Study of the factors influencing the life cycle cost of green buildings using SEM-SD method

ABSTRACT

The recent surge in carbon emissions from the building sector has raised significant environmental concerns. While green building practices have proven effective, their widespread adoption has been hindered by high costs. This study aims to explore the factors impacting the life cycle costs of green buildings, with the aim of achieving “double carbon” reduction. Through an analysis of 42 articles, 24 factors were distilled based on expert opinion. After collecting 322 data through questionnaires, a model of the factors influencing the life cycle cost of green buildings was constructed using structural equation modeling, and a cost simulation study was carried out through the system dynamics method in the practical case to examine how the cost changed. The findings highlight the pivotal role of planning and design, implementation, and operation and maintenance phases. Notably, green building design programs, green construction programs, and the property management level stand out as critical factors emerged as critical factors. These insights can inform strategies to reduce the cost of green buildings, thereby fostering energy conservation and emission reduction in the construction industry.

Graphical Abstract

KEYWORDS:

• Green building
• life cycle cost
• structural equation modeling
• system dynamics

1. Introduction

Excessive greenhouse gas emissions and global industrial development present a significant threat to human society (Breivik 2019; Gao et al. 2023; Robinson 2021). In response, an increasing number of countries have prioritized “carbon neutrality” at a national level (Wei et al. 2022). China, for instance, announced its commitment to carbon peak emissions by 2030 and achieve carbon neutrality by 2060 (referred to as the “dual carbon goals”) in 2020. This commitment is rooted in the principles of sustainable development and the responsibility to build a community of human destiny. All industries face varying levels of pressure to reduce emissions to meet this target within the specified timeframe. According to statistical findings from the China Building Energy Consumption and Carbon Emission Research Report (2022), China’s entire process energy consumption and building-related carbon emissions accounted for 45.5% and 50.9% respectively of the nation’s total energy consumption and carbon emissions in 2020. There is an urgent need to accelerate the development of green buildings and promote energy efficiency and emission reduction in the building industry.

Around 2005, the concept of green building was introduced and widely circulated in China, yet its promotion and application have lagged. Only in recent years have advancements been made in green building-related technologies due to relevant policy regulations. The primary reason for China’s slow progress in green building development is the high costs associated with such projects (Li et al. 2020). This has made developers hesitant to invest (Zuo and Zhao 2014), and the market has shown low participation intentions (Wu, Zheng, and Li 2022). However, due to the rapid development of the Chinese economy and the pursuit of high-quality living standards, there has been a noticeable trend of urban floor area expansion. In 2022, the per capita floor space in cities increased to 36.6 square meters compared to previous years, providing more opportunities for the building industry to expand. In this context, the development of green buildings holds excellent market prospects and is an inevitable trend for future development, given the global emphasis on energy savings and emission reduction.

Besides legislative support, controlling and optimizing the entire life cycle costs of green buildings is crucial for fostering their rapid development in China (Tokbolat et al. 2020).

The majority of recent studies conducted by numerous academics, both domestically and internationally, focus on various aspects of green building, such as purchase intention (Judge, Warren-Myers, and Paladino 2019; Zhang and Dong 2020), policy promotion (Yeganeh et al. 2022), green building transition (Jiang and Payne 2022), market game (MacAskill et al. 2021; Ma, Ren, and Ke 2022), and green building technology (Ge et al. 2020; Luo, Lu, and Ge 2021), etc. However, there have been few studies addressing the issue of green building costs, with most concentrating on incremental costs (Chunling, Zhiying, and Xin 2019; He and Sun 2021; Liu et al. 2022). The mechanism for cost control remains unclear, hindering the promotion of green building due to its high costs. Given these limitations, this study examines the factors influencing green building costs from a whole life cycle perspective, aiming to optimize green construction costs, accelerate green building promotion, and achieve the “double carbon” objective.

This study aims to achieve two theoretical and practical goals. Firstly, it compiles and analyses factors affecting the cost of green building based on relevant literature and cases. Next, the dynamic feedback mechanism of system thinking should be adopted to study the factors throughout the life cycle of green building. This approach will reveal causal relationships between the system’s factors and the overall cost target, as well as dynamic feedback among the factors. Secondly, the simulation model is enhanced using cost information from real green building projects, and the simulation results are compared and examined. This enables a more effective proposal of cost control methods and serves as a benchmark for similar research endeavors.

2. Relevant concepts and research methods

2.1. Description of relevant concepts

2.1.1. Green building

In the 1960s, when Italian architect Paolo Soleri (Austin and Soleri 1974) introduced the concept of “ecological architecture,” the notion of green building emerged. As the energy crisis unfolded and energy-saving building systems underwent continuous development and improvement, green buildings gradually gained prominence in the construction sector during the 1970s. By the 1990s and beyond, with an increase in people’s quality of life, buildings became not only functional spaces but also essential living environments. Simultaneously, the status of green buildings in the construction industry was elevated due to heightened emphasis on ecological, green, and sustainable development. Various research perspectives have provided different definitions of green building. In this study, a green building is defined as one that is environmentally friendly and resource-efficient throughout its life cycle. This encompasses the integration of sustainable development principles into the planning and construction process, adhering to the “four savings and one environmental protection” philosophy. This philosophy combines environmental preservation with the conservation of energy, land, water, and materials. Furthermore, it involves maximizing the use of local environmental and natural resources. Green construction technologies and techniques are utilized to their fullest extent to create a living environment that is green, comfortable, energy-efficient, and conducive to emission reduction.

2.1.2. Whole Life Cycle (WLC) costing theory

The concept of whole life cycle cost was initially proposed by the U.S. Department of Defense in the late 1960s for research and development in weapon assembly. As the theory has evolved over time, its application and research have expanded into other fields (Friedrich 2002). However, in China, due to unique social development and environmental factors, the study of whole life cycle costs in construction projects emerged relatively late. Additionally, there are definitional discrepancies compared to other nations, resulting in various perspectives from both the construction project and societal viewpoints: (1) Whole life cycle costs of construction projects include the discounted cost of construction capital, considering the time value of money. (2) It encompasses expenses incurred by all parties involved in a building project, including economic, social, and environmental aspects throughout the project’s life cycle, with a focus on monetizing all resources.

Based on the theoretical analysis above, coupled with the current state of China’s construction projects and the aims of this paper, the whole life cycle of a green residential building project is segmented into the following phases: decision-making, planning and design, implementation, and operation and maintenance. Since no single green building project in China has yet completed its entire life cycle, as green building is still emerging, we will consider the phase of end-of-life disposal to examine cost fluctuations in typical building projects. By integrating relevant literature with green building materials and resource recycling, this study will develop a suitable simulation model to simulate the dynamic changes in the whole life cycle cost of green building over time.

