Abstract

There has been incredible interest in Internet-of-Things (IoT) and blockchain technology (BCT) around the world and across sectors. Following great achievement in the other sectors, the implementation of IoT and BCT have gained great interest in Humanitarian Logistics (HL) at many levels despite remaining in an earlier stage. The profit and non-profit organizations both are under increasing worldwide pressure for transparency, with donors and governments calling for enhanced transparency and information exchange in the humanitarian sector. This study, which is based on transactive memory systems (TMS) theory perspectives, proposes a study framework to understand "how can the transparency, public trust, and coordination in HL be improved through the integration of IoT with BCT?". We framed and tested six research hypotheses, using data collected from Humanitarian Organizations (HOs) employees. We have applied a Covariance-based structure equation model (CB-SEM) with confirmatory factor analysis (CFA). This study results confirm that our all hypotheses were supported. The research results show that the association between explanatory variables (i.e., IoT and BCT) and the response variables (i.e., public trust and coordination) is mediated by transparency. This study provides substantial and valid contributions to the literature on IoT, BCT, transparency, public trust and coordination. This study proves that transparency plays a crucial role in enhancing public trust, coordination, and ultimately HL performance through the integration of IoT with BCT. The study results could be helpful for all the stakeholders of disaster risk management since they are insistently looking for strategies to support afflicts. Our study is a good candidate solution to raise awareness of fast, fair, and safe HL to reveal research gaps and provide opportunities for future research. The study will provide an enormous understanding of IoT and BCT in HL, which has not been investigated empirically before.

The key purpose of the article is to analyze the effect of digital transformations, such as blockchain technology (BCT), the social internet of things (SIoT), and artificial intelligence (AI) techniques, on the supply chain (SC) for traceability and for creating transparency. The partial least squares (PSL) structural equation modeling (SEM) method was applied in combination with SmartPLS v3.3.6. The package was employed to obtain information through a survey of SC Pakistani professionals using the snowball sampling technique. Traceability plays a crucial role in enhancing transparency and ultimately the performance of SC through BCT, SIoT, and AI. Therefore, the study recommends starting the digital transformation of the SC because this is a complex process that involves a wide range of internal and external stakeholders. The study findings show the importance of technologies of traceability and transparency as an analytical multidisciplinary approach to enhance the SC sector, although with certain limitations this can be taken into account by stakeholders. This study will be useful for decision makers investing in technologies of traceability and transparency in the SC. The study raises the awareness of traceability and transparency in the SC process, and also reveals research gaps and provides opportunities for further research. Despite the prevalence of studies in supply-chain traceability (SCT) and transparency, there is a dearth of empirical proof on how the digital transformation of the SC could lead to transparency and ultimately performance.

No abstract

There has been considerable worldwide attention to the Internet of Things (IoT), blockchain technology (BCT), and artificial intelligence (AI) in all sectors of the economy. Despite still being in the expansion phase, the application of the IoT, BCT, and AI to humanitarian logistics (HL) has drawn a lot of interest due to their significant success in other industries. Commercial and noncommercial organizations are both under growing universal pressure for transparency. Therefore, this study offers a model for understanding the mediating association of transparency between emerging technologies and HL sustainability. The partial least squares structural equation modeling (PLS-SEM) approach was used in conjunction with SmartPLS3. The software was applied to information acquired via questionnaires from 434 disaster relief workers (DRWs) chosen using the snowball sampling approach. The findings suggest that in disaster relief operations (DROs), where corruption and mismanagement in HL have been key concerns for all stakeholders, emerging technologies could be a way forward to achieving system transparency and HL sustainability. The ultimate beneficiaries of transparent and sustainable HL will be all of society, especially the victims of catastrophes. Such victims can receive proper aid on time if the appropriate technology is used in DROs, and early warnings can save many lives. This study adds to the body of knowledge by providing the first empirical evidence assessing the role of emerging technologies in HL transparency and sustainability.