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The efficiency of major industrial enterprises in Sichuan province of China: A super slacks-based measure analysis

  • *Corresponding author: Kai He

    *Corresponding author: Kai He

The first author is supported by the Fundamental Research Funds for the Central Universities grant 331510004007000002

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  • The main objective of this research is to measure the efficiency of 397 major industrial enterprises in Sichuan province of China in 2013.To this end, we employed DEA super slacks-based measure (Super-SBM) model for performance evaluation of 397 major manufacturing firms.The empirical results show that 21 of the 397 enterprises operate efficiently, and the average efficiency score of the analyzed enterprises is only 0.15. The enterprise with the highest efficiency score is 96.15% higher than the average score, which is the benchmark enterprise of operational efficiency. Among the selected sample enterprises, 5.29% of the industrial enterprises are highly efficient in operation. It was also noticed that the average efficiency score of pharmaceutical firms was the highest among all industrial firms with a mean score of 0.75, which is 80% higher than the overall average score of all industries. While the average efficiency of manufacturing of chemical raw materials and chemical products was the lowest with a mean score of 0.39. Results of sensitivity analysis show that profit has a great impact on the efficiency score of special equipment manufacturing firms, but a relatively weak impact on the firms which manufacture computers, communications, and other electronic equipment. The effect of export delivery value on efficiency score is not obvious.

    Mathematics Subject Classification: Primary: 90B50, 90C46; Secondary: 90B90, 90-11.

    Citation:

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  • Figure 1.  Proportion of industries in the sample population

    Figure 2.  Proportion of industries in the sample population

    Figure 3.  Proportion of industries in the sample population

    Figure 4.  Proportion of industries in the sample population

    Table 1.  Descriptive statistical results of variables

    Variables Mean S.D. Minimum Maximum
    Net asset ($ \yen $1000) 1228690.67 5267546.094 5915 64945892
    Profit total ($ \yen $1000) 79682.71 603428.902 -3216012 10639417
    Gross output value ($ \yen $1000) 1378248.21 7365880.709 59544 124326532
    Export delivery value ($ \yen $1000) 679411.74 6679930.64 15 124326532
    Employees(person) 977.82 4488.57 5 86303
     | Show Table
    DownLoad: CSV

    Table 2.  Results of Pearson's correlation test

    Net asset Profit total Gross output value Export delivery value
    Net asset 1 - - -
    Profit total 0.606** 1 - -
    Gross output value 0.857** 0.854** 1 -
    Export delivery value 0.624** 0.895** 0.915** 1
    Employees 0.660** 0.833** 0.841** 0.899**
    **. Correlation is significant at the 0.01 level (2-tailed).
     | Show Table
    DownLoad: CSV

    Table 3.  The industry classification of 397 enterprises and the corresponding number of enterprises. Note: For the convenience of description, the industry code will be used as a synonym for the industry, i.e., ind. x stands for industry x

    NO. The name of the industry Number of companies
    1 Agricultural and sideline food processing industry 16
    2 Food manufacturing 26
    3 Leather, furs, feathers and their products and footwear 26
    4 Manufacturing of chemical raw materials and chemical products 60
    5 Pharmaceutical manufacturing industry 25
    6 Nonmetallic mineral products industry 19
    7 Metal products industry 18
    8 General Equipment manufacturing 42
    9 Special Equipment manufacturing 44
    10 Automobile manufacturing industry 31
    11 Electrical machinery and equipment manufacturing 34
    12 Manufacturing of computers, communications, and other electronic equipment 56
    Total 397
     | Show Table
    DownLoad: CSV

    Table 4.  Mean and standard deviation of DEA efficiency score of sample population and different industries and corresponding number of effective enterprises

    Industry No. Of DMUs Average of scores SD No. Of efficient DMUs
    Overall 397 0.15 0.37 21
    1 16 0.57 0.6 5
    2 26 0.6 0.6 9
    3 26 0.52 0.57 7
    4 60 0.39 0.54 12
    5 25 0.75 0.71 13
    6 19 0.42 0.63 5
    7 18 0.48 0.69 5
    8 42 0.59 0.6 17
    9 44 0.6 1.52 12
    10 31 0.65 0.73 11
    11 34 0.49 0.77 10
    12 56 0.48 0.8 11
     | Show Table
    DownLoad: CSV

    Table 5.  The list of efficient enterprises and their efficiency scores in the overall evaluation

    Name of the entity Efficiency Industry
    Hongfujin Precision Electronics (Chengdu) 3.9 12
    Sichuan Jinglei Technology 2.51 7
    Dell (Chengdu) 2.47 12
    Sichuan Changhong 1.58 12
    Compal Computer (Chengdu) 1.51 12
    Chengdu Dixin Biotechnology Co 1.37 4
    Sihai development industry 1.33 1
    Intel Products (Chengdu) 1.3 12
    Chengdu Lijun Industry 1.23 9
    Fisher Kuian Transmission and Distribution Equipment (Chengdu) 1.2 8
    Mianzhu Hanwang Inorganic salt chemical industry 1.16 4
    Honghua Petroleum Equipment 1.11 9
    Koren pharmaceutical Co. 1.1 5
    Trida Industries 1.08 7
    Baohe Taiyue communication cable 1.08 11
    Yongxin Meat food 1.06 1
    Jincheng petroleum Machinery 1.05 9
    Xinzhonghao Chemical Co., LTD 1.02 4
    Fly leather industry 1 3
    Huatuo Optical Communications 1 12
    Zyprexa technology 1 7
     | Show Table
    DownLoad: CSV