The whole life cycle cost of a green building is categorized into decision-making and project cost, planning and design cost, implementation cost, operation and maintenance cost, and end-of-life disposal cost through a synthesis of related literature findings and the whole life cycle division outlined in this paper. Methodologies for analysing the whole life cycle cost of green buildings typically include whole life cycle cost analysis (LCC analysis) (Li et al. 2020), whole life cycle cost assessment (LCC evaluation) (Li et al. 2020), and whole life cycle cost management (LCC management) (Li et al. 2020). This paper primarily focuses on LCC analysis. To optimize cost control and management for the entire life cycle of green buildings, it identifies influencing factors such as “four-saving” indexes, usage functions, high technology, and technology programs. Additionally, it examines the interplay between these factors and their impact on the cost units of subsystems. Ultimately, key factors are scrutinized and managed to optimize the whole life cycle cost control of green buildings.

2.2. Research methods

2.2.1. Structural equation model

Structural Equation Model (SEM) falls within the realm of advanced statistics and constitutes a multivariate statistical method for covariance structural analysis. It encompasses two statistical techniques: factor analysis and path analysis, both of which can be applied under the assumption that factor analysis criteria are met. These statistical techniques essentially entail substituting data with latent variables.

This study proposes examining the path analysis of variables influencing the whole life cycle cost of green buildings, utilizing the standardized path coefficients as inputs for system dynamics equations.

2.2.2. System dynamics

System Dynamics (SD) (Karnopp, Margolis, and Rosenberg 1990) combines structural, functional, and historical methods to study, analyze, and address complex social and economic system issues. Its theory and methodology enable the creation of models that facilitate qualitative and quantitative analysis of complex system problems through computer visualization programming simulation.

In this study, a system flow diagram is created, and real-world data are used to parameterize system variables. This allows for the analysis of how each factor influences the system’s goals and fulfils the simulation’s objectives. System dynamics provide the evolutionary outcomes for this study, and structural equation modelling ensures the validity of the system dynamics parameters. The combination of these two approaches results in a more comprehensive and logical examination.

3. Simulation modeling of the whole life cycle costs of green buildings

3.1. Identification of factors influencing the whole life cycle costs of green buildings

The subjects involved in the factors affecting them are complex, with various types of indicators and interpretations. This study aims to establish a preliminary system of cost-influencing factors for green buildings. It will utilize a literature review method to identify these factors across different types of literature, categorize them step by step, comprehend their meanings, and organize them systematically.

The Web of Science search tool was employed to visualize and assess the literature. Keywords like “green building”, “green building cost”, “whole life cycle cost”, and “green building cost influencing factors” were utilized to retrieve 42 articles. The indicators of the factors mentioned in the literature were then compiled, and the list of papers is presented in the Appendix.

The criteria indicators included in the 42 green building cost-related literature screened in Section 3.1.1 are too dispersed and need to be generalized to facilitate future studies due to the diverse research objectives, backgrounds, and relevance of the literature. The first step was to consolidate indicators with similar or comparable meanings. Secondly, indicators with ambiguous definitions were categorized based on the study’s purpose and the principle of the indicator. The selected indicators underwent the aforementioned logic, and Table 1‘s statistical calculation of each indicator’s frequency was performed.

Table 1. Frequency statistics of initial factors.

Initial impact factor system (Frequency)
Green construction organizationand management level (11)	Policy and regulations (21)	Green building design program (7)	Energy conservationand energy use (24)	Water conservationand water use (14)	Wood saving and materialutilization (12)
Land saving and outdoor environmental quality (12)	Indoor environmentalquality (13)	Enterprise development strategy (5)	Geographical conditions of the project (10)	Green building materials and equipment market prices (8)	Architectural star rating (13)
Green building standard (9)	Level of green constructiontechnology (15)	Waste recovery and recycling technologies (4)	Level of green building design (6)	Quality level of constructionpersonnel (8)	Scale of construction (8)
Public awareness ofenvironmental protection (8)	Operations managementtechnology (9)	Green building market environment (6)	Green building assessment and certification system (11)	Government green awareness (7)	Extent of green building research (6)
Level of property management (3)	Green ecological restorationmeasures in case of dismantling (2)	Recycling program (6)	Green building acceptancesystem (4)	Green constructionregulatory efforts (5)	Financial situation of the enterprise and financing conditions (4)
Timing of the green building feasibility study (1)	Green building design contract management (1)	Industry normsand standards (2)	Green construction contract management (2)	Green demolition and repair techniques (6)	Development of related industries (5)

3.2. System of influencing factors on the whole life cycle costs of green building

3.2.1. Revision of the indicator system based on actual cases

Much academic research in this field prioritizes theoretical knowledge but lacks the support of actual projects, leading both the research process and outcomes to stray from reality. Therefore, this study aims to refine the composition of the influencing factors of the entire life cycle cost of green buildings. It will achieve this by integrating traditional examples of green buildings in China and utilizing the expert consultation method to define the final factor system.

The 2021 China Green Real Estate Development Report was officially released during the conference for the 2021 Carbon Neutral Index Research Report for the Real Estate and Construction Industry in January 2022. From among hundreds of green building projects by 75 real estate companies, the top 10 green buildings for 2021 were selected after project disclosure, screening, and expert review. Refer to Table 2 for a detailed analysis.

Table 2. Classic green building analysis.

