The construction industry and the production of inputs in this sector are the activities that show the highest consumption rates of materials and raw materials worldwide (1-3). The main inputs used and extracted from nature for the construction of buildings and infrastructure can be aggregates, copper, asphalt, cement, plastics, iron, aluminum, wood, plaster and bricks, of which a high percentage is discarded during the construction stage and also become waste when damaged by mishandling, or by demolition, or by weather, or when affected by natural disasters such as earthquakes and tsunami, among other reasons buildings (4). The term construction and demolition waste (CDW) is generally used to refer to solid waste generated in the construction industry, more specifically, the term is defined as waste arising from construction, renovation and demolition activities, including land excavation or formation, civil and building construction, site clearance, demolition activities, road works and building renovation (4, 5). Therefore, it is necessary not only to quantify the amount of waste in construction, but also to quantify and estimate the associated costs (4, 5). In addition, makes it possible to quantify the project’s financing needs, considering the most appropriate mechanisms to successfully materialize the project (6).

In addition, it is not only necessary to quantify and estimate the costs of waste, but also to correctly classify and typify the waste generated in construction, since if the actors in the production or waste process know with certainty the origin of their waste, the raw materials used, the production processes, and know the current regulations and a correct classification and typification, then the waste identification process will be considerably more effective (7, 8). Knowing, for example, whether the waste is hazardous or not, will help to decide the most appropriate type of treatment for the identified waste, thus helping to prevent harm to people and the environment (9).

The present research proposes a methodology that incorporates the estimation and cost associated with the waste generated in construction, incorporating a new column called “Loss Factor” to the Unit Cost Analysis (UCA) which is associated with the cost per loss of a particular material, being a value, which can be represented in quantity or in percentage, in which to facilitate its understanding it is defined as a percentage, this value will be defined by the construction company or the professional in charge of the cost estimation. In addition, the proposed methodology incorporates the “Ábaco-Chile” typification of the waste generated by each material defined in the Unit Cost Analysis (UCA).

Therefore, proper waste typification and reliable estimation of the cost of construction waste before the commencement of construction activities will help decision-makers to better understand the cost implication of waste generation and improve their decision-making in developing the appropriate strategy that can mitigate waste.

The construction industry is one of the most significant in the consumption of raw materials (1, 10). The International Resource Panel (IRP) report on “Priority products and materials” mentions the influence of different economic activities on the use of natural resources and waste generation (11). Figure 1 shows the evolution of the extraction of materials based on the extraction of four categories of raw materials: construction minerals, metals and industrial minerals, fossil fuels and biomass.

The twentieth century was a time of progress for human civilization, due to technological progress and great demographic and economic growth. The annual extraction of minerals grew by a factor of 27, construction materials by 34, fossil fuels by 12 and biomass by 3.6 (1, 11). In total, material extraction increased by a factor of about eight, while GDP increased by a factor of 23. This increase in material consumption was not evenly distributed and had profound impacts on the environment.

If the production or waste process actors know with certainty the origin of their waste, the raw materials used, the production processes, and know the current regulations and a correct classification and typification, then the waste identification process will be considerably more effective (7, 8). Knowing, for example, whether the waste is hazardous or not, will help to decide the most appropriate type of treatment for the identified waste, thus helping to prevent harm to people and the environment (9).

This research begins with a comprehensive literature review, according to the Web of Science, Scopus and Scielo databases. The literature review provided an updated understanding of the existing knowledge on waste generated in construction.

In the next stage, a methodology that incorporates quantification and cost in the budget study is proposed, also coding and classifying materials through Ábaco-Chile. This coding and classification method then proposes a classification and coding structure for the resources used on-site, oriented to generate construction budgets. This would also allow the identification and choice of different waste management options, know their hazardous characteristics, and thus decide the most appropriate type of treatment for the waste identified through the Ábaco-Chile coding.

The results are then validated through surveys carried out with experts in the construction sector. Finally, the results are concluded and analyzed, and future research is proposed.

