A confirmatory Framework PLS-SEM for Construction Waste reduction as part of achieving Sustainable Development Goals of a building

As a result of rapid population growth, an exponentially growing human population, and industrial expansion, it has become increasingly difficult to manage municipal solid wastes throughout the world. Decentralized waste management systems have created difficult situations in developing countries such as Malaysia. Wastes generated in the country, due to various cultural, social, and religious activities, organic and contributing to environmental pollution (air, water, and soil) and human health troubles. A questionnaire survey was participated by 220 construction professionals in Malaysia using structured and semi-structured methods. The framework was assessed using A partial least square structural equation modeling (PLS-SEM) to target sustainable development goals (SDG). Statistical analysis results indicate a significant effect between SCW management, since(r(270) = .687, P < 0.001). Improving factors has strong relationship with SCW management, since(r(270) = .723, P < 0.001). The mediation results also suggested a significant indirect positive effect of improving factors drivers on SCW management through policy-related factors since (β = 0.688, t = 8.254, P < 0.001, 95% CI for β = [0.536,0.866]) . Finally, policy-related factors construct has a strong relationship with SCWM) management, since (r(270) = .811, P < 0.001) With the R Square of 0.787 and 0.785. The developed framework can improve construction waste management in the construction industry and enhance construction waste management to achieve global sustainable development goals. The findings show that one of the most critical issues of enhancing profitability is using preventive policies to reduce construction waste. This study could guide construction industry stakeholders in identifying the different waste management features during a building project's construction and design stage


Introduction
The construction industry generated 16.6 million tonnes of waste in 2007, comprising 38% of destruction (2019), and 43% of those wastes sent to landfills [1,2]. The amount of waste generated is enormous in the processes of construction and demolition (C&D). In 2020, C&D waste was reported to account for about 26% of Malaysian solid waste [3]. The problems associated with C&D are increasingly becoming a nightmare to practitioners and researchers [4,5]. Furthermore, the amount of C&D waste continues to rise rapidly and is not entirely managed in most countries [6]. Therefore, the Architectural, Engineering, and Construction (AEC) industry should seek to minimize and manage C&D waste more efficiently [7,8]. Many previous studies have suggested strategies for reducing C&D waste by reusing and recycling it [9]. Construction waste reduction is the first step in minimizing C&D waste. This is achieved by mitigating the root causes of waste [10,11]. Design defects left unattended during the construction process will need to fix through renovation works and or reconstruction after project completion. This renovation or reconstruction may demand changing or demolition of some of the structural elements, leading to the accumulation of waste [9]. Improper design and unexpected design changes have been considered the fundamental causes of waste generation in construction [12,13]. The inappropriate design has significantly led to an unexpected increase in construction waste total volume to about 33%. [14]. With an integrated building design, the causes of construction waste can be minimized and prevented where necessary., design problems and improvements, thereby reducing the volume of waste generation [15,16]. In the work of Leemans, et al. [17], In Malaysia, residential and non-residential buildings use approximately 7.6% of total primary energy and emit about 6.0% of total (equivalent) carbon dioxide emissions as all direct and indirect contributions are listed for all major industries MILLHONE and Transfer [18]. The construction industry generated 16.6 million tonnes of waste in 2007, comprising 38% of total waste (2019) and 43% of those sent to landfills. In most of the countries, solid wastes are being dumped into the landfill sites. However, there will be risks of economic loss as well as environmental pollution as a result of doing so [19]. Sludge (35 percent waste) is also generated by the pulp and paper industries, and it can be divided into three categories based on the level of contamination and the method of treatment [19].
These steps reduce the electricity use and CO2 emissions of a building's life cycle [20]. Initially, now there are significant costs incurred. Nevertheless, the expense of lowering the carbon emissions of a house is control by long-term gains in energy conservation, not to mention the ever-increasing energy prices [21]. As a consequence, the idea of low-carbon buildings and, eventually, the carbon-free building developed. Globalization and demographic changes, and rising income levels since the 1970s had influenced the Malaysian housing provision system. Since the 1970s, Malaysia has experienced rapid economic growth with rising per capita income and rapid urbanization. The important green policies such as the utilization of renewable energy (RE), the adoption of energy efficiency (EE), and the promotion of green technology (GT) for sustainable development and towards the construction industry. However, currently lack the profound management devices to assist in the robust evaluation and execution of CWM by constructing configuration stages [22].
However, Environmental systems have been contaminated due to a lack of proper waste management practices, which have had negative effects on living creatures (including humans) and have also contributed to the current economic crisis [23]. Hence, its management has become a global concern. Solid wastes can be divided into five major categories: municipal solid waste (MSW), construction and demolition debris, electrical waste, sludge, and food waste. MSW is the most common type of solid waste. This challenge of increasing MSW magnitude seems inevitable as it is a byproduct of human activities that is growing alarmingly faster than that of urbanization [24].
Furthermore, even though MSW contains a high proportion of recyclable materials, incineration or illegal dumping are common practices due to a lack of land for new landfill construction [24]. As a result, time must be given to developing appropriate waste management strategies, inviting all relevant stakeholders. Many developing countries have 4 of 31 et al. [30], waste minimization comprises several activities (including waste reduction, reuse, and recycling) that reduce waste entering the environment. In particular, waste minimization in the construction sector includes the processes, including but not restricted to: improvements, adjustments in inventory management, product design, material changes, changes in operation and maintenance methods, replacement or improvement of infrastructure, and re-use or recycling of waste materials [31]. While the exact language used to define the concept and its scope may vary among regulatory bodies, all definitions highlight the significance of avoiding the creation of waste rather than focusing on the management of residuals after they are generated.
Furthermore, waste minimization requires reducing or removing waste production at the source and environmentally sustainable recycling strategies when source mitigation is not economically sustainable. Waste minimization does not require waste treatment, i.e., any method designed to change the physical, chemical, or biological design or quality of hazardous waste or treatment of waste. For instance, pacification, dilution, compacting, and incineration are not waste minimization practices [32]. The strategy and process for reducing waste imply mitigating waste production at the environment and the specific stage. The broader aspect of the purpose related to waste management is generally known as a waste hierarchy. Thus, the continuation of constructing waste disposal facilities is not a good idea, and building and operating new disposal facilities is very costly. It could only lead to a higher refuse disposal fee [33].

