A novel knowledge management method about integrated grounded theory for performance assessment of green building construction engineering

ABSTRACT

The green building construction is an important part of the green building, and setting up a suitable assessment model about green building construction engineering has great significance. This paper combined green construction and project management knowledge for performance assessment of green building construction engineering and used integrated method of grounded theory and G2 (G2 empowerment method) entropy method as a knowledge management strategy to build the performance assessment index set. Firstly, based on the existing literature and semi-structured interview data, grounded theory coding technology is used to identify the influencing factors of green construction performance to determine the assessment index set and corresponding assessment standards and formed the assessment index system. Then, the subjective and objective weighting methods are combined, and the G2 entropy method is used to carry out comprehensive weighting. This method has the advantages of comprehensive weighting and avoids the problem of how to allocate the proportion of subjective and objective weight in traditional comprehensive weighting. Finally, a novel knowledge management comprehensive method of performance assessment about green building construction engineering was presented. The detailed methods and steps presented in this paper can provide reference for performance assessment and knowledge management of green building construction engineering.

Graphical Abstract

KEYWORDS:

• Green construction management
• building engineering
• knowledge management
• performance assessment
• grounded theory

1. Introduction

By the end of 2020, the promotion ratio of green buildings in the new buildings in Chinese towns has exceeded 50%, and more than 300 related procedures were issued, which enough reflect the determination of developing green building in the Chinese government. However, compared to some developed countries, China’s green buildings start lately, and the greening of the building has still a large lifting space (Wen et al, 2020). At present, China’s building has some problems including high energy consumption, low emission, low efficiency, and poor quality, and these problems were mainly concentrated in the construction stage (Wan, Bao, and Li 2020). Promoting green buildings in the construction stage is very necessary, and presenting the practical performance assessment method about green building construction has great significance, which can effectively promote the construction transformation and help green building development.

Green building construction is a kind of construction activities that have some characteristics such as people-oriented, resource-saving and are achieved by the scientific management, technological progress, maximizing resource, and reducing the negative impact of engineering construction activities on environmental under the premise of ensuring quality, safety, etc. (GB/50640-2010,2010). Unlike traditional construction, green building construction emphasizes the concept of “four-section and one environmental protection” and will include management, new technology applications, personnel guarantees, etc. (Grunwald et al, 2020). Some countries have now launched a series of green building assessment systems such as the “Leadership in Energy & Environmental Design Building System (Leed) (the United States), “Building Research Establishment Environmental Assessment Method” (U.K.), Australian Building Greenhouse Rating Scheme (Australia), and Comprehensive Assessment System for Building Environmental Efficiency (Japan). Integrating the economic efficiency and social efficiency, short-term efficiency, short-term efficiency, long-term benefits, industry status, and future trends and establishing a green assessment system about construction projects, are important for the improvement of the core competitiveness of construction companies and sustainable development (Zhang et al, 2017). Traditional construction project assessment focuses on the economic benefits, but with the rapid development of information technology and the increasing environmental awareness of environmental protection, traditional assessment models have not met the green sustainable development concept of the current construction industry (Dong, Qing, and Li 2020)

Experts actively participated in the study of the green building construction assessment system and had achieved some certain results.

Bronson (2005) explored the potential of the collaborative approach for local government program assessment, particularly programs administered by nonprofits. The presentation of the concept of green building can be traced back to the 1950s (M HAJEEH et al, 2005). In 1851, in order to improve the air quality in the London Crystal Palace, the designers designed a passive system consisting of “roof ventilation and underground air cooling room” (Ibrahim, Geoffrey, and Robert 2018). In the 1930s, the American architect R. BuckminiSer Fuller took the lead in proposing a “small fee and more” principle, its main concept is the most sufficient, reasonable utilization of limited substance resources, and satisfying humanity survival needs, and reducing resource consumption, which can provide an important theoretical basis for the development of green building construction (Xu et al, 2008). In the 1990s, some developed countries set off research on construction environment. After a longer development and improvement, the green building assessment index system of these countries was basically established, and had been tested in the market. It has strong operation and guiding features. At present, the green building assessment system has a strong representation in the world, and has been widely used and developed by U.K (ECD Energy and Environment 1998), Canada (Raymond and Nils 2020), the United States (Leadership in Energy and Environmental Design, 2004) and Japan (CASBEE-NCB_2006 VI.1, 2016). Ruikar (2007) reviewed different knowledge management (KM) techniques and technologies and then reported the findings of case studies of selected U.K. Han, Lee, and Ko (2014) studied the implementation method of construction performance database prototype for curtain wall operation in high-rise building construction. Zhang et al. (2017) applied “Pressure-Status-Response” theory to green building construction by combining with DEMATEL method and ideal point to build the construction green assessment model. The Leadership in Energy and Environmental Design (LEED) for New Construction and Major Renovations v3 (NC) and LEED for Existing Buildings: Operations and Maintenance v3 (EB) schemes were studied to examine the application of the shearing layer concept to green buildings (Pushkar et al. 2018). Han et al. (2019) considered the logical relationship between the assessment indexes to apply the DEMATEL-ANP method of the dust control assessment model in railway station construction. Ruoslahti (2020) demonstrated that the elements of complexity can be used to gain insight into innovation projects. Wan, Bao, and Li (2020) used the assessment system for environmental impact of tunnel engineering to construct the environmental impact system of the tunnel engineering.

