Xiaotian Xie

Despite the significant attention given to blockchain technology, there needs to be more understanding of the related organizational challenges to adoption. This research provides a systematic literature review (SLR) to comprehensively explore the current literature and answer the following three research questions: 1) Which organizational theories are used to examine blockchain technology in supply chain management (SCM)? 2) What is the value of blockchain technology for SCM? 3)What are the organizational capabilities that influence the success of blockchain technology implementation in supply chains? Through the SLR, we identify the organizational theories applied to investigate the impact of blockchain technology on SCM and examine the main drivers of blockchain deployment. The study also investigates specific dimensions of blockchain technology capability, laying the groundwork for further research on this important emerging research area.

Blockchain technology is expected to have a disruptive impact on supply chain management. To date practical implementations are fewer than expected and insights into the critical success factors (CSFs) of blockchain implementation are limited. This study couples a systematic literature review (SLR) with expert insights captured through a Delphi study to answer the following research questions: 1) What are the CSFs for implementing blockchain technology in the supply chain? 2) How do supply chain management practitioners perceive the CSFs in supply chains? 28 success factors have been identified by SLR. The Delphi study was employed test if these are necessary and sufficient, and prioritise them. This study provides a novel theoretical framework for the CSFs of blockchain technology adoption. This study assists decision-makers and policymakers in understanding each CSFs’ significance and devising the appropriate strategies and policies to address implementation challenges.

The maritime industry is facing increasing challenges due to decarbonization requirements, trade disruptions, and geoeconomic fragmentation, such as International Maritime Organization (IMO) sets out clear framework to reach net zero emissions by 2050, Russia-Ukraine war disrupted maritime activities in the Black and Azov seas, and increased trade tensions between the United States and China. To enhance their sustainability, operational efficiency, and competitiveness, maritime organizations are therefore very keen to build big data analytics capability (BDAC). However, various barriers, mean that only a handful are able to do so. We adopt a mixed-method approach to analyze these barriers. Thematic analysis is used to identify five categories of barriers and 16 individual barriers based on empirical data collected from 26 maritime organizations. These are then prioritized using the analytic hierarchy process (AHP), followed by total interpretive structural modelling (TISM) to understand their interrelationships. Finally, cross-impact matrix multiplications applied to classification (MICMAC) is employed to differentiate the role of each barrier based on its driving and dependence power. This paper makes several theoretical contributions. First, China's hierarchical cultural value orientation encourages competition and obedience to rules, resulting in unwillingness to share knowledge, lack of coordination, and lack of error correction mechanisms. These cultural barriers hinder BDAC development. Second, organizational learning category barriers are found to be the most important in impeding BDAC development. This study also raises practitioners' awareness of the need to tackle cultural and organizational learning barriers. •Identifying, ranking, linking, and categorizing BDAC development barriers•16 barriers to BDAC development of maritime industry were identified.•Cultural and organizational learning related barriers found to be critical to BDAC development.•Allocating barriers into different layers of a framework to understand their interactions•Differentiating the barrier's role based on its driving and dependence power

Smooth, efficient agri-food supply chain (AFSC) operations are becoming ever more difficult due to more intense and frequent natural disasters and man-made disruptions. Helping AFSCs to survive disturbances requires re-consideration of how to build their resilience. This study addresses this issue through a cross-country comparative analysis involving interviews with AFSC practitioners, thematic analysis to generate agri-food supply chain resilience (AFSCRes) capability factors, total interpretive structural modelling (TISM) to establish interrelationships among the factors, cross-impact matrix multiplication applied to classification (MICMAC) analysis to categorise the factors, and comparative analysis. The results reveal that contractual restraints regulating farmers' opportunistic behaviour and regular interactions are key factors for building AFSCRes in France and Argentina, respectively. This study also confirms the critical role of farmers' associations and coordinated activities amongst all AFSC stakeholders to build AFSCRes. For triggering AFSCRes, farmers' resilience must be particularly prioritised, as they are the least resilient point in AFSCs.

Agri-food supply chains (AFSCs) are facing more pressures in terms of increasing volatility, growing population, and intensifying climate change. It is expected that global agri-food production must be doubled by 2050 in order to tackle the world population explosion crisis. Digital technologies have the capability to produce more food with fewer resources, reduce food waste and loss, and revolutionize the agri-food industry completely, which has been widely recognized by scholars and practitioners as a potential solution. However, it is not clear about enablers to facilitate digital technologies application from a developing country's perspective. Thus, this study aims to analyze enablers to the application of digital technologies in the AFSC of China. Three research questions were formulated to understand what digital technologies are applied in the China's agri-food industry, what are the enablers to facilitate AFSC practitioners to use digital technologies, and how the identified enablers are prioritized. To answer these research questions, we employed a mixed-method approach, including semi-structured interviews to collect empirical data from 16 experienced AFSC practitioners, thematic analysis to identify enablers, and fuzzy analytical hierarchy process (AHP) to prioritize the identified enablers. Our study significantly contributes to new knowledge. For example, this study identifies that frequently discussed digital technologies such as blockchain technology, big data analytics, and automatic tractor are seldom used in the agri-food industry of China, other technologies such as water-fertilizer integrated technology, internet of things (IoTs), and smart greenhouses are widely deployed. Ten enablers are identified that may facilitate AFSC practitioners to apply digital technologies, including those merely mentioned by scholars, such as workforce reduction, early detection of plant diseases, accurate determination of the maturity of crops, and improving working conditions. Finally, our prioritization results show that reducing working intensity, reducing water and fertilizer consumption, and improving fertilizer use efficiency are the top three enablers. This study also contributes to managerial practices.