ArticleScientific reports2025
Life cycle cost of communication towers: identification and hierarchical classification of influencing factors.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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4 authors.
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Abstract
Communication towers are essential infrastructure in modern society, require effective life cycle cost (LCC) control for long-term sustainability. While existing research has focused on structural optimization and technological advancements, few studies address cost-related issues across various stages, perspectives, and stakeholders. A multi-source factor identification approach was employed, combining literature review, field surveys, expert interviews, brainstorming, and questionnaires. An integrated Grey-SNA-ISM model was then developed. The method identified 49 factors influencing LCC, integrated Grey-SNA centrality indicators, and established four network hierarchies, which include source-driven, intermediary conduction, collaborative central control, and outcome response. A nine-layer causal hierarchy categorizes factors into fundamental, transitional, and direct influences, revealing a multi-level transmission path from institutional drivers to execution feedback. The results indicate that inadequate policy standards, insufficient management experience, and environmental constraints serve as top-level drivers. These factors flow through intermediary stages like procurement errors and design deviations, leading to downstream cost risks, such as construction delays and operational failures. This creates a dynamic, three-tier cascading structure at the strategic, organizational, and execution levels. The integrated model proposed demonstrates significant adaptability in LCC modeling for communication towers, offering methodological support for factor classification and path identification. Additionally, it shows potential for application in other complex cost systems, facilitating precise interventions and cost control throughout the life cycle.
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