Humanitarian supply chains involve many different entities, such as government, military, private, and non‐governmental organizations and individuals. Well‐coordinated interactions between entities can lead to synergies and improved humanitarian outcomes. Information technology (IT) tools can help facilitate collaboration, but cost and other barriers have limited their use. We document the use of an IT tool to improve last‐mile supply distribution and data management in one of many camps for internally displaced persons after the January 2010 earthquake in Haiti, and we describe other current uses of technology in camp management. Motivated by these examples and the interest among humanitarian organizations in expanding the use of such tools to facilitate coordination, we introduce a cooperative game theory model and explore insights about the conditions under which multi‐agency coordination is feasible and desirable. We also outline an agenda for future research in the area of technology‐enabled collaboration in the humanitarian sector.

Extended Producer Responsibility (EPR) is a policy tool that holds producers financially responsible for the post-use collection, recycling and disposal of their products. Many EPR implementations are collective-a large collection and recycling network (CRN) handles multiple producers' products in order to benefit from scale and scope economies. The total cost is then allocated to producers based on metrics such as their return shares by weight. Such weight-based proportional allocation mechanisms are criticized in practice for not taking into account the heterogeneity in the costs imposed by different producers' products. The consequence is cost allocations that impose higher costs on certain producer groups than they can achieve independently. This may lead some producers to break away from collective systems, resulting in fragmented systems with higher total cost. Yet, cost efficiency is a key legislative and producer concern. To address this concern, this paper develops cost allocation mechanisms that induce participation in collective systems and maximize cost efficiency. The cost allocation mechanisms we propose consist of adjustments to the widely-used return share method, and include the weighing of return shares based on processing costs and the rewarding of capacity contributions to collective systems. We validate our theoretical results using Washington state EPR implementation data and provide insights as to how these mechanisms can be implemented in practice.

Summary The goal of this article is to contribute to the understanding of how the multiple, and sometimes conflicting, stakeholder perspectives and prevailing conditions (economic, geographic, etc.) in the implementation locality shape extended producer responsibility (EPR) “on the ground.” We provide an in‐depth examination of the implementation dimension of EPR in a specific case study by examining concrete activities at the operational front of the collection and recycling system, and probing the varying stakeholder preferences that have driven a specific system to its status quo. To this end, we conduct a detailed case study of the Washington State EPR implementation for electronic waste. We provide an overview of various stakeholder perspectives and their implications for the attainment of EPR policy objectives in practice. These findings shed light on the intrinsic complexity of EPR implementation. We conclude with recommendations on how to achieve effective and efficient EPR implementation, including improving design incentives, incorporating reuse and refurbishing, expanding product scope, managing downstream material flows, and promoting operational efficiency via fair cost allocation design.

A key goal of Extended Producer Responsibility (EPR) legislation is to provide incentives for producers to design their products for recyclability. EPR is typically implemented in a collective system, where a network of recycling resources are coordinated to fulfill the EPR obligations of a set of producers, and the resulting system cost is allocated among these producers. Collective EPR is prevalent because of its cost efficiency advantages. However, it is considered to provide inferior design incentives compared to an individual implementation (where producers fulfill their EPR obligations individually). In this paper, we revisit this assertion and investigate its fundamental underpinnings in a network setting. To this end, we develop a new biform game framework that captures producers' independent design choices (non-cooperative stage) and recognizes the need to maintain the voluntary participation of producers for the collective system to be stable (cooperative stage). This biform game subsumes the network-based operations of a collective system and captures the interdependence between producers' product design and participation decisions. We characterize the manner in which design improvement may compromise stability and vice versa. Yet we establish that a stable collective EPR implementation can match and even surpass an individual implementation with respect to product design outcomes. Our analysis uncovers network properties that can be exploited to develop cost allocations that achieve such superior design outcomes.

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