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Sustaining business performance in an ever changing economic and technical environment is a challenge to be addressed with relevant management implements. This goal can be achieved by using business modelling by processes allowing for costing deliverables, controlling operations and designing information sytems aligned with business procedures and organisation. It has to be stressed that the same process model can fulfill the three purposes above mentioned so that coherent views are secured for the various business stakeholders. In addition, adequate descriptions of business processes can “scavenge” the features of business assets such as organisation, personnel qualification, information systems to be taken into account in strategic decisions.

The purpose of this paper is to critically examine existing models for cost of quality. Having identified issues and limitations of historic models, develop and implement a novel, structured hybrid cost of quality model to identify and effectively manage cost of company’s product.

A theoretical framework is proposed based on an integration of three existing, historical cost of quality models into a structured hybrid model. Subsequently, an exploratory pilot case study in a manufacturing environment is described that illustrates the value of the model.

The paper manages to find how a hybrid model can help identify cost of quality more accurately than the traditional models. Thanks to the new model, the author shows how gaps between product’s theoretical and actual costs can be highlighted. This allows management to drive down cost of quality and improve business performance.

The model would benefit from a company-wide implementation. The present study provides a starting point for further research in the international manufacturing sector.

The framework improves the knowledge of cost of quality by providing a new case study with full results and analysis from a UK-based manufacturing company. It provides a critical re-evaluation of available literature, including the most recent publications as far as practically possible within timescale available. The study shows the importance of comprehensive cost collection if companies are to have the right data needed to manage business excellence.

The paper presents a development of the first structured hybrid model for measuring cost of quality using the strongest points of main three approaches and addresses their limitations. It gives new arguments against allocation of some cost elements within BS 6143-2:1990, resulting in recommendations for further brainstorming of pros and cons of the suggestion.

The purpose of this paper is to analyze the effect of the relationship between stakeholder demand, resources, knowledge and product uniqueness on green marketing and its implication on sustainability performance.

This study used a quantitative research approach that explains the phenomenon by collecting numerical data analyzed using mathematically based methods. The research location was Batik Lawean Center of Surakarta, which is the centers of Batik industry and heritage. These locations were chosen because Laweyan and Kedung Baruk have a vision as the center of Batik industry and environment-friendly heritage through sustainable development.

Stakeholder demand, resource, knowledge and the uniqueness of the product have a significant effect on the application of green management, and the green management has a significant effect on the sustainability performance. It means that the stakeholder demand, resources, knowledge and product uniqueness have a significant effect on green management, and green management simultaneously shows a significant effect on sustainability performance. The application of green management will also improve sustainability performance.

The originality of this study is on the testing of simultaneous relationships between the factors making up the application of green marketing, namely stakeholder demand, resources, knowledge and product uniqueness, as well as the impact of green marketing implementation on sustainability performance. This study focuses on the application of green management by involving the measurement of environmental performance and financial performance, as has been investigated by Karagiorgos (2010) and Earnhart and Lizal (2006). On the other hand, this study attempts to review the application of green management in the form of environmental performance as studied by Filbeck and Gorman (2004) and Sarah and Peter (2000), which reveal several determinants of environmental performance, as suggested by Mutamimah and Handoko (2011). However, this study focuses on the qualitative determinants that have been found by researchers (Raharjo, 2016) that the low or high level of green management application is determined by the demand of stakeholders, resources, knowledge, and product uniqueness considering the object of research is the Batik industry, which is certainly different from other industries, such as those that have been investigated by Karagiorgos (2010), Earnhart and Lizal (2006), Mutamimah and Handoko (2011), Filbeck and Gorman (2004), and Sarah and Peter (2000). This study also combines the measurement of financial performance and non-financial performance in the form of sustainability performance variables.

The use of waste polyethylene terephthalate (PET) plastics derived from shredded bottles in concrete is not formalized yet, especially in reinforced members such as beams and columns. The disposal of plastic wastes in concrete is a viable alternative to manage those wastes while minimizing the environmental impacts associated to recycling, carbon dioxide emissions and energy consumption.

This paper evaluates the suitability of 2D deterministic and stochastic finite element (FE) modeling to predict the shear strength behavior of reinforced concrete (RC) beams without stirrups. Different concrete mixtures prepared with 1.5%–4.5% PET additions, by volume, are investigated.

Test results showed that the deterministic and stochastic FE approaches are accurate to assess the maximum load of RC beams at failure and corresponding midspan deflection. However, the crack patterns observed experimentally during the different stages of loading can only be reproduced using the stochastic FE approach. This later method accounts for the concrete heterogeneity due to PET additions, allowing a statistical simulation of the effect of mechanical properties (i.e. compressive strength, tensile strength and Young’s modulus) on the output FE parameters.

Data presented in this paper can be of interest to civil and structural engineers, aiming to predict the failure mechanisms of RC beams containing plastic wastes, while minimizing the experimental time and resources needed to estimate the variability effect of concrete properties on the performance of such structures.

The purpose of this study is to develop and verify a methodology for a zoned deformation prediction model for super high arch dams, which is indeed a panel data-based regression model with the hierarchical clustering on principal components.

The hierarchical clustering method is used to highlight the main features of the time series. This method is used to select the typical points of the measured ambient and concrete temperatures as predictors and divide the deformation observation points into groups. Based on this, the panel data of each zone can be established, and its type can be judged using F and Hausman tests successively. Then hydrostatic–temperature–time–season models for zones can be constructed. Through the comparative analyses of the distributions and the fitted coefficients of these zones, the spatial deformation mechanism of a dam can be identified. A super high arch dam is taken as a case study.

According to the measured radial displacements during the initial operation period, the investigated pendulums are divided into four zones. After tests, fixed-effect regression models are established. The comparative analyses show that the dam deformation conforms to the natural condition. The factors such as the unstable temperature field and the nonlinear time-dependent effect have obvious effects on the dam deformation. The results show the efficiency of the proposed methodology in zoning and prediction modeling for deformation of super high arch dams and the potential to mining dam deformation mechanism.

A zoned deformation prediction model for super high arch dams is proposed where hierarchical clustering on principal component method and panel data model are combined.