Past assessment studies are generally focused on financial-related indicators, which did not pay attention to non-financial indicators. There are many quantitative indicators in traditional assessment systems. When evaluating, the integrity and comprehensiveness of the assessment content were difficult to achieve, and the operation is very difficult. The assessment standards are not clear and difficult to achieve. The assessment standards do not reflect the regional nature well, which also makes it difficult for construction enterprises to combine policy requirements with the company’s own situation. The assessment system is not advanced after a period of implementation. Therefore, the traditional assessment system needs to be improved. Based on this, this paper presented a novel knowledge management method about integrated grounded theory to collect and summarize the determination index set to determine the weight of the G2 with the entropy value method and can avoid the weight of the main customer right, ultimately presents reasonable, operable performance assessment innovation method of green sustainable building construction.

2. Methods

2.1. The process of the methodology

The process flow graph of the methods used in this paper is shown as Figure 1.

Figure 1. The process flow graph of the methods used in this paper.

2.2. Grounded theory

The principle of combining practicality, appropriateness, quantitative, and qualitative knowledge management methods should be followed when building performance assessment index system of green construction. The encoding technology of grounded theory will be used in the construction performance assessment index system. The grounded theory is a research method by combining the scientific quantitative and qualitative knowledge management methods and according to the basic ideas of “data collection – grade square coding – leading and category” (Charmaz, et al, 2006). The grounded theory was first proposed by scholars Glaser and Strauss used to solve social problems (Edgington 1967). Chen (1999) introduced the grounded theory to China’s social science research, and the grounded theory began to receive attention from Chinese scholars. Li et al. (2006) introduced the grounded theory to management field. Jia et al. (2020) combed the evolutionary process and the path of the grounded theory based on the novelty and quantitative research ideas. Currently, the grounded theory has been widely used in scientific research in the management field. The coding flow diagram of the grounded theory is shown as Figure 2.

Figure 2. The coding flow diagrams of the grounded theory.

2.3. Performance assessment indexes of green building construction

The original statements of the paper are mainly collected through two methods of interviews and literature. Semi-structured interviews are firstly set up in advance to achieve targeted interviews and then communicate with the respondents in the formula. This semi-structured interview method can improve the efficiency of interviews and achieve the goals of interviews through targeted questions. The papers are collected through the semi-structured interview outline of the issue of green construction performance in advance to collect data. The semi-structured interviews are mainly divided into two stages. The first stage is to conduct background investigations of the interviewees. The second stage is to collect the collection of green construction performance factors in actual work.

The interview outline is shown in Table 1.

Table 1. The interview outline table.

The interview step	The interview issue
The background investigation	What is your current occupation? How long have you worked in this industry? Whether you have participated in green construction projects? What is the scale of the project? How is your award case?
In terms of green construction performance	(6) What do you think is the key factor in determining the effectiveness of green construction? Why? (7) What do you think is the significant feature of distinguishing the green construction project and the traditional construction project? (8) In order to achieve green construction, what effective measures have your company taken? What kinds of results have been achieved? (9) What do you think of the pain points of green construction at present and what is worth improving? (10) Have you participated in the management work of green construction projects? (11) What role do you think the management played in green construction? (12)What methods do you use to the manage work? Which indicators are used as the basis for your management work? (13) What are the parts that are not sufficient or need to be updated about the green construction evaluation system and evaluation standards that are currently used?

