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The purpose of this paper is to identify the key drivers and challenges to supply chain collaboration in the humanitarian sector; to appraise the relationships between international non-governmental organizations (INGOs) and local non-governmental organizations (LNGOs) during disaster relief; and to explore the humanitarian context in regard to supply chain collaboration.

Literature from both the commercial and humanitarian sectors is discussed in the context of vertical partnerships. A Jordanian study spanning a network of 26 international and LNGOs is explored via semi-structured interviews.

The research provides valuable insights on the challenges facing LNGOs and INGOs when developing partnerships. Contextual factors, including host governmental policies and the social-economic setting of a disaster directly affect the motivations for supply chain collaboration between LNGOs and INGOs.

The research is built on interviewees with 30 humanitarian professionals working in one country during an extended crisis. The majority of the empirical data are only from one actor’s perspective, thus further research into dyadic and network relationships is required. Approaches to addressing the diverse cultural and decision-making perspectives of LNGOs and INGOs warrant further investigation.

Recognizing the motives and challenges to vertical partnerships between LNGOs and INGOs will assist the managers, both at the strategic and operational levels, to find solutions and evolve strategies to build effective partnerships. Compromise and consideration for partner’s drivers and cultural views are essential for effective joint humanitarian relief initiatives.

This paper extends supply chain collaboration to a humanitarian context. Overcoming the challenges facing collaborative efforts and complementary nature of the drivers provide a means to achieve effective partnerships. Despite the uniqueness of the humanitarian context, such as the secondary nature of cost and dynamic demand, the core principles of collaboration still hold.

Due to increasing supply chain complexity, the supply chain uncertainty has become an imperative issue, which hinders the development of modern logistics and supply chain management. The paper attempts to conceptualize reverse logistics uncertainty from supply chain uncertainty literature and present the types of reverse logistics uncertainty in a triadic model.

The concept of reverse logistics uncertainty is developed based on a triadic model of logistics uncertainty and supply chain uncertainty literature. A desk research is conducted to develop a taxonomy of reverse logistics uncertainty. To better depict the reverse logistics uncertainty, we use case studies to discuss the types of reverse logistics uncertainty in the triadic model.

The study reveals four types of supply chain uncertainties in the reverse logistics. We call them reverse logistics uncertainty. Type-A and Type-B uncertainty are new types of supply chain uncertainty in the reverse logistics.

The types of reverse logistics uncertainty have not been empirically validated in industries. Especially, the two new types including Type-A and Type-B reverse uncertainty need further exploration.

Although reverse logistics has been discussed in the past decades, very few studies have been conducted on the supply chain uncertainty in returns management arena. The paper offers valuable insights to better understand the supply chain uncertainty in the reverse logistics. This also provides suggestions for both managers and researchers to reflect on the reverse logistics uncertainty management and business sustainability.

The purpose is to identify and explore barriers to overcome for developing collaborative innovation between a global service supplier and two of its industrial customers in Sweden.

The research had an action-based research approach in which the researchers were interacting and collaborating with the practitioners in the companies. The empirical part includes primary data from multiple interviews, and two workshops with dialogues with participants from the involved companies. The use of complementary data collection methods gave rich input to understanding the context for collaborative innovation, and to uncovering barriers, to develop solutions for collaborative innovation. The empirical barriers were analysed using theoretically derived barriers from a literature review. The analysis generated four broad themes of barriers which were discussed and led to conclusions and theoretical and practical implications on: the customer's safety culture, the business model, the parties' understanding of innovation and the management of collaborative innovation in supply chains.

The thematic analysis generated four broad themes: the customer's safety culture, the business model, the parties' understanding of innovation and the management of collaborative innovation. These themes where analysed using theoretically derived barriers from a literature review. The industrial context, the understanding of innovation and its management created barriers.

The unique access to the service supplier and its two independent industrial customers adds a rich contextual framing to the process of identifying and exploring the barriers to collaborative innovation. The conclusion emphasizes the importance of an industrial business context, the business logic in terms of business models and for the understanding and management of collaborative innovation.

Buying companies in the food industry increasingly recognize the need to cultivate relationships with their suppliers. Social capital and power are important to understand buyer–supplier relationships. Maintaining these relationships appears highly dependent on the degree of information sharing.

The study investigates how power and social capital dimensions are related to information sharing. A survey of first-tier suppliers in the Dutch meat processing industry was carried out. The data from 82 suppliers was analyzed using partial least squares.

It appears that expert power contributes to the cognitive and structural social capital. In contrast, coercive power showed no influence at all. Cognitive and structural social capital dimensions have a direct link to relational social capital, which significantly improves buyer–supplier information sharing in the food industry.

Buying companies can encourage supplier information sharing by building up their own expertise and cultivating social relationships. They should refrain from strong-handed practices.

Companies in the food and food processing industry are dependent on effective information exchange for their very survival. This study investigates the role of power and social capital in making such exchange possible and sustainable.