Root causes of construction waste
The root causes of construction waste obtained from the primary sources are Architects' failure to enforce waste management strategies during Osmani and Sciences [34]. Mohammed, et al. [35] stated that construction waste generation by design. Numerous project stakeholders contribute directly or indirectly in a waste generation which includes last-minute client demands (resulting in rework); lack of expertise of planners in assessing building methods and the order of construction activities (leading to specification errors causing work to be modified or terminated); Lack of expertise of planners in assessing building methods and the order of construction activities (leading to specification errors causing work to be modified or terminated); Lack of expertise of planners in assessing building methods and the Uncertainty in the design (producing in off-cuts); Lack of design knowledge (resulting in over-ordering of materials due to decisions made by contractors and subcontractors);, studies or laws, and regulations) Osmani, et al. [36] and Ghafourian, et al. [37]. Osmani, et al. [36] stated that waste produced during the design process is mainly due to: 'poor teamwork' which leads to errors and defects; and ''Overlapping design and construction adds to the complexity of managing the design process and raises waste mitigation issues to the top of the priority list.. Osmani, et al. [36] identifies "the shortage of designers' expertise in evaluating construction techniques and the schedule of construction processes" as a significant cause of design variations during the construction phase.
Furthermore, the interpretation is the origin of waste production. It examines the causes and impacts of the numerous stated elements on the management of construction waste. The categories include design, labour management, procurement site condition handling, and external factor set. The list of the selected construction waste factors is shown in the Table. 1.

