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This study bridges the gap in quality control strategies for high-volume production by balancing the cost and effectiveness of inspection strategies. Using the cost of quality (CoQ) to manage cost and external failures (EF) to gauge effectiveness, this research introduces an innovative inspection strategy chart that serves as a decision-making tool for optimizing inspection processes.

This paper presents a scenario-based framework designed to support strategic decision-making in inspection processes by integrating empirical data analysis with inspection strategy charts. This approach allows for a dynamic assessment and visualization of the relationship between CoQ and EF, facilitating more informed decision-making in quality management. Notably, it contrasts the traditional models with a novel approach that more accurately captures the uncertainty and correlation among key quality indicators, showcasing its potential for more refined decision-making in quality management.

Application of the framework illustrates its effectiveness in offering a nuanced understanding of the cost implications and effectiveness of various quality control strategies. This facilitates enhanced strategic decision-making, optimizing inspection processes and reducing external failures in high-volume production settings.

The study focuses on a single industry case study, limiting the generalizability of findings across different high-volume production contexts. Future research could explore the framework’s applicability in other sectors and refine the model based on additional empirical data.

The research introduces a versatile framework that navigates the unique challenges of high-volume manufacturing environments. Diverging from models optimized for low-volume settings, this approach provides a valuable tool for adapting inspection strategies to complex production demands, marking a significant contribution to quality management and control literature.

The purpose of this paper is to present a methodology to represent the uncertainty generated in performance measures (PMs) during the operational step or “use step” of the performance measurement process (PMP). The different steps of the methodology are described and exemplified through an application example.

An index that reflects the level of uncertainty originated by the factors and the strength of their inter-relationships is developed through the use of graph theory. A graph is developed considering all sources or factors of uncertainty that may be present in this process. Based on the graph, the methodology includes the use of a matrix and the determination of the associated permanent function which is used for determining the uncertainty index.

During the development of the methodology, it was found that the use of a scale that includes zero for assigning values of the elements of the matrix is not appropriate when using graph theory and permanent function calculation, since in this case the permanent function is insensible to changes in some matrix elements.

This paper identifies all the sources that can affect the quality of performance measurement values during the operational step of the PMP and proposes a method to characterize the strength of this uncertainty. Beyond alerting decision makers to the level of uncertainty associated with a PM, it also allows defining appropriate actions to improve PMs’ quality.

The general objective of this research was to identify the practices of the mass production industries, on the decisions related to the detection of defective products and to identify relevant criteria, actions, effects and variables to be used in a decision-making model.

A survey questionnaire was developed and structured in 20 questions, with 18 closed questions and 2 open questions. The questions were constructed based on the literature review, with the identification of 15 theoretical and practical concepts of quality. Seven other information requests were included, concerning the initial characterization of the defective items and industry. The company, the product, the processes and the defects were contextualized, and then the decision-making process was framed, to understand the factors that influenced it.

The industries of the Industrial Pole of Manaus discard or rework their defective products influenced by promoting the lowest cost and the required quality. The factors with the biggest influence on decisions are rework and disposal costs, and time available for rework and replacement. The main requirements defined for the decision-making model were: 1) compare the rework and discard options, only if the rework reaches the required quality level; and 2) identify and account the effects of defective items on quality, productivity and costs.

Overall, 109 questionnaires were sent, representing 21.3% (109/512) of the companies at the Industrial Pole of Manaus. The respondents represent 14.6% (75/512) of the population.

Defects can occur, requiring a decision that promotes the lowest cost and the required quality. Quality cost models do not show a systematic analysis for identification, accounting, evaluation of effects and criteria associated with the destination of manufactured defective items. Therefore this research was done to fill this gap.

This paper proposes a decision support model that can be used to help decide the destination of defective products, for mass production industries. The objective of this model is to reduce the cost of the defect, and consequently reduce the total quality costs.

The decision model was developed based on the theory of quality costs and decision-making models, considering the practical aspects of reality through data collection, observation and experience in Industrial Pole of Manaus (Brazil) industries. A decision model adjusted to reality assists in the construction of the decision process, indicating the facts, data collection and the planning of the actions to choose the best alternative.

The specific contributions of this research are: (1) define a sequential structure of actions, effects and costs associated with defective items; (2) allow a comprehensive approach to failure costs, including various elements of lost opportunity costs; (3) minimize failure costs, and consequently reduce total quality costs, without necessarily investing in prevention and assessment; (4) describe the use and application of the built theory; (5) identify the quality cost elements most representative in existence of defective items; and (6) identify improvement points in the management of possible future defective items.

Much of the work of implementation of quality cost models do not emphasize the analysis of the destination of defective items. Also, there are no studies that use decision models with identification, accounting and evaluation of effects and criteria of quality, productivity and cost to define the destination of manufacture defective items.

The purpose of this paper is to research the way in which Lean practices are affecting the performance of manufacturing small and medium enterprises (SMEs), analyzing the effects of Lean practices on companies’ operational, financial and market performance.

