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A multi-attribute decision-making model for improving inefficient industrial parks

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Abstract

Although certain countries have proposed revitalization to address the issue of inefficient industrial parks in recent years, there is little research exploring the causes of inefficient industrial parks—although this would help in formulating improvement strategies and further resource allocation. This study presents an evaluation framework for the causes of inefficient urban industrial parks based on a novel hybrid modified multi-attribute decision-making model in real cases, which includes three dimensions and 10 criteria. Two cases of “industrial parks designated by urban planning” in Taiwan were examined. The results of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and the DEMATEL technique based on the basic concept of the analytic network process indicated that the parcel dimension (A1) and policy dimension (A3) had more influence on causing inefficiency in industrial parks. The criteria with bigger impact were “property rights (B1),” “size and shape (B2),” “location (B3),” “planning and development mechanisms (B8),” “management mechanisms (B9),” and “spatial planning policy for industry (B10).” The modified Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) revealed that policy dimension (A3) and its criteria have relatively poor performance in two cases; solving the policy dimension is the most critical strategy for IPDUP. This presented decision-making model not only identifies the key causes of the inefficient industrial park and further improvements to it, but also provides a direction for evaluating, planning, and developing sustainable industrial parks.

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Notes

  1. In the beginning, a total of 30 experts were listed, including nine government officials related to planning and management of industrial land, 10 scholars engaged in research about industrial land planning, development, or use in university, and 11 consultants or managers engaged in industrial land planning or development. After invitations were sent by mail, 15 experts, with five covering each field, were willing to be interviewed. They were then informed of the purpose of the investigation in detail by mail or telephone and sent the expert questionnaire by email or fax.

  2. PIP was usually initiated by a government authority (that is, the industrial authority of the Ministry of Economic Affairs, the processing export park management office, or the competent scientific and technological authority), and development work was usually entrusted to the public sector, such as Taiwan Land Development Corporation or China Engineering Corporation. These development sectors could request that government authorities assist in land acquisition to engage in development work. The construction of roads and necessary public facilities has also been provided by these institutions. When development was completed, the development sectors calculate the development costs to present the pre-price for renting or selling the land. The industrial authority of the Ministry of Economic Affairs ultimately declared the final price for renting or selling land, and then management authority (industrial park management units) leased or sold to various vendors and limited its holding years prior to transfer to other parties (Shen 2002). When the vendors transferred the land in later years, the management authority did not interfere with its prices (Lin and Ben 2009).

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Acknowledgements

This work was supported by Major Program of the National Social Science Foundation of China (Grant No. 17ZDA061) and National Natural Science Foundation of China (Grant Nos. 41701608 and 41771189). The authors also thank Mr. Chen Li,-Wei and Mr. Liu, Kung-Ming for useful help for data collection.

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Authors and Affiliations

  1. School of Government, Nanjing University, 163 Xianlin Avenue, Qixia District, Nanjing City, 210023, Jiangsu Province, China

    Sheng-Hau Lin

  2. School of Geography and Ocean Science, Nanjing University, No. 163, Xianlin Avenue, Qixia District, Nanjing City, 210023, Jiangsu Province, China

    Danyang Wang & Xianjin Huang

  3. School of Public Administration, Hohai University, No. 8, Focheng West Rd., Jiangning District, Nanjing City, 211000, Jiangsu Province, China

    Xiaofeng Zhao

  4. Department of Land Management, College of Construction and Development, Feng Chia University, No. 100, Wenhwa Rd., Seatwen District, Taichung City, 40724, Taiwan

    Jing-Chzi Hsieh

  5. Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, No. 151, University Rd., San Shia District, New Taipei City, 23741, Taiwan

    Gwo-Hshiung Tzeng

  6. School of Geographical Sciences, Nanjing University of Information Science and Technology, No. 219, Ningliu Rd., Pukou District, Nanjing City, 210044, Jiangsu Province, China

    Jia-Hsuan Li

  7. Department of Architecture and Urban Design, College of Environmental Design, Chinese Culture University, No. 55, Hwa-Kang Rd., Yang-Ming-Shan, Taipei City, 11114, Taiwan

    Jia-Tsong Chen

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  1. Sheng-Hau Lin
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Appendices

Appendix 1: Schematic diagram and evaluation form in questionnaire

See Tables 4, 5, and 6 and Fig 4.

Table 4 The 15 experts interviewed and its information
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Table 5 Evaluation form for ten criteria in questionnaire (figure)
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Table 6 Performance evaluation form for ten criterion based on Taiwan’s cases in questionnaire
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Fig. 4
figure 4

Schematic diagram for description of how to fill in the relationship between each criterion in questionnaire

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Appendix 2: Informations of empirical cases

See Table 7.

Table 7 Introduction of Taichung Harbor Related Industrial Park phases 2 and 3 in Taichung City, Taiwan
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Appendix 3: Calculated result related to influence relation matrix

See Tables 8, 9, and 10.

Table 8 Initial influence relation matrix \({\rm A}\)
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Table 9 Normalized influence relation matrix \(\varvec{X}\)
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Table 10 Total influence relation matrix for criteria
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Lin, SH., Wang, D., Huang, X. et al. A multi-attribute decision-making model for improving inefficient industrial parks. Environ Dev Sustain 23, 887–921 (2021). https://doi.org/10.1007/s10668-020-00613-4

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