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The recent COVID-19 outbreak and severe natural disasters make the design of the humanitarian supply chain network (HSCN) a crucial strategic issue in a pre-disaster scenario. The HSCN design problem deals with the location/allocation of emergency response facilities (ERFs). This paper aims to propose and demonstrate how to design an efficient HSCN configuration under the risk of ERF disruptions.

This paper considers four performance measures simultaneously for the HSCN design by formulating a weighted goal programming (WGP) model. Solving the WGP model with different weight values assigned to each performance measure generates various HSCN configurations. This paper transforms a single-stage network into a general two-stage network, treating each HSCN configuration as a decision-making unit with two inputs and two outputs. Then a two-stage network data envelopment analysis (DEA) approach is applied to evaluate the HSCN schemes for consistently identifying the most efficient network configurations.

Among various network configurations generated by the WGP, the single-stage DEA model does not consistently identify the top-ranked HSCN schemes. In contrast, the proposed transformation approach identifies efficient HSCN configurations more consistently than the single-stage DEA model. A case study demonstrates that the proposed transformation method could provide a more robust and consistent evaluation for designing efficient HSCN systems. The proposed approach can be an essential tool for federal and local disaster response officials to plan a strategic design of HSCN.

This study presents how to transform a single-stage process into a two-stage network process to apply the general two-stage network DEA model for evaluating various HSCN configurations. The proposed transformation procedure could be extended for designing some supply chain systems with conflicting performance metrics more effectively and efficiently.

This study aims to examine the influence of the blue economy factors on the economic growth of the South Asian Association for Regional Cooperation (SAARC) countries.

Secondary data from 1995 to 2018 have been used for the analysis of eight countries. The contributing factors that measure the fishing production are total aquaculture production, total fisheries production and agriculture, forestry and fishing. Trade and the rate of inflation are used as control variables. Using the feasible generalized least square technique.

It was found that the blue economy factors play a statistically significant role in the economic growth of SAARC countries and contribute to the achievement of Goal 14 of the United Nations’ sustainable development goals: to conserve and sustainably use the oceans, seas and marine resources for sustainable development.

This study highlights the fact that proper management and utilization of water resources may assist the stimulation of economic growth and meet the challenges of food insecurity by improving the supply of seafood in developing South Asian countries. The study proposes that the sustainable management of water resources requires an alliance across nation states. The alliance will be useful in understanding the concept of the blue economy and the role it plays in ensuring economic growth in developing nations throughout the world.