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The objective of this study is to improve the food supply chain performance taking into consideration the fundamental concepts of traceability by combining the current frameworks, its principles, its implications and the emerging technologies.

A narrative literature review of already existing empirical research on traceability systems was conducted resulting in 862 relevant papers. Following a step-by-step sampling process, the authors ended up with 46 final samples for the literature review.

The main findings of this study include the various descriptions of the architecture of traceability systems, the different sources enabling this practice, the common desirable attributes, and the enabling technologies for the deployment and implementation of traceability systems. Moreover, several technological solutions are presented, which are currently available for traceability systems, and finally, opportunities for future research are provided.

It provides an insight, which could affect the implementation process of traceability in the food supply chain and consequently the effective management of a food traceability system (FTS). Managers will be able to create a traceability system, which meets users' requirements, thus enhancing the value of products and food companies.

This study contributes to the food supply chain and the traceability systems literature by creating a holistic picture of where something has been and where it should go. It is a starting point for each food company to design and manage its traceability system more effectively.

This chapter discusses the application of fuzzy cognitive map (FCM) modelling to construction management (CM) challenges and problems. It focuses on the critical issue of managing the complexity and uncertainty inherent in CM by providing a new intelligent layer that enhances classical approaches to construction modelling and management. It investigates how the myriad types of internal and external factors affecting the feasibility and performance of construction projects can be modelled using a fuzzy hybrid method that explores the complex relationships among many contributing factors and assesses and evaluates their impacts on past and future projects. This chapter proposes a hybrid modelling approach in the traditional context of cost, schedule and risk management and describes how augmenting and enhancing existing state-of-the-art tools and processes in CM can assist construction managers. This chapter provides a background on the theory of FCMs, presents foundational and current research, and explains how to apply this approach in the CM domain. This chapter also provides a detailed description of how to develop, modify and employ interactive models to specific CM challenges and problems. It includes a customisable, interactive base model and demonstrates how the model has been applied to specific CM events and issues. Examples are presented that highlight the interplay between project-specific goals and characteristics and the way these impact the interrelated and often opposing triad of cost, schedule and risk. The presented examples and practical applications make this state-of-the-art approach useful to both academic and industry practitioners.

Total quality management (TQM) is a process and philosophy to achieve customer satisfaction in long term by improving the products, processes and services effectively and efficiently. TQM implementation is turning into a complex practice due to the increasing number of effective factors and key elements labelled as critical success factors (CSFs). The purpose of this paper is to analyse the relations between CSFs of TQM and to provide decision makers has a clear picture of relations by determining the most affecting – both the number of CSFs which this factor affects and the its effect degree on relevant CSFs are higher comparing to other factors – of this factors affected factors – both the number of CSFs and their effect degree on these factors are higher – that influences a successful TQM implementation.

The paper refers to fuzzy cognitive maps (FCMs) that allow dynamic modelling of a system in consideration of a complex network structure and the effects of factors to each other. The method demonstrates causal representations between CSFs under uncertainty to represent the relations and interaction between them and performs qualitative simulations to analyse the factors that have the highest impact on continuous improvement of quality management process. The evaluations are performed by five academicians whose professions are on both the areas of TQM and FCM.

FCM analysis shows how the most affecting and affected factors influence the other CSF in order to manage a successful TQM implementation.

The critical factors of TQM implementation are in the focus of most of the empirical studies in the literature. However, none of them considers the dynamic interactions between the factors. This study employs FCM to explore the CSFs that influence the TQM implementation process considering the relations among them to observe the most affecting and affected factors based on the changes of determined CSFs.