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Evaluation Model of Industrial Operation Quality Under Multi-source Heterogeneous Data Information

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Abstract

Constructing scientific evaluation system and evaluation methods to make timely quantitative evaluation for regional industrial operation quality is of great practical significance for expediting the new industrialization process and promoting the improvement of national economic operation quality. Aiming at the problem of evaluating the industrial operation quality, this paper constructs a new evaluation system from the perspective of industrial operation performance and industrial development potential, and then proposes a multi-source heterogeneous multi-attribute decision-making method based on the linguistic 2-tuple model to evaluate the industrial operation quality. In this method, the original multi-source heterogeneous data whereby real numbers, interval numbers, and linguistic fuzzy numbers coexist are all transformed into linguistic 2-tuples, then a new ranking method based on grey relational degree of linguistic 2-tuple matrix is presented to rank the level of industrial operation quality for the given cities. Further, a decision-making example of evaluating the industrial operation quality for 14 cities in Hunan Province of China is provided to highlight the implementation, availability, and feasibility of the proposed evaluation model.

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References

  1. Staron, M., Meding, W., Nilsson, C.: A framework for developing measurement systems and its industrial evaluation. Inf. Softw. Technol. 51, 721–737 (2009)

    Google Scholar 

  2. Lv, Z.K., Xu, T.: Is economic globalization good or bad for the environmental quality? New evidence from dynamic heterogeneous panel models. Technol. Forecast. Soc. Chang. 137, 340–343 (2018)

    Google Scholar 

  3. Coulibaly, S.K., Erbao, C., MetugeMekongcho, T.: Economic globalization, entrepreneurship, and development. Technol. Forecast. Soc. Chang. 127, 271–280 (2018)

    Google Scholar 

  4. Rao, C.J., Zhao, Y., Zheng, J.J., Wang, C., Chen, Z.W.: An extended uniform-price auction mechanism of homogeneous divisible goods: supply optimisation and non-strategic bidding. Int. J. Prod. Res. 54(13), 4028–4042 (2016)

    Google Scholar 

  5. Liang, Y.Y., Liu, J., Qin, J.D., Tu, Y.: An improved multi-granularity interval 2-tuple TODIM approach and its application to green supplier selection. Int. J. Fuzzy Syst. 21(1), 129–144 (2019)

    MathSciNet  Google Scholar 

  6. Arbolino, R., Boffardi, R., Lanuzza, F., Ioppolo, G.: Monitoring and evaluation of regional industrial sustainability: evidence from Italian regions. Land Use Policy 75, 420–428 (2018)

    Google Scholar 

  7. Wang, B.X.: Study on Construction of Industrial Economic Operation Quality Evaluation System in Yunnan Province. Master Degree Thesis of Yunnan University (2015)

  8. Bian, Y.W., Liang, N.N., Xu, H.: Efficiency evaluation of Chinese regional industrial systems with undesirable factors using a two-stage slacks-based measure approach. J. Cleaner Prod. 87, 348–356 (2015)

    Google Scholar 

  9. Neri, A., Sebastiano, E., Trianni, A.: Industrial sustainability: modelling drivers and mechanisms with barriers. J. Cleaner Prod. 194, 452–472 (2018)

    Google Scholar 

  10. Luh, Y.H., Jiang, W.J., Huang, S.C.: Trade-related spillovers and industrial competitiveness: exploring the linkages for OECD countries. Econ. Model. 54, 309–325 (2016)

    Google Scholar 

  11. UNIDO: Industrial Development Report 2011—Industrial Energy Efficiency for Sustainable Wealth Creation: Capturing Environmental, Economic and Social Dividends (2011)

  12. Luthra, S., Mangla, S.K.: Evaluating challenges to Industry 4.0 initiatives for supply chain sustainability in emerging economies. Process Saf. Environ. Protect. 117, 168–179 (2018)

    Google Scholar 

  13. Bhowmik, C., Bhowmik, S., Ray, A.: Social acceptance of green energy determinants using principal component analysis. Energy 160(1), 1030–1046 (2018)

    Google Scholar 

  14. Wang, Z.X., Wang, Y.Y.: Evaluation of the provincial competitiveness of the Chinese high-tech industry using an improved TOPSIS method. Expert Syst. Appl. 41, 2824–2831 (2014)

    Google Scholar 

  15. Fu, Z.G., Liao, H.C.: Unbalanced double hierarchy linguistic term set: the TOPSIS method for multi-expert qualitative decision making involving green mine selection. Inf. Fusion 51, 271–286 (2019)

    Google Scholar 

  16. Yang, S.L., Bai, Y., Wang, S.F., Feng, N.P.: Evaluating the transformation of China’s industrial development mode during 2000–2009. Renew. Sustain. Energy Rev. 20, 585–594 (2013)

    Google Scholar 

  17. Ghasemi, E., Aaghaie, A., Cudney, E.A.: Mahalanobis Taguchi System: a review. Int. J. Qual. Reliab. Manag. 32(3), 291–307 (2015)