Project name	Project Location	Project Type	Certification Marks	Project Profile
Nanjing Hexi Jinmao Mansion	Nanjing	Residential buildings	Green Building 3 Stars	Utilizing green eco-technology and building energy-saving technology, combining the local characteristics of Nanjing, we strive to achieve the corresponding three-star green building standards in six aspects: land saving, material saving, energy saving, water saving, indoor environmental quality, and innovation.
Xuhui Shanghai Century Gummi	Shanghai	Residential buildings	International Green Building 2 Stars	Concerning the “Implementation Opinions on Promoting the Development of Ultra-Low Energy Buildings in the City” issued by the Shanghai Municipal Ministry of Housing and Construction, the project incorporates the application of energy-saving technologies, such as passive, active, and renewable energies, into the design scheme of the building, to make the house consume less energy, emit less carbon, and have a better living experience.
Shanghai Wanda Plaza Lingang	Shanghai	Commercial buildings	Green Building 2 Stars; Healthy two stars; Smart Samsung	The project is designed and constructed in strict accordance with the green building concept, with comprehensive consideration given to safety and durability, health and comfort, the convenience of life, resource conservation, environmental livability, and other relevant requirements of green buildings, and the program focuses on the selection of mature green technologies, and the project also employs a digital operation and maintenance management platform based on digital twins to ensure that the building is energy-efficient, high-efficiency, and intelligent in the operation process.
Jindi Huayue	Beijing	Commercial offices	Green Building 3 Stars; LEED Gold	Technical measures: rational use of underground space, saving and intensifying land resources; air-conditioning system adopts high-efficiency cold source system to reduce the energy consumption of supporting systems; renewable energy sources are used to provide heat energy for the buildings; water conservation and indoor environment are both using high and new technologies to realize the requirements of green buildings.
Contemporary Times	Beijing	Residential buildings	LEED: New National Standard 2 stars	The building is designed to be a healthy, green, and low-carbon building with medical care for the elderly, as well as a waste disposal and waste recycling facility.
Lanson Green Center	Shanghai	Commercial offices	LEED/WELL Dual Platinum; Green Building 3 Stars; DGNB; BREEAM	The project adheres to the design principle of “people-oriented” and adopts 108 building technologies in 14 technical systems to realize humanistic design, health and comfort, energy saving, and environmental protection, and the overall energy consumption is lower than 30% of the average value of 5A office buildings.
Hangzhou Zhongyue Jinxiu Mansion	Hangzhou	Residential buildings	Green Building 3 Stars	The project follows the concept of “people-oriented”, adopts the building design science and technology system of “green basic concept, health fundamental principle, and intelligent realization means”, and puts more effort into high-performance thermal insulation enclosure structure, sunshine, outdoor wind and thermal environment, sponge city, and rainwater reuse design, etc. to build a green building in line with the new era.
Greenland Fengdong Wenshang	Shaanxi Province	Residential Offices	Green Building 3 Stars	The project features green roofs, rainwater recycling systems, energy-saving transformers, fresh air ventilators with heat recovery, etc., water-saving technical measures, integrated design of civil construction and decoration, and a CO2 concentration detection system with fan linkage.
Sino-Ocean Lodi Harbor	Beijing	Commercial Synthesis	LEED Gold	The project applies new energy-saving technologies, such as the use of fan frequency conversion, high-efficiency chillers, and district energy supply forms to achieve high-performance operation of the project, and the project’s LEED energy saving reaches 14%; the indoor use of Level 2 water-saving appliances and the use of non-traditional sources of water for flushing toilets, and the project’s overall indoor water-saving rate exceeds 40%.
TaiKoo Hui, Guangzhou	GuangZhou prefecture-level city in Guangdong	Commercial Synthesis	LEED Platinum	The glass and steel structure of the mall not only emphasizes the sense of space but also saves energy. Roof gardens on top of the mall help reduce rainwater runoff and mitigate the urban heat island effect. The project has been finely tuned to improve the energy efficiency performance of the equipment and to utilize renewable energy sources on and off-site.

The analysis of the top ten green building case studies in China in 2021 provides comprehensive coverage of the factors. Traditional case studies of green buildings not only enhance understanding of the factors influencing the whole life cycle cost of green buildings but also validate the reliability of the factors identified using literature techniques.

3.2.2. Modification of factors through expert counselling

To ensure the completeness and effectiveness of the identified influencing factors for the entire life cycle of green buildings, this paper further screens them using the expert consultation method. The panel comprised 10 experts from universities, design firms, construction companies, building materials suppliers, third-party entities (such as supervisors, consultants, and bidding agents), and certified construction professionals. The results and recommendations of the consultation are summarized in Table 3.

Table 3. Experts’ opinions summary.

Suggest	Rationale
Under “project function and size,” “building star rating” and “building size” are unified.	The content of “Project Function and Scale” consolidates both building scale and star rating, which are redundant in the project team workshop material.
“Green building market environment” and “related industry development” are categorized as “extent of the feasibility study”.	During the decision-making phase, feasibility studies will analyse project characteristics across social, economic, and environmental aspects, encompassing the market environment and industrial development.
“Industry norms and standards” and “green building acceptance system” are categorized as “green building policies and regulations”.	The components are interconnected comprehensively, encompassing rules and regulations that address economic subsidies and normative standards.
Replace “prices of green building materials and equipment” with “green construction program” and “level of green construction organization and management” with “level of green construction cost management”.	During the project’s implementation phase, the construction program will encompass the pricing of relevant building materials and equipment. Considering the research objectives of this paper, the focus has been shifted from organizational management to the level of cost management.
“Green ecological restoration measures in the event of dismantling” and “Recycling programs” have been harmonized into “Dismantling and recycling programs”.	The two factors are interconnected and can be uniformly categorized.
Add factor “project location”	The new 2019 standard introduces regulations concerning the “convenience of life” indicator, which includes requirements regarding urban transportation, nearby green spaces, sports venues, and more. Additionally, the economic status of the project location will impact factors such as building prices. Therefore, this indicator has been included.
“Indoor environmental quality” is categorized as a “green building design program”. “Green Building Assessment and Certification System” is categorized as a “Green Building Standard”.	The factors are interrelated.
“Green building design contract management” is categorized as “Green construction contract management”	Primarily contractual changes arise, predominantly during the construction phase.

Based on the initial identification of these factors in the literature study, twenty-four influencing factors on the life cycle cost of green buildings were ultimately identified. These factors were further refined and organized through case profiling and expert consultation. The specifics are displayed in Table 4.

Table 4. Impact factor index system for green buildings’ entire life cycle costs.

Level 1 number	Level 1 indicators	Secondary number	Secondary indicators
A	Government-related factors	A1	Green building standards
		A2	Green building policies and regulations
		A3	Government green awareness
B	Factors related to decision-making on the establishment of projects	B1	Project location
		B2	Project function and scale
		B3	start time of feasibility study
		B4	Extent of feasibility studies
		B5	Enterprise capital position
		B6	Enterprise development strategy
C	Planning and design-related factors	C1	Green building design program
		C2	Green building design level
		C3	Geographical conditions of the project
D	Implementation-related factors	D1	Green construction cost management level
		D2	Green construction program
		D3	Green Construction regulatory efforts
		D4	Green construction technology level
		D5	Green construction contract management
		D6	Quality level of construction personnel
E	Operation and maintenance-related factors	E1	Property management level
		E2	Green operation and maintenance management technology
		E3	Public awareness of greening
F	Factors related to end-of-life disposal	F1	Dismantling and recycling program
		F2	Green demolition and restoration techniques
		F3	Waste recovery and recycling technologies

3.3. Factors influencing the whole life cycle costs of green building: SEM modeling

3.3.1. Modeling and hypothesis formulation

Hypotheses were formulated, and SEM models were constructed based on the aforementioned study with the following assumptions:

H1:

Government-related factors positively influence the whole life cycle cost of green building.

H2:

Factors related to project establishment decision-making positively influence the whole life cycle cost of green building.

