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The purpose of this paper is to proactively analyse and mitigate the root causes of the product and security risks. The case study approach examines the effectiveness of the fuzzy logic approach for assessing the product and process-related failure modes within global supply chain context.

The case study of a Printed Circuit Board Company in China is used as a platform for conducting the research. Using data triangulation, the data are collected and analyzed through interviews, questionnaires, expert opinions and quantitative modelling for some interesting insights.

Fuzzy logic approach for failure mode and effect analysis (FMEA) provides a structured approach for understanding complex behaviour of failure modes and their associated risks for products and processes. Today’s managers should conduct robust risk assessment during the design stage to avoid product safety and security risks such as recalls.

The research is based on the single case study and multiple cases from different industry sectors may provide some additional insights.

The study attempts to mitigate the root causes of product and processes using fuzzy approach to FMEA in supply chain network.

Business, consumers and governmental organisations are harbouring a growing need to gain an appreciation of behaviours connected to food criminality. In order to acquire a cross-functional understanding of these thematic areas (crime and fraud) the mapping of existing research is needed. The paper aims to discuss these issues.

This paper contributes to the process of knowledge understanding, by systematically reviewing literature to provide an analysis of the current body of business knowledge against the thematic criterion of “supply chain food crime” and “supply chain food fraud”. The analysis derives themes from the literature and maps this across the eight pillars underpinning the UK Government paper on food supply chain resilience.

A distinct gap lies with the eight pillars of food supply chain resilience, business interest into supply chain criminality and academic research into the field. There are noteworthy gaps when the literature is analysed to that of the UK Government report.

The limitation of the study was its focus on business-only journals; a plethora of literature resides in the science field (e.g. testing) that has not made its way to business text.

Drawing inference between business research and the government report, clear identification and tangible research areas can be immediately exploited to align cross-functional thinking.

The gap of consumer is not as yet addressed in this field, this research contributes originally to this gap and the need to address the same for societal benefit.

The paper concentrates on the metrics know to contribute to “food crime” and “food fraud” and deviating views of academic vs non-academic literature. In conclusion the paper identifies thematic areas for further research and presents a conceptual framework of food supply chain resilience.

The purpose of the paper is to develop a conceptual framework for improving the effectiveness of risk management in supply networks following a critical literature review.

A critical review of 91 scholarly journal articles published between 2000 and 2018 supports the development of an integrated conceptual framework.

The findings emphasize that supply chain integration (SCI) can have both a positive and negative impact on the effectiveness of risk management in supply networks. It is possible to have a positive effect when SCI can be used to develop competencies in joint risk planning within the organization and with wider supply network members and, in turn, to develop collaborative risk management capabilities. Supply network characteristics can influence whether and the extent to which SCI has a positive or negative impact on risk management effectiveness.

The conceptual framework can be used to empirically assess the role of SCI for effective risk management. Dynamic evaluation of the effectiveness of risk management and potential redesign of the supply network by considering other contingent factors are some future research avenues.

There is a need for developing specific competencies in risk planning within organizations and joint risk planning with supply network members which, in turn, can help develop collaborative risk management capabilities to improve the effectiveness of risk management in supply networks. Network characteristics will influence whether and the extent to which SCI results in the effectiveness of risk management.

Moving beyond recent (systematic) reviews on supply chain risk management, this study develops a novel conceptual framework interlinking SCI and the effectiveness of risk management while considering network characteristics.

This paper examines supply chain risk management (SCRM) from a holistic systems thinking perspective by considering the different typologies that have evolved as a result of earlier research. The purpose of this paper is to identify important strategic changes in the field and to outline future requirements and research opportunities in SCRM.

The systematic literature review (SLR) methodology employed by this research was used to evaluate and categorise a literature survey of quality articles published over a period of ten years (2000‐2010). Additionally, the findings from the SLR have been strengthened through cross validation against results obtained from an associated text mining activity.

The SLR methodology has provided a rich, unbiased and holistic picture of the advances in the field of SCRM. Consequently, important new research areas have been identified based on a multi‐perspective descriptive and thematic data analysis. In addition, the analysis, based on evolved typologies, indicates a growth of SCRM from a nascent to a fairly established activity over the past decade.

The systematic approach undertaken for the literature review will provide future researchers and managers with an insightful understanding of the scope of the SCRM field. Also, the literature review provides important clues on new research directions for SCRM through identification of gaps in current knowledge.

The holistic approach to SCRM was found to be an important missing link in earlier literature surveys. The outcome of the SLR reported in this paper has provided critical insights into the present and future scope of the SCRM field. The identified research insights, gaps and future directions will encourage new research techniques, with a view to managing the risks in the globalized supply chain environment.

With increasing exposure to disruptions, it is vital for supply chains to manage risks proactively. Prediction of potential failure points and overall impact of these risks is challenging. In this paper, systems thinking concepts are applied for modelling supply chain risks. The purpose of this paper is to develop a holistic, systematic and quantitative risk assessment process for measuring the overall risk behaviour.

