Barriers to blockchain adoption in humanitarian logistics in an uncertain environment

In the digital age, blockchain technology is recognized as an operational innovation that is rapidly joining the field of supply chain and humanitarian logistics. Hence, blockchain technology has the potential to fundamentally change the field of humanitarian aid, but still relatively little research has been published aimed at improving understanding of the various barriers to blockchain adoption in humanitarian logistics. The aim of this research is to provide an integrated framework for evaluating the barriers to blockchain adoption in the field of humanitarian logistics. To assess the barriers, integrated approach has been applied in three phases. In the first phase of this approach, based on the literature, 10 barriers to the adoption of blockchain in humanitarian logistics are identified and evaluated using the FMEA method. In the second phase, using the opinions of experts, the weights of the three factors are calculated. Then, in the third phase and according to the outputs of the previous phases, obstacles are prioritized using the proposed Z-ARAS method. In addition to assigning different weights to the three factors considering uncertainty and reliability in barriers is also considered in this approach through the theory of Z numbers. The proposed approach of current study was implemented in the evaluation of blockchain adoption barriers in humanitarian logistics. According to the results, the most critical barriers concern with integrating issues, risk of cyber-attacks, and technology risks. The results shown the capability and superiority of the proposed approach compared to other traditional methods such as FMEA and Fuzzy ARAS.

In the context of the Fourth Industrial Revolution, advanced technologies are reshaping production and business models across various industries, offering new opportunities for enhanced competitiveness but also introducing challenges in terms of adoption and optimization (Wong et al., 2020; Khan et al., 2021). Notably, the convergence of advanced technology and humanitarian logistics is crucial, especially in addressing natural and man-made disasters (Ar et al., 2020; Dubey et al., 2020). This necessitates effective management and the combination of humanitarian logistics with blockchain technology, although this integration comes with multifaceted challenges (Baharmand et al., 2021).
To address these challenges, we explore the Failure Modes and Effects Analysis (FMEA) method as a systematic approach to identify and assess barriers and risks. Traditional FMEA approaches rely on subjective evaluations, which introduce uncertainty into the results. In this context, our research aims to introduce an innovative approach that addresses these limitations by integrating the ARAS method and Z-numbers theory. This approach allows for more reliable prioritization of barriers related to blockchain technology adoption in humanitarian logistics, enhancing the robustness and effectiveness of decision-making processes. In this extended abstract, we present our method and compare its outcomes with traditional approaches to prioritize barriers and risks in blockchain technology adoption within humanitarian logistics. Also, the barriers to blockchain technology adoption in humanitarian logistics and how to prioritize these barriers are among the main research questions.

Blockchain technology is gaining traction in supply chains due to its diverse applications and unique advantages. As supply chains face increasing disruptions, blockchain technology adoption can address challenges and enhance performance (Akhavan & Philsoophian, 2022; Hald & Kinra, 2019). Blockchain structures data into interconnected blocks, ensuring the security and transparency of transactions (Akhavan & Namvar, 2021; Azizi et al., 2021). Blockchain technology is appealing for supply chains due to four main characteristics: encouraging data sharing, minimizing fraudulent transactions, ensuring data immutability, and providing asset security (Babich & Hilary, 2020; Cole, Stevenson, & Aitken, 2019; Rahimi, Akhavan, Philsofian, & Darabi, 2022).
Research on blockchain applications in humanitarian logistics primarily focuses on motivations, such as improved collaboration, transparency, trust, cost reduction, intermediary removal, and shared participation (Baharmand, Maghsoudi, et al., 2021; Seyedsayamdost & Vanderwal, 2020). However, more research is needed in this area (Sahebi, Masoomi, & Ghorbani, 2020). Existing studies have identified barriers to blockchain adoption in humanitarian supply chains, including financial constraints, senior management support, organizational readiness, technological complexity, infrastructure, technology compatibility, and regulatory issues (Baharmand & Comes, 2019).
Multi-criteria decision-making methods (MCDM) have been used to improve FMEA's performance (Ghoushchi et al., 2021; Ghoushchi et al., 2022). These approaches often combine FMEA with methods like GRA, BWM, TOPSIS, and AHP in various fuzzy environments. Such integrated methods have been proposed for barrer identification in the context of blockchain adoption (Li, Li, Sun, & Wang, 2018; Lo & Liou, 2018; Kolios, Umofia, & Shafiee, 2017; Carpitella, Certa, Izquierdo, & La Fata, 2018; Sayyadi Tooranloo & Ayatollah, 2017). Additionally, unified methods like MOORA have been applied to address specific challenges in different contexts (Jafarzadeh Ghoushchi, Memarpour Ghiaci, et al., 2022).
The literature indicates a gap in research on blockchain applications in humanitarian logistics, as most studies focus on business supply chains. Using insights from business supply chains to inform decisions in humanitarian logistics can be misleading, given their fundamental differences (Baharmand, Saeed, Comes, & Lauras, 2021). Consequently, this study aims to address these gaps by proposing an extended FMEA approach based on MCDM methods to identify and prioritize barriers to blockchain adoption in humanitarian logistics, using Z-numbers theory.

The proposed approach of this research is presented, utilizing FMEA and Z-ARAS methods for barrier assessment. The proposed approach consists of three phases. In the first phase, barriers are identified, and the values of the criteria are scored by the FMEA team using linguistic variables from Z-number theory. In the second phase, considering the differences in the importance of criteria, the weight of each criterion is determined based on expert opinions as triangular fuzzy numbers. In the third phase, based on the results of the first and second phases, barrier prioritization is performed while taking into account the criterion weights, using the Z-ARAS method. Unlike the conventional fuzzy ARAS method, the Z-ARAS method can consider uncertainty and reliability for each criterion concerning the options. In this method, after determining the decision matrix, which comprises fuzzy numbers and reliability values (Z-numbers), these values are transformed into triangular fuzzy numbers, and then the Z-ARAS method is executed.

Humanitarian logistics is a relatively new area of research. The impact of humanitarian logistics is crucial, as it saves lives and improves conditions. Research has shown that effective humanitarian logistics is a key driver for the performance of humanitarian organizations. Currently, there exists a significant gap in humanitarian logistics research, particularly in developing countries, between theoretical research and practical implementation.
The adoption of blockchain technology will play a pivotal role in the future development of humanitarian logistics. Therefore, the identification and prioritization of barriers to adopting blockchain technology in humanitarian logistics have gained increasing importance. In this study, an enhanced approach to FMEA is proposed using the Z-ARAS method. Based on the results obtained, "Integration Issues," "Cybersecurity Risks," and "Technology Risks" have been chosen as critical barriers to blockchain technology adoption in humanitarian logistics and are given priority for mitigation and resource allocation. The use of this enhanced approach has addressed some of the limitations of the conventional FMEA method, such as not providing a complete ranking of options. While the developed FMEA approach using the Z-ARAS method is a promising and reliable method, it has limitations. This model may be complex for decision-makers, and it is expected that software tools will be developed to assist decision-makers using this enhanced approach. Additionally, the interaction and impact of barriers were not discussed in this study. Future work can analyze the interplay between barriers to identify critical barriers. Furthermore, researchers can consider multi-criteria decision-making methods like PIPRECIA, SWARA, BWM, and others to determine the importance and weights of criteria. Developing the FMEA method using multi-criteria decision-making methods such as MARCOS, EDAS, CoCoSo, and others for ranking barriers in uncertain environments, including pythagorean, q-rung, and spherical fuzzy scenarios, is also suggested for future studies. Regardless of the issue used for implementing the proposed approach in this research, this approach can be applied to identify and analyze risks and failure modes in various scenarios.