H3:

Planning and design-related factors positively influence the whole life cycle cost of green building.

H4:

Implementation-related factors positively influence the whole life cycle cost of green building.

H5:

Operation and maintenance-related factors positively influence the whole life cycle cost of green building.

H6:

End-of-life disposal-related factors positively influence the whole life cycle cost of green building.

The hypothetical model is shown in Figure 1.

Figure 1. Theoretical model of green buildings’ whole life cycle costs.

3.3.2. Reliability test

To explore the aforementioned research hypotheses, this study created a questionnaire comprising two sections: one gathering respondents’ basic information and the other presenting survey questions. Survey questions were rated on a five-point Likert scale from 1 to 5. To ensure the data’s validity and consistency, the questionnaires were distributed to university teachers, experts, and professionals closely related to the study’s topic. In total, 350 questionnaires were distributed, of which 322 valid surveys were obtained after screening for factors such as respondents’ demographics and response times. This represents 92% of the 350 recovered questionnaires.

The alpha reliability analysis approach was typically applied in tandem with the Likert five-level scale method. Upon analysis, it was found that the alpha coefficient value for each variable exceeded 0.8, indicating the reliability of the questionnaire data and meeting the criteria for the next phase of the study. Detailed findings are presented in Table 5.

Table 5. Reliability test results for each variable.

Variable name	Alpha coefficient	Item count (of a consignment etc)
Overall questionnaire	0.938	27
Government-related factors (A)	0.852	3
Factors related to decision-making on the establishment of projects (B)	0.912	6
Planning and design-related factors (C)	0.828	3
Implementation-related factors (D)	0.924	6
Operation and maintenance-related factors (E)	0.871	3
Factors related to end-of-life disposal (F)	0.842	3
Whole life cycle costs of green building (G)	0.889	3
Criterion	Alpha coefficient>0.7 (Xiao et al. 2023)

The questionnaire results underwent evaluation for factor analysis suitability through the KMO and Bartlett’s sphericity tests as part of the validity assessment. Using SPSS software, the validity of the questionnaire data was tested, revealing that the KMO value for each variable exceeded 0.7 and the Bartlett value was less than 0.01 (Feng and Chen 2020). These results confirmed the questionnaire data’s validity, meeting the criteria for the next phase of the study. Specific findings are outlined in Table 6.

Table 6. Validity test results for each variable.

Variable name	KMO values	Bartlett’s value
Overall questionnaire	0.919	0.000
Government-related factors (A)	0.717	0.000
Factors related to decision-making on the establishment of projects (B)	0.909	0.000
Planning and design-related factors (C)	0.714	0.000
Implementation-related factors (D)	0.926	0.000
Operation and maintenance-related factors (E)	0.740	0.000
Factors related to end-of-life disposal (F)	0.717	0.000
Whole life cycle costs of green building (G)	0.748	0.000

3.3.3. Model analysis

Before commencing the path analysis, conducting a model goodness-of-fit test is essential. In this study, a total of 11 indices were selected to evaluate the model’s fit using AMOS26. The results indicate that each index meets the study’s requirements, suggesting a good fit for the model and enabling progression to the next phase [35]. The measurement results for the model fit indices are presented in Table 7.

Table 7. Fitting index results.

Form	Fit Indices	Criteria	Indicators
Absolute Fit Indicator	GFI	>0.8 acceptable >0.8 acceptable	0.881
	AGFI		0.852
	RMSEA	<0.05 good; <0.08 reasonable	0.048
	RMR		0.056
Incremental Fit Indicator	CFI	>0.9	0.960
	NFI		0.911
	IFI		0.960
	TLI		0.953
Simple Fitting Indicator	CMIN/DF	<2	1.743
	PNFI	>0.5	0.787
	PGFI		0.707

In this study, AMOS 26 was utilized to perform the path coefficient test. Table 8 displays the results of the structural model, with six hypotheses being supported at the 0.05 significance level. The standardized path coefficients depicted in Table 8 indicate the relationship and extent of influence between the constructs in the structural model.

Table 8. Parameter estimation and hypothesis testing results of the model.

Variable name	Measurement relationship	Variable name	Unstandardized regression coefficient	Standardized regression coefficient	S.E.	C.R.	p
Government-related factors	→	Whole Life Cycle Costs of Green Building	0.239	0.197	0.070	3.403	***
Factors related to decision-making on the establishment of projects	→		0.148	0.121	0.071	2.075	0.038
Planning and design-related factors	→		0.269	0.255	0.061	4.394	***
Implementation-related factors	→		0.176	0.151	0.062	2.857	0.004
Operation and maintenance-related factors	→		0.190	0.185	0.066	2.873	0.004
Factors related to end-of-life disposal	→		0.180	0.176	0.057	3.159	0.002
Government-related factors	→	A1	1.227	0.864	0.086	14.349	***
	→	A2	1.144	0.836	0.081	14.101	***
	→	A3	1.000	0.738
Factors related to decision-making on the establishment of projects	→	B1	1.073	0.793	0.072	14.936	***
	→	B2	1.164	0.847	0.072	16.174	***
	→	B3	1.070	0.784	0.073	14.745	***
	→	B4	1.092	0.821	0.070	15.583	***
	→	B5	0.978	0.751	0.070	14.022	***
	→	B6	1.000	0.769
Planning and design-related factors	→	C1	1.023	0.830	0710	14.343	***
	→	C2	0.961	0.725	.0750	12.864	***
	→	C3	1.000	0.806
Implementation-related factors	→	D1	1.156	0.856	0.068	16.956	***
	→	D2	1.139	0.820	0.071	16.055	***
	→	D3	1.054	0.814	0.066	15.897	***
	→	D4	1.075	0.829	0.066	16.272	***
	→	D5	1.099	0.816	0.069	15.948	***
	→	D6	1.000	0.781
Operation and maintenance-related factors	→	E1	0.081	0.844	0.066	13.343	***
	→	E2	1.030	0.804	0.065	15.845	***
	→	E3	1.000	0.849
Factors related to end-of-life disposal (F)	→	F1	1.003	0.716	0.059	17.012	***
	→	F2	0.092	0.859	0.056	16.150	***
	→	F3	1.000	0.825
Whole life cycle costs of green building (G)	→	G1	1.000	0.874
	→	G2	0.937	0.830	0.051	18.498	***
	→	G3	1.021	0.852	0.053	19.272	***

3.4. Empowerment of impact factors

By utilizing the correlation coefficient approach, normalized path coefficients are objectively assigned to the variables based on the structural equation model of the entire life cycle cost of a green building.

1) Empowerment of external latent variables

$\mathit{Ki}=\frac{\mathit{Ri}}{\sum _{\mathit{i}=1}^6\mathit{Ri}},$

where K_i is the weight of the external latent variable and R_i is the overall intensity of influence.

