A conceptual framework for supply chain collaboration:empirical evidence from the agri-food industry

Purpose - The purpose of this paper is to analyse the concept of supply chain collaboration and to provide an overall framework that can be used as a conceptual landmark for further empirical research. In addition, the concept is explored in the context of agri-food industry and particularities are identified. Finally, the paper submits empirical evidence from an exploratory case study in the agri-food industry, at the grower-processor interface, and information regarding the way the concept is actually applied in small medium-sized enterprises (SMEs) is presented. Design/methodology/approach - The paper employed case study research by conducting in-depth interviews in the two companies. Findings - Supply chain collaboration concept is of significant importance for the agri-food industry however, some constraints arise due to the nature of industry's products, and the specific structure of the sector. Subsequently, collaboration in the supply chain is often limited to operational issues and to logistics-related activities. Research limitations/implications - Research is limited to a single case study and further qualitative testing of the conceptual model is needed in order to adjust the model before large scale testing. Practical implications - Case study findings may be transferable to other similar dual relationships at the grower-processor interface. Weaker parts in asymmetric relationships have opportunities to improve their position, altering the dependence balance, by achieving product/process excellence. Originality/value - The paper provides evidence regarding the applicability of the supply chain collaboration concept in the agri-food industry. It takes into consideration not relationships between big multinational companies, but SMEs. © Emerald Group Publishing Limited.

A Conceptual Foresight Model to Investigate the Adoption of Radio Frequency Identification Technology in the English National Health Service

Radio Frequency Identification Technology (RFID) adoption in healthcare settings has the potential to reduce errors, improve patient safety, streamline operational processes and enable the sharing of information throughout supply chains. RFID adoption in the English NHS is limited to isolated pilot studies. Firstly, this study investigates the drivers and inhibitors to RFID adoption in the English NHS from the perspective of the GS1 Healthcare User Group (HUG) tasked with coordinating adoption across private and public sectors. Secondly a conceptual model has been developed and deployed, combining two of foresight’s most popular methods; scenario planning and technology roadmapping. The model addresses the weaknesses of each foresight technique as well as capitalizing on their individual, inherent strengths. Semi structured interviews, scenario planning workshops and a technology roadmapping exercise were conducted with the members of the HUG over an 18-month period. An action research mode of enquiry was utilized with a thematic analysis approach for the identification and discussion of the drivers and inhibitors of RFID adoption. The results of the conceptual model are analysed in comparison to other similar models. There are implications for managers responsible for RFID adoption in both the NHS and its commercial partners, and for foresight practitioners. Managers can leverage the insights gained from identifying the drivers and inhibitors to RFID adoption by making efforts to influence the removal of inhibitors and supporting the continuation of the drivers. The academic contribution of this aspect of the thesis is in the field of RFID adoption in healthcare settings. Drivers and inhibitors to RFID adoption in the English NHS are compared to those found in other settings. The implication for technology foresight practitioners is a proof of concept of a model combining scenario planning and technology roadmapping using a novel process. The academic contribution to the field of technology foresight is the conceptual development of foresight model that combines two popular techniques and then a deployment of the conceptual foresight model in a healthcare setting exploring the future of RFID technology.