Li, Y; Yao, Z; Wu, J; Zeng, S and Wu, G (2024) Toward ecological environmental risk for spoil ground group management in mega projects. Engineering, Construction and Architectural Management, 31(9), pp. 3706-3726. ISSN 0969-9988
Abstract
Purpose: The numerous spoil grounds brought about by mega transportation infrastructure projects which can be influenced by the ecological environment. To achieve better management of spoil grounds, this paper aims to assess their comprehensive risk levels and categorize them into different categories based on ecological environmental risks. Design/methodology/approach: Based on analysis of the environmental characteristics of spoil grounds, this paper first comprehensively identified the ecological environmental risk factors and developed a risk assessment index system to quantitatively describe the comprehensive risk levels. Second, this paper proposed a comprehensive model to determine the risk assessment and categorization of spoil ground group in mega projects integrating improved projection pursuit clustering (PPC) method and K-means clustering algorithm. Finally, a case study of a spoil ground group (includes 50 spoil grounds) in a mega infrastructure project in western China is presented to demonstrate and validate the proposed method. Findings: The results show that our proposed comprehensive model can efficiently assess and categorize the spoil grounds in the group based on their comprehensive ecological environmental risk. In addition, during the process of risk assessment and categorization of spoil grounds, it is necessary to distinguish between sensitive factors and nonsensitive factors. The differences between different categories of spoil grounds can be recognized based on nonsensitive factors, and high-risk spoil grounds which need to be focused more on can be identified according to sensitive factors. Originality/value: This paper develops a comprehensive model of risk assessment and categorization of a group of spoil grounds based on their ecological environmental risks, which can provide a reference for the management of spoil grounds in mega projects.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | categorization; ecological environment; k-means clustering algorithm; projection pursuit clustering method; risk assessment; spoil grounds |
| Index terms: | environmental risk, China, methodology, clustering, infrastructure project, risk assessment, PPC, transportation infrastructure, case study |
| Subjects: | infrastructure and transport systems, Geography, financial risk, research methods, data science, data collection methods, standard forms of contract |
| Topics: | Digital Applications, Cost Management, Engineering Principles, Geographical Context, Research Practice, Procurement |
| Descriptive scope: | 4 PCTE |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here