Religious Experience and the Modernist Novel

Output Type: Book Revie

Conceptual Framework for Managing Uncertainty in a Collaborative Agri-Food Supply Chain Context

[EN] Agri-food supply chains are subjected to many sources of uncertainty. If these uncertainties are not managed properly, they can have a negative impact on the agri-food supply chain (AFSC) performance, its customers, and the environment. In this sense, collaboration is proposed as a possible solution to reduce it. For that, a conceptual framework (CF) for managing uncertainty in a collaborative context is proposed. In this context, this paper seeks to answer the following research questions: What are the existing uncertainty sources in the AFSCs? Can collaboration be used to reduce the uncertainty of AFSCs? Which elements can integrate a CF for managing uncertainty in a collaborative AFSC? The CF proposal is applied to the weather source of uncertainty in order to show its applicability.The first author acknowledges the partial support of the Program of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport (FPU15/03595). The other authors acknowledge the partial support of the Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems, funded by the EU under its funding scheme H2020-MSCA-RISE-2015.Esteso-Álvarez, A.; Alemany Díaz, MDM.; Ortiz Bas, Á. (2017). Conceptual Framework for Managing Uncertainty in a Collaborative Agri-Food Supply Chain Context. IFIP Advances in Information and Communication Technology. 506:715-724. https://doi.org/10.1007/978-3-319-65151-4_64S715724506Taylor, D.H., Fearne, A.: Towards a framework for improvement in the management of demand in agri-food supply chains. Supply Chain Manag. Int. J. 11, 379–384 (2006)Matopoulos, A., Vlachopoulou, M., Manthou, V., Manos, B.: A conceptual framework for supply chain collaboration: empirical evidence from the agri-food industry. Supply Chain Manag. Int. J. 12, 177–186 (2007)Ahumada, O., Villalobos, J.R.: Application of planning models in the agri-food supply chain: a review. Eur. J. Oper. Res. 196, 1–20 (2009)Tsolakis, N.K., Keramydas, C.A., Toka, A.K., Aidonis, D.A., Iakovou, E.T.: Agrifood supply chain management: a comprehensive hierarchical decision-making framework and a critical taxonomy. Biosyst. Eng. 120, 47–64 (2014)van der Vorst, J.G., Da Silva, C.A., Trienekens, J.H.: Agro-industrial supply chain management: Concepts and applications. FAO (2007)Borodin, V., Bourtembourg, J., Hnaien, F., Kabadie, N.: Handling uncertainty in agricultural supply chain management: a state of the art. Eur. J. Oper. Res. 254, 348–359 (2016)van der Vorst, J.G.A.J., Beulens, A.J.M.: Identifying sources of uncertainty to generate supply chain redesign strategies. Int. J. Phys. Distrib. Logist. Manag. 32, 409–430 (2000)Klosa, E.: A concept of models for supply chain speculative risk analysis and management. J. Econ. Manag. 12, 45–59 (2013)Samson, S., Reneke, J.A., Wiecek, M.M.: A review of different perspectices on uncertainty and risk and an alternative modeling paradigm. Reliab. Eng. Syst. Saf. 94, 558–567 (2009)Backus, G.B.C., Eidman, V.R., Dijkhuizen, A.A.: Farm decision making under risk and uncertainty. Neth. J. Agric. Sci. 45, 307–328 (1997)van der Vorst, J.G.: Effective food supply chains; Generating, modelling and evaluating supply chain scenarios. (2000)Amorim, P., Günther, H.O., Almada-Lobo, B.: Multi-objective integrated production and distribution planning of perishable products. Int. J. Prod. Econ. 138, 89–101 (2012)Amorim, P., Meyr, H., Almeder, C., Almada-Lobo, B.: Managing perishability in production-distribution planning: a discussion and review. Flex. Serv. Manuf. 25, 389–413 (2013)Costa, C., Antonucci, F., Pallottino, F., Aguzzi, J., Sarria, D., Menesatti, P.: A review on agri-food supply chain traceability by means of RFID technology. Food Bioprocess Technol. 6, 353–366 (2013)Pahl, J., Voss, S.: Integrating deterioration and lifetime constraints in production and supply chain planning: a survey. Eur. J. Oper. Res. 238, 654–674 (2014)Grillo, H., Alemany, M.M.E., Ortiz, A.: A review of Mathematical models for supporting the order promising process under Lack of Homogeneity in product and other sources of uncertainty. Comput. Ind. Eng. 91, 239–261 (2016)Zwietering, M.H., van’t Riet, K.: Modelling of the quality of food: optimization of a cooling chain. In: Management Studies and the Agri-business: Management of Agri-chains, Wageningen, The Netherlands, pp. 108–117 (1994)Akkerman, R., Farahani, P., Grunow, M.: Quality, safety and sustainability in food distribution: a review of quantitative operations management approaches and challenges. Spectrum 32, 863–904 (2010)Apaiah, R.K., Hendrix, E.M.T., Meerdink, G., Linnemann, A.R.: Qualitative methodology for efficient food chain design. Trends Food Sci. Technol. 16, 204–214 (2005)Lehmann, R.J., Reiche, R., Schiefer, G.: Future internet and the agri-food sector: State-of-the-art in literature and research. Comput. Electron. Agric. 89, 158–174 (2012)Kusumastuti, R.D., van Donk, D.P., Teunter, R.: Crop-related harvesting and processing planning: a review. Int. J. Prod. Econ. 174, 76–92 (2016)Dreyer, H.C., Strandhagen, J.O., Hvolby, H.H., Romsdal, A., Alfnes, E.: Supply chain strategies for speciality foods: a Norwegian case study. Prod. Plan. Control 27, 878–893 (2016)Baghalian, A., Rezapour, S., Farahani, R.Z.: Robust supply chain network design with service level against disruptions and demand uncertainties: a real-life case. Eur. J. Oper. Res. 227, 199–215 (2013)Aggarwal, S., Srivastava, M.K.: Towards a grounded view of collaboration in Indian agri-food supply chains: a qualitative investigation. Br. Food J. 115, 1085–1106 (2016)Teimoury, E., Nedaei, H., Ansari, S., Sabbaghi, M.: A multi-objective analysis for import quota policy making in a perishable fruit and vegetable supply chain: a system dynamics approach. Comput. Electron. Agric. 93, 37–45 (2013)Opara, L.U.: Traceability in agriculture and food supply chain: a review of basic concepts, technological implications, and future prospects. J. Food Agric. Environ. 1, 101–106 (2003)Kruize, J.W., Wolfert, S., Goense, D., Scholten, H., Beulens, A., Veenstra, T.: Integrating ICT applications for farm business collaboration processes using Fl Space. In: 2014 Annual SRII Global Conference, pp. 232–240. IEEE (2014)Oriade, C.A., Dillon, C.R.: Developments in biophysical and bioeconomic simulation of agricultural systems: a review. Agric. Econ. 17, 45–58 (1997)Camarinha-Matos, L.M., Afsarmanesh, H.: Collaborative networks: value creation in a knowledge society. In: Wang, Kesheng, Kovacs, G.L., Wozny, Michael, Fang, Minglun (eds.) PROLAMAT 2006. IIFIP, vol. 207, pp. 26–40. Springer, Boston, MA (2006). doi: 10.1007/0-387-34403-9_4Prima Dania, W.A., Xing, K., Amer, Y.: Collaboration and sustainable agri-food supply chain: a literature review. MATEC Web Conf. 58 (2016)Simatupang, T.M., Sridharan, R.: The collaborative index: a measure for supply chain collaboration. Int. J. Phys. Distrib. Logist. Manag. 35, 44–62 (2005)Fischer, C., Hartmann, M., Reynolds, N., Leat, P., Revoredo-Giha, C., Henchion, M., Albisu, L.M., Gracia, A.: Factors influencing contractual choice and sustainable relationships in European agri-food supply chains. Eur. Rev. Agric. Econ. 36, 541–569 (2009