2) Assigning weights to observed variables

$\mathit{xij}=\frac{\mathit{rij}}{\sum _{\mathit{j}=1}^n\mathit{rij}},$

$\mathit{kij}=\mathit{Ki}\times \mathit{xij},$

where x_ij is the normalized path coefficient, r_ij is the path coefficient of the observed variable on the latent variable, and k_ij is the weight of the observed variable.

According to the above calculation steps for assigning weights and organizing the weight table of the influencing factors of the entire life-cycle cost of green buildings, the specific results are shown in Table 9.

Table 9. Assignment of factors influencing green buildings’ entire life cycle costs.

Latent variable	Assign a value	Observed variable	Assign a value
Government-related factors(A)	0.182	A1	0.064
		A2	0.062
		A3	0.055
Planning and design-related factors(B)	0.112	B1	0.019
		B2	0.020
		B3	0.018
		B4	0.019
		B5	0.018
		B6	0.018
Planning and design-related factors(C)	0.235	C1	0.083
		C2	0.072
		C3	0.080
Implementation-related factors(D)	0.139	D1	0.024
		D2	0.023
		D3	0.023
		D4	0.023
		D5	0.023
		D6	0.022
Operation and maintenance-related factors(E)	0.171	E1	0.058
		E2	0.055
		E3	0.058
Factors related to end-of-life disposal(F)	0.162	F1	0.053
		F2	0.063
		F3	0.061

3.5. Modeling system dynamics

3.5.1. System boundaries

Based on the research objectives of the simulation system and the structural equation modelling generated for the entire life cycle costs of green buildings, the boundaries of the simulation system were established as follows:

1. The whole life-cycle cost of a green building is primarily influenced by factors related to the government, the decision-making phase of the project, the planning and design phase, the implementation phase, the operation and maintenance phase, and the end-of-life disposal phase. Other external factors, such as force majeure events, are not considered in the indicators affecting its cost.

2. The values assigned to the whole life cycle cost levels of green buildings in this simulation model are generalized and do not account for individual differences between different green buildings.

3. The specified simulation time in the model does not consider the potential impact of force majeure situations, such as natural disasters, on the functionality of the building.

3.5.2. Construction of system flow diagrams

The most crucial component of the system, the system flow diagram of the entire life cycle cost level of the green building, incorporates 56 auxiliary variables alongside seven state variables and six rate variables. This diagram is constructed based on the causal relationships within the simulation system for the entire life cycle cost of green buildings. Table 10 details the specific contents of each variable.

Table 10. System variables for green buildings’ entire life cycle costs.

System Variables	Variable names
State Variables	Green building whole life cycle cost level value: Government level value(A); Value of the cost level at the decision-making phase of the project(B); Planning and design phase cost level value(C); Implementation phase cost level value(D); Operation and maintenance phase cost level value(E); End-of-life disposal phase cost level value(F)
Rate Variables	R(A); R(B); R(C); R(D); R(E); R(F)
Auxiliary Variables	Government level value	Green building standards; L(A1); Green building policies and regulations; L(A2); Government green awareness; L(A3)
	Value of the cost level at the decision-making phase of the project	Project location; L(B1); Project function and scale; L(B2); Start time of the feasibility study; L(B3); Extent of feasibility studies; L(B4); Enterprise capital position; L(B5); Enterprise development strategy; L(B6)
	Planning and design phase cost level value	Green building design program; L(C1); Green building design level; L(C2); Geographical conditions of the project; L(C3);
	Implementation phase cost level value	Green construction cost management level; L(D1); Green construction program; L(D2); Green construction regulatory efforts; L(D3); Green construction technology level; L(D4); Green construction contract management; L(D5); Quality level of construction personnel; L(D6)
	Operation and maintenance phase cost level value	Property management Level;L(E1); Green operation and maintenance management technology;L(E2); Public awareness of greening;L(E4)
	End-of-life disposal phase cost level value	Dismantling and recycling program; L(F1); Green demolition and restoration techniques; L(F2); Waste recovery and recycling technologies; L(F3)

In conclusion, the Vensim-PLE program is utilized to construct a system flow diagram depicting the entire life cycle cost level of green buildings, illustrated in Figure 2. Here, “R” represents input rate and “L” signifies the degree of influence of each indicator on the target variable.

Figure 2. System flow diagram of green buildings’ entire life cycle costs.

3.5.3. Setting of functional equations for variables in simulation models

(1)Related Parameter Settings

Firstly, the simulation system for the whole life cycle cost of green buildings is configured for the following period: INITIAL TIME = 0, FINAL TIME = 50, TIME STEP = 1, and Units=(year, 1). Secondly, state variables have their initial values determined according to parameters derived from the cash flow statement of the specific green building project. Meanwhile, auxiliary variables have their parameters (L) set based on the normalized path coefficients obtained from the structural equation model. The initial values of the factors are established using the mean value extracted from their scoring table and the sum of the errors in the structural equation model.

(2) Setting of SD equations

Functional equations for the variables in the SD model are established based on the system flow diagram of the whole life cycle cost of green buildings and the setting methods of relevant parameters. Since most variables in the model are qualitative, the data need to be dimensionless to ensure the rigour and logic of the study. The specific functional equations are shown below:

1. Green building whole life cycle cost level value = INTEG(L(A) * Government level value + L(B) * Value of the cost level at the decision-making phase of the project + L(C) * Planning and design phase cost level value + L(D) * Implementation phase cost level value + L(E) * Operation and maintenance phase cost level value + L(F) * End-of-life disposal phase cost level value, initial value)

2. Government level value = INTEG(R(A), initial value); R(A) = Equations(L(A1) * Green building standards + L(A2) * Green building policies and regulations + L(A3) * Government green awareness)

3. Value of the cost level at the decision-making phase of the project = (R(B), initial value); R(B) = Equations(L(B1) * Project location + L(B2) * Project function and scale + L(B3) * Start time of feasibility study + L(B4) * Extent of feasibility studies + L(B5) * Enterprise capital position + L(B6) * Enterprise development strategy)

4. Planning and design phase cost level value = (R(C), initial value); R(C) = Equations(L(C1) * Green building design program + L(C2) * Green building design level + L(C3) * Geographical conditions of the project)

5. Implementation phase cost level value = (R(D), initial value); R(D) = Equations(L(D1) * Green construction cost management level + L(D2) * Green construction program + L(D3) * Green construction regulatory efforts + L(D4) * Green construction technology level + L(D5) * Green construction contract management + L(D6) * Quality level of construction personnel)

6. Operation and maintenance phase cost level value = (R(E), initial value); R(E) = Equations(L(E1) * Property management level + L(E2) * Green operation and maintenance management technology + L(E3) * Public awareness of greening)

7. End-of-life disposal phase cost level value = (R(F), initial value); R(F) = Equations(L(F1) * Dismantling and recycling program + L(F2) * Green demolition and restoration techniques + L(F3) * Waste recovery and recycling technologies − 0.03 * Implementation phase cost level value)

4. Empirical studies

This section further enriches the simulation model by integrating relevant cost data from actual green building projects in Beijing’s Daxing District. This integration complements the earlier analysis of the entire life cycle cost of green buildings and the development of the research model, enabling the study to propose more targeted cost control measures.

