The mitigating role of blockchain-enabled supply chains during the COVID-19 pandemic

Blockchain-enabled supply chain operations and financing: the perspective of expectancy theory

Purpose

This study examines the cognitive factors of adopting blockchain technology in various supply chain scenarios and its role in reframing the distinctive values of supply chain financing. Based on expectancy theory, this study explores the different profiles underlying the components of expectancy, valence and instrumentality.

Design/methodology/approach

This is a multiple-case study of four Fintech companies using blockchain technology to promote the performance of supply chain operations and financing.

Findings

The results show that blockchain-enabled supply chain finance (BSCF) can be classified into four scenarios based on the scope and purpose of blockchain technology applications. The success of BSCF depends on the profiles of BSCF expectancy (the recognized purpose and scope of BSCF), instrumentality (identified blockchain attributes and other technology combinations) and valence (the perceived distinctive value of BSCF). Blockchain attributes help solve information asymmetry problems and enhance financing performance in two ways: one is supporting transparency, traceability and verification of transmissions and the other entails facilitating a transformation to new business models.

Originality/value

This research applies a new perspective based on expectancy theory to study how cognitive factors affect Fintech companies' blockchain solutions under a given supply chain operation or financing activity. It explains the behavioral antecedents for applying blockchain technology, the situations appropriate for the different roles of blockchain technology and the profiles for realizing the value of blockchain technology.

Clients’ digitalization, audit firms’ digital expertise, and audit quality: evidence from China

Purpose

This study aims to examine whether clients’ degree of digitalization and audit firms’ expertise in information technology (IT) influence audit quality (AQ).

Design/methodology/approach

Data of Chinese A-share firms listed on the primary board of the Shanghai and Shenzhen stock exchanges from 2011 to 2019 are taken as the sample. All the data are obtained from the China Stock Market and Accounting Research. Clients’ digitalization is determined using the keywords “AI technology,” “blockchain,” “cloud computing,” “big data technology” and “digital technology.” Auditor firm’s digital expertise is determined by the proportion of higher IT expertise. As the proxy for AQ, this study uses audit fees, given that its quantum reflects the effort auditors expend that in turn affects the AQ.

Findings

A fixed-effect regression model shows that clients with high digitalization attain AQ. This study also finds a significant and positive coefficient of audit fees, indicating that AQ is high in the same situation if an audit firm’s IT is mature and developed. Furthermore, results confirm the moderating effect of clients’ digitalization and auditors’ expertise and on AQ. Auditors’ expertise in IT mitigates the audit risk and increase AQ.

Originality/value

Findings can enhance AQ and corporate governance literature by clarifying how external audits must evolve through digitalization and incorporating newly developed digital tools such as big data, analytics, artificial intelligence and robotic process automation. This study also provides important insights regarding how the development of new digital tools allow the audit profession to perform as a corporate governance mechanism.

Blockchain technology in supply chain management: an organizational theoretic overview and research agenda

Blockchain technology is touted as a game-changer. Many experts consider blockchain technology as one of the disruptive innovations. Following significant success in the banking and finance sector, blockchain technology has found significant success in all fields, including health, manufacturing, transportation, disaster relief operations, and many others. Recently, the academician has contributed significantly towards understanding blockchain technology and its application in the management field. To understand how the literature on blockchain technology in the supply chain has progressed, we undertook an extensive review of the literature published in peer-reviewed journals using databases such as SCOPUS. We have further classified our literature into four stages (pre-adoption, adoption, implementation, and application). Finally, we synthesized the findings of the study and proposed a research framework to explain how an organization can build supply chain resilience and enhance supply chain performance with the help of blockchain technology. Finally, we have noted the limitations of the study and future research directions.

Why, where and how are organizations using blockchain in their supply chains? Motivations, application areas and contingency factors

Purpose

Blockchain is increasingly being considered for applications in operations and supply chain management. However, evidence from practice is still scarce on why, where and how organizations seek to apply the technology in the supply chain across different industries. The study develops a comprehensive framework to enhance understanding of the application areas of blockchain technology in the supply chain, as well as organizations' motivations in seeking blockchain solutions and relevant contingency factors influencing applications.

Design/methodology/approach

The authors investigate 50 use cases of blockchain applications in the supply chain, covering six industries. Contingency theory is applied in conducting a qualitative textual and correlation analysis to identify and compare blockchain adoption motivations, application areas and contingency factors across different industries.