Current Practice of Waste Management Construction in Malaysia
Development in the standard of living led to rapid growth in the construction industries, and the demand for infrastructure projects, shifts in utilization patterns, and population growth contributed significantly to waste generation [46]. Construction waste consists of delays. [47,48] mentioned that building waste might be hazardous, such as asbestos produced during the demolition of existing structures. It is, therefore, necessary to have a proper and well-defined policy and technology used in the management of waste produced from construction activities to reduce the adverse effect that may have on environmental, social, and economic aspects.

Construction Waste Management Policy
With the advancement in sustainable improvements as a new norm, the construction industries have started to understand its harmful effects on the environment [47]. It is known that by nature, construction is not an environmentally friendly activity. The Negative Impact of the construction activities has been compressively reviewed by the researchers, including waste generation, resource depletion, land deterioration, and different forms of pollution [49][50][51][52]. In response, the Government of Malaysia has developed a Construction Industry Development Board (CIDB) agency to transform the industry by improving its environmental performance [53]. CIDB has produced a Master Plan for the Construction Industry to enhance sustainability awareness among the construction key players. In conjunction with this, the government of Malaysia has established Standard Building Works Specifications (SBW) governed by the Ministry of Works. At the same time, the 1994 Pembinaan Malaysia Act (PMA) is also governed by the CIDB). SBW's goal is to ensure twice a week garbage and construction clearance and send into landfill while PMA is to avoid and decrease pollution caused by building waste. All the policies and acts established by government bodies demonstrate the desire to manage building waste properly. Construction practitioners do not follow all policies implemented, however, and a more holistic policy is needed to ensure that economic, social, and environmental aspects can be protected.

Waste Management Technologies
Researcher Fercoq has indicated that the most environmentally sound measure for the waste management hierarchy should start with waste minimization, waste reuse, recycling, and ultimately composting. The adoption of waste minimization in the construction industry has shown its importance [47]. Minimization of waste involves reducing supply, which reduces waste generation at origin, and recycling, which reflects a recovery to recycling waste material [54]. Malaysia is moving towards adopting the Industrial Building System (IBS), which can control waste generation in construction activities and is environmentally friendly [55]. IBS is defined as a construction system that is built using a prefabricated component [56]. However, Mohammad and Sciences [57], due to higher initial costs, hinder construction professionals from adopting this method, although IBS may be one of the great ways to minimize on-site waste.

Factors for improving waste management practices
The interpretation on factors for improving waste management to mitigate the shortcomings of (CWM). C&DW management hierarchy, including reducing, reuse, and recycling strategies, is discussed, after which the most essential contributing factors to C&DW management are introduced. After determining the factors that impact C&DW management, this study classifies those that help to further sustainable C&DW management into four categories, which are the framework for sustainable C&DW management, construction, management factors, and industry policy factors. Tables 2 and 3 illustrate some of the major contributing factors to the management of C&D waste. The interpretation on drivers and factors for improving waste management to mitigate the shortcomings of (CWM) via application of 3r. The interpretation of drivers and factors for improving waste management to mitigate the shortcomings of (CWM) via 3r.

Construction waste Determinant for Sustainable Attributes
Construction waste management techniques have been used for specific applications, methods, equipment, and final products through construction waste sources. For instance, techniques such as aggregate crushing, powder grinding, polishing, and ash burning would be used to control glass waste [47]. In tackling construction waste sustainably, The technique should be chosen from the possibilities based on its lengthy viability. Sustainable qualities contribute to long-term Development while also balancing environmental, social, and economic factors. Economic features address the financial benefit or expense of dealing with unique construction waste. Environmental qualities are used to assess the influence of waste management technology on the environment.
Nonetheless, Recently, social considerations have been imposed on building projects, requiring contractors to consider social aspects such as local jobs and neighborhood quality of life while selecting appropriate waste management strategies. It indicates that the criteria for assessing waste management activities differ from time to time. In this regard, it is important to establish an integrated system for choosing the preferred CWM method based on up-to-date, sustainable attributes.
Construction & Demolition waste is a term that refers to the process construction Environmental Protection Agency (EPA) defines waste as "waste materials generated in the design, remodeling, or demolition of structures and roads." Materials resulting from natural calamities are also included [61]. Sustainable construction is also a critical strategy that can be regarded for sustained Development through deliberating on environmental, social, economic, and cultural issues. The need to uncover the balance between the economic, environmental, and social elements of the design, construction, and use of buildings is a more substantial meaning for sustainable construction. Indeed, sustainable construction is seen as a significant sub-component to drive sustainable development [62]. For example, Umar, et al. [63] highlight the benefits of high-performance C&D waste management for a smooth building process while decreasing environmental impacts. It adheres to the two pillars of construction sustainability: resource conservation and pollution abatement [64]. As shown in Figure 1, sustainable construction mainly depends on waste management [65]; sustainable construction would have affected the evaluation of CWM performance. It is commonly agreed that the outcomes of the CWM are affected by environmental sustainability, social sustainability, and economic sustainability variables [66][67][68].