4.1. Overview of actual cases

The study focuses on a residential building project situated in Daxing District, Beijing, an area that blends residential and commercial properties. This project, classified as a high-rise, single-multi-story public residential building, is designed to have a service life of 50 years. Its structural design features an assembled monolithic shear-wall structure and a raft slab foundation. The project’s green building design adheres to the “Beijing Green Building Evaluation Standard” and “Criteria for Reviewing Construction Drawings of Beijing Green Buildings”. Tables 11 and 12 present the key technical, economic indicators, and green building rating scores.

Table 11. Main technical and economic indicators.

Enterprise	Numerical Value
Total site area	39652.049㎡
Total floor area	149481.59㎡
The floor area above the ground	99130.12㎡
Residential building area	93657.76㎡
Commercial building area	5000㎡
Building heights	45 meters
Residential units (households)	888 households
Number of inhabitants	2176 persons
the ratio of a green area	30%
plot ratio	2.5
building density	25%

Note: The total site area means the area of the horizontal projection of the land occupied or used by the building. The total floor area means the sum of the floor areas above and below the ground level of single or multiple buildings within the construction site.

Table 12. Green building grade score.

Control items	Fulfillment of relevant requirements
Scoring Items	Safety and Durability (Q1)	Health and Comfort (Q2)	Convenience (Q3)	Resource Conservation (Q4)	Livable Environment (Q5)	Improvement and Innovation (Q6)
Scores	32	74	31	101	49	30
Total score	Q = (Q0+Q1+Q2+Q3+Q4+Q5+Q6)\10 = (400+32+74+31+101+49+30)\10 = 71.1>70， Satisfy the requirements of a two-star green building rating

The green building grade calculation follows the guidelines outlined in the Green Building Evaluation Standard GB/T 50,378–2019. Q0 represents the base score of control items, with a maximum of 400 points awarded when all control item requirements are met.

4.2. Simulation model parameter estimates

According to the actual cost data of the green building project, the initial values of the seven state variables in the simulation model are set. Initially, the whole life cycle cost level value of a green building is set as “1”. Then, the normalization method is proposed to handle the cost units at different phases of the actual project, completing the initial value setting of the remaining 6 state variables, and the specific parameters are shown in Table 13. Finally, considering that the parameters of each variable have been normalized and referring to the research of related scholars, the total cost level target value is set as “100”. The aim of this study is to investigate the relationship between the influencing factors and the whole life cycle cost of green buildings. Consequently, the state variables in the simulation model do not change in the actual cost, and their numerical changes only reflect the degree of influence of the indicators on the total cost.

Table 13. Summary of variable economic indicators.

State variables	Cost modules	Amount of costs ($ million)	Normalized values
Green building whole life cycle cost level value	Total Cost	170188.0749	1
Government level value	Government Incentives and Subsidies	468.289	0.002
Value of the cost level at the decision-making phase of the project	Feasibility Study Costs	7	0
Planning and design phase cost level value	Land Costs	110128.39	0.66
	Survey and Design Costs	757
	Cost Consulting Fee	146
	Application for approval of construction capacity increase fee	1365
Implementation phase cost level value	Construction works	23355.99	0.181
	Installation	2348.87
	Preparation Fee	1285.243
	Three passes and one leveling fee	104
	Temporary construction cost	144
	Supervision Fee	158
	Inspection Costs	37
	Cost of Community Pipe Network Project	2527.7
	Landscaping Project Costs	627.18
	Supporting Facilities Fee	252.63
	Environmental Acceptance Fee	7
Operation and maintenance phase cost level value	Residents’ Use Fee	2886	0.164
	Property Management Fee	11463.71
	Specialized Maintenance Fund	11707.22
	Marketing Facility Construction Fee	350
	Property Improvement Fee	138
	Period Charges	1406
End-of-life disposal phase cost level value	Waste disposal costs	327.802	0.003
	Salvage value	873.371

4.3. Comparative analysis of simulation results

The aim of simulation modelling is to analyze the effect of various influencing factors on the whole life cycle cost of green buildings and propose effective targeted improvement measures. This study utilizes the control variables method and scenario simulation to compare and analyze the simulation results under different conditions, primarily focusing on the effects of primary and secondary index factors on the system objectives

• (1) Comparative analysis of the impact of first-level indicator factors

The principle of the control variable method is to assess the impact of first-level indicator elements on the whole life cycle cost of green buildings by maintaining other variables constant and altering only one at a time. Seven scenarios are set, and the trend of green building whole life cycle cost is compared and analyzed based on the simulation results as follows:

• (1) Comparative analysis of the impact of first-level indicator factors

• Scenario 1: Initial state (i.e., parameters of each variable are initial data) simulates the trend of the whole-life cost of green buildings, denoted as “P”;

• Scenario 2: The state variable “government level value” is assigned a 50% higher value to simulate the trend of changes in green building life cycle cost, denoted as “P(A)”;

• Scenario 3: Increase the parameter value of the state variable “value of the cost level at the decision-making phase of the project” by 50% to simulate the trend of changes in green building life cycle cost, denoted as “P(B)”;

• Scenario 4: Increase the parameter value of the state variable “planning and design phase cost level value” by 50% to simulate the trend of changes in green building life cycle cost, denoted as “P(C)”;

• Scenario 5: Increase the parameter value of the state variable “implementation phase cost level value” by 50% to simulate the trend of changes in green building life cycle cost, denoted as “P(D)”;

• Scenario 6: Increase the parameter value of the state variable “operation and maintenance phase cost level value” by 50% to simulate the trend of the whole life cycle cost of the green building, denoted as “P(E)”;

• Scenario 7: Increase the parameter value of the state variable “end-of-life disposal phase cost level value” by 50% to simulate the trend of the whole life cycle cost of the green building, denoted as “P(F)”.

The simulation results are presented in Figure 3.

Figure 3. Trend graph of green buildings’ whole life cycle cost under first level index (partial).

Note: As the normalized value of the “value of the cost level at the decision-making phase of the project” (the initial value of the state variable) is 0, the P(B) line is nearly identical to the P line (with an error rate of 3 per thousand).