    Google Scholar 

  18. Wan, S.P., Wang, Q.Y., Dong, J.Y.: The extended VIKOR method for multi-attribute group decision making with triangular intuitionistic fuzzy numbers. Knowl.-Based Syst. 52, 65–77 (2013)

    Google Scholar 

  19. Mokhtarian, M.N., Sadi-nezhad, S., Makui, A.: A new flexible and reliable interval valued fuzzy VIKOR method based on uncertainty risk reduction in decision making process: an application for determining a suitable location for digging some pits for municipal wet waste landfill. Comput. Ind. Eng. 78, 213–233 (2014)

    Google Scholar 

  20. Rao, C.J., Goh, M., Zheng, J.J.: Decision mechanism for supplier selection under sustainability. Int. J. Inf. Technol. Decis. Making 16(1), 87–115 (2017)

    Google Scholar 

  21. Rao, C.J., Xiao, X.P., Goh, M., Zheng, J.J., Wen, J.H.: Compound mechanism design of supplier selection based on multi-attribute auction and risk management of supply chain. Comput. Ind. Eng. 105, 63–75 (2017)

    Google Scholar 

  22. Liao, H.C., Xu, Z.S., Herrera-Viedma, E., Herrera, F.: Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the art survey. Int. J. Fuzzy Syst. 20(7), 2084–2110 (2018)

    MathSciNet  Google Scholar 

  23. Liu, P.D., Rong, L.L.: Multiple attribute group decision-making approach based on multi-granular unbalanced hesitant fuzzy linguistic information. Int. J. Fuzzy Syst. (2019). https://doi.org/10.1007/s40815-019-00672-4. (in press)

    Article  Google Scholar 

  24. Liao, H.C., Tang, M., Zhang, X.L., Al-Barakati, A.: Detecting and visualizing in the field of hesitant fuzzy sets: a bibliometric analysis from 2009 to 2018. Int. J. Fuzzy Syst. 21(5), 1289–1305 (2019)

    Google Scholar 

  25. Peng, J.J., Wang, J.Q., Wu, X.H.: Extended ELECTRE I method with multi-hesitant fuzzy information. Int. J. Fuzzy Syst. (2019). https://doi.org/10.1007/s40815-019-00716-9. (in press)

    Article  MathSciNet  Google Scholar 

  26. Liao, H.C., Mi, X.M., Yu, Q., Luo, L.: Hospital performance evaluation by a hesitant fuzzy linguistic best worst method with inconsistency repairing. J. Cleaner Prod. 232(20), 657–671 (2019)

    Google Scholar 

  27. Liao, H.C., Wu, X.L.: DNMA: a double normalization-based multiple aggregation method for multi-expert multi-criteria decision making. Omega (2019). https://doi.org/10.1016/j.omega.2019.04.001. (in press)

    Article  Google Scholar 

  28. Bakhshi, H., Edwards, J.S., Roper, S., Scully, J., Shaw, D., Morley, L., Rathbone, N.: Assessing an experimental approach to industrial policy evaluation: applying RCT+ to the case of Creative Credits. Res. Policy 44, 1462–1472 (2015)

    Google Scholar 

  29. Li, Z.Y., Yang, T., Huang, C.H., Xu, C.Y., Shao, Q.X., Shi, P.F., Wang, X.Y., Cui, T.: An improved approach for water quality evaluation: TOPSIS-based informative weighting and ranking (TIWR) approach. Ecol. Ind. 89, 356–364 (2018)

    Google Scholar 

  30. Ren, Z.L., Xu, Z.S., Wang, H.: Normal wiggly hesitant fuzzy sets and their application to environmental quality evaluation. Knowl. Based Syst. (2019). https://doi.org/10.1016/j.knosys.2018.06.024. (in press)

    Article  Google Scholar 

  31. Govindan, K., Shankar, K.M., Kannan, D.: Application of fuzzy analytic network process for barrier evaluation in automotive parts remanufacturing towards cleaner production—a study in an Indian scenario. J. Cleaner Prod. 114, 199–213 (2016)

    Google Scholar 

  32. Liu, W.J., Zhang, J., Jin, M.Z., Liu, S.F., Chang, X.Y., Xie, N.M., Wang, Y.T.: Key indices of the remanufacturing industry in China using a combined method of grey incidence analysis and grey clustering. J. Cleaner Prod. 168, 1348–1357 (2017)

    Google Scholar 

  33. Liu, W.J., Wu, C., Chang, X., Chen, Y., Liu, S.F.: Evaluating remanufacturing industry of China using an improved grey fixed weight clustering method-a case of Jiangsu Province. J. Cleaner Prod. 142, 2006–2020 (2017)

    Google Scholar 

  34. Liu, X., Tao, Z.F., Chen, H.Y., Zhou, L.G.: A new interval-valued 2-tuple linguistic bonferroni mean operator and its application to multiattribute group decision making. Int. J. Fuzzy Syst. 19(1), 86–108 (2017)