A framework for supply chain risk management (SCRM) is developed and tested using an industrial case study. A systematically developed research design is employed to capture the dynamic behaviour of risks. Additionally, a system‐based supply chain risk model is conceptualized for risk modelling. Sensitivity modelling results are combined for validating the supply chain risk model.

The systems approach for modelling supply chain risks predicts the failure points along with their overall risk impact in the supply chain network. System‐based risk modelling provides a holistic picture of risk behavioural performance, which is difficult to realise through other research methodologies commonly preferred in SCRM research.

The developed framework for SCRM is tested in an industry setting for its viability. The framework for SCRM along with the supply chain risk model is expected to benefit practitioners in understanding the intricacies of supply chain risks. The system model for risk assessment is a working tool which could provide a perspective of future disruptive events.

A holistic, systematic and quantitative risk modelling mechanism for capturing overall behaviour of risks is a valuable contribution of this research. The paper presents a new perspective towards using systems thinking for modelling supply chain risks.

The purpose of this paper is to present the findings of research carried out as part of an industrial project for selection of an enterprise resource planning (ERP) system in a made‐to‐order (MTO) small‐to‐medium enterprise (SME) scenario. It develops a framework or methodology for selection. It also highlights the areas pertaining to the unique needs of, first, the SME sector and, second, the MTO sector, to be considered while selecting a solution. A work book is developed to provide a structured ERP software selection process for SMEs using a comprehensive literature review plus practical experience. This research is potentially aimed at being useful to other SMEs as a guide for a structured selection process.

A combination of comprehensive literature review and experience of managing the selection process for an ERP system in an SME was employed for the study.

Over the past few years, the number of large companies buying new ERP systems has reached saturation point. This has led to the ERP developers seeking instead other potential markets among SMEs. The MTO scenario within the SME sector is one which is very capricious in terms of demand forecasting, lead times, routings, etc. When selecting a system, an organisation in such a segment needs a tailored methodology and a list of key target areas to consider.

The paper represents a very useful source of practical information for the SME sector to consider when selecting an ERP system.

The paper provides valuable insight into the details of ERP selection, focusing on the peculiarities of the SME MTO sector.

The purpose of this paper is to reflect on how representative the literature is in identifying industrial practice to designing product‐service systems (PSSs).

The paper analyses literature to report on the existing approaches used to design PSSs. A single exploratory case study approach, based on semi‐structured interviews and archival data analysis, was used to understand an existing product‐service organisation's approach to designing PSSs. A total of 12 senior managers were interviewed from a cross section of the organisation, to gain multiple perspectives on the PSS design process and ten company reports were analysed.

The research has identified that the PSS design process reported by literature is not representative, lacking inputs and outputs to some phases and feedback. In total, 18 inputs and 11 outputs have been identified from the case study that are not reported by the literature. These create five feedback loops within the PSS design process used by the case study organisation. This suggests that the PSS design process is cyclic and iterative and not sequential, as reported by existing literature.

This research is based on a single‐case study approach, limiting the ability to generalise findings, and does not provide a complete PSS design approach.

This research compares literature against industrial practice to PSS design, presenting insight to aid practitioner's design PSSs.

This paper fills a gap in the servitization and PSS literatures; evaluating the approaches reported by literature against existing industrial practice.

This paper presents a review of the existing state-of-the-art literature on machine learning (ML) in logistics and supply chain management (LSCM) by analyzing the current literature, contemporary concepts, data and gaps and suggesting potential topics for future research.

A systematic/structured literature review in the subject discipline and a bibliometric analysis were organized. Information regarding industry involvement, geographic location, research design and methods, data analysis techniques, university, affiliation, publishers, authors, year of publications is documented. A wide collection of eight databases from 1994 to 2019 were explored using the keywords “Machine Learning” and “Logistics“, “Transportation” and “Supply Chain” in the title and/or abstract. A total of 110 articles were found, and information on a chain of variables was gathered.

Over the last few decades, the application of emerging technologies has attracted significant interest all around the world. Analysis of the collected data shows that only nine literature reviews have been published in this area. Further, key findings show that 53.8 per cent of publications were closely clustered on transportation and manufacturing industries and 54.7 per cent were centred on mathematical models and simulations. Neural network is applied in 22 papers as their exclusive algorithms. Finally, the main focuses of the current literature are on prediction and optimization, where detection is contributed by only seven articles.

This review is limited to examining only academic sources available from Scopus, Elsevier, Web of Science, Emerald, JSTOR, SAGE, Springer, Taylor and Francis and Wiley which contain the words “Machine Learning” and “Logistics“, “Transportation” and “Supply Chain” in the title and/or abstract.

This paper provides a systematic insight into research trends in ML in both logistics and the supply chain.