    Table 6.  The input-output benchmark

    Net asset ($ \yen $1000) Employees Gross output value ($ \yen $1000) Export delivery value ($ \yen $1000) Profit total ($ \yen $1000)
    Current
    General analysis 1228691 978 1378248 679412 79683
    ind.1 635946 469 1304598 35027 95323
    ind.2 240166 496 559188 88369 35379
    ind.3 175921 584 253902 159556 21333
    ind.4 1085540 924 1109159 121324 75691
    ind.5 1052549 435 581058 36860 85528
    ind.6 471576 656 371023 59675 38883
    ind.7 353214 911 647743 28144 57516
    ind.8 1678640 1058 933981 133813 62761
    ind.9 1303109 949 601445 190435 19052
    ind.10 608704 777 637654 40284 12043
    ind.11 980491 894 684541 98161 7254
    ind.12 3226200 2085 5297026 4183804 287258
    Suggestion after analyses
    General analysis 926616 594 3974512 3198523 166636
    ind.1 499935 225 1309227 102404 109285
    ind.2 235144 349 646932 151758 38953
    ind.3 163556 493 314933 308298 35525
    ind.4 1011311 568 1432152 297795 177101
    ind.5 1052549 374 581058 67545 85528
    ind.6 320679 353 468506 163454 80670
    ind.7 326686 801 906470 49946 104271
    ind.8 1678640 813 933981 164141 70845
    ind.9 998251 555 830374 467787 192450
    ind.10 466446 542 637654 178296 31675
    ind.11 763963 668 703241 248042 51609
    ind.12 3226200 1981 5297026 4183804 287258
     | Show Table
    DownLoad: CSV

    Table 7.  Input excesses and output shortfalls(Pct)

    Input excesses (%) Output shortfalls (%)
    Net asset ($ \yen $1000) Employees Gross output value ($ \yen $1000) Export delivery value($ \yen $1000) Profit total ($ \yen $1000)
    General analysis -24.59% -39.26% 188.37% 370.78% 109.12%
    ind.1 -21.39% -51.94% 0.35% 192.36% 14.65%
    ind.2 -2.09% -29.66% 15.69% 71.73% 10.10%
    ind.3 -7.03% -15.68% 24.04% 93.22% 66.53%
    ind.4 -6.84% -38.55% 29.12% 145.45% 133.98%
    ind.5 0.00% -14.02% 0.00% 83.25% 0.00%
    ind.6 -32.00% -46.29% 26.27% 173.91% 107.47%
    ind.7 -7.51% -12.07% 39.94% 77.47% 81.29%
    ind.8 0.00% -23.11% 0.00% 22.66% 12.88%
    ind.9 -23.39% -41.54% 38.06% 145.64% 910.14%
    ind.10 -23.37% -30.27% 0.00% 342.59% 163.01%
    ind.11 -22.08% -25.30% 2.73% 152.69% 611.42%
    ind.12 0.00% -5.01% 0.00% 0.00% 0.00%
     | Show Table
    DownLoad: CSV

    Table 8.  Three combinations of input-output variables

    Input-Output variables All
    I Net asset
    Employees
    Gross output value
    O Export delivery value - -
    Profit total - -
               
    √ means Selected
     | Show Table
    DownLoad: CSV

    Table 9.  The efficiency results of different input-output variable combinations

    Abbr. of enterprise name Diff. combination
    All
    Hongfujin Precision Electronics (Chengdu) 3.9 3.94 3.74 2.23
    Sichuan Jinglei Technology 2.51 1.77 10.32 7.56
    Dell (Chengdu) 2.47 3.92 1.67 2.39
    Sichuan Changhong 1.58 1.5 2.22 3.01
    Compal Computer (Chengdu) 1.51 2.04 1.34 2.01
    Chengdu Dixin Biotechnology Co 1.37 0.94 1.35 0.82
    Sihai development industry 1.33 0.02 1.59 0.98
    Intel Products (Chengdu) 1.3 1.01 1.41 0.92
    Chengdu Lijun Industry 1.23 0.01 1.39 0.17
    Fisher Kuian Transmission and Distribution Equipment (Chengdu) 1.2 0.16 1.33 0.63
    Mianzhu Hanwang Inorganic salt chemical industry 1.16 1.23 1.25 1.61
    Honghua Petroleum Equipment 1.11 0.2 1.18 0.28
    Koren pharmaceutical Co. 1.1 0 1.15 0.16
    Trida Industries 1.08 0.01 1.13 0.48
    Baohe Taiyue communication cable 1.08 0.05 1.13 0.34
    Yongxin Meat food 1.06 0 1.1 0.42
    Jincheng petroleum Machinery 1.05 0.04 1.08 0.38
    Xinzhonghao Chemical Co., LTD 1.02 1.03 0.36 0.32
    Fly leather industry 1 0.83 0.38 0.31
    Huatuo Optical Communications 1 1 1 1
    Zyprexa technology 1 1 1 1
     | Show Table
    DownLoad: CSV
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