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The purpose of this paper is to explore the impact of the cost of quality (COQ) expenditure allocations on a capacitated supply chain (SC) network.

This paper proposes a non-linear optimization model which integrates the opportunity cost (OC) (i.e. customer satisfaction cost), into the COQ with consideration of the QL in the supply chain network design decisions. In addition, it examines the effect of considering an investment at each SC echelon to ensure the best overall QL. A numerical example is presented to illustrate the behavior of the model.

The results show how the QL, COQ and facility location decisions change when incorporating the OC, investments and transportation costs into the SC model.

The novelty of this paper is that it considers the effect of OC, investment at each echelon and transportation costs on SC design by minimizing the overall spending on the COQ. These issues have not been explored, and for that reason, this paper contributes to the understanding of the critical factors that optimizes the SC COQ.

The purpose of this paper is to develop an optimization model to better allocate cost of quality (COQ) in the supply chain (SC). In addition, the paper provides a roadmap based on COQ that allocates limited given budget among the SC entities.

This paper presents a comprehensive SC model while introducing six different scenarios, where each scenario minimizes fixed costs and COQ of the SC.

The results showed that the highest portion of the COQ should be allocated at the retailer echelon while the lowest portion should be kept at the manufacturer echelon. The findings also presented that the retailer should always maintain the highest quality level (QL) compared to the manufacturer and supplier.

Considering prevention, appraisal and failure (PAF) cost model, this research defines the tradeoff among PA, F costs, QL and material flow in the SC network; no work has been published regarding integrating PAF, QL and material flow into SC modeling.

By developing a better understanding of costs associated with improving organizational quality and costs incurred by neglecting it, banks could devise more optimal operational policies. The paper aims to discuss this issue.

This paper proposes a generic banking cost of quality (COQ) model developed from Colombian banking data. The model has been developed using the product performance approach, which is consistent with strategizing from a long-term and organization-wide perspective. The proposed COQ function is composed of prevention and appraisal categories, costs caused by events of operational risks and opportunity costs caused by events of credit risks measured though non-performing loans.

The model was validated using data obtained from three major Colombian banks. The significant theoretical contribution of this research stems from the development of a banking COQ model which represents a pioneer effort at quantifying quality costs in financial institutions.

This is a unique attempt at using a product performance approach in service industry and also a rare effort toward incorporating opportunity costs in COQ. Managerially, the proposed COQ model can be established as a holistic business strategy and can serve as a tool helping managers to evaluate the impact of quality management initiatives and to decide on trade-offs between quality level and quality costs.

This paper aims to present a survey of published literature about various quality costing approaches and reports of their success in order to provide a better understanding of cost of quality (CoQ) methods.

The paper's approach is a literature review and discussion of the issues surrounding quality costing approaches.

Even though the literature review shows an interest by the academic community, a CoQ approach is not utilized in most quality management programs. The evidence presented shows that companies that do adopt CoQ methods are successful in reducing quality costs and improving quality for their customers. The survey shows that the method most commonly implemented is the classical prevention‐appraisal‐failure model; however, other quality cost models are used with success as well.

The paper shows that the selected CoQ model must suit the situation, the environment, the purpose and the needs of the company in order to have a chance to become a successful systematic tool in a quality management program.

Though the components and concepts of cost of quality (COQ) are well understood in the domain of manufacturing, only limited data are available from the construction industry for various reasons. The present study seeks to establish a relationship between project defect score (pds), representing the quality of construction in the project, and the COQ in the building construction industry. The study also seeks to estimate the contributions of the various components to the overall COQ in the construction industry, along with their distribution and interrelationships among themselves.

A framework for estimating COQ was developed, and the data regarding prevention, appraisal and failure cost were collected from 122 projects. Various mathematical and statistical tools like Pearson's correlation, multiple linear regression (MLR) and curve fitting have been used for data analysis.

The prevention–appraisal–failure (PAF) model was found to be appropriate to estimate COQ, and the prevention, appraisal, conformance cost (CC) and failure cost were found to vary between 0.19 and 8%, 0.05 and 5%, 0.3 and 10% and 0.01 and 5%, respectively, whereas the overall COQ varied from 3.5 to 10.01% of the project cost. The correlations between various components of COQ were found to be significant. MLR suggested that appraisal cost is more impactful in reducing failure cost than prevention cost. Using curve fitting, the cubic model appropriately represented all interrelationships. The optimal overall COQ was found to be 3.86%, and the reasons for low COQ have been explored.

The study evaluates the applicability of available models for COQ calculations for the construction industry and presents a framework to estimate its components. The study also explores the interrelationship between the various components of COQ and presents a generalized relationship between COQ and the pds.

