Supply chain disruptions: the influence of industry and geography on firm reaction speed

Speed as an expression and texture of space: theory at play in a movement activity

In recent years, following new materialist, posthumanist and non-representational turns, human geography has increasingly understood the worlds it studies as vital, immediate and emergent. As part of this vision, studies have empirically animated and theoretically articulated various expressions/textures in the movement of space, including its rhythms, shapes, timings, repetitions, sensuousness, and infections. Speed is one such expression/texture that has received some empirical attention but, in comparison to most others, has not been so thoroughly theorized. In response, this paper conducts a reconnaissance into speed, its intentions being to convey some foundational theoretical understandings of speed and, through empirical research, show these at play in social contexts. Specifically, naturalistic participant observations of forms of the movement activity of cycling are used to animate how; (i) speed can be represented and affective as a scalar quantity; (ii) all objects possess speeds and affect other speeds; (iii) speeds and objects are known through relative positions and speeds; (iv) speeds create rates of happening; (v) speeds occur in all expressions/textures of space; (vi) the accelerating world is engaged at relational speeds. From this reconnaissance, to assist future research on speed, the paper closes with some suggested avenues for further inquiry.

Explaining Firm Performance During the COVID-19 With fsQCA: The Role of Supply Network Complexity, Inventory Turns, and Geographic Dispersion

The COVID-19 pandemic has significantly affected firm performance. As a result, many studies have examined the significance of supply network complexity. Our paper uses the fuzzy set qualitative comparative analysis (fsQCA) method to investigate the causal relationships among the supply network complexity, geographic dispersion, inventory turns, and firm performance. Using a sample of 263 Chinese listed firms, we find that no single factor is necessary to achieve high firm performance during COVID-19 and reveal four paths to produce high performance: operational level driven, supply base complexity driven, and customer base complexity driven with supplier distance, and supply network complexity absence. Furthermore, our findings suggest that supply-based complexity-driven and customer-based complexity-driven can improve firm performance, but not all supply network complexity dimensions can improve firm performance. Hence, firms need to choose the suitable path based on their specific situations.

Artificial intelligence and big data analytics for supply chain resilience: a systematic literature review

Artificial Intelligence (AI) and Big Data Analytics (BDA) have the potential to significantly improve resilience of supply chains and to facilitate more effective management of supply chain resources. Despite such potential benefits and the increase in popularity of AI and BDA in the context of supply chains, research to date is dispersed into research streams that is largely based on the publication outlet. We curate and synthesise this dispersed knowledge by conducting a systematic literature review of AI and BDA research in supply chain resilience that have been published in the Chartered Association of Business School (CABS) ranked journals between 2011 and 2021. The search strategy resulted in 522 studies, of which 23 were identified as primary papers relevant to this research. The findings advance knowledge by (i) assessing the current state of AI and BDA in supply chain literature, (ii) identifying the phases of supply chain resilience (readiness, response, recovery, adaptability) that AI and BDA have been reported to improve, and (iii) synthesising the reported benefits of AI and BDA in the context of supply chain resilience.

The stakeholder's roles in risk management related to food supply chain recalls: a systematic literature review

Purpose

Food supply chains (FSCs) are becoming increasingly complex and vulnerable to recall risks due to quality failures. Measures for supply chain risk management can minimize these recall risks. However, this responsibility must be shared by all stakeholders in the chain. This study aims to analyze the roles of different stakeholders in managing risks in the events of food recalls.

Design/methodology/approach

A systematic literature review was carried out, and 110 articles were explored to identify risk management actions and to link them to the role of stakeholders involved in FSC recall.

Findings

The study found that nine stakeholders were responsible for 25 hazard management actions related to food safety and traceability systems, regulatory and preventive measures, and control and response mechanisms for food recalls in the FSC.

Originality/value

This article contributes to the literature by proposing an explanatory map associating risk management actions to different stakeholders in food recall. The actions were grouped according to whether they were prevention actions to avoid a food recall or contention actions to limit the negative economic effects and maintain the health of the population.

Blockchain-Based Information Supervision Model for Rice Supply Chains

Rice is a major food crop around the world, and its various quality and safety problems are closely related to human health. As an important area of food safety research, the rice supply chain has attracted increasing attention. Based on blockchain technology, this study investigated problems of data privacy and circulation efficiency caused by complex rice supply networks, long circulation cycles, and various risk factors in each link. First, we deconstructed the quality and safety of each link of the rice supply chain at the information level and established a key information classification table for each link. On that basis, we built a rice supply chain information supervision model based on blockchain. Various encryption algorithms are used to secure the sensitive data of enterprises in the supply chain to meet regulators' needs for efficient supervision. Moreover, we propose a practical Byzantine fault-tolerant consensus algorithm that scores the credit of enterprise nodes, optimizes the selection strategy of master nodes, and ensures high efficiency and low cost. Then, we built a prototype system based on the open-source framework of hyperledger fabric, analyzed the model's viability, and implemented the system using cases. The results indicated that the proposed system can optimize the information supervision process of rice supply chain regulators and provide a feasible solution for the quality and safety supervision of grain and oil.

Spatial Patterns of Production-Distribution-Consumption Cycle: The Specifics of Developing Russia

The existing body of academic literature reveals that production, distribution, and consumption might be both consistently connected and geographically scattered. This requires assessing the spatial order of production–distribution–consumption cycle, within which exploring of spatial relationship would be based on mutual dependence on each other’s of production, distribution and consumption. Hierarchical and spatial nesting of production, distribution, and consumption data allows us to apply hierarchical spatial autoregressive models (HSAR). The study was conducted on data from 2132 municipalities within 84 regions of the Russian Federation in 2018. The created models enabled distinguishing intraregional and interregional effects and highlighted the positive effect of spatial interactions in production volume. The calculations showed that population income, which determine the demand for goods are positively associated with production volume while relationship between manufacturing and wholesale is negative, resulting in revision of relations between wholesale and manufacturing enterprises and boosting ways of improvement the competitiveness of manufactured goods. The results allow us not only to enhance understanding of the spatial pattern of production–distribution–consumption cycle, but also to reveal new opportunities in the development of supply chain location policy.