The choice of interviewing objects is a very critical step in grounded theory. This is a decisive link to ensure the quality of the original data. Although the main body of green construction is a construction enterprise, promoting green construction development requires the cooperation of government, real estate enterprises, construction enterprises, supervision units, and experts and scholars in the field of green construction. Therefore, when the interview object is selected, the basic data is communicated and collected through online interviews, offline interviews, etc., ensuring the diversity and comprehensiveness of the original data. During the semi-structured interview stage, a total of 15 personnel at different occupations and different management levels were interviewed. After soliciting the consent of the interviewees, they conducted interviews, records, and recording. In order to facilitate subsequent coding work, the original information of 15 respondents was marked as A to O.

The basic information of the respondent is shown in Table 2

Table 2. The basic information table of the respondent.

Working years	Less than 3 years	3 ~ 5 years	6 ~ 10 years	More than 10 years
Personnel number	2	5	6	2
Occupation ratio	13.3%	33.3%	40%	13.3%
Employer	Real estate enterprise	Building construction enterprise	Consulting supervision unit	Scientific research unit	Government Environmental Protection Management Department
Personnel number	1	7	3	3	1
Occupation ratio	6.7%	46.7%	20%	20%	6.7%
Position level	Grassroots	Middle layer	High level	other
Personnel number	3	5	3	3
Occupation ratio	20%	33.3%	20%	26.7%

Due to the limited number of objects for interviews, in order to ensure the richness, objectivity, systemic, and comprehensiveness of the original statements, it has been collected to supplement the explanation of objective information related to green construction and project performance assessment.

The sources of objective information are mainly in the following aspects: 1) relevant policies and standards promulgated by the country and localities. 2) from 2018 to 2021, publicity documents and related reports of green construction demonstration sites across the country and localities. In the end, during the collection of the original statement, the basic data collected by the interview and interviews, relevant documents related to the green construction performance assessment, the relevant document policies related to the green construction promulgated by the country and the local area, and the relevant reports of the green construction demonstration site in various places were collected.

Authors use a programmatic rooting theory. This method includes three steps: open encoding, spindle encoding, and selective coding. By analyzing many literatures about performance assessment of green building construction, organizing the assessment criteria about green building construction issued by national and local governments, through the acquisition of 132 interview information statements and 205 original text information statements, uses the rooted coding and axial coding to collect basic data, as shown in Table 3.

Table 3. Open coding and axial coding of the original statement.

Number	Original statements	Index layer	Criterion layer
01	A001 The promotion of green building construction requires the company’s support, coordinate leadership and specific implementation of the managers. The use of passive, negative, and deductive attitude should not be used to treat green building construction technology. Managers should actively use a scientific management method and system’s thinking mode to instruct personnel to carry out green building construction.	Green management, project management, personnel management	Management class
02	A011 The BIM technology can be helpful for clear grasping the actual effect of green environmental protection materials and technology during construction which can be provided the basis for the subsequent resource consumption and environmental protection.	BIM Technical application	Technical class
03	A057 Many urban green building construction projects can be participated in the awards, which can be used to enhance the reputation of the company and increase the competitiveness of enterprises.	Project award	Influence class
04	A101 In order to meet the requirements of the government and the people, the contractors and construction units generally take some techniques to carry out environmental protection, such as sprinkling water at the construction site to control dust height, regularly perform noise detection on the site, in the construction site for sewage settings at the construction site, the sedimentation tank, reducing nighttime construction, etc for enhancing the corporate self-image.	Dust emissions, domestic sewage emission rate, construction waste water emission rate, noise index	Environment class
05	A135 Many construction workers do not understand the green construction, not familiar, and have no awareness of green construction.	Personnel management	Personnel class

The open encoding process can be divided into three stages: the labialization of the original statement, the conceptualization of the label, and the category. The process of labelling of the original sentence is to analyze and identify the original statements collected by the interview and to follow the sentence by word, and in the original statement, refining and a brief label to automatically encode the theme and label the identification object; the conceptual category can be carried out at the same time. This stage is to compare and analyze all labels. The indicators with less frequency and repeated frequency and repetition are eliminated to form a main concept. During the open encoding stage, the 15 parts of the samples collected earlier were split into two parts, of which 12 were used as an open encoding stage encoding translation, and 3 were used as the theoretical saturation test.