Based on the comparative analysis of the scenario simulation results for each state variable in Figure 3, it can be observed:

Factors related to planning and design, implementation, operation and maintenance exert the most significant influence on the whole life cycle cost of green buildings. Among these, Scenario 4 (P(C)) reaches the target value (100) for the total cost first, followed by Scenario 6 (P(E)) and Scenario 5 (P(D)). It is essential to conduct a comprehensive and systematic assessment of the project’s building location, architectural style, and environment during the planning and design phase. Research indicates that although the actual cost incurred in this phase constitutes only 3 percent compared to other phases, the design scheme and level of design have an 80–90% impact on subsequent phases. Therefore, factors related to planning and design play a crucial role in controlling the whole life cycle cost of green buildings. The operation and maintenance phase is when a building realizes its value in use and typically lasts the longest. Upon comparing simulation results, it is evident that this phase ranks second only to the planning and design phase in terms of its influence on the whole life cycle cost. Elements such as operation and maintenance management technology and property management level directly impact residents’ experience and usage fees, thus playing a pivotal role in determining the whole life cycle cost. The implementation phase is pivotal for buildings to realise their full potential, as it involves resource consumption and alterations to the natural environment during the building’s life cycle. The construction program, construction methods, and level of construction technology directly impact the operation and maintenance phase and subsequent life-cycle costs.

Factors related to the government level and project decision-making have more of an indirect impact on the whole life cycle costs of green buildings. The planning and design phase and the implementation phase are more directly impacted by government policies and regulations on green building and industry standards, as well as by the project site selection and project scale decisions made throughout the project decision-making phase. The residual value of the building during the end-of-life disposal phase is, however, more significantly impacted by the degree of technology and management throughout the implementation phase and the operation and maintenance phase. Based on a comparative analysis of the simulation results, it can be observed that the scenario simulation of this echelon has a minor influence because it is closer to the trend graph of the change in the value of the whole life cycle cost level of the green building in its initial state.

• (2) Comparative analysis of the impact effect of secondary indicator factors

In the same way as the above research process, we analyze the influence of secondary indicator factors on the whole life-cycle cost of green buildings at different phases: government level, project decision-making, planning and design, implementation, operation and maintenance, and end-of-life disposal. Adhering to the principle of assigning a 30% increase in parameter values to individual auxiliary variables, the variations in each variable are depicted in Figure 4.

Figure 4. Trend of green buildings’ whole life cycle cost (partial) at each phase of secondary indicators.

Based on the comparative analysis of the simulation results for each scenario of the secondary indicators in Figure 4, the priority order to achieve the goal value (100) of the green building’s whole life cycle cost level is as follows:

Among the relevant factors at the government level, green building policies and regulations have the greatest impact, followed by green building standards and government green awareness. It is evident that green building policies and regulations should significantly influence government cost control. The impact of green building standards and government green awareness on costs should also be duly considered.

The factors in the decision-making phase of the project, in descending order of relevance, are project function and scale, project location, extent of feasibility study, enterprise capital position, enterprise development strategy, and start time of feasibility study. Cost control during the decision-making phase of the project should prioritize project function and scale as key factors, followed by project location and the extent of the feasibility study. The impact of enterprise capital position, enterprise development strategy, and the start time of the feasibility study on costs should also be duly considered.

Among the relevant factors in the planning and design phase, the priority order is green building design program > geographical conditions of the project > green building design level. Therefore, cost control during the planning and design phase should primarily focus on green building design programs. Secondarily, the impact of geographical conditions of the project and the level of green building design on costs should be considered.

Among the relevant factors in the implementation phase, the priority order is green construction program > green construction cost management level > green construction regulatory efforts > green construction contract management > green construction technology level > quality level of construction personnel. It follows that cost control during the implementation phase should prioritize the green construction program as a key factor. Secondary considerations should include the impact of the green construction cost management level, green construction regulatory efforts, green construction contract management, green construction technology level, and the quality level of construction personnel on the cost.

In the operation and maintenance phase, the property management level holds greater significance compared to public awareness of greening and green operation and maintenance management technology. Cost control during the operation and maintenance phase should primarily consider the property management level. Secondly, it should address the influence of public green awareness and green operation and maintenance management technologies on costs.

Among the factors related to the end-of-life disposal phase, green demolition and restoration techniques take precedence, followed by waste recovery and recycling technologies, and dismantling and recycling programs. The cost control of the end-of-life disposal phase should prioritize green demolition and restoration techniques. Additionally, the impact of waste recovery and recycling technologies, along with dismantling and recycling programs on costs, should be duly considered.

From the above analyses, it’s evident that the planning and design phase, the implementation phase, and the operation and maintenance phase exert the most significant influence on the whole life cycle costs of green buildings. Specifically, the green building design program, the green construction program, and the property management level emerge as pivotal factors impacting the entire life cycle cost of green buildings, demanding focused attention.

5. Discussion of countermeasures related to the whole life cycle costs of green buildings

The key index factors for each stage are conclusively identified based on the simulation and analysis results in section 4.3. These aspects must be thoroughly considered when formulating strategies for controlling the whole life cycle cost of green buildings. The specifics are outlined below:

The government should enhance the management of policies, regulations, and standards, as green building policies and regulations play a crucial role in the comparable results of the simulation analysis. Relaxing the criteria for accessing green building financial incentives and developing financial subsidy policies for both labelled and non-labelled green projects are recommended. These enhancements will maximise financial incentives to offset the additional costs of green buildings and ensure the sustainability of the policy, thereby increasing developers’ motivation to opt for green buildings.

• (1) Relevant responses at the decision-making phase of projects

The project’s function and size are significant factors to consider in the comparison simulation study outcomes at this phase. However, when devising countermeasures for this phase, it’s crucial to also take into account factors such as the project’s location and the depth of the feasibility study. It’s advisable to determine the functions and scope of the project as early as possible, based on market research results, to allow ample time for conducting feasibility studies on the program. The new standards clearly indicate that the standard requirements and incremental costs vary greatly for different classes of green buildings. Therefore, the sooner the project’s function and scale are established, the higher the level of feasibility study and program maturity, resulting in better management of incremental costs arising from market and technological uncertainty.

• (2) Relevant responses at the planning and design phase

In the comparative results of the simulation analysis, the green building design program and the geographical conditions of the project emerge as pivotal factors in this phase. When formulating relevant countermeasures, it’s essential to also consider the level of green building design. Utilizing the project’s geographic characteristics and natural resources adequately in the program design is crucial to avoid significant increases in construction costs. Therefore, thorough analysis of the project’s geographical environment and other conditions is necessary at this stage. Different professional and technical personnel should refer to the requirements of different building levels of green residential integrated design, conduct multi-program comparative analysis, and optimize designs to develop a cost-effective and energy-efficient green building program.