Findings

The analysis develops an evidence-based framework that captures ten principal motivations in seeking blockchain solutions, three main blockchain application areas along with important application sub-categories and five clusters of contingency factors that influence blockchain deployment and its uses in different industrial sectors.

Research limitations/implications

The study expands the limited cross-sectoral research on blockchain applications and motivations in the supply chain. Using contingency theory, it presents a comprehensive framework that captures the drivers and factors relating to blockchain adoption in the supply chain in a nomological network. The study lays the foundation for further theoretical perspectives and empirical research to investigate relevant sectoral characteristics and their importance for different types of blockchain application in the supply chain.

Practical implications

The study informs practitioners about potential supply chain application areas that can be enhanced through blockchain technology, taking account of the specific characteristics of their products, business and manufacturing processes, supply network configurations, industry standards, regulations and market demand.

Originality/value

The study is the first to provide cross-sectoral evidence on the relevance of organizations' motivations and numerous contingency factors on blockchain application areas in the supply chain.

COVID-19 vaccine hesitancy: a social media analysis using deep learning

Hesitant attitudes have been a significant issue since the development of the first vaccines-the WHO sees them as one of the most critical global health threats. The increasing use of social media to spread questionable information about vaccination strongly impacts the population's decision to get vaccinated. Developing text classification methods that can identify hesitant messages on social media could be useful for health campaigns in their efforts to address negative influences from social media platforms and provide reliable information to support their strategies against hesitant-vaccination sentiments. This study aims to evaluate the performance of different machine learning models and deep learning methods in identifying vaccine-hesitant tweets that are being published during the COVID-19 pandemic. Our concluding remarks are that Long Short-Term Memory and Recurrent Neural Network models have outperformed traditional machine learning models on detecting vaccine-hesitant messages in social media, with an accuracy rate of 86% against 83%.

Resilience and complexity measurement for energy efficient global supply chains in disruptive events

The whole world is faced with the COVID-19 epidemic that causes major disruptions in global supply chains. The aim of study is to evaluate the effects of COVID-19 on energy efficient global supply chains (SCs) and to model the global supply chain resilience and energy management affected during the COVID-19 considering trade between Turkey and China, and Turkey and the EU. In this study, firstly using System Dynamics (SD) model, the behavior of countries against COVID-19 for a certain period of time is observed, subsequently the increase in complexity is analyzed with entropy measurement to determine whether the systems are resilient or not and to mark the differences arising from reporting in the first and second wave of the pandemic in the developed model. It is determined that the second wave reporting differences is less than first wave reporting differences except Turkey. From the learning effect perspective, it has been seen that the effect on the economy and foreign trade are less than first wave of pandemic even though the number of patients originating in the second wave are higher. It means that countries responded to the second wave of COVID-19 in a more resilient way. It is found that as a major finding of this study, perceived complexity of the system decreases in the second wave because of the resilience of supply chain considering learning effect and centralized decision making ensure increasing resilience and resilience measure in global supply chains. The study is highly helpful for governments, decision makers and managers to understand and manage the impacts of COVID-19 on global supply chains being resilient and energy efficient.

Mitigation themes in supply chain research during the COVID-19 pandemic: a systematic literature review

Purpose

The purpose of this paper is to understand the themes and direction of supply chain mitigation and resilience research during the COVID-19 pandemic by conducting a systematic literature review (SLR) of supply chain mitigation literature since pandemic.

Design/methodology/approach

This study uses the Web of Science (WoS) Database to analyze the contribution in supply chain mitigation literature by authors, themes in supply chain mitigation and the citing articles. An investigation based on bibliometric approach for the SLR represents the bibliographic data of over 530 publications between the years 2020–2021. Additionally, the article also develops graphical visualizations of the bibliographic data analyzed using the R-program Bibliometrix to ascertain the top sources, authors, keywords and conceptual themes.

Findings

Most strategies in the existing literature focused on reactive approaches to supply chain disruption and current mitigation literature has not evolved in parallel to the changing macro environment leaving a wide gap in considering vaccines as a supply chain mitigation strategy. Hence, this study identifies the potential need to focus on building proactive supply chain mitigation strategies preferably by studying the role of vaccines in mitigating supply chains.

Practical implications

This article helps the reader to understand the scientific research in terms of contributions in supply chain mitigation research since pandemic. Though, the time frame considered limits the connection the findings to previous work on supply chain disruptions and mitigation, it offers an understanding of the various mitigation themes evolved in light of mitigating the supply chain disruptions as one caused by the current pandemic. Further, this research helps us understand how businesses can help reduce the social consequences by preventing the disruptions and helping life normalize during this ongoing COVID-19 pandemic.

