Methodology of industry scale analysis under the constraint of regional resource capacity using HSY algorithm

This paper develops a methodology of proper scale analysis for regional industry development, which can be used in industry planning with the consideration of regional resource capacities. In the face of different data sources and even data scarcity, alternative methods based on linear programming a...

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Veröffentlicht in:Resources, conservation and recycling Jg. 53; H. 11; S. 631 - 638
Hauptverfasser: Mo, Hongpin, Wen, Zongguo, Chen, Jining
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Kidlington Elsevier B.V 01.09.2009
Elsevier
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ISSN:0921-3449, 1879-0658
Online-Zugang:Volltext
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Zusammenfassung:This paper develops a methodology of proper scale analysis for regional industry development, which can be used in industry planning with the consideration of regional resource capacities. In the face of different data sources and even data scarcity, alternative methods based on linear programming and quadratic programming algorithms for calculating the resource intensity factors are designed. Based on the empirical study of industrialization, initial scenarios of industry development were set. Using HSY algorithm, sensitive industries that may cause exceeding regional resource capacity can be identified, and the risk of exceeding can be predicted and expressed in probability. Furthermore, a proper scale range can be designed for these sensitive industries according to resource capacity. Taking the case of Dalian city in China, this paper estimated the regional urban development plan, various resources capacities were studied, and land resources were estimated to be the most critical resource for the city. The land resource depletion intensities of different industries are calculated by quadratic programming algorithm. Under the constraint of 427.56 km 2 available industrial land resources, the electronic and power industries have the most significant impact on total land use, if the scale of power industry exceeds 1.27 billion USD, the probability of land resource capacity breakthrough will be 50%.
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ISSN:0921-3449
1879-0658
DOI:10.1016/j.resconrec.2009.04.013