income.pdf 4.0 should help meeting sustainable challenges by increasing the agri-food supply chain stakeholders revenues as well as decreasing their pressure for handling complex and external factors they cannot control, such as weather, market behaviours and policies, but also to react on time by visualising current trends in needs. This paper focus principally on the factory farm model issued from the European and north American style. In those typologies of farms the Industry 4.0 elements can be introduced and merged with the agricultural domain to create the Agri-Food 4.0. The focus is more specialised on the industrial farming although the Agri-Food 4.0 is started to be adapted also to the organic and silvo-pasture paradigms. Thus, this paper, considering a review over than two hundred papers, provides a contribution to knowledge by establishing the linkages between new 4.0 trends in technologies and Agri-Food Supply Chain Challenges, which opens the 4.0 research field for a multidisciplinary work. The choice of the literature review methodology focused firstly on key words related to the Agri-food technology, then the second approach was to focus on selected journals and at the end we looked for the data-based repository and the linked publications. To accomplish this, the structure in this paper is as follows: in the first place, a compressive state of the art of Agri-Food 4.0 related technologies is covered. In the second place, a review and contribution coming from digital technologies to the new supply chain methods in Agri-Food shows linkages with next trends and technologies. Next, and linked to the agri-food supply chain challenges, the fourth section presents new trends and models in agri-food supply chains, especially in the domain of risk management, collaboration, governance, cold chain management, globalization, information and communication technologies, Logistics, supply chain structures and sustainable agri-food supply chains. Finally, the fifth section covers the main conclusions, visions and perspectives for this novel research. 2-Agri-food 4.0 and Technologies a State of the Art The agricultural sector has been active in digital innovation for decades already. Especially the advances in Precision Agriculture, remote sensing, robots, farm management information

ISBN 978-1-4244-3460-2International audienceThis paper presents a new method for segmentation and interpretation of 3D point clouds from mobile LIDAR data. The main contribution of this work is the automatic detection and classification of artifacts located at the ground level. The detection is based on Top-Hat of hole filling algorithm of range images. Then, several features are extracted from the detected connected components (CCs). Afterward, a stepwise forward variable selection by using Wilk's Lambda criterion is performed. Finally, CCs are classified in four categories (lampposts, pedestrians, cars, the others) by using a SVM machine learning method

PurposeThis paper seeks to propose an overall model of collaborative forecasting for networked manufacturing enterprises.Design/methodology/approachContributions by several authors to collaborative forecasting have been analysed from different viewpoints. A collaborative‐forecasting model for networked manufacturing enterprises has been proposed and validated by means of a simulation study.FindingsThis model significantly reduces the inventory levels of the whole network and improves customer service.Research limitations/implicationsSimulation experiments were done with the enterprise network herein described. Future research will include the simulation of more complex enterprise network scenarios with different characteristics.Practical implicationsThe model can be implemented node‐to‐node, since not all the companies in the network have to participate, thus facilitating implementation and propagation throughout the network.Originality/valueThe paper proposes a new structured planning and forecasting collaboration model for networked manufacturing enterprises.

PurposeThis study explores how sharing platforms achieve platform loyalty through various operation management strategies.Design/methodology/approachA multiple case study method has been conducted in two Chinese sharing economy industries: ride- and bike-sharing. Data were collected through 30 semi-structured interviews with managers from four platform companies (DiDi, Uber China, ofo and Mobike). Individual case studies were developed from the triangulation of all existing data. Concurrent with the development of these individual case studies was a cross-case analysis. Emerging patterns have been identified and compared to previous findings in the literature to build upon and modify the existing knowledge base and to formulate a series of propositions.FindingsPlatform asset characteristics and mergers and acquisitions affect supply network readiness and operational capacity, respectively, and this effect would consequently contribute to achieving platform loyalty through user satisfaction. Moreover, externality, as a moderator, may influence the strength of the relationship between satisfaction and platform loyalty.Practical implicationsThe proposed theoretical model provides an overarching framework for sharing platform companies to design and operate their businesses while carefully examining the situations, contexts and actions of users and other stakeholders and choosing an appropriate strategic mechanism to drive platform growth.Originality/valueThis study is one of the first to empirically explain how firms in a sharing economy sector could gain platform loyalty by adopting an expectation–confirmation theory perspective.

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