Menials and Methods
The proposed study applied two stages of analysis methods, namely variances-based structural equation modeling (PLS-SEM). A survey research strategy was used to collect data, including a questionnaire and walkthrough observational procedures. The Methodology questionnaire was adapted and used in the Malaysian construction industry. Before conducting the field survey, the questionnaire was pretested, and a pilot survey was conducted to ensure that it was accurate. Improving the questionnaire before the pilot survey, the pretest was conducted by discussing the questionnaire with colleagues [69].
A total of 220 questionnaires were administered to the respondents the local consultants and contractors registered with the Construction Industry Development Board (CIDB), out of which 131 representing 79 percent were retrieved of which 122 representing 74 percent of the total questionnaires distributed were considered valid for the analysis as recommended by Aziz, et al. [70] and [71] and a population of about 1000 for the field survey. According to the pilot study's findings, positive feedback was received in response to the questionnaire's design and presentation. It was refined in response to the pilot results to improve the questionnaire's face validity. The Statistical Package for Social Science (SPSS) version 21 was used in the preliminary analyses, was used for the Analysis. The data were screened to ensure univariate and multivariate normality as required [72]. The descriptive analysis of the categorical items was also carried out to determine the normality of the data. The mean, standard deviation, skewness, and kurtosis of the categorical items were used to determine the normality of the data. Later, factor analyses were conducted to determine the reliability and validity of using the factors in measurement models for evaluating public housing performance. These analyses included reliability, exploratory factor analyses, and confirmatory factor analyses.

Results
Data collection was carried out by employing a questionnaire survey. It has been undertaken to demonstrate existing theories and reinforce research findings with previous research views and conclusions. Pretesting was carried out by discussing the questionnaire. It also entailed having the questionnaire evaluated by professionals in the same subject to ensure that the questions were relevant and that the questionnaire was simple and eligible. After collecting the data from the study area, the questionnaires were coded and posted into SPSS and subsequently transported to PLS-SEM. The analysis was carried out using frequency to identify missing data and wrong postings. Data were screened before using them for further analysis. That was important in ensuring that data used in analysis meet the criteria of normally distributed Parr, et al. [73] and was free from missing data. The questionnaires were of two different kinds. Variables used to develop the first questionnaire were obtained from the literature and other studies by Heberlein and Baumgartner [74]. Survey respondents include civil engineers, architects, quantity surveyors, and others (building designers and interior designers). The reliability and validity of using the variables in measurement models for effective CW management for assessment were then determined using reliability, exploratory, and confirmatory factor analyses. The following analysis discussed as follows.

Profiles of respondents
Following the data screening, the sample's demographic profiles with 122 instances were presented. The gender distribution indicated that about 85% of the respondents were males, and 15% were females. The data showed that more than 90% of the respondents were married and aged between 30 years to 60 years. Even though more than 73% of the respondents were civil servants, about 42% reported mostly at private companies. This probably indicated a significant number of the respondents are from construction companies in Malaysia.

Data Reliability and validity of the Measurement Models
A reliability test for all the constructs was carried out using Cronbach's alpha, as suggested by Taber [75]. Even though the recommended level is 0.7 Wong [76], The purpose of the reliability assessment is to test whether the consistency of the data in the questionnaire is consistent or not to obtain the correct results of the study. C and I received acceptable values of 0.882 and 0.815, respectively, in the first repetition of field data. The value of the P construct is 0.889. Also, the variables under the S had a value of 0.889. A similar study by Eisinga, et al. [77] on BIM achieved the alpha value of 0.71.

