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This paper applies fuzzy grey cognitive maps (FGCM) to support multicriteria group decision making (GDM) on supply chain performance (SCP) considering the role of organizational culture as a moderating factor.

This paper follows the quantitative axiomatic prescriptive model-based research. It introduces a MGDM model that relies on the SCOR® model performance attributes and Hofstede’s cultural dimensions. The proposal is underpinned by the soft computing technique of FGCM, aimed at addressing the inherent subjectivity associated with evaluating the culture-performance relationship within supply chains.

The FGCM-based model proposes a management matrix tool for supporting SPC management. It results in a graphical representation that deconstructs SCP and organizational culture into key elements and provides directives for action plans that align improvement efforts. An illustrative application is presented to guide and promote the model’s application in different configurations of supply chains.

This model offers valuable insights into addressing the impact of organizational culture on decision-making related to SCP. Additionally, it facilitates scenario simulation. The management matrix visually illustrates how each performance attribute is influenced by each cultural dimension on a quantitative scale. It also ranks these attributes based on the overall level of influence they receive from culture.

The study provides a unique outlook on the use of FGCMs to support the SCP decisional process by detailing and accounting for the influence of organizational culture. This is done through the development of a novel matrix that allows for visual management and benchmarking.

The purpose of this paper is to propose a supply chain risk management (SCRM) maturity model combined with a fuzzy TOPSIS classification method to evaluate and sort an organization into a pre-defined maturity level.

An axiomatic and prescriptive research method guided this study. Therefore, it proposes a prescriptive approach of maturity classification based on a theoretical SCRM maturity model combined with a multi-criteria decision technique.

The results of a pilot application indicated a consistent classification and the value of the model for diagnosing flaws and pointing directions for improving operational and disruption risk management. Its comprehensiveness allows applying it to supply chains of several industry sectors.

The proposed model does not include all possible risks and could be revised in further developments. Also, adjustment of the maturity profiles of the multi-criteria decision-making (MCDM) model requires a learning process from practical applications.

The adoption of the risk management maturity grid by practitioners may bring the benefit of a more objective and comprehensive evaluation of risk management processes in the supply chain context.

An immediate social implication derives from the improvement actions that may result from the diagnosis of risk management vulnerabilities identified in the pilot application. In general, the proposed model has the potential to reduce risks, improve results and contribute to economic sustainability.

The maturity grid and decision model integrate overall aspects of risk management, bringing together managerial concepts to deal with a variety of supply chain operational risks. The combined multi-criteria classification procedure to sort the maturity level of an organization is also a novelty.

The number of standards for management systems (MSs) has increased recently. Among the most recognizable ones are ISO9001, ISO14001 and OHSAS18001. The need for integration has risen due to the development and adoption of more than one MS in the same business, in a process known as integrated management systems (IMS). Some authors have argued that the use of IMS contributes toward sustainability. The purpose of this paper is to present an instrument to assess the integration of different MSs and its effect on sustainable performance.

A review of IMS, maturity of IMS and sustainability was conducted to build the instrument used in this research. Domingues et al. (2016), Poltronieri et al. (2017), Bernardo et al. (2009) and ISO9001:2015 were used as references pertaining to IMS, whereas Global Reporting Initiative and the research of Delai and Takahashi (2011) were employed for performance issues. All were evaluated both qualitatively and quantitatively.

In the pre-test the order of some questions was changed, some other questions were reformulated and a new classification was created. The evaluation of specialists contributed to reduce the number of questions and make the questionnaire more clear. Cronbach’s α was used to prove the reliability of the questionnaire.

The importance of this study lies in the development of an instrument that helps assess the maturity of the integration of MSs and evaluate sustainable performance.

The purpose of this article is to present and discuss a conceptual model for performance measurement and management of a cluster based on the concepts of the Balanced Scorecard and other models.

This paper was based on a case research as the field research methodology for theory testing and refinement.

The proposed model adequately captures the perspectives of performance management of a cluster, emphasizing the importance of measuring leading and lagging dimensions of performance such as collective efficiency and economic/social results.

Research is still at an early stage and applications of the model need to be carry on further so as to review and validate it.

Absence of a culture of decision making based on analysis of information and lack of resources may create some difficulty in using metrics for a cluster of SMEs.

The paper proposes applying the concepts and techniques of business performance management and measurement to manage performance of clusters of companies, offering a new approach on how to improve the collective efficiency of a cluster.

To provide and illustrate a structured engineering approach for conceptual design of enterprise performance measurement and management systems.

The paper proposes and utilizes a design approach based on combining an enterprise engineering process with a system dynamics (SD) modeling methodology. A research case application in a call center using real data serves as an illustration of these ideas.

This proposed approach provided clear guidance through all the steps of the research case developed. When compared to traditional alternatives, it especially enhanced considerations pertaining to causality relationships among performance metrics, both in a qualitative as well as in a quantitative way.

The explicit combination of enterprise engineering and SD methods creates new research and application opportunities. From a research perspective it establishes a framework for dealing with performance from a systems life‐cycle perspective as well as points to the need for developing integrated modeling techniques. From a practical perspective, the results achieved to this point provide a conceptual design guideline of immediate applicability.

The purpose of this paper is to investigate if a firm’s organizational culture affects the set of quality techniques it uses, and if these quality techniques affect the relationship between organizational culture and operational performance.

Based on data collected from 250 firms in Brazil and Denmark, structural equation modeling is used to investigate the relationship between organizational culture and the use of quality techniques, and its impact on operational performance. Four quality technique groups, four cultural profiles adopted from the Competing Values Framework and a set of operational performance indicators are used to operationalize the study.

Culture does not appear to be an unequivocal predictor of the use of quality techniques. Furthermore, while most quality technique groups contribute indirectly to the total effect on operational performance in the developmental, group and hierarchical cultures, the performance effects are insignificant for all four groups in the rational culture.

Managers need to be actively aware of the cultural characteristics of their organization before adopting quality techniques, in order to benefit most from the use of these techniques.

Most previous studies address the relationships between culture, quality management and performance at the level of quality practices. This study takes the unitarist-pluralist discussion to the level of quality techniques and extends that discussion to what should be its core, namely, the influence of quality techniques on the performance impact of culture.

This paper presents a proposal of adaptation of the failure mode and effect analysis method to analyze wastes and define priorities for actions aimed at minimizing or eliminating these wastes based on the criteria of severity, occurrence and detection.

The proposition was developed in parallel to the implementation of a lean production system of a manufacturing company. A pilot application of the proposal was based on the analysis of a flow of information for order processing.

Application of the proposed procedure results in a classification of levels of priority for waste reduction of the analyzed waste modes. Following this procedure, high priority will be given to actions focused on the elimination or minimization of the most common causes of the most severe waste modes.

Prioritization of actions to minimize waste is essential to sustain lean production systems. However, identifying the wastes most in need of attention is not always straightforward and methods presented in the literature to evaluate leanness do not focus on waste reduction prioritization. Adoption of the proposed technique can certainly aid planning implementation and improvement of lean production programs, and in the end, it can contribute to the effectiveness and sustainability of lean production systems.