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A safe and effective medical waste transport network is beneficial to control the COVID-19 pandemic and at least decelerate the spread of novel coronavirus. Seldom studies concentrated on a two-phase COVID-19 medical waste transport in the presence of multi-type vehicle selection, sustainability, and infection probability, which is the focus of this paper. This paper aims to identify the priority of sustainable objectives and observe the impacts of multi-phase and infection probability on the results. Thus, such a problem is formulated as a mixed-integer programming model to minimise total potential infection risks, minimise total environmental risks, and maximise total economic benefits. Then, a hybrid solution strategy is designed, incorporating a lexicographic optimisation approach and a linear weighted sum method. A real-world case study from Chongqing is used to illustrate this methodology. Results indicate that the solution strategy guides a good COVID-19 medical waste transport scheme within 1 min. The priority of sustainable objectives is society, economy, and environment in the first and second phases because the total Gap of case No.35 is 3.20%. A decentralised decision mode is preferred to design a COVID-19 medical waste transport network at the province level. Whatever the infection probability is, infection risk is the most critical concern in the COVID-19 medical waste clean-up activities. Environmental and economic sustainability performance also should be considered when infection probability is more than a certain threshold. Funding Agencies|National Natural Science Foundation of China [71904021]; Chunhui Plan of the Ministry of Education of the People?s Republic of China [CQ2019001]; Natural Science Foundation of Chongqing, China [cstc2020jcyj-msxmX0164]; China Scholarship Council [202008500051]; Undergraduate Innovation and Entrepreneurship Training Planning Grant [S202111799038, 202111799004]; Graduate Scientific Research and Innovation Foundation of Chongqing [CYS21383, CYS21384, CYS22604, CYS22608]; Natural Science Foundation of Hunan Province [2022JJ40455]

Disaster waste management received increasing attention in recent years, 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. This paper systematically examines 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. (C) 2019 Elsevier Ltd. All rights reserved. Funding Agencies|National Natural Science Foundation of China [71672074]; Scientific Research Start-up Foundation for Introduction of Advanced Talents in Chongqing Technology and Business University [1955011]; Research Project of Chongqing Technology and Business University; Twelfth Five-Year Planning Project of Philosophy and Social Science of Guangdong Province [GD15CGL07]

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 supply chain were given from the perspective of organizational coordination and strategy. Funding agencies: National Natural Science Foundation of China [71672074, 71772075]; Twelfth Five-Year Planning Project of Philosophy and Social Science of Guangdong Province [GD15CGL07]

Active participation closely associates with the sustainable operation of co-creation communities. Different from recent studies on the promotion of sustainable operation by identifying the internal and external motivations of user participation, this paper aims to analyze the mechanism regarding how different motivations affect the decision of user participation from group-level perspective. To better understand the mechanism, internal and external motivations are, respectively, captured by return-cost analysis and user interactive network. Afterwards, a network evolutionary game model was formulated to analyze the dynamic strategy selection (e.g., active participation and passive participation) of all users. In addition, the stable equilibrium and evolutionary path of strategies are analyzed through computational experiments. Results indicate the following: (a) Rewards have an influence on the promotion of active participation. However, with the continued growth of rewards, this promotion does not make sense sustainably. (b) The promotional effect of information noise on the selection of active participation can be found when passive participation is the dominant strategy. However, the inhibitory effect can be seen in populations that mainly adopt active participation. (c) The scale-free feature of user interactive network inhibits the selection of active participation when active participation is the dominant strategy in populations. Results found here is beneficial for managers to implement the specified policies and thus to achieve the sustainability of co-creation community.

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.