Horizontal logistics collaboration (HLC) practices have gained much attention in recent years as innovative ways for companies to improve their performance. However, literature does not reveal which factors influence the success or failure of HLC, especially in agri-food supply chains (AFSCs) in developing countries. Therefore, this paper aims to investigate HLC in the context of AFSCs in Morocco as a case of a developing country. First, a literature review is performed to develop a conceptual model for HLC considering AFSCs characteristics. Then, indepth case studies are conducted in Morocco to refine the conceptual model based on insights from real collaboration experiences. The results show that collaboration outcomes are influenced by operational collaborative activities through the mediation of relational elements. The operational collaborative activities are impacted by AFSCs' characteristics, such as products specific handling conditions. Furthermore, the research shows that local cultural factors influence the development of trust in the relationship.

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PurposeThe purpose of this paper is to develop a comprehensive model for horizontal logistics collaboration (HLC), including the collaboration types, enablers, context influence and performance indicators.Design/methodology/approachFirst, this study discusses the currently available typologies and their limitations and defines relevant collaboration classification dimensions. Then, a detailed analysis of each dimension is conducted, including the identification of resulting collaboration types. Next, collaboration enablers and the context influence are discussed, as well as their implications on the logistics system, with a specific focus on agri-food supply chains (AFSCs). Additionally, adequate key performance indicators (KPIs) are selected to evaluate collaboration outcomes. Finally, the horizontal logistics collaboration concept (HLCC) is applied to an illustrative case study from AFSCs.FindingsThe results show that HLC is a complex strategy where several elements intervene in the creation of the collaboration scenario. The research also shows that the specific characteristics of AFSCs influence the partners' selection process and increase the importance of partners' similarity and information exchange.Practical implicationsThe results provide managers with practical insights into the dynamic nature of HLC both at the operational and relational levels.Originality/valueThis paper provides a theoretical contribution by introducing a new comprehensive model for HLC and a practical typology that allows a deeper understanding of the mechanisms governing different HLC scenarios.

PurposeThis study investigates the impact of agri-food supply chains (AFSCs) characteristics on the antecedents of horizontal logistics collaboration (HLC). Specifically, the study compares the relationship between collaboration activities and outcomes for companies in and outside AFSCs.Design/methodology/approachFirst, a survey was used to collect data from different industries. Second, confirmatory factor analysis and structural equation modeling were applied to compare the measurement and structural models from different industry categories.FindingsThe results support the premise that collaboration improves trust and commitment in the relationship, which in turn enhance satisfaction. The results also show the existence of a minor influence of AFSCs characteristics on HLC antecedents, in the form of an indirect impact of dedicated investments on commitment.Practical implicationsThe factors having a significant influence on the collaboration outcomes and their respective effects are generally similar across food and nonfood supply chains, providing opportunities for interdisciplinary and collaboration experiences.Originality/valueThis research contributes to the body of knowledge on interfirm collaboration by considering the specificities of HLC. It also highlights the importance of conducting contingency research on collaborative experiences, as firms from different industry contexts operate under distinct operational conditions.