The main axis coding is to refine the category formed by open encoding. Based on the labels, concepts, and categories generated by the open encoding stage, we find the internal connection and the relationship between the categories and summarize the main categories. Through the open encoding of the interview data and the analysis of existing literature, identifying the green construction performance assessment factors of 26 sub-categories levels, after the main coding of the main axis, the three main categories of green construction, technology and management, and effective results have been obtained.

Further, the collected data were analyzed, some frequency less and repetition indexes were removed, and the primary index layer was formed. Analyzing the connection between the index layers to present the criterion layer index and finally build the assessment index set about green building construction performance of 27 indicators of 6 dimensions, shown as in Table 4.

Table 4. The performance assessment index of green building construction.

Criterion layer	Index layer	Index type
Management class A1	Project management A11	Qualitative/Positive direction
	Green management A12	Qualitative/Positive direction
	Personnel management A13	Qualitative/Positive direction
Technical class A2	BIM Technology application A21	Qualitative/Positive direction
	Project dynamic tracking management A22	Qualitative/Positive direction
	Green building construction technology uses A23	Qualitative/Positive direction
	Green equipment input rate A24	Quantification/Positive direction
Environment class A3	Construction waste water emission rate A31	Quantification/Positive direction
	Domestic sewage emission A32	Quantification/Positive direction
	Dust emissions A33	Quantification/Negative direction
	Exhaust emissions A34	Quantification/Negative direction
	Garbage loss quantity A35	Quantification/Negative direction
	Garbage recycling utilization A36	Quantification/Positive direction
	Noise index A37	Quantification/Negative direction
Resource class A4	Water sailor put into A41	Quantification/Positive direction
	Waste water circulation utilization A42	Quantification/Positive direction
	Effective utilization of land resources A43	Quantification/Positive direction
	Green material usage rateA44	Quantification/Positive direction
	Approach take the material rate A45	Quantification/Positive direction
	Material turnover usage A46	Quantification/Positive direction
	Radiolarian rate A47	Quantification/Positive direction
	Energy integrated use A48	Quantification/Positive direction
Economy class A5	Enterprise Increase and End Yield A51	Quantification/Positive direction
	Improve the level of corporate economic internal rate of return A52	Quantification/Positive direction
Influence class A6	Service customer satisfaction A61	Quantification/Positive direction
	Radiation regional public satisfaction A62	Quantification/Positive direction
	Project awards A63	Quantification/Positive direction

2.4. Establishing indicator weight based on G2 entropy value method

2.4.1. The G2 method

The G2 method is to reasonably determine the weight of the assessment index in the group decision one of the effective methods is that the core is to determine the importance of the assessment indicators ratio. The G2 method is also named the only reference comparison judgment method, which is a typical subjective empowerment method and includes point assignment and interval assignment (Yan, Chi, and He 2010). For example, Liu et al. (2020) used the G2 method corrected by entropy value in a comprehensive assessment of the benefits of water-saving measures and avoiding the situation of the traditional G2 method and objective data conflict. Its basic ideas of G2 method are:

(1) The least important indicator selection: Experts first select the index set x {x1, x2, … , xn}, the least important indicator is written as xin, put xin at the last bit of the collection, at this time the set is written as Xi {xi1, xi2, …, xin}.

(2) Determine the important degree ratio: treat the indicator xin as a unique reference, experts give the remaining index xij (j = 1, 2 … n-1) compared to the importance degree ratio of the indicator xin.

(3) Calculate the indicator weights: calculate the respective assessment index weights through important degree ratio.

First of all, use the G2 method to determine the most important indicators and invite experts to select the most important indicators in the indicators: Energy-saving equipment, noise index, project dynamic tracking management, personnel management, radiation regional people’s satisfaction, green construction increase costs. The most important indicators of the second-level indicators on the first-level indicators are land conservation, land resource protection, technical application, and economic impact. The most important indicator of the first-level indicators for the target layer is technical and management. From data constructive characteristic matrix XIJ, the most important indicator is placed in the last line of the corresponding criteria and the matrix is processed infinitely. If the subjective judgment of experts conflicts with the objective information reflected by the value, it will be considered that the importance of the two will be the same.

2.4.2. The entropy value method

The entropy value method that can be realistic, objective information contained in itself is an objective empowerment method that is often used in the comprehensive assessment (Guo et al, 1994). The basic idea is shown as following.

