Life cycle cost of communication towers: identification and hierarchical classification of influencing factors

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 va...

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Main Authors: Jing Zhang, Yang Wang, Qianyi Xu, Hongshuai Gao
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
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Online Access:https://doi.org/10.1038/s41598-025-06334-w
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author Jing Zhang
Yang Wang
Qianyi Xu
Hongshuai Gao
author_facet Jing Zhang
Yang Wang
Qianyi Xu
Hongshuai Gao
author_sort Jing Zhang
collection DOAJ
description 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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spelling doaj-art-a13648a4e58c416ab0c9bfeb2d1516632025-08-20T03:03:27ZengNature PortfolioScientific Reports2045-23222025-07-0115113010.1038/s41598-025-06334-wLife cycle cost of communication towers: identification and hierarchical classification of influencing factorsJing Zhang0Yang Wang1Qianyi Xu2Hongshuai Gao3School of Civil Engineering, Heilongjiang UniversitySchool of Civil Engineering, Heilongjiang UniversityCollege of Computer Science and Technology, College of Software, Heilongjiang UniversitySchool of Civil Engineering, Heilongjiang UniversityAbstract 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.https://doi.org/10.1038/s41598-025-06334-wCommunications towerLife cycle costMulti-source factor identificationGrey-SNAISM
spellingShingle Jing Zhang
Yang Wang
Qianyi Xu
Hongshuai Gao
Life cycle cost of communication towers: identification and hierarchical classification of influencing factors
Scientific Reports
Communications tower
Life cycle cost
Multi-source factor identification
Grey-SNA
ISM
title Life cycle cost of communication towers: identification and hierarchical classification of influencing factors
title_full Life cycle cost of communication towers: identification and hierarchical classification of influencing factors
title_fullStr Life cycle cost of communication towers: identification and hierarchical classification of influencing factors
title_full_unstemmed Life cycle cost of communication towers: identification and hierarchical classification of influencing factors
title_short Life cycle cost of communication towers: identification and hierarchical classification of influencing factors
title_sort life cycle cost of communication towers identification and hierarchical classification of influencing factors
topic Communications tower
Life cycle cost
Multi-source factor identification
Grey-SNA
ISM
url https://doi.org/10.1038/s41598-025-06334-w
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AT yangwang lifecyclecostofcommunicationtowersidentificationandhierarchicalclassificationofinfluencingfactors
AT qianyixu lifecyclecostofcommunicationtowersidentificationandhierarchicalclassificationofinfluencingfactors
AT hongshuaigao lifecyclecostofcommunicationtowersidentificationandhierarchicalclassificationofinfluencingfactors