Purpose – In the emerging disciplines of risk management and supply chain management, resilience is a relatively undefined concept. The purpose of this paper is to present an integrated perspective on resilience through an extensive review of the literature in a number of disciplines including developmental psychology and ecosystems. In addition, the paper identifies and addresses some of the current theoretical gaps in the existing research.Design/methodology/approach – Supply chain resilience has been defined by a number of disciplines. An integrative literature review is conducted in an attempt to integrate existing perspectives. This review also serves as the basis for the development of a conceptual model.Findings – The key elements of supply chain resilience and the relationships among them, the links between risks and implications for supply chain management, and the methodologies for managing these key issues are poorly understood. Implications for future research advocate testing the proposed mod...

Understanding the concept of supply chain resilience

A terminology and typology of uncertainty is presented together with a framework for the modelling process, its interaction with the broader water management process and the role of uncertainty at different stages in the modelling processes. Brief reviews have been made of 14 different (partly complementary) methods commonly used in uncertainty assessment and characterisation: data uncertainty engine (DUE), error propagation equations, expert elicitation, extended peer review, inverse modelling (parameter estimation), inverse modelling (predictive uncertainty), Monte Carlo analysis, multiple model simulation, NUSAP, quality assurance, scenario analysis, sensitivity analysis, stakeholder involvement and uncertainty matrix. The applicability of these methods has been mapped according to purpose of application, stage of the modelling process and source and type of uncertainty addressed. It is concluded that uncertainty assessment is not just something to be added after the completion of the modelling work. Instead uncertainty should be seen as a red thread throughout the modelling study starting from the very beginning, where the identification and characterisation of all uncertainty sources should be performed jointly by the modeller, the water manager and the stakeholders.

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Uncertainty in the environmental modelling process - A framework and guidance

Manufacturing industry profoundly impact economic and societal progress. As being a commonly accepted term for research centers and universities, the Industry 4.0 initiative has received a splendid attention of the business and research community. Although the idea is not new and was on the agenda of academic research in many years with different perceptions, the term “Industry 4.0” is just launched and well accepted to some extend not only in academic life but also in the industrial society as well. While academic research focuses on understanding and defining the concept and trying to develop related systems, business models and respective methodologies, industry, on the other hand, focuses its attention on the change of industrial machine suits and intelligent products as well as potential customers on this progress. It is therefore important for the companies to primarily understand the features and content of the Industry 4.0 for potential transformation from machine dominant manufacturing to digital manufacturing. In order to achieve a successful transformation, they should clearly review their positions and respective potentials against basic requirements set forward for Industry 4.0 standard. This will allow them to generate a well-defined road map. There has been several approaches and discussions going on along this line, a several road maps are already proposed. Some of those are reviewed in this paper. However, the literature clearly indicates the lack of respective assessment methodologies. Since the implementation and applications of related theorems and definitions outlined for the 4th industrial revolution is not mature enough for most of the reel life implementations, a systematic approach for making respective assessments and evaluations seems to be urgently required for those who are intending to speed this transformation up. It is now main responsibility of the research community to developed technological infrastructure with physical systems, management models, business models as well as some well-defined Industry 4.0 scenarios in order to make the life for the practitioners easy. It is estimated by the experts that the Industry 4.0 and related progress along this line will have an enormous effect on social life. As outlined in the introduction, some social transformation is also expected. It is assumed that the robots will be more dominant in manufacturing, implanted technologies, cooperating and coordinating machines, self-decision-making systems, autonom problem solvers, learning machines, 3D printing etc. will dominate the production process. Wearable internet, big data analysis, sensor based life, smart city implementations or similar applications will be the main concern of the community. This social transformation will naturally trigger the manufacturing society to improve their manufacturing suits to cope with the customer requirements and sustain competitive advantage. A summary of the potential progress along this line is reviewed in introduction of the paper. It is so obvious that the future manufacturing systems will have a different vision composed of products, intelligence, communications and information network. This will bring about new business models to be dominant in industrial life. Another important issue to take into account is that the time span of this so-called revolution will be so short triggering a continues transformation process to yield some new industrial areas to emerge. This clearly puts a big pressure on manufacturers to learn, understand, design and implement the transformation process. Since the main motivation for finding the best way to follow this transformation, a comprehensive literature review will generate a remarkable support. This paper presents such a review for highlighting the progress and aims to help improve the awareness on the best experiences. It is intended to provide a clear idea for those wishing to generate a road map for digitizing the respective manufacturing suits. By presenting this review it is also intended to provide a hands-on library of Industry 4.0 to both academics as well as industrial practitioners. The top 100 headings, abstracts and key words (i.e. a total of 619 publications of any kind) for each search term were independently analyzed in order to ensure the reliability of the review process. Note that, this exhaustive literature review provides a concrete definition of Industry 4.0 and defines its six design principles such as interoperability, virtualization, local, real-time talent, service orientation and modularity. It seems that these principles have taken the attention of the scientists to carry out more variety of research on the subject and to develop implementable and appropriate scenarios. A comprehensive taxonomy of Industry 4.0 can also be developed through analyzing the results of this review.

Literature review of Industry 4.0 and related technologies

Traceability in a food supply chain: Safety and quality perspectives

Purpose – The objective of this paper is to conceptualise supply chain resilience (SCRES) and to identify and explore empirically its relationship with the related concepts of supply chain vulnerability (SCV) and supply chain risk management (SCRM).Design/methodology/approach – From a review of the literature the conceptual domain of SCRES is defined and the proposed relationships with SCRM and SCV are derived. Data from a longitudinal case study with three supply chains are presented to explore the relationship between the concepts in the context of the global financial crisis.Findings – The empirical data provide support for a positive impact of supply chain risk (SCR) effect and knowledge management on SCRES and from SCRES on SCV. SCR effect and knowledge management seem to enhance the SCRES by improving the flexibility, visibility, velocity and collaboration capabilities of the supply chain. Thereby, they decrease the SCV in a disruptive risk event. The positive effects manifest themselves in upstream...

Supply chain resilience in the global financial crisis: an empirical study

Dynamic demands and constraints imposed by a rapidly changing business environment make it increasingly necessary for companies in the food supply chain to cooperate with each other. The main questions individual (food) companies face are whether, why, how and with whom they should start supply chain management activities. Presents a qualitative research method for analyzing a supply chain network and for identifying effective chain redesign strategies. Presents a generic list of supply chain redesign strategies based on a multi‐disciplinary literature review. Proposes that in order to identify the most effective strategies in a specific chain scenario one should focus on the identification and management of the sources of uncertainties in the supply chain’s decision‐making processes. The application of the research method in three food supply chains resulted in a valuable tool that can be used in supply chain redesign projects, as it indicates potentially effective redesign strategies when a specific source of uncertainty is encountered in a supply chain.

A.J.M. Beulens

Papers

Identifying sources of uncertainty to generate supply chain redesign strategies

Managing traceability information in manufacture

Virtualization of food supply chains with the internet of things

Transparency in complex dynamic food supply chains

Food safety and transparency in food chains and networks Relationships and challenges