Originality/value

This is the first of its kind contribution offering a SLR of supply chain mitigation strategies during the COVID-19 pandemic identifying the focal themes in current literature and establishing the need for future venues of research studying the role of vaccines in supply chain mitigation strategies.

Supply chains' sustainability trajectories and resilience: a learning perspective in turbulent environments

Purpose

While various supply chain (SC) sustainability investigations exist, their connection to supply chain resilience (SCRes) remains largely unexplored. To fill this gap, the authors answer the question: “How do firms' sustainability actions affect their SCs' resilience and sustainability trajectories in turbulent environments?" by exploring the context of the COVID-19 pandemic.

Design/methodology/approach

The authors conducted 10 case studies in five industries located in six European countries. A total of 19 semi-structured interviews and relevant secondary data were collected and analyzed in reference to SC sustainability learning and the literature on SCRes approaches (i.e. engineering, ecological and social-ecological).

Findings

31 SC actions referring to different sustainability dimensions were identified to map SCRes learning through a temporal, spatial and functional scale analysis. While five cases are related to an engineering approach focused on “bouncing back” to pre-pandemic goals, three cases were focused on “bouncing forward” as part of an ecological approach. Moreover, the authors identified the existence of two social-ecological resilience cases which developed long-term actions, updating functional set-ups transcending the SC level. The results furthermore illustrate an influence of the SCRes approaches on SC sustainability learning, generating three different paths: flat, flat ascending and ascending SC sustainability trajectories.

Research limitations/implications

The study develops an overview of the adoption of SCRes approaches due to temporal, spatial and functional scales, and their effect on SC sustainability trajectories through exploitation and exploration capabilities. Future research should elaborate on potential moderators in the proposed relationships.

Practical implications

A better understanding of the link between SC sustainability actions and SCRes will help practitioners to make better informed decisions in turbulent environments.

Originality/value

Unlike previous research, this paper provides empirical evidence on engineering, ecological and social-ecological SCRes approaches, as well as SC sustainability trajectories.

Drivers, barriers and supply chain variables influencing the adoption of the blockchain to support traceability along fashion supply chains

The critical role of blockchain technology in ensuring a proper level of traceability and visibility along supply chains is increasingly being explored in the literature. This critical examination must focus on the factors that either encourage or hinder (i.e. the drivers or barriers) the implementation of this technology in extended supply chains. On the assumption that the blockchain will need to be adopted at the supply chain level, the enabling factors and the contingent variables of different supply chains must be identified and analysed. The appropriate identification of supply chain partners is becoming a critical factor of success since the globalization of supply chains makes their management and control increasingly difficult. This is particularly true of the fashion industry. Five blockchain providers and seven focal companies working in the fashion industry were interviewed to compare their different viewpoints on this topic. The results highlight which drivers, barriers, and supply chain variables impact the implementation of the blockchain and specific research propositions are formulated.

Supply chain resilience in the UK during the coronavirus pandemic: A resource orchestration perspective

The COVID-19 pandemic caused significant disruptions to global operations and supply chains. While the huge impact of the pandemic has nurtured important literature over the last couple of years, little is being said about the role of resource orchestration in supporting resilience in highly disruptive contexts. Thus, this study aims to this knowledge gap by proposing an original model to explore supply chain resilience (SCRE) antecedents, considering supply chain alertness (SCAL) as a central point to support resilience. This study focuses on the resource orchestration theory (ROT) to design a conceptual model. The partial least squares structural equation modeling (PLS-SEM) served to validate the model, exploring data from the UK supply chain decision-makers. The study reveals a number of both expected and unexpected findings. These include the evidence that supply chain disruption orientation (SCDO) has a strong positive effect on the SCAL. In addition, SCAL plays a strong positive effect in resource reconfiguration (RREC), supply chain efficiency (SCEF) and SCRE. We further identified a partial mediation effect of RREC on the relationship between SCAL and SCRE. Surprisingly, it appeared that SCAL strongly influences SCEF, while SCEF itself does not create any significant effect on SCRE. For managers and practitioners, the importance of resource orchestration as a decisive approach to adequately respond to huge disruptions is clearly highlighted by our results. Finally, this paper helps to grasp better how important resource orchestration in operations and supply chains remains for appropriate responses to high disruptions such as the COVID-19 impacts.