Causes of construction waste generation in Malaysia.
This section contains the Malaysian construction industry's causes and practices to manage and control sustainable construction waste management strategies in this study. Table 5: illustrates the results obtained from the respondents. The results are arranged from the highest mean to the lowest. The five most significant factors among all stakeholders were; Lack of Design and documentation (RD1) as the most critical factors that cause prevalent practices adopted by the Malaysian construction industry to manage and control the sustainable construction wastes management strategies and ranked first having a mean value of 2.90 and SD of 0.856 which is higher than all the remaining factors within the group. Transportation problem (RD2) ranked second, having a mean and S.   Table 6 shows the causes of construction waste generation and Malaysian practices adopted by many professionals in the Malaysian construction industry, which indicates that (CDW). The reduction is significant. Most of them have no idea how to reduce C.D.W. in the design process. According to the results obtained and supported by Gouldson, et al. [78]. Lack of guidance for effective C.D.W. collection and sorting (RU1) has 2.92 mean with S. D of 0.845 and ranked first among the causes of low the Malaysian construction industry practices while Lack of knowledge and standards for reused (CDW). (RU2) having a mean value of 2.90 with an SD of 0.861 and ranked second among the causes of low practices. Also, an accident due to negligence (RU3) has a 2.89 mean value and SD 0.  Moreover, Table 7. Illustrated the respondents' results indicating the under-developed market for recycled CDW. Products In Malaysia (RC1) is the most significant factor with a mean value of 2.94 with an SD of 0.845. Immature recycling market operation (RC2) ranked second has 2.91 with an SD of 0.856. Green recycling technology (RC3), with a mean value of 2.90 and SD of 0.848, is the third-ranked factor among the causes of low practices adopted by the Malaysian construction industry. The summary of less significant factors was shown in Table8; the result showed that Damage during transportation (RC4) has 2.89 mean and SD of 0.848 and ranked fourth, while difficulties for delivery vehicles accessing construction sites (RC5) ranked fifth, has 2.31 mean. SD: 0.832 and Inefficient method of unloading (RC6) has a mean value of 1.68 and SD of 0.979 selected as less significant factors that cause standard practices adopted by the Malaysian construction industry to manage and control the sustainable construction wastes hence these factors chosen for further analysis.

Barriers to Implementing Effective Construction Waste Management
This section presents the barriers that impede effective construction and demolition waste management strategies in the Malaysian construction industry. The ranking of the 15 identified barriers is shown in Table 9.   Table 9 shows the barriers to implementing effective construction and demolition waste management strategies in the Malaysian construction industry. As a result, using mean ranking, There is a lack of attention to waste management in current rules; there is a lack of attention to designing buildings according to waste management needs. There is a lack of attention to waste management in current regulations. Lack of waste management awareness among contractors; a lack of rules making waste management mandatory; and a lack of regulatory incentives, respectively having mean values of 4.56, 4.36, 4.23, 4.04, and 4.03, are the 1st to 5th major barriers against the implementation of effective construction and demolition waste management strategies in the Malaysian construction industry.
Lack of waste management culture; Lack of support from owners and stakeholders; Lack of community attention to trash management; Lack of environmentally suitable waste management infrastructure; and The Lack of waste management requirements in national building codes was found to be the 6th to 10th biggest barrier to implementing efficient construction waste management strategies in Malaysia, with mean values of 4.01, 3.91, 3.87, 3.71, and 3.65.
The factors that were considered the least barriers to implementing effective construction and demolition waste management strategies in the Malaysian construction industry and ranked 11th to 15th were low costs of sending materials to landfill, Lack of budget for managing waste, low prices of building materials (waste management is not economically justified), Lack of support from building supervisors, and tight scheduling of construction projects as indicated by mean values of 3.47, 3.45, 3.41, 3.21 and 3.01 respectively. Table 10 shows the results of descriptive statistics derived for the selected constructs. The mean (M), standard deviation (SD), and coefficient of variation (CV) are the three statistics in question.    Table 11 shows the matrix of Pearson correlation coefficients between all variables in the study. The correlation coefficients suggest a significant positive (moderate to strong) correlation among all variables. Pearson product-moment correlation coefficient was calculated and found that there is a moderate positive relationship between Current Practices/Generation and Sustainable Construction Waste Management, since ( (270) = .687, < 0.001). Improving Factors Drivers construct has a strong relationship with Sustainable Construction Waste Management, since( (270) = .723, < 0.001). Finally, the