    MathSciNet  Google Scholar 

  35. Rao, C.J., Goh, M., Zhao, Y., Zheng, J.J.: Location selection of city logistics centers under sustainability. Transport. Res. D 36, 29–44 (2015)

    Google Scholar 

  36. Luo, W., Xu, G.R.: A study on China’s industry development quality. China Soft Sci. 1, 50–60 (2013)

    Google Scholar 

  37. Estorilio, C., Vaz, G., Lisboa, F., Bessa, L.: The relationship between industrial process maturity and quality certification. Comput. Stand. Interfaces 39, 22–33 (2015)

    Google Scholar 

  38. Noroozi, S., Wikner, J.: Sales and operations planning in the process industry: a literature review. Int. J. Prod. Econ. 188, 139–155 (2017)

    Google Scholar 

  39. Mumtaz, U., Ali, Y., Petrillo, A.: A linear regression approach to evaluate the green supply chain management impact on industrial organizational performance. Sci. Total Environ. 624, 162–169 (2018)

    Google Scholar 

  40. Haydo, P.A.: From morphological analysis to optimizing complex industrial operation scenarios. Technol. Forecast. Soc. Chang. 126, 147–160 (2018)

    Google Scholar 

  41. Rao, C.J., Zheng, J.J., Wang, C., Xiao, X.P.: A hybrid multi-attribute group decision making method based on grey linguistic 2-tuple. Iran. J. Fuzzy Syst. 13(2), 37–59 (2016)

    MathSciNet  MATH  Google Scholar 

  42. Chen, L., Peng, J., Liu, Z.B., Zhao, R.Q.: Pricing and effort decisions for a supply chain with uncertain information. Int. J. Prod. Res. 55(1), 264–284 (2017)

    Google Scholar 

  43. Liu, Z.B., Zhao, R.Q., Liu, X.Y., Chen, L.: Contract designing for a supply chain with uncertain information based on confidence level. Appl. Soft Comput. 56, 617–631 (2017)

    Google Scholar 

  44. Herrera, F., Martinez, L.: A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Trans. Fuzzy Syst. 8(6), 746–752 (2000)

    Google Scholar 

  45. Herrera, F.: A model based on linguistic 2-tuple for dealing with multi-granularity hierarchical linguistic contexts in multi-expert decision-making. IEEE Trans. Syst. Man Cybern. B 31(2), 227–234 (2001)

    Google Scholar 

  46. Park, J.H., Park, J.M., Kwun, Y.C.: 2-tuple linguistic harmonic operators and their applications in group decision making. Knowl.-Based Syst. 44, 10–19 (2013)

    Google Scholar 

  47. Herrera, F., Martinez, L., Sanchez, P.J.: Managing non-homogeneous information in group decision making. Eur. J. Oper. Res. 166(11), 115–132 (2005)

    MATH  Google Scholar 

  48. Xiao, X.P., Song, Z.M., Li, F.: Grey technology and its application. Science Press, Beijing (2005)

    Google Scholar 

  49. Deng, J.L.: Grey forecasting and grey decision-making. HUST Press, Wuhan (2002)

    Google Scholar 

  50. Yue, Z.L.: An extended TOPSIS for determining weights of decision makers with interval numbers. Knowl.-Based Syst. 24(1), 146–153 (2011)

    Google Scholar 

  51. Wei, G.W.: Grey relational analysis method for 2-tuple linguistic multiple attribute group decision making with incomplete weight information. Expert Syst. Appl. 38, 4824–4828 (2011)

    Google Scholar 

  52. Li, G.X., Kou, G., Peng, Y.: A group decision making model for integrating heterogeneous Information. IEEE Trans. Syst. Man Cybern. 48(6), 982–992 (2015)

    Google Scholar 

  53. Tang, M., Zhou, X.Y., Liao, H.C., et al.: Ordinal consensus measure with objective threshold for heterogeneous large-scale group decision making. Knowl.-Based Syst. 180, 62–74 (2019)

    Google Scholar 

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Acknowledgements

This work is partially supported by the National Natural Science Foundation of China (Grant Nos. 71871174, 71671135), and the Fundamental Research Funds for the Central Universities (WUT: 2019IB013).

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Authors and Affiliations

  1. Business School, Hunan University, Changsha, 410082, People’s Republic of China

    Qinzi Xiao & Miyuan Shan

  2. School of Science, Wuhan University of Technology, Wuhan, 430070, People’s Republic of China

    Xinping Xiao & Congjun Rao

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  1. Qinzi Xiao
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  2. Miyuan Shan
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  4. Congjun Rao
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Correspondence to Miyuan Shan.

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Xiao, Q., Shan, M., Xiao, X. et al. Evaluation Model of Industrial Operation Quality Under Multi-source Heterogeneous Data Information. Int. J. Fuzzy Syst. 22, 522–547 (2020). https://doi.org/10.1007/s40815-019-00776-x

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