To save lives and reduce suffering of victims, the focus here is to design the strategies of relief distribution regarding beneficiary perspective on sustainability. This problem is formulated as a multi-objective mixed-integer nonlinear programming model to maximize the lowest victims' perceived satisfaction, and minimize respectively the largest deviation on victims' perceived satisfaction for all demand points and sub-phases. Then, genetic algorithm is proposed to solve this mathematical model. To validate the proposed methodologies, a case study from Wenchuan earthquake is illustrated. Computational results demonstrate genetic algorithm here can achieve the trade-off between solution quality and computation time for relief distribution with the concern of sustainability. Furthermore, it indicates that the methodology provides the tools for decision-makers to optimize the structure of relief distribution network and inventory, as well as alleviate the suffering of victims. Increasingly, this paper expects to not only validate the proposed model and method, but highlight the importance and urge of considering beneficiary perspective on sustainability into relief distribution problem.

Sustainable humanitarian supply chain has a great impact on saving lives, decreasing human suffering and contributing to development. Organizational coordination plays an important role in it, although it is uncommon to be established due to the conflicting interests and expectations. To cope with the problem and achieve the sustainability of humanitarian supply chain, the coordination between private sector and humanitarian organization was further discussed with the help of sustainable principle regarding stakeholder approach. Different from the existing literature that elaborated the drivers and the advantages of coordination, this paper aims to explore the coordination mechanism regarding whether to coordinate, when to adopt the optimal coordinated strategy and how such a strategy can perform well. To analyze the tendency of the coordinated decisions, evolutionary game models concerning traditional and trust mechanisms were developed. Then, computational studies based on hypothetic data were simulated to validate the effectiveness of the proposed model. Results indicated that the coordination decision was affected by coordinated returns and costs, normal returns and extra returns in terms of the traditional mechanism. Several situations in regard to the coordinated decisions were analyzed by adopting evolutionary stable strategies. Moreover, trust had a significantly positive impact on coordination promotion under the support of potential returns and high-level trust. Finally, managerial insights for achieving the sustainable humanitarian

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Firms have increasingly relied on information technology (IT) to remain agile in today's hypercompetitive business environment. Drawing on the organizational inertia theory and literature on IT-enabled agile, this study examines the relationship between organizational inertia, IT ambidexterity (i.e., IT exploration and exploitation), and organizational agility. Quantitative data were collected from 326 respondents through a questionnaire survey in China and analyzed using the partial least squares structural equation modeling. Results show that organizational agility is negatively influenced by organizational inertia, whereas IT exploration and exploitation positively related to organizational agility and IT exploitation is the dominant force. Furthermore, IT exploration and exploitation partially mediate the relationship between organizational inertia and agility. These findings offer new theoretical perspectives on organizational agility and guide practitioners to deal with related inertia issues to effectively improve organizational agility.

Abstract:To mitigate or reduce various losses and improve efficiency of disaster response, the focus of this paper is to design optimized strategies of emergency organization allocation regarding sustainability. Firstly, an integrated framework including several elements such as emergency organization, task, decision-agents, environment and their relations is developed from a systematic perspective. Then, this problem is formulated as a novel multi-objective 0-1 integer programming model to minimize total weighted completion times, total carbon emissions and total emergency costs. Next, branch and bound approach and handling strategies for multiple objectives are designed to solve this model. Finally, a case study from the Wenchuan earthquake is presented to illustrate the proposed model and solution strategies. Computational results demonstrate their significant potential advantages on allocating emergency organization from the perspectives of best practice, objective functions, preferences of decision-agents, and problem size.

Disaster waste management received increasing attention in recent year, but there was no review updating the evolving development after the study of Brown et al. (2011a). To explore how the topics in disaster waste management evolved in recent years and to analyze whether the gaps identified by Brown et al. (2011a) are covered, 82 papers published from 2011 to 2019 were selected from the Scopus database based on the defined process and criteria, to systematically examine the disaster waste management research from nine aspects of planning, waste, waste treatment options, environment, economics, social considerations, organizational aspects, legal frameworks and funding. The results suggested that there were no obvious changes or developments in the field of disaster waste management, although a few research gaps have been addressed, such as waste separation, waste quantities, case studies of incineration and waste to energy, direct economic effects, social considerations as well as application of GIS technology. Except for the comparative studies, future directions were suggested by the gaps that persist since Brown et al. (2011a) and the new gaps that were identified in this review.

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After the outbreak of COVID-19 pandemic, devising an effective reverse logistics supply chain to clean up disaster medical waste is conducive to controlling and containing novel coronavirus transmission. Thus, the focus of this paper concentrates on multi-period multi-type disaster medical waste location-transportation integrated optimization problem with the concern of sustainability, which is formulated as a tri-objective mixed-integer programming model with the goals of maximizing total economic benefits, minimizing total carbon emissions and total potential social risks. Then, a real-world case from Wuhan using CPLEX solver is used to validate the developed model. Results indicate that constructing DMWTTSs with flexible capacity in different periods is encouraged to handle the sharply increasing disaster medical waste. The multi-period decision model outperforms the single-period one in disaster medical waste supply chains because the former has the capability of handling the uncertainties in the future periods. Increasingly, since the increase of budget doesn’t always work well and social resources are limited, the estimation of minimum budget to obtain optimum overall performance is of great importance.