Structural Equation Modeling
In this study, the researcher has applied structural equation modeling (SEM) for the model analysis. The SEM is a broad strategy to test hypotheses and determine the relationship between exogenous and endogenous variables. A partial least square analysis of SEM (PLS-SEM) is followed in this study. The first stage of this technique is about specifying the structural model, while the second stage is about defining the measurement models. The third stage focuses on collecting and examining the data. These three stages have been implemented in (Ch.). The fourth stage involves PLS-SEM path model estimation, while the fifth stage requires assessing the measurement model's results. The sixth stage is for assessing the results of the structural model. The final stage is making final interpretations of the results and conclusions.

Assessing the Measurement Model
The assessment of the reflective measurement models in PLS-SEM requires evaluating the internal consistency reliability, convergent validity, and discriminant validity. Fig  (4.1) shows the measurement model of the current study. Once the reliability and validity of the measurement model have been established, the structural model will be assessed. The following subsections will discuss the reliability and validity of the measurement model.

Internal reliability and convergent validity
The internal consistency reliability examines whether all of the indicators associated with a constructed measure it [79]. There are different ways to measure internal consistency. Cronbach's alpha is a statistical measure that is the most commonly used for this purpose. Cronbach's alpha provides the average correlation between all of the indicators that belong to one construct. The accepted value of Cronbach's alpha is 0.7; all weights of Cronbach's alpha in Table (4.18) were above 0.7. Despite its popularity, Cronbach's alpha is criticized for assuming that all of the indicators have equal outer loadings [80] and that the number of indicators influences the calculation of Cronbach's alpha in that fewer items produces lower value, especially in scales with items fewer than 10 [80].
Due to the limitations of Cronbach's alpha, researchers are advised to use other measures of internal consistency such as composite reliability (CR) and rho [81]. Jöreskog rho measure is a better reliability measure than Cronbach's alpha in structural equation modeling. It is based on the loadings rather than the correlations observed between the observed variables [81]. Composite reliability measures the internal consistency while considering that each indicator has a different outer loading. Following the previous rules, the reliability of each construct was assessed using the calculations provided in Smart -PLS. The results in Table (4.18) show that all constructs had reliability (Cronbach's Alpha, rho, and Composite Reliability) scores of more than 0.70. Figures (4.18) present the results of the internal consistency reliability. Those findings provide evidence of the high reliability and sufficient internal consistency of the constructs. The convergent validity evaluates the correlation between the variables that measure one construct. The convergent validity of reflective measurement models is usually evaluated using the outer loadings of the items and the average variance extracted (AVE).

Discriminant Validity
Discriminant validity examines how much a construct differs from other constructs. Discriminant validity is usually established using the Fornell-Larcker criterion, crossloadings, or Hetrotrait-Monotrait (HTMT) ratio. The Fornel Larcker criterion, the square root of AVE, is compared against the construct's correlations. The square root of the construct's AVE should be higher than any of the construct's correlations with other constructs; the results of the Fornell-Larcker criterion were reported in Table (13). HTML is "the ratio of the between-trait correlations to the within-traits correlations. The HTMT value in Table ( 13) should be lower than 0.9 [361]. Following these guides, the results reveal that the discriminant validity is agreed. The third method, the cross-loading criterion, has also been used in this study to determine discriminatory validity. This method attempts to determine that the loading of indicators on a given latent construct should be higher than the loading on all other constructs by row. In other words, the loading of the indicators (items) of their constructs should be higher than the loading of another construct. Table 4.20 showed that the loading of all indicators of the allocated latent construct is higher than the cross-loading on other constructs (by row). The result showed a substantial degree of unidimensionality for each construct.     m1  m2  x11  x12  x13  x14  x21  x22  x23  x24  x25  y1  After establishing the reliability and validity of the measurement models, it is time to assess the structural model. Researchers in the literature provided guidelines for evaluating and reporting the structural model, including collinearity, path coefficients, coefficient of determination (R2), effect size (f²), predictive relevance (Q2), and goodness of fit (GoF) index.

