Blockchain systems and ethical sourcing in the mineral and metal industry: a multiple case study

PurposeThe purpose of this paper is to examine blockchain's roles in promoting ethical sourcing in the mineral and metal industry.Design/methodology/approachIt analyzes multiple case studies of blockchain projects in the mineral and metal industry.FindingsIt gives detailed descriptions of how blockchain-based supply chain networks' higher density of information flow and high degree of authenticity of information can increase supply chain participants' compliance with sustainability standards. It gives special consideration to blockchain systems' roles in overcoming the deficits in the second party and the third-party trust. It also demonstrates how blockchain-based supply chain networks include outside actors and configure the supply chain networks in a way that enhances the empowerment of marginalized groups.Practical implicationsIt suggests various mechanisms by which blockchain-based supply chain networks can give a voice to marginalized groups.Originality/valueIt demonstrates how blockchain is likely to force mineral and metal supply chains to become more traceable and transparent.

Exploring blockchain adoption intentions in the supply chain: perspectives from innovation diffusion and institutional theory

PurposeDespite blockchain's potential supply chain benefits, few organizations have moved beyond pilot projects. The paper aims to explore blockchain adoption intentions for supply chain applications using two theoretical perspectives: innovation diffusion theory (IDT) and institutional theory (IT).Design/methodology/approachBased on theory, five propositions were developed addressing the intention to adopt blockchain. The propositions were tested using scenario-based experiments with supply chain professionals. To provide additional insights, interviews with 21 supply chain professionals in 15 organizations representing 8 industries were content analyzed.FindingsExperiments suggest that the intention to adopt blockchain is higher when there are government regulations regarding product origin, organizations are using updated cloud-based information systems and organizations are working with third-party consultants. The content analysis suggests that organizations that face normative pressures to adopt blockchain supply chain applications and recognize blockchain's relative advantage, compatibility and complexity are more likely to be actively seeking information about and adopting blockchain supply chain applications. The authors synthesize findings and provide new propositions to guide future research.Originality/valueUsing a multi-method approach, the study provides an important window into supply chain managers' perceptions of the necessary conditions to support organization-level blockchain adoption. The findings also indicate key characteristics present in supply chain networks poised for blockchain adoption.

Impact of the COVID-19 on Global Supply Chain

As the coronavirus pandemic engulfed the globe, it has disrupted economic activities, including supply chain networks in consequent to the existing interconnected trade networks making more countries to be more susceptible and major traders affected. This Chapter aims to analyse the COVID-19 effect on the global and sectoral supply chain and the structural policy and economic measures taken by governments and business organisations to recover and stay resilient during this challenging period. Systematic literature review approach focusing on challenges and policy and economic and business responses during the COVID-19 pandemic. Online databases utilising Scopus and ISI Web of Science (WoS) for studies published from 2019-2021. 28 journal articles were selected for the final review. There is compelling evidence that COVID-19 has made profound impact that governments and companies seek to strengthen operations and business resilience, underscore the importance of supply chain resilience and risk management is more critical than ever. Prolong COVID-19 trade measures such as borders closure, export embargo and import sanction are a threat to supply value chain and total lockdown should be implemented with caution. Currently, many companies have begun to move from a “recovery mode” to more “sustainable and resilient mode” and have started longer term planning. The implication of the study is that policymakers and business leaders should pay attention to more proactive and flexible policy, economic and structural business reform. This review will help policymakers and business leaders to enforce policy and economic as well as business reform that build upon resilient supply chain to mitigating economic risks in bad times to reduce the effect of COVID-19 on global supply chain.

Customer complaints encountered in the online food retail during the COVID-19 intermittent curfew period

Almost everything has changed fundamentally with the coronavirus (COVID-19) epidemic. The pandemic has adversely affected the retail industry and the global economy. After detecting COVID-19, customers’ shopping preferences have moved to popular platforms like online shopping websites. Meanwhile, due to inadequate distribution structures and decentralized supply chain networks of businesses, customers have experienced many failures in service encounters. This study employed a document review method to analyse customer complaints covering common logistic service failures in the food sector during the three months (March, April and May 2020) intermittent curfew period. In addition, using content analysis, “şikayetvar.com” complaints were classified according to the service quality gap model. Since disruptions in the food industry are critical with their stimulating effects on supply chains, this industry has been analysed in detail. In terms of practical contribution, the study introduces an insight to enhance the customer service capabilities of private shopping sites. Furthermore, the theoretical background of the study reveals the service quality dimensions prioritized by customers in the pandemic environment and their critical role in service quality gaps.

Distributed Consensus Tracking Control of Chaotic Multi-Agent Supply Chain Network: A New Fault-Tolerant, Finite-Time, and Chatter-Free Approach

Over the last years, distributed consensus tracking control has received a lot of attention due to its benefits, such as low operational costs, high resilience, flexible scalability, and so on. However, control methods that do not consider faults in actuators and control agents are impractical in most systems. There is no research in the literature investigating the consensus tracking of supply chain networks subject to disturbances and faults in control input. Motivated by this, the current research studies the fault-tolerant, finite-time, and smooth consensus tracking problems for chaotic multi-agent supply chain networks subject to disturbances, uncertainties, and faults in actuators. The chaotic attractors of a supply chain network are shown, and its corresponding multi-agent system is presented. A new control technique is then proposed, which is suitable for distributed consensus tracking of nonlinear uncertain systems. In the proposed scheme, the effects of faults in control actuators and robustness against unknown time-varying disturbances are taken into account. The proposed technique also uses a finite-time super-twisting algorithm that avoids chattering in the system’s response and control input. Lastly, the multi-agent system is considered in the presence of disturbances and actuator faults, and the proposed scheme’s excellent performance is displayed through numerical simulations.

Key challenges and developments in non-targeted methods or systems to identify food adulteration

Food fraud is an ongoing global challenge that is amplified by the complexity of supply chain networks and fraudsters becoming more innovative in the way they commit fraud. There is a great need for rapid analytical tools that offer broad product screening. Non-targeted methods provide an approach by which a food matrix can be analysed and screened for adulterations. While various developments exist for rapid non-targeted approaches, there are still multiple challenges to overcome. More work is required to validate, harmonise and standardise non-targeted methods and the associated data interpretations. Promising advances include novel technological developments with devices becoming smaller and portable with increased sensitivity. It is undoubtedly that fingerprinting approaches generate huge datasets that need to be stored and utilised as effectively as possible; creating new opportunities for Big data analysis and the Internet of Things – both addressing the need to convert data into insights to act upon.

An Unsupervised Machine Learning-Based Framework for Transferring Local Factories into Supply Chain Networks

Transferring a local manufacturing company to a national-wide supply chain network with wholesalers and retailers is a significant problem in manufacturing systems. In this research, a hybrid PCA-K-means is used to transfer a local chocolate manufacturing firm near Kuala Lumpur into a national-wide supply chain. For this purpose, the appropriate locations of the wholesaler’s center points were found according to the geographical and population features of the markets in Malaysia. To this end, four wholesalers on the left island of Malaysia are recognized, which were located in the north area, right area, middle area, and south area. Similarly, two wholesalers were identified on the right island, which were in Sarawak and WP Labuan. In order to evaluate the performance of the proposed method, its outcomes are compared with other unsupervised-learning methods such as the WARD and CLINK methods. The outcomes indicated that K-means could successfully determine the best locations for the wholesalers in the supply chain network with a higher score (0.812).