• (3) Relevant responses at the implementation phase

In the simulation analysis of the comparison results, the phase involving the green construction program, green construction cost management level, and green construction regulatory efforts significantly impact the outcome. When developing relevant countermeasures, it’s essential to also consider factors like green construction contract management. Additionally, other factors such as the development of pertinent countermeasures and the management of green construction contracts should be considered. Firstly, timely organisation of green building management entails adopting new technologies, methods, processes, and adhering to green building-related policies, regulations, and standards. Learning from experiences of green building cost cases is crucial for developing scientific and reasonable green construction programs to lay the necessary foundation. Secondly, improving the approach to cost management and contract management involves establishing a uniform cost management system and clarifying management responsibilities. Engineering changes and claims involved in contract management should be handled realistically, with well-documented and justified details. Finally, enhancing green building regulation is crucial for maximizing the value of green buildings. Strengthening regulations requires a focus on cooperation and communication within the regulatory process. At all project phases, implementing an incentive-driven monitoring system encourages team members to share knowledge and experience and collaborate to solve problems. Through these measures, maximizing the value of green buildings and maintaining a high standard of green construction practice throughout a project becomes achievable.

• (4) Relevant responses at the operation and maintenance phase

In the comparative results of the simulation analysis, property management level emerges as a key factor in this phase. However, the development of relevant countermeasures should also consider the factors of green operation and maintenance management technology and public awareness of environmental issues. Firstly, increasing public awareness of environmental issues is crucial. Utilizing tools such as the Internet, mobile phones, posters, media, and other mediums can help individuals understand the societal and personal benefits of green consumption and behavior. Secondly, with advancements in technology, the construction industry is incorporating smart buildings and digital technologies. Therefore, implementing an intelligent information service platform and upgrading management practices can significantly enhance the operation of green buildings during the maintenance phase. Intelligent management not only enhances residents’ quality of life but also enables precise energy usage control, leading to reduced operating costs. Finally, enhancing consumers’ understanding and proficiency in green equipment and intelligent technology is essential. This enables them to optimize the use of modern tools effectively.

• (5) Relevant responses at the end-of-life disposal phase

In the comparative results of the simulation analysis, green demolition and restoration technology emerge as key factors in this phase. Additionally, the development of relevant countermeasures should consider factors such as waste recovery and recycling technology. In the disposal and recycling of construction waste, a “producer responsibility” approach should be implemented, wherein those who produce the waste are responsible for its recycling and processing. Advanced green demolition and restoration technologies, along with waste recycling technologies, should be actively utilized in the recycling program to allow for comparison and optimization of multiple options, thereby maximizing the utilization of construction waste. Furthermore, the process of building demolition should not overlook the supervision of green regulators.

6. Conclusion

The advent of green building has offered a promising concept for revolutionizing the construction industry. However, the high cost has emerged as a significant obstacle to its development. Despite increasing research in these domains, the control of whole life cycle costs remains unclear.

This study focuses on investigating the factors influencing the whole life cycle cost of green buildings. It utilizes methods such as literature review, case analysis, and expert consultation to identify these factors comprehensively. A dynamic simulation evolution model of green buildings’ whole life cycle cost is developed, integrating structural equation modelling and system dynamics. Using a two-star green building residential complex in Daxing District, Beijing as a case study, and drawing on simulation results, we analyze the trajectory of the project’s entire life cycle cost. Our analysis indicates that the planning and design phase, the implementation phase, and the operation and maintenance phase are crucial for cost management throughout the life cycle of green buildings, based on an assessment of cost control across various phases. Further analyzing the key influencing factors across different phases of the whole life cycle reveals that government-level green building policies and regulations are pivotal. Additionally, the function and scale of the project during the decision-making phase, the green building design program in the planning and design phase, the green construction program in the implementation phase, the level of property management during operation and maintenance, and green demolition and restoration techniques in the end-of-life disposal phase emerge as key factors. Consequently, to control the life cycle cost of green buildings effectively, optimizing the green building design program, refining the project’s green construction program, and enhancing property management level stand out as the most impactful approaches, significantly reducing overall life cycle costs. These findings offer guidance to stakeholders seeking efficient avenues for green building cost control and program optimization.

The study provides several contributions: (1) Enhanced theoretical understanding of green building costs: By investigating the key factors influencing the whole life cycle costs of green buildings, this research advances theoretical exploration in the field. It also lays the groundwork for the future expansion of green construction in China, providing a theoretical basis for its further development, popularization, and application. (2) Active promotion of high-quality green building: This study concentrates on identifying the influencing factors of green building costs in practical projects. It systematically constructs a simulation system to assess the costs of green buildings throughout their entire life cycle and offers specific cost-cutting recommendations based on the simulation results. These findings can serve as a guide for real estate developers, facilitating the transformation and upgrading of construction enterprises, cost management, and the regulation of the green building materials market. Such efforts effectively drive the growth of green building in China and contribute to the realization of the strategic goal of “greening” the construction industry.

While this paper provides a systematic examination of the whole life cycle costs of green building, it also has certain limitations. Firstly, to enhance its applicability to real-world projects, the variables in the simulation model could be parameterized using actual values. This would enable the construction of more accurate parametric equations and the incorporation of actual cost units into the time dimension for real-time observation of cost trends. By adjusting initial values based on external factors, this approach would offer administrators a more scientifically grounded reference for decision-making. Second, because the cost composition of the entire life cycle of green building is complicated and varied, the research object can be more narrowly defined. The system dynamics simulation model is created to handle the issues brought about by the complex system; the more precisely the variables are divided, the more accurately the simulation results reflect the actual project, and the more effective the pertinent advice is.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available from the corresponding author upon request.

Additional information

Funding

This research was supported by the Postgraduate Innovation Fund of Hebei University of Architecture [XY2024057].

Notes on contributors

Lei Li

Lei Li, M.Sc, is currently working on sustainable engineering.

Shuochen Xiao

Shuochen Xiao, PhD, is a lecturer whose research focuses on user behavior analysis and intelligent decision-making. She has published more than 15 papers in domestic and international academic journals and conferences, and has participated as a key researcher in projects supported by the National Natural Science Foundation of China and the National Key R&D Program.

Zhen Liu

Zhen Liu, M.Sc, is currently working on the renovation of an old neighborhood resident satisfaction.

Changxin Wu

Changxin Wu, M.Sc, is currently conducting research on the performance of whole-process consulting projects.

Shihao Li

Shihao Li, M.Sc, is currently conducting research on urban regeneration.