Collinearity
Collinearity occurs when there is a high correlation between two constructs, producing interpretation issues [82]. Collinearity can be assessed using the variance inflation factor (VIF); a VIF value of 5 or higher indicates high collinearity [83]. Table (4.10) shows that most VIF values were below the cut-off point, providing evidence that the collinearity problem between independent constructs does not exist.

Path Coefficients
Path coefficients refer to the estimates of the relationships between the model's constructs [84]. Those coefficients range from +1 to -1, where +1 means a strong positive relationship, 0 means a weak or non-existence relationship, and -1 means a strong negative relationship. Figure (

Coefficient of Determination
Coefficient of determination ( ) refers to the effect of independent variables on the latent dependent variables, one of the structural model [84]. Hair Jr, et al. [85] suggested that with 0.19, 0.33, or 0.67 are low, moderate, or high, respectively. Furthermore, the adjusted values are useful in assessing the quality of various models or comparing the model across different contexts. The results were reported in Table ( 18), and the variations in the exogenous variables show high variations in the endogens variables [86].  The most significant obstacles to implementing effective building waste management solutions in Malaysia's city were discovered to be: There is a lack of attention to waste management in current regulations; there is a lack of attention to designing buildings according to waste management requirements; there is a lack of waste management awareness among contractors; there are no rules that make waste management mandatory, and there are no incentives from regulatory authorities. This finding confirmed that of [91], They discovered that the problems above prevent developing countries from implementing effective building and demolition waste management. Malaysia is no different., as [92] observed that C&D waste management legislations are deficient in Malaysia. Lack of culture in favor of waste management; Lack of support from owners and stakeholders; Lack of attention to waste management from the Community; Lack of economically viable facilities for waste management; and Lack of waste management necessities within the national building codes were found to be the 6th to 10th among the barriers hampering implementation of effective C&D waste management strategies in Malaysia. This finding is in agreement with [13]. The variables are deemed the least obstructive to the Malaysian construction industry's implementation of effective construction and demolition waste management techniques. Low costs of shipping materials to landfills rated them 11th to 15th.
The finding agrees with [93], [94] and [95]. The main barriers to the proper implementation of waste reduction strategy occur when actors in the construction industry are vulnerable to communicating and cooperating. Stakeholders properly do not have a common understanding among themselves regarding 3R CW management strategies due to the similarity of reducing reuse and recycling strategies. Construction actors will take advantage of all aspects of reduction strategy if reduction strategy is included in the C&DW management cycle for waste minimization; therefore, it is vital to pay extra attention to the reduction strategy's execution. Regarding the rapid growth of the CW generation worldwide, it is crucial to consider high priority in reducing strategy in the construction industry [96].

Impact of improving factors on SCW management
The respondents were asked to measure the effect of BIM design on sustainable construction waste during the building's design and construction using a scale of 1-5 (Very high to very low). The results revealed that Improving factors have a strong relationship with SCW management, since(r(270) = .723, P < 0.001) and R Square of 0.787. Assessment and brief design step specific (CWM). Improvements related to briefing requirements were identified during the evaluation and Brief design stages as presented in the work of Liu, et al. [97].

