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Construction activities taken place in ecologically fragile regions (EFRs) of China are facing a series of environmental obstacles. Studying critical success factors (CSFs) to arrive at the sustainable objectives for construction project in EFRs is needed. Understanding the interrelationships of these CSFs is one of the vital ways to achieve this. This paper identifies and analyzes 18 CSFs for construction projects in EFRs through a literature review from a multi-perspective and a case study of Korla City in China. The causal relationship between each CSF is obtained by pairwise comparisons and thereafter, an ISM (Interpretative Structural Modeling) method is employed to study the hierarchical structuring of the CSFs. As a result, we established a five-level ISM. Subsequently, an MICMAC (cross-impact matrix multiplication applied to classification) approach is implemented to partition and classify each CSF into four quadrants (independent, linkage, autonomous, and dependent) according to their driver and dependence powers. Through the implementation of an MICMAC approach, the degrees of relationship between each CSF is gained. The findings reveal that the studied 18 CSFs have a strong hierarchy and interrelationship. The project manager’s leadership style and economic viability are the root source of project success and has the highest influence, which is supported by the result of MICMAC analysis. CSF planning and implementation of sustainable strategies are more dependent and are influenced by others. The CSFs on the top level of ISM: conflict resolution, planning and implementation of sustainable strategies and resources of water play a significant role in arriving at the project success, and has a great potential for future study. The approaches implemented in this paper can be helpful for decision-makers and managers of construction projects in comprehending the interrelationships and the degrees of CSFs for construction projects in EFRs and for efficiently achieving the project success.

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High-speed railway construction is extending to mountainous areas, and the harsh environment and complex climate pose various risks to the slope construction. This seriously threatens human lives and causes huge economic losses. The existing research results on the construction safety risks of high cutting slope construction in HSRs are limited, and a complete set of safety risk assessment processes and methods has not yet been formed. Therefore, in this study, we aimed to develop a safety risk assessment model, including factor identification and classification and assessment data processing, to help project managers evaluate safety risks in high cutting slope construction. In this study, comprehensive identification of high cutting slope construction safety risks was carried out from three dimensions, risk technical specification, literature analysis, and case statistical analysis, and a list of risk-influencing factors was formed. Based on the historical data, a high side slope risk evaluation model was established using a BP neural network algorithm. The model was applied to the risk evaluation of HF high cutting slopes. The results show that the risk evaluation level is II; the main risks are earthwork excavation method, scaffolding equipment, slope height, slope rate, groundwater, personnel safety awareness, and construction safety risk management system. Finally, a case study was used to verify the proposed model, and control measures for safety risks were proposed. Our findings will help conduct effective safety management, add to the knowledge of construction safety risk management in terms of implementation, and offer lessons and references for future construction safety management of HSR.