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The purpose of this paper is to explore the impact of the product residual value (PRV) and the loss of value over time of returned products in the reverse supply chain configuration. It also examines whether or not the distinction of Fisher's functional and innovative products holds for the reverse supply chain.

In order to identify the relevance of the Fisher model, the model needs to be recast in terms of PRV, which, in this context, is considered the independent variable in the reverse logistics arena. Products defined as innovative in Fisher's taxonomy correspond to disposed products with high residual value, whereas functional products correspond to disposed products with low residual value. Furthermore, the PRV and the speed at which returned products lose their value are considered in order to determine the configuration of the reverse supply chain that allows for recapturing most of the PRV. These notions have then been tested by analyzing two reverse supply chains with a case study research methodology.

The findings show that low PRV is associated with second‐class recovery options (recycling and energy recovery) and that high PRV is associated with first‐class recovery options (reconditioning and remarketing). When the recovery option is recycling, time is not relevant, the primary objective is cost reduction (efficiency), the chain is centralized, and actors and phases of the reverse chain are determined by the specificity of the recycling process. When the recovery option is reconditioning, time is primarily relevant, tradeoffs between costs and time efficiency are necessary, the chain presents a centralized structure, and the presence of other types of actors and phases influences the structure of the reverse supply chain.

The focus is restricted to the industry of electrical and electronic products.

Based on the outcome of the study, managers are able to determine the basic prerequisites for the design of their reverse supply chains.

Previous literature suggests that when the PRV is high, early product differentiation is necessary, and the chain is therefore decentralized. The paper demonstrates that this is not confirmed in the case of low returned volumes and high reconditioning quality standards.

The purpose of this paper is to investigate how buyers and the vendors pursue alignment in collaborative purchasing (CP) of complex medical technologies.

Through a literature review in CP, the paper identify factors for shareholder alignment (i.e. aligning the needs of the buyers within the purchasing group) and customer alignment (i.e. aligning buyers’ needs with the vendors offering strategies) and investigate how they manifest in the case of CP of complex technology in the Danish National Healthcare System.

Shareholder alignment requires appropriate management of the relationships, expertise and guidance in simplifying procedures and effective management of the purchasing group. Customer alignment is facilitated by buyers’ understating of the vendor’s design options, which are moderated by the vendor’s design strategies.

The findings and generalizations from a single case study are limited to the complexity of the purchased technology and the specific cultural context. However the paper represents the first explorative study that poses the attention on the relevance of shareholder and customer alignment in CP.

The study can offer hospitals, vendors, governmental and regional institutions a better understanding about the alignment mechanisms for successful implementation of CP and how to avoid pitfalls.

Literature on CP is scarce as there are virtually no contributions that debate the key elements and tradeoffs that need to be considered for strategic alignment. The study addresses this gap.

This paper explores innovation adoption in inter-organizational healthcare networks. The authors develop theoretical speculations to investigate better the role of artificial intelligence (AI) as an innovative tool to improve buyer-supplier relationships, creating better performance outcomes.

The research is based on a theoretical investigation aiming at exploring the role of AI-based solutions for managing buyer-supplier relationships. The conceptual approach allows us to identify some research streams (e.g. co-working collaborations in supply chain management) by proposing a matrix that helps clarify the analysis's directions.

The results show the importance of AI that can help the operator in accessing supplier information, including current prices, available stocks, and delivery status, thereby reducing the risk of information asymmetry. AI is intended not only as a technology tool but also as an innovative solution to promote business relationships and support vertical alliances through the value chain between buyer and supplier.

This paper can help healthcare actors examine the choices behind their operational strategies by providing transparency of the activities and availability of information in real-time. Finally, our study reflects the future directions to enhance the cooperation and innovation adoption among healthcare operators.