Impact on policy-related factors on Sustainable construction waste management
The results indicate that policy-related factors have a significant moderating effect with sustainable construction waste management by constituting The mediation results also suggested a significant indirect positive effect of improving factors drivers on SCW management through policy-related factors since (β = 0.688, t = 8.254, P < 0.001, 95% CI for β = [0.536,0.866]). Finally, policy-related factors construct has a strong relationship with SCWM) management, since(r(270) = .811, P < 0.001) and the R Square of 0.785. It is well-aligned with the work of Bamgbade, et al. [98], Samari (2012), government funding is the most successful in stimulating green construction, as it is more result-oriented than other techniques that can drive to progress sustainable construction waste management. Also, governments can enhance the adoption of sustainable construction waste management in several ways. The research of Bamgbade, et al. [98] stated that government could drive sustainable construction waste agendas with several policies, including fiscal supports, legislation and standards, and building labeling with energy efficiency rating in the Malaysian construction industry. This process may transform into the waste management system, which comprises reduction, minimization, reuse, recycling, recovery, and construction waste disposal. Many researchers have sported the above result [47,[99][100][101][102] -various sustainable waste management steps on government policy-related factors.

Conclusion
This paper presented the research on prevention approaches using BIM-based design for construction waste management in Malaysian projects. The following conclusions were Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 19 July 2021 doi:10.20944/preprints202107.0409.v1 drawn at the accomplishment of research objectives: The factors that course construction waste generation was identified through extensive literature review and descriptive statistic, Impact of Improving factors on SCW management contain correlation analysis and Impact on policy-related factors on Sustainable construction waste management constitute with PLS-SEM formwork. A questionnaire was developed to obtain the required information for the study from the relevant professionals. Cronbach alpha was calculated to determine the reliability and validity of the instrument. The calculated reliability and validity of the instrument are 0.882,0.815, and 0.889, respectively. SEM was determined to be the most appropriate statistical analysis technique for this study. Based on their findings, the authors stressed that employees must use data when solving quality-related problems. Customer satisfaction (r = 0.29) and operational performance (r = 0.30) are both statistically significant at the p-value of 0.05. Statistical analysis results indicate a significant effect between Sustainable Construction Waste management, since(r(270) = .687, P < 0.001). Improving factors has a strong relationship with Sustainable Construction Waste management, since (r(270) = .723, P < 0.001).
The mediation results also suggested a significant indirect positive effect of improving factors drivers on Sustainable Construction Waste management through policy-related factors since (β = 0.688, t = 8.254, P < 0.001, 95% CI for β = [0.536,0.866]) .
Finally, policy-related factors construct has a strong relationship with SCWM) management, since(r(270) = .811, P < 0.001) With the R Square of 0.787 and 0.785. The results may also be helpful to many construction companies, particularly those in developing countries where there is a lot of construction waste with low awareness. It can assist small and medium construction companies to become extremely sustainable and technologies for practical and sustainable manner. The barriers against the implementation of effective construction and demolition waste management strategies in the study area.
The significant barriers to implementing effective construction waste management strategies in Malaysia metropolis were found to be Lack of attention to waste management in current regulations; Lack of attention to designing buildings according to requirements of waste management; Lack of awareness among contractors about waste management; Stakeholders properly do not have a common understanding among themselves regarding 3R CW management strategies due to the similarity of reducing reuse and recycling strategies.
This paper contributes to the literature to allow academic researchers to replicate similar research using additional variables from different locations and compare the results obtained because the data used in this research may have limited generalizability because it was collected in Malaysia. The results enable project leadership teams to prioritize the workforce, materials, equipment, and time of their construction projects in the planning phase to eliminate the waste generated by the projects, thereby improving efficiency and sustainability. The sustainability approaches proposed in this study can be used as a guideline for any project team to build successful management toolkits for minimizing essential productivity-enhanced SCWmanagement implementation activities. This study has established a basis for improvements in the specifications that could be critical for evaluating and removing waste. Construction waste prevention is significant, leading to avoiding design errors contributing to waste generation. The construction waste is identified chiefly through processes that involve conventional construction. In the conflict of interest, the authors declare that they have no established conflicting financial interests or personal relationships that may seem to have influenced the research presented in this paper.
Data Availability Statement: Data used and analyzed during this study is available from the corresponding author by request.