to 100 points indicates that the urban infrastructure development which represents by the index is good. It can fully meet community needs and provide quality services for residents. 50 to 80 points says that the urban infrastructure development can fully meet the needs of production and residents’ life well, but it has further optimized space in relation to urban development needs. 20 to 50 points indicates that the urban infrastructure development lags behind, which would constrain urbanization if not to transform. 0 to 20 points means that the level of urban infrastructure development lagged far behind, which has already caused great damage to people's daily lives and need to be improved immediately. Secondly, we determine the critical value of grading index. To determine and measure the critical value of urban infrastructure’s development level, the paper compiled the original data of 19 relevant indicators from 1990 to 2008. Based on the reference of average level and target value of international cities whose related indicators developed, and combined with the China's current urbanization development level and regional differences with consideration of the research results which has done by other experts and scholars, this paper at last determined the evaluation criteria and classification threshold of the measurement indicators in current empirical evaluation system. Then, we get the comprehensive weight and the evaluation criteria of the 19 indicators in the urban infrastructure development listed in Table 3. Combined with the indicators weight given above, we can get the comprehensive evaluation value of a city’s infrastructure development level V as follows:
V = ? in=1?i × f i (i = 1, 2K n)
?5?
Where V is the comprehensive value of urban infrastructure development, ?i and fi are the comprehensive weight and the evaluation value of the indicator i respectively. Obviously, a higher comprehensive value indicates a better urban infrastructure development.
·364· Table 3
Proceedings of the 7th International Conference on Innovation & Management
Evaluation Index System Weight and Index Critical Value of Urban Infrastructure Construction
First-level indexes Indicator Weight
Second-level indexes Indicator Urban road traffic Weight
Third-level indexes Indicator Road area per citizen Weight 0.199 0.455 0.346 0.297 0.540 0.163 0.500 0.500 0.423 0.227 0.123 0.227 0.5 0.5 0.317 0.317 0.189 0.103 0.074 80?100
?15 ?20 ?8
Grade value and critical value 50?80 10?15 15?20 6?8 85?95 1.8-1.6 0.65-0.85 1100-1350 200-400 200-250 1.5?1.8 90?95 8-10 1.8?3 0.5?0.8 40%?60% 65%?80% 70%?85% 0.15?0.2 3.8?4.3 20?50 5?10 10?15 4?6 70?85 1.6-1.3 0.85-1 500-1100 100-200 150-200 1.2?1.5 80?90 6-8 1?1.8 0.2?50 20%?40% 50%?65% 55%?70% 0.10?0.15 3.3?3.8 0?20
?5
0.423
The number of cars owned by citizen Rail transportation conditions Urban gas popularization rate
<10
?4 ?70 ?1.3 ?1 ?500 ?100 ?150 ?1.2 ?80 ?6 ?1 ?0.2 ?20% ?50% ? 55% ?0.10 ?3.3
95% 2.2-1.8
?0.65 ?1350 ?400 ?250
Urban energy resources Urban physic environment system 0.7 Urban communication system
0.227
The ability of urban distribution network to change electricity Energy consumption per unit of GDP
0.123
Telephone penetration rate Internet penetration rate Per capita water quantity
Urban water drainage system
0.227
Water supply capacity Urban water penetration rate Drain pipe density
1.8?2 95?100
?10 ?3 ?0.8 ?60% ?80% ?85% ?0.2 ?4.3
External environment Urban soft environment system
0.3
Urban economic development level Financial ecological environment City green coverage rate
0.3 Environmental health system 0.7
Urban sewage treatment MSW processing ability Waste harmless treatment rate The number of public toilets people have
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2.3 Model establishment of performance evaluation on urban infrastructure investment and financing Construction of urban infrastructure is a long process. In order to scientifically evaluate the performance of the urban infrastructure investment and financing mode, we have to investigate that whether level of urban infrastructure development matches the increase value of investment and financing scale of the city within a period of time. If in a certain period of time the growth rate of urban infrastructure development is higher than the growth rate of investment for urban infrastructure, then the choice of investment and financing mode is more suitable for the development of the city with a higher performance level. Shall use the formula said:
Pt ,t + k =
(Vt + k ? Vt ) / Vt ? It +k I ? ?I ? = t ?/? t ? ? ? Rt + k Rt ? ? Rt ?
?6?
Where Pt,t+k indicates the investment and financing pattern performance of a city’s urban infrastructure from year t to t+k ; Vt+k?Vt represents the composite scores of this city ‘s infrastructure development level at year t+k and t respectively ; It+k?It indicates the amount of investment put into urban infrastructure at year t+k and t respectively; Rt+k?Rt states the Average population of urban resident at the year t+k and t respectively.
3 Empirical Analyses
China’s vast territory and distinguish between big cities makes the role of the same kind of investment and financing modes in different urban infrastructure construction different. Obviously, it is not scientific and objectively if only uses the data of one city to reflect the performance problems. Therefore, this paper chose Shanghai, Tianjin and Kunming, these three typical cities to make an empirical analysis. Among these three cities, Shanghai is an international metropolis, whose economic strength, financial resources are rich, and has a rapid development of urbanization. Tianjin city is one of the traditional industrialization whose urbanization development is rapid in recent years, while Kunming is located in southwestern China whose geographical environment is complex and economic strength is relatively backward. It is on behalf of the western underdeveloped region of the city. In terms of time, the years from 2004 to 2008 in China is the peak of urbanization development, and at that time the urban infrastructure investment and financing mode innovations are emerge in an endless stream. This paper will select the related data about urban infrastructure development and performance in 2004 and 2008 respectively in Shanghai, Tianjin and Kunming, and evaluate the investment and financing mode in this period, in order to find the existing problems in Chinese urban infrastructure construction and the way to innovation. This original data comes from “China statistical yearbook”, “China urban statistical yearbook” “Shanghai statistical yearbook”, “Tianjin statistical yearbook” and “Kunming statistical yearbook” respectively in 2005 and 2009 etc. Due to the reasons of statistical data of individual phenomenon inevitably default, this study will use the calculation of sample the default value as the "imaginary value”. Through calculation we can get the urban infrastructure development synthetically score in Shanghai, Tianjin, and Kunming city, seen in Table4. According to the formula of 5 calculated the performance of urban infrastructure investment and financing mode in 2004-2008 in Shanghai Tianjin and Kunming, the result came out that Shanghai is 0.065, while Tianjin and Kunming are 0.2714 and 0.070 respectively.