A survey is prepared in order to estimate the percentage of loss associated with the cost of the most incident materials, i.e., those materials that generate the most waste in construction. Professionals of the construction sector would estimate the percentage of loss through the survey, where for this, the sample size must be calculated, to know how many construction professionals need to be surveyed.

Once the survey has been carried out, the range of the Loss Factor (%) and the one recommended by experts will be estimated, which will be done through software that allows simulations and statistical analysis. For this, Crystal Ball will be used, being an analysis tool that allows users to make decisions by performing simulations on spreadsheet models. In addition, Crystal Ball is the simplest method to perform simulations using the Monte Carlo method in a spreadsheet.

Twelve materials were selected, which are the most incident materials, that is, those materials that generate more waste in construction, according to Bravo (37), who determined through a survey of 38 professionals the most incident materials; and according to Rodrigo Caniullán and Carlos Fuentealba (38), who surveyed 55 professionals, to determine the most incident items, wherefrom those items the materials that generate more waste on-site were selected.

Based on the above, the materials selected for construction professionals to estimate the percentage of loss associated with the cost are: ceramic tile, gypsum plasterboard, gypsum, ceramic tile adhesives powder, mortar (masonry), wall mounted paper, paint, cement, sand, steel bars (reinforcement), brick, and timber (timber stud wall).

Of the 71 respondents, 48% were Civil Engineers, 25% Civil Builders, and 18% were Construction Engineers.

Based on the results of the survey, in which 71 construction professionals estimated, according to their experience and criteria, the loss factor (%) associated with the cost of the 12 most common construction materials. Once the survey results were obtained, the probabilistic distribution of the 12 construction materials was calculated using Crystal Ball software, since it facilitates Monte Carlo simulations in a spreadsheet. In addition, the goodness-of-fit analysis of each probabilistic distribution is calculated for each selected building material.

Table 5 presents the probabilistic distribution that best fits each selected building material, with its confidence interval (CI) of 5% and 95%, the standard deviation, the mean and the most probable loss factor (%), which would be the most recommended.

The construction industry is traditionally environmentally unfriendly. The environmental impacts of construction waste include soil contamination, water pollution and landscape deterioration. In addition, construction waste has a negative economic impact by contributing additional costs to construction due to the need to replace wasted materials. However, to mitigate waste, construction companies should explore management options, which include waste reduction, recycling and disposal.

The reduction has the highest priority among waste management options, but efficient reduction cannot be achieved without proper identification of waste sources (39-42). That is why it is necessary to typify and classify waste, which is why this study incorporated Ábaco-Chile in the Unit Cost Analysis, where it would allow future identification and choice of different waste management options, and would provide information and guidance on whether the waste is classified as hazardous or non-hazardous. Therefore, if the producers or holders of waste know how to identify them through Ábaco-Chile, they will be able to know what type of waste they are, as well as its hazardous characteristics, and thus be able to decide the most appropriate type of treatment for the identified waste.

Excessive waste of materials, inadequate on-site management and low awareness of the need to reduce waste are common on construction sites. The enormous increase in the amount of waste generated due to the growth of the construction industry can lead to waste materials that have significant economic value. For this reason, a loss factor (expressed as a percentage) was incorporated in this study, which is associated with the cost of the material, where this loss factor will be defined by the construction company or the professional in charge of the cost estimation, allowing the company bidding for a project to be more competitive and the client to see the costs associated with the loss of materials, thus benefiting both parties.

As an example, for the item that was used in this study to explain the proposed methodology, “Concrete Foundations of H20”, if the company in the bidding stage estimates a loss factor of 10% for cement, 7% for Ripio 1” and 4% for coarse sand, the material costs of this item can be considered 8.8% more, The total cost of the item (considering also labor, tools/machinery, general expenses, financial expenses, utilities, VAT) can be considered an additional 5%, that is, the percentage variation without considering the loss factor and considering the loss factor in the materials is 5.2%.