(1) Build the feature matrix. This article selects the characteristic matrix of 27 indicators of 5 construction projects and the assessment index set constructed above Xij, i = (1,2, … ,m); j = (1, 2 … n); Where m = 5, n = 27.

(2) Dimensionless processes. The feature matrix is subjected to a quantity of abutment. This paper has the forward and negative indexes for two types of indicators. The forward index uses the formula (1), and the negative direction index is equipped with equation (2)(2) $y_{ij}=\frac{max{x}_{ij}-x_{ij}}{max{x}_{ij}-min{x}_{ij}}$(2) , and finally obtains a normalized matrix. A = (yij)m × n, i = (1,2, … ,m); j = (1, 2 … n).

(1) $y_{ij}=\frac{x_{ij}-min{x}_{ij}}{max{x}_{ij}-min{x}_{ij}}$(1)

(2) $y_{ij}=\frac{max{x}_{ij}-x_{ij}}{max{x}_{ij}-min{x}_{ij}}$(2)

(3) Calculate the entropy value of the index. Firstly, eliminate the zero value.

Set

(3) $A_{ij}=A_{ij}+\alpha ,\alpha \mathrm{i}\mathrm{s}0.001$(3)

Set

(4) $p_{ij}=ln\left(\frac{(\alpha +y_{ij})}{\sum _{i=1}^m(\alpha +y_{ij})}\right)$(4)

The entropy value is

(5) $e_j=-\frac{1}{lnm}\sum _{i=1}^m{p}_{ij}ln\left(p_{ij}\right)$(5)

2.4.3. G2 combined entropy value method

The index weight of the performance assessment of green building construction is set by the comprehensive empowerment method, the G2 and entropy value methods can be integrated to comprehensively consider the subjective and objective information (Jia, Zhao, and Zhu 2019). The detailed steps of G2 combined entropy value method are shown as following.

(1) The identification of the least important indicator. Set the indicator set X {x1, x2 … xn}. Experts determine the most unimportant indicator in the given indicator set X by the own experience, the most unimportant index is xin. The new index set Xi {xi1, xi2 … xin}.

(2) Quantitative calculation of the importance degree of each index. The above least important index Xin is described as the only comparison reference, and the entropy value eij of each assessment index is calculated by the entropy value method, and the eij (j = 1,2, …, n-1) is compared to ein. There will be two situations, discussed separately as following.

If eij>ein, compared to other indexes, the impact of the index Xij on whole assessment system is small; however, experts believe that the indicator Xij is more important than Xin, in order to balance the judge of experts, it is considered Xij to be equally important with Xin. At this time, the importance degree is 1.

If eij<ein, then, the impact of the index Xij is larger than Xin on the whole system, which is consistent with the judgment of the experts. At this time, the ein/eij is used to represent the important degree of the indexes.

In summary: set ajn (j = 1, 2, … , n – 1) is the importance degree ratio of xij relative to xin, then

(6) $a_j=\left\{\begin{array}{c}{e}_{in}/e_{ij}\\ 1\end{array}\right.\begin{array}{c},\\ ,\end{array}\begin{array}{c}{e}_{ij}<e_{in}\\ e_{ij}\ge e_{in}\end{array}$(6)

Where aj ≥ 1, an = 1。

(3) The comprehensive weight of each index is determined. By above analysis, the greater the aj value, the important degree of the index xij is greater, the weight of the index is greater. So

(7) $w_j^{\hspace{0.17em}}=a_j/\sum _{i=1}^m{a}_i$(7)

3. Case study

Select five typical cases of two-star and three-star green building in China, and industry experts evaluated the index layers. The original data is shown in Table 5, and finally the most unimportant index of the corresponding index layer is Personnel management, BIM technology application, domestic sewage emission rate, water-saving instrument input, corporate increase or decrease, income and interest rate, project award-winning situation. The least important index is the influence class index.

Table 5. The original data table.