Material procurement constitutes a large share of the overall cost of construction projects. Understanding the factors influencing the cost of quality (COQ) in the procurement process could help identify opportunities for lowering quality cost without compromising quality. The paper aims to discuss these issues.

In this paper, a COQ model for the construction material procurement process is developed using the traditional prevention–appraisal–failure (PAF) approach. Using data from a $4bn aluminum smelter construction project, the authors conducted a simulation of the COQ model to evaluate various quality assurance policies.

This paper confirms that raising the prevention cost leads to a drop in failure cost as well as COQ for the project studied. While the authors are unable to provide blanket recommendations as the results are derived from a single project case study, it does suggest that construction material procurement processes would benefit from a higher prevention expenditure. And for certain cases where the authors observe a deviation from the traditional Juran’s model of COQ – the high appraisal cost in the procurement process – reduction of appraisal expenditure may in fact be more beneficial than its increase.

The research results suggest that appraisal expenditure should be tailored to each purchase order in order to maximize the total benefits. Additionally, this paper presents the first COQ model developed for the construction material procurement process. Another unique feature of the model is its inclusion of supplier-side costs, which are excluded in the conventional COQ analysis.

The purpose of this paper is to provide empirical evidence for competing representations of the prevention-appraisal-failure model of quality cost.

The authors conduct regression analysis on a secondary data set to reveal relationships among total cost of quality, its components and overall quality performance.

Total cost of quality and its failure cost component are significantly lower at higher levels of quality, while the prevention and appraisal cost components are not observed to be significantly higher at higher levels of quality. The authors propose a modification to the modern representation of the prevention-appraisal-failure model.

In manufacturing, ever higher levels of quality are associated with significantly lower quality cost.

Using a large, unique data set for secondary analysis, combined with employing a high-level measure for overall quality performance, the authors provide evidence for the aggregate explanatory power of prevalent representations of the prevention-appraisal-failure cost of quality model.

Construction industry faces challenges in making objective decisions due to monetary value attached to quality. Among various quality management techniques available, cost of quality (COQ) is one such method used to address the concern. However, the absence of measurable COQ factors to monitor quality costs hampers the implementation of COQ framework in the construction industry. Therefore, this study aims to identify COQ factors focused on visible factors (VF) and hidden factors (HF) and the current requirements to achieve it.

This study is based on Preferred Reporting Items for Systematic Review and Meta-Analyses protocol guidelines. The present study identified 57 articles published between 1992 and 2023 in peer-reviewed journals.

The findings reveal 22 factors, which are grouped into four categories based on COQ. Through systematic review, the authors observed limited methodological and theoretical diversity. In fact, there are no quantitative frameworks to calculate COQ. The study, therefore, developed a framework comprising four major routes/paths of COQ factors within the framework.

The COQ routes developed through this study will enable the practitioners to meticulously categorise VF and HF, facilitating quantifying of quality throughout the lifecycle of project, which is currently absent from the existing quality assurance/quality control (QA/QC) approach. In addition, these COQ routes stand as essential construction strategies, significantly enhancing outcomes related to time, cost, quality, sustainability and fostering closer relationships within project frameworks.

The current study contributes significantly to the existing body of knowledge by developing various COQ routes and proposing future research directions to address gaps in the literature.

The objective of this paper is to present results of the study of the quality costing practices at four large successful multinational companies.

The method of benchmarking was used for the purpose of this study. Company representatives, who were invited for a benchmarking session, described the quality management programs running at their companies. Direct observation and archival records data collection were also used to extract more precise information for the following analysis and discussion.

The findings of the study show that all four companies use systematic quality initiatives; however, a formal cost of quality (CoQ) methodology was only employed at one of them. This is in agreement with the literature findings arguing that a CoQ approach is not utilized in most quality management programs.

This paper discusses and compares the quality programs of four companies and explains the benefits of the eventual adoption of a CoQ approach in each case. The analysis provides a new insight into company practice, useful both for academic research and industry.

This paper aims at exploring the challenges of introducing a model integrating the Cost of Quality (COQ) into the modeling of a supply chain network.

This paper introduces a comprehensive supply chain model that minimizes a series of costs, in which COQ is integrated.

The scenario of incorporating COQ in supply chain network design will ensure the lowest overall cost, because it reduces the probability of defects and hence the probability of additional cost which might be due to corrective action.

With many industries today on the quest of improving their quality systems, finding ways to reduce nonconformities and failure of products is crucial. In industries such as the aerospace industry, the variable production cost is high; hence producing extra parts to compensate for defectives would be a costly option.

While COQ is a very good indicator of how much poor quality is costing a company, no work has been published in regard to integrating COQ into supply chain modeling.