4 Results Analysis
Underway empirical analysis on urban infrastructure investment and financing patterns of Shanghai, Tianjin and Kunming these three cities, which has different scale and are in three different stages of economic growth using performance evaluation model we found Shanghai is best developed. It is due to the substantial wealth, economic power and financial ecological environment (inside it its urban financial ecological environment index scores is 100 points) which Shanghai have. However, the level of performance in Shanghai is not high as concerns to the 5 years from 2004 to 2008 because of the soaring population. The indicators such as number of private owned cars, City power substation capacity and Per capita water consumption for residential use don’t have obviously improvement. Increasing in
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investment fund scale failed to make great improvement in urban infrastructure construction also indicates that there exist problem of wasting fund in the process of construction. Although the overall development level of urban infrastructure construction of Tianjin is slightly lower than that of Shanghai, its performance of urban infrastructure investment and financing pattern is the best in these three cities. Its contribution reached 27.14%, which shows that Tianjin choice a suitable investment and financing mode for their urban infrastructure. Comparatively speaking, the development level of Kunming is the lowest, which is only 48.20 % in year 2008. It is closely related to its external economic environment. Kunming is located in the southwest of China, whose traffic is relatively isolated and financial ecological environment comparatively lag behind. It is difficult to obtain other social capital input for its urban infrastructure construction program except the government financial support. Therefore, the performance level of current financing mode in Kunming is difficult to meet the development needs, which need further mercerization reform and attract non-governmental funds into the market, so as to supplement the shortage of financial capital.
Qscore of the Evaluation Index System on Urban Infrastructure Development Level in City Shanghai, Tianjin and Kunming from2004 to 2008 City Shanghai Tianjin Kunming Year 2004 2008 2004 2008 2004 2008 Urban infrastructure development index 62.06 67.63 39.73 58.37 41.83 48.20 1.Urban hardware environment System index 52.89 60.56 35.28 56.74 37.70 45.31 (1)Urban road traffic system index 68.15 68.37 22.32 60.96 53.73 44.73 Urban road traffic system index 81.00 89.40 45.8 70.34 20.12 61.10 Number of private owned cars index 38.30 35.12 24.2 45.8 99.36 63.98 Rail transport situation index 100 100 6.35 75.5 13.05 10 (2)City energy and power Systems index 39.15 47.02 38.51 45.34 26.71 37.65 City gas penetration index 100 100 94 100 57.23 92.48 City power substation capacity index 12.31 11.24 15.38 15.38 17.08 14.46 Unit GDP energy consumption index 17.17 69 14 45 3 14.46 (3)Urban communication system index 87.68 100 51.45 70.38 23.73 81.84 Telephone penetration index 88.56 100 39.85 52.76 38.25 63.68 Internet penetration index 86.8 100 63.05 88 9.2 100 (4)Urban water supply and drainage system index 23.42 46.22 57.46 63.86 31.93 41.39 Per capita water consumption index 9.87 18.13 6 17.24 8.93 7.47 Water supply capacity index 19 62 91 95 74 100 Urban water coverage index 92 99 94 100 63.80 98 Drainage channels density index 15.93 54.2 100 100 15.47 15.30 2.Urban soft environment system index 83.47 84.12 50.10 62.17 51.46 54.94 (1)Urban external environment index 100 92.70 65.38 62.5 43.63 32.75 Urban development index 100 85.4 79.75 65 49.25 24.5 Urban financial ecological environment index 100 100 51 60 38 41 (2)Urban sanitation systems index 76.39 80.44 43.55 62.03 54.82 64.45 Urban green coverage index 44.05 50.93 44.53 46.25 27 43.9 Wastewater treatment rate index 96.3 93.8 23.6 64.8 58.24 69.28 Municipal solid waste ability index 100 100 98 86 89.78 90.14 Garbage disposal rate index 97.19 98 18.95 93.50 97.85 99.34 Number of Public toilets index 40.4 75.2 20 12.79 10.18 17.64 Table 4
5 Conclusion
In short, this paper analyzed investment and financing pattern of China’s urban infrastructure with the application of performance evaluation model and investigated the rationality and profitability of the model choice in this area from the overall prospective. It provides basis for improvement of profitability level and is efficient for manager in making a timely choice of the model to advance the construction of the urban infrastructure.
References
[1] Charnes, Cooper &Hodes. Measuring the Efficiency of Decision Making Units, Eur. J. Opnl. Res. 429-444
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[2] W. Alexander Roever. Public Capital, Productive Efficiency and Convergence in Spanish Regions[J]. Review of Income and Wealth, 1998, (9): 44 [3] Cui Guo qing. Research on Financing Patterns of China’s Urban Infrastructure[D]. Tianjin: Tianjin University of Finance & Economics, 2009: 39-41 (In Chinese) [4] Guan Hui, Yang Jian. Infrastructure’s Perspective on the Research of Government Investment and Financing[J]. Theory, 2009(5) (In Chinese)
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