Human suffering has increased in recent years owing to increased intensity ad frequency of disasters. These are expected to further increase in the coming years due to climate change. Although natural disaster risks to humans cannot be completely eliminated, they can be minimized through efficient and effective humanitarian logistics (HL). Considering the importance of HL in reducing the impacts of disasters through fair distribution, this study aims to address the following question: “How can the performance, efficiency and effectiveness of HL be improved through transparency?” The primary data were collected through an online structured questionnaire from the employees participating in relief operations in Pakistan. This specific research model is reflective. Therefore, a covariance-based structure equation model (CB-SEM) based on confirmatory factor analysis (CFA) with SmartPLS software was used. The study tested the items’ reliability, discriminate validity, goodness of fit, and psychometrical soundness of the hypothesized model. The study results indicate that the relationship between predictor variables (disclosure, clarity, accuracy, corporate governance, decision making and accountability) and the response variable (effective HL) is mediated by public trust. Furthermore, the study suggests that public trust plays an imperative role in enhancing the performance, efficiency and effectiveness of HL. In addition, first, the study findings are expected to be beneficial for all stakeholders of disaster risk management, especially for governments, donors and humanitarian organizations (HOs), because they are persistently seeking strategies to assist victims. Second, most importantly, this study raises awareness of the need to carefully evaluate decisions related to the fair distribution of relief items. Third, the structure of this article reveals research gaps and promising areas for further research. This article provides a deeper understanding of transparency in HL using empirical data, which has not been explored before.

The purpose of this study is to identify and analyze the methods for increasing the volume of Inward Foreign Direct Investment (FDI) in Pakistan. Two different approaches are investigated: firstly, identifying the main barriers to investing in Pakistan, and secondly, examining the key success factors (KSFs) of the top FDI recipients in the world. Both parametric and non-parametric statistical analyses are applied. The study findings provide guidance to the implementation of common KSFs for increasing inward FDI. The paper discusses cultural barriers in developing markets for investors’ collective performance, the consequence and significance of cultural barriers in emerging markets, and the requirement for social adaptation for successfully attract inward FDI in developing counties. This paper identifies and proposes suggestions for resolving the internal problems of Pakistan’s investment climate that act as impediments to increased FDI volume.

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.

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