Criterion layer	Index layer	A	B	C	D	E
Management class A1	Project management A11	85	91	84	80	88
	Green management A12	62	87	75	73	79
	Personnel management A13	65	89	80	84	81
Technical class A2	Project dynamic tracking management A22	79	85	89	77	75
	Green building construction technology uses A23	72	77	82	80	71
	Green equipment input rate A24	75	86	80	72	74
	BIM Technology application A21	59	80	72	66	60
Environment class A3	Construction waste water emission rate A31	84	82	76	86	80
	Domestic sewage emission A33	48	66	52	62	58
	Dust emissions A34	61	58	66	67	73
	Garbage loss quantity A35	55	71	58	50	53
	Garbage recycling utilization A36	73	65	68	76	71
	Noise index A37	51	58	57	62	55
	Domestic sewage emission rate A32	86	90	88	84	79
Resource class A4	Waste water circulation utilization A42	74	86	75	93	72
	Effective utilization of land resources A43	62	93	71	68	63
	Green material usage rate A44	54	78	71	82	52
	Approach take the material rate A45	70	88	85	79	80
	Material turnover usage A46	48	55	61	59	71
	Radiolarian rate A47	51	75	84	72	81
	Energy integrated use A48	57	86	83	68	80
	Water sailor put into A41	90	95	88	92	81
Economy class A5	Improve the level of corporate economic internal rate of return A52	72	81	60	65	73
	Enterprise increase and end yield A51	63	70	66	64	64
Influence class A6	Service customer satisfaction A61	60	86	72	77	81
	Radiation regional public satisfaction A62	70	84	80	71	79
	Project awards A63	60	85	70	70	70

Based on the existing literature and semi-structured interview data, the grounded theory coding technology is used to identify the influencing factors of green construction performance, determine the assessment index set and corresponding assessment standards, and form an assessment index system. The subjective and objective weighting methods are combined, and the G2-entropy method is used as the index to carry out comprehensive weighting. Firstly, calculate the weight of the index layer for the criterion layer, the characteristic matrix Xij is calculated by Table 6, and the least important index is placed in the last row of the corresponding index layer and the matrix is made dimensionless process.

Table 6. The entropy value of each index and weight lists.

Column 1	Column 2	Column 3	Column 4	Column 5	Column 6	Column 7	Column 8	Column 9	Column 10	Column 11	Column 12	Column 13
Criterion layer	Index layer	A	B	C	D	E	Index layer entropy value	Index layer Important degree ratio	Weight of index layer for criteria layer	Criteria layer entropy value	Criteria layer Important degree	Weight of criteria layer for target layer
Management class A1	Project management A11	0.455	1.000	0.364	0.000	0.727	0.816	1.044	0.340	0.833	1.000	0.161
	Green management A12	0.000	1.000	0.520	0.440	0.680	0.832	1.024	0.334
	Personnel management A13	0.000	1.000	0.625	0.792	0.667	0.852	1.000	0.326
Technical class	Project dynamic tracking management A22	0.286	0.714	1.000	0.143	0.000	0.730	1.000	0.250	0.717	1.107	0.178
	Green building construction technology uses A23	0.091	0.545	1.000	0.818	0.000	0.741	1.000	0.250
	Green equipment input rate A24	0.214	1.000	0.571	0.000	0.143	0.710	1.000	0.250
	BIM Technology application A21	0.000	1.000	0.619	0.333	0.048	0.685	1.000	0.250
Environment class A3	Construction waste water emission rate A31	0.800	0.600	0.000	1.000	0.400	0.830	1.009	0.141	0.821	1.000	0.161
	Domestic sewage emission A33	1.000	0.000	0.778	0.222	0.444	0.784	1.069	0.149
	Dust emissions A34	0.800	1.000	0.467	0.400	0.000	0.821	1.021	0.142
	Garbage loss quantity A35	0.762	0.000	0.619	1.000	0.857	0.854	1.000	0.140
	Garbage recycling utilization A36	0.727	0.000	0.273	1.000	0.545	0.806	1.040	0.145
	Noise index A37	1.000	0.364	0.455	0.000	0.636	0.817	1.026	0.143
	Domestic sewage emission rate A32	0.636	1.000	0.818	0.455	0.000	0.838	1.000	0.140
Resource class A4	Waste water circulation utilization A42	0.095	0.667	0.143	1.000	0.000	0.656	1.286	0.144	0.768	1.032	0.166
	Effective utilization of land resources A43	0.000	1.000	0.290	0.194	0.032	0.586	1.439	0.161
	Green material usage rate A44	0.067	0.867	0.633	1.000	0.000	0.732	1.152	0.129
	Approach take the material rate A45	0.000	1.000	0.833	0.500	0.556	0.838	1.006	0.112
	Material turnover usage A46	0.000	0.304	0.565	0.478	1.000	0.807	1.045	0.117
	Radiolarian rate A47	0.000	0.727	1.000	0.636	0.909	0.853	1.000	0.112
	Energy integrated use A48	0.000	1.000	0.897	0.379	0.793	0.830	1.016	0.114
	Water sailor put into A41	0.643	1.000	0.500	0.786	0.000	0.843	1.000	0.112
Economy class A5	Improve the level of corporate economic internal rate of return A52	0.571	1.000	0.000	0.238	0.619	0.799	1.000	0.500	0.735	1.079	0.173
	Enterprise increase and end yield A51	0.000	1.000	0.429	0.143	0.143	0.672	1.000	0.500
Influence class A6	Service customer satisfaction A61	0.000	1.000	0.462	0.654	0.808	0.840	1.000	0.324	0.793	1.000	0.161
	Radiation regional public satisfaction A62	0.000	1.000	0.714	0.071	0.643	0.736	1.090	0.353
	Project awards A63	0.000	1.000	0.400	0.400	0.400	0.803	1.000	0.324