Research Challenges in Municipal Solid Waste Logistics Management

During the last two decades, EU legislation has put increasing pressure on member countries to achieve specified recycling targets for municipal household waste. These targets can be obtained in various ways choosing collection methods, separation methods, decentral or central logistic systems etc. This paper compares municipal solid waste (MSW) management practices in various EU countries to identify the characteristics and key issues from a waste management and reverse logistics point of view. Further, we investigate literature on modelling municipal solid waste logistics in general. Comparing issues addressed in literature with the identified issues in practice result in a research agenda for modelling municipal solid waste logistics in Europe. We conclude that waste recycling is a multi-disciplinary problem that needs to be considered at different decision levels simultaneously. A holistic view and taking into account the characteristics of different waste types are necessary when modelling a reverse supply chain for MSW recycling

Designing New Supply Chain Networks: Tomato and Mango Case Studies

Consumers expect product availability as well as product quality and safety in retail outlets. When designing or re-designing fruit and vegetables supply chain networks one has to take these demands into consideration next to traditional efficiency and responsiveness requirements. In food science literature, much attention has been paid to the development of Time-Temperature Indicators to monitor individually the temperature conditions of food products throughout distribution as well as quality decay models that are able to predict product quality based upon this information. This chapter discusses opportunities to improve the design and management of fruit and vegetables supply chain networks. If product quality in each step of the supply chain can be predicted in advance, good flows can be controlled in a pro-active manner and better chain designs can be established resulting in higher product availability, higher product quality, and less product losses in retail. This chapter works towards a preliminary diagnostic instrument, which can be used to assess supply chain networks on QCL (Quality Controlled Logistics). Findings of two exploratory case studies, one on the tomato chain and one on the mango chain, are presented to illustrate the value of this concept. Results show the opportunities and bottlenecks for quality controlled logistics depend on product—(e.g. variability in quality), process—(e.g. ability to use containers and sort on quality), network- (e.g. current level of cooperation), and market characteristics (e.g. higher prices for better products)