An online questionnaire was distributed among Portuguese organizations that fitted the category of SMEs and belonged to the manufacturing sector. A sample of 329 enterprises was analyzed with partial least squares–structural equation modelling. Four hypotheses on the impact of Lean practices on company performance were tested.

The results show that the effects of Lean on performance are positive, which stresses the benefits attainable with the implementation of Lean practices. The aggregated implementation of Lean practices, namely, customer involvement, statistical process, continuous flow and total productive maintenance leads to improvements in company’s global performance measured by market, financial and operational performance measures, and also improves each of these performance measures individually. It was also noticed that financial capability is one of the indispensable factors for the successful implementation of Lean practices.

The results contribute to the investigation on the topic, broadening the literature on the implementation of Lean practices in companies around the world.

The research outcomes may be used as a motivation for other SMEs to implement Lean practices by acknowledging the positive impact on their performance. Furthermore, the degree of Lean implementation in the particular industry may constitute a signal for government and/or economic decision makers to define incentives such as fiscal benefits for companies that engage in Lean implementation programmes, partly financing workers cross-training, among other necessary investments.

This is the first study that examines the impact of the effect of Lean on operational, financial and market performance in a discriminated and simultaneous way.

The purpose of this paper is to propose a new methodology to be used by small and medium enterprises to characterize their performance in quality, highlighting weaknesses and areas for improvement. The methodology aims to identify the main causes of quality problems and help to prioritize improvement initiatives. This is a methodology that intends to be easy to implement by companies with low maturity level in quality.

Based on the literature review a methodology for diagnosing and prioritizing quality problems is proposed. Then two longitudinal case studies are performed to refine and validate the proposed methodology. The methodology is organized in six different steps which include gathering information about predetermined processes and sub-processes of quality management, defined based on Juran’s trilogy, and about predetermined results categories.

The application of the methodology was successful in two case studies and a report was produced on the quality state of each industry, including a prioritization of the causes of poor performance.

The methodology may have to be adapted to better suit the needs of companies from different sectors, either by reviewing the processes, by integrating new tools or refining the existing ones.

This paper presents a new methodology for identifying and prioritizing quality problems.

Due to its simplicity and comprehensiveness, it is believed that the developed methodology can be applied periodically by companies as self-diagnostic and prioritization tool, aimed at continuous improvement.

To determine the current state of knowledge related to performance measures and their degree of implementation in small and medium enterprises (SMEs) in England.

The paper starts with a literature review and then goes on to discuss the methodology used. The survey is briefly presented together with the analysis of the resultant data. General opinions regarding performance measurement in English SMEs are described, including the most important measures and the biggest obstacles to the adoption of new ones. Hypotheses about differences between groups are tested and discussed.

This work concludes that there is a gap between the theory/knowledge of performance measures and the practice in English SMEs. Training of employees and difficulty in defining new performance measures were highlighted as the major obstacles to the adoption of new performance measures.

The low response rate of the survey precludes the generalisation of the findings.

Innovation and learning measures should be applied more widely.

This paper is relevant to academics and SME managers because it supports the existence of a gap between the theory of performance measurement and its degree of implementation. In addition, it introduces both theoretical information on performance measurement, including that based on the balanced scorecard perspectives, and practical information from a survey conducted in English SMEs.

The complexity of business environments often causes organizations to produce several inconsistent views of the same business process (BP), leading to fragmentation. BP view integration attempts to produce an integrated view from different views of the same model, facilitating the management of BP models.

To study the trends of BP view integration, the authors conduct an extensive and systematic literature review to summarize findings since the 1970s. With a starting corpus of 918 documents, this survey draws up a systematic inventory of solutions used in academia and industry. By narrowing it down to 71 articles, the authors discuss in-depth 17 BP integration techniques papers, classifying each solution according to 9 criteria.

The authors' study shows that most view-integration methods (11) utilize annotation-based matching, based on formal merging rules. While most solutions are formalized, only approximately half are validated with a real-world use case scenario. View integration can be applied to areas other than database schema integration and BP view integration.

By summarizing existing knowledge up to June 2021, the authors explore possible future research directions. The authors highlight the application of view integration to the blockchain research area, where stakeholders can have different views on the same blockchain. The authors expect that this study contributes to interdisciplinary research across view integration, namely to the context of blockchain.

This survey serves to pave the way for future trends, where the authors highlight the application of view integration to blockchain research.

The purpose of this study is to analyze the influence of the firms' external environment on their export intensity. More specifically, it assesses whether domestic market characteristics such as domestic demand and general export environment related to tradability across borders affect firms' export intensity.

The authors use a sample of 29,266 firms from nine European countries, for the period of 2010–2016, and test several estimation methods (random effects models, Tobit models, and Heckman's selection models).

Results show that external factors such as domestic demand and ease of trade across borders are important determinants of firms' export intensity. Moreover, results reveal that firm's internal characteristics such as age, size and productivity also play an import role.

Studies about the influence of the firms' external environment on firms' export intensity are scarce because most of them are confined to a single country context. In this way, the present study contributes to the body of knowledge on the influence that external factors can have on firms' export performance by analyzing firms from nine European countries, which has important policy implications.