On the other hand, this study incorporated a statistical study for the most probable loss factor (%) of the most incident materials in the generation of construction waste. For this purpose, 71 construction professionals were surveyed and, based on their experience and criteria, they were asked to estimate the loss factor (%) of the 12 most incident materials. For each material, the probabilistic distribution that best fits were determined, calculating also the confidence interval (5%-95%), the mean, the standard deviation, the average and the most probable loss factor, among other statistical data, where the most probable loss factor for ceramics is 9%, for plasterboard 6%, for gypsum 7%, for ceramic powder adhesive 5%, for mortar 6%, for wallpaper 6%, for paint 5%, for cement 7%, for sand 6%, for framing 6%, for brick 6% and partition wood 6%. Of the 12 materials studied, ceramics is the construction material with the highest loss factor associated with cost.

It should be noted that none of these materials conform to a normal distribution, which means that the Gaussian bell is not symmetrical, nor are the mean, median and mode at the center of the curve, and their values do not coincide, neither does it reach its maximum (the maximum point of the Gaussian bell) at the mean as is the normal distribution, but in the 12 materials studied the Gaussian bell is asymmetrical, skewed to the right (positive skew), which implies that the mode is less than the median, and this in turn less than the mean (Mode<Median<Mean). Therefore, knowing the shape of the Gaussian bell allows for characterizing the data in terms of its uniformity and degree of concentration in the central region of the data distribution, in this sense, the symmetry of the data is related to the measures of central tendency for quantitative variables, where the asymmetric or skewed state is due to the sensitivity of the mean to outliers.

On the other hand, client demands and regulations are recognized as the main driver of change by Chilean construction companies. However, government regulations and policies are scarce and the ministries related to the construction industry should play a more active role in the creation and promotion of regulations and policies for the sector. That is why there are need for the education of owners and construction companies, the generation of regulations and policies to enforce the implementation of sustainable construction practices, and the implementation of financial incentives for sustainable projects to reduce owners’ risk-taking aversion Therefore, it is important to know with certainty the quantification and estimation of costs from the planning phase of the construction project, since in this phase the costs are lower, but their influence on the costs is significantly higher.

In addition, the goal of all companies is to generate profits, so the implementation of sustainable construction and waste management practices within the company should be recognized as an opportunity to create value. Therefore, more research is needed to evaluate the economic impacts of sustainable construction actions (techniques and processes) implemented on construction sites, so construction companies should be well informed about those practices that will balance environmental protection and costs appropriately.

This study proposes a model to estimate the cost of construction waste, at the bidding stage, where a reliable estimation of the cost of construction waste before the start of construction activities will help decision-makers to better understand the cost implication of waste generation and improve their decision making in developing the appropriate strategy that can mitigate waste. Also, the results of this study show that waste is an important factor contributing to the cost of construction. A cost offered in the bidding, the losses of the resources are incorporated into the final amount offered, so that with the proposed methodology the losses of the materials of each item will be known, where the processes can be improved to lower these costs. It should be noted that the estimation of costs and valuation also has an impact on the bidding process, since the higher the losses, the higher the cost to the client, resulting in less competition with the other bidders. And, if losses are effectively managed or processes are improved, there should be lower costs in losses that do not add value to the project.

In the future, project stakeholders can evaluate and estimate the likely cost of waste using the method developed in this study, defining the loss factor associated with the cost of each material, and typifying and classifying the waste in the project planning phase, in order to be more transparent and competitive when bidding for a construction project, and to decide in advance the most appropriate type of treatment for the identified waste, which involves savings in total project costs.

On the other hand, investigations could consider a new waste cost factor, adding one that incorporates the cost of disposing of this waste, for example, knowing the scope of the contribution and the cost implication of the incorrect location, and, to facilitate decision-making, use can be made of Information and Communication Technology (ICT), based tracking systems, such as radio frequency identification devices (RFID), which can mitigate incorrect location and abandonment of materials in large construction works, and the implementation of Lean Construction methodologies, in order to improve the traditional construction management model through the identification and reduction or elimination of losses and activities that do not add value to the project.