4. Results and discussion

This article selects the characteristic matrix of 27 indicators of 5 construction projects and the assessment index set constructed above Xij, i = (1,2, … ,m); j = (1, 2 … n); Where m = 5, n = 27. Wherein the positive direction index is calculated by formula (1), the negative direction index is calculated by formula (2). Data after dimensionless process is shown in Table 6 column 3 to 7, the index entropy value is calculated by equation (3)(3) $A_{ij}=A_{ij}+\alpha ,\alpha \mathrm{i}\mathrm{s}0.001$(3) (4) (5) and is shown in Table 6 column 8. Calculates the important degree ratio of the index by formula (6); uses the formula (7) to determine the weight of the index layer for the criterion layer, shown as in Table 6 column 10. Then, the average value of the criterion layer for the index entropy value is made as entropy value of the criterion layer, such as the management class A1 entropy value = (0.816 + 0.832 + 0.852)/3, and finally determines that the criteria layer entropy values are shown in Table 6 column 11, and calculates the weight of the criterion layer for the target layer, which is shown in Table 6 column 13. In this paper, when the assessment standards are formulated, due to the different geographical environment and the different policies and regulations of the local geographical environment, so the assessment model may have certain geographical characteristics. The comprehensive assessment model constructed by this paper is suitable for housing construction projects. The assessment index system is based on the construction of housing construction projects. Due to the extensive field of engineering research, the selection and assessment standards of different research areas have their own particularity. They need state and local norms and related policies, and some assessment indicators and assessment standards in this paper are not applicable to the assessment of engineering projects in highway engineering, power engineering, municipal engineering, and other fields.

5. Conclusions

This paper combined green building construction and project management knowledge, presented a novel knowledge management method about integrated grounded theory to build the index sets, used G2 and entropy value method to give index weight, and finally constructed a performance assessment model of green building construction engineering. By Table 6, it can be seen that the technical and economic indexes have a large impact on the final assessment results when comprehensively evaluating the green building construction performance so should it focus on these two kinds of indexes when improving the performance of the green building construction project. In the new model, there are 27 indexes in the model, and the enterprise can refer to Table 6 column 13. So the performance score of the final green building construction can be calculated.

When investigating visits, many managers and first-line construction workers did not understand the concept of green buildings and green building construction and have not formed awareness of green building construction engineering. Many company’s self-assessment is only in the form. Construction companies should promote the landing of green building construction in the training and publicity of the relevant personnel and promote the use of performance assessment methods of green building construction engineering, and improve the green building construction level.

Disclosure statement

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

Additional information

Funding

This work was supported in part by the National Natural Science Foundation of China (NSFC) (51774228).

Notes on contributors

Bai Xiaoping

Bai Xiaoping is currently an Associate Professor of Xi’an University of Architecture & Technology, Xi’an, PRC. His research interests include construction management, system engineering, etc. His articles have appeared in the Sage Open (SSCI), Journal of Asian Architecture and Building Engineering (A&HCI/SCIE), Frontiers of Structural and Civil Engineering (SCIE), Kybernetes (SCIE), Discrete dynamics in nature and society (SCIE), Scientific World Journal (SCIE), Applied Mathematics & Information Sciences (SCIE), Tsinghua Science and Technology, etc.

Liu Wansong

Liu Wansong is Master in Xi’an University of Architecture & Technology, Xi’an, PRC .Her research interests include construction management, system engineering, and etc.