33 research outputs found

    Internet-based applications in the agri-food supply chain:a survey on the Greek canning sector

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    In the agri-food industry, Internet-based applications changed the way companies conduct business mainly by facilitating activities that were already taking place, rather by giving birth to virtual networks creation. Due to the specific characteristics of the sector, Internet's huge potential has not been fully exploited yet, still remaining a new communication tool. This paper aims at giving empirical insights regarding the use of Internet-based applications in the agri-food supply chain, by focusing on the Greek fruit canning sector. In particular, the paper identifies companies' perceptions regarding perceived benefits, constrained factors and motivation factors towards the use of Internet-based applications. Results indicate that companies recognise benefits arising from the use of Internet, however they still use traditional ways when communicating with their partners. Regarding transportation issues, while companies' overall satisfaction is rather moderate and differs significantly from the importance placed on a number of criteria, companies are still sceptical in using Electronic Transportation Marketplace

    Exploring the impact of e-business adoption on logistics processes:empirical evidence from the food industry

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    The objectives of the research were to identify factors that influence e-business adoption and its impact on logistics processes in the Greek food industry. Drawing on existing research, a conceptual framework and propositions were developed and six in depth case studies were carried out. In the framework, three major categories of influencing factors were distinguished: intra-enterprise, sector and supply chain factors. Findings suggest that e-business adoption is more affected by supply chain and sector factors, rather than intra-enterprise factors. Regarding the impact of e-business on logistics process, it seems that it is affected by the frequency of its use and it is greater in processes occurring at the company-customer interface. Finally, e-business impact is more related to the dimensions of time and quality, rather than cost improvements

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

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    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

    Incentivising Bioenergy Production: Economic and Environmental Insights from a Regional Optimization Methodology

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    In conjunction with the European Union (EU) targets, the United Kingdom (UK) Government has introduced a range of mechanisms to foster the development and deployment of low carbon energy technologies and markets. This study focuses on the three main financial incentive schemes to promote renewable energy sector in the UK for electricity, heat and fuel production from renewables, namely feed-in tariff (FiT), Renewable Heat Incentive (RHI) and Renewables Obligation Certificate (RoC), considering the fact that optimal policy design depends on effective analyses of the impacts of incentives on the performance of renewable energy systems. The effects of potential changes in these incentive schemes on the economic and environmental performance of bioenergy sector are investigated using an analytical methodology. The methodology integrates fuzzy decision making and multi objective mathematical modelling in the same framework to capture uncertainties in the system parameters as well as economic and environmental sustainability aspects. Computational experiments are performed on bioenergy production using the entire West Midlands Region in the UK as case study region. The results reveal that the changes in incentive policies have a significant impact on the profitability of the supply chain, whereas environmental performance of the supply chain in terms of total GHG emissions is the least affected performance indicator by the changes in the incentive policies

    Future business and the role of purchasing and supply management: Opportunities for ‘business-not-as-usual’ PSM research

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    The raison d'être for this article is simple: traditional ways of researching, theorizing, and practicing purchasing and supply management (PSM) are no longer sufficient to ‘meet the moment’. Scholars need to advance a “business-not-as-usual” footing approach to their work, if they are to make a meaningful contribution to addressing the current and future emergencies, as highlighted by recent extreme weather and the COVID-19 pandemic. Yet, what can this, or should this, mean for a field rooted in traditional business thinking? This article builds on the Journal of Purchasing and Supply Management's (JPSM) 25th Anniversary Special Issue editorial (2019); members of the JPSM's editorial team advance their unique perspectives on what “business-not-as-usual” means for PSM. Specifically, we advocate both thinking much more widely, in scope and ambition, than we currently do, and simultaneously building our ability to comprehend supply chains in a more nuanced and granular way. We explore whether the bias toward positivist work has omitted potentially interesting findings, and viewpoints. This leads to a call to re-think how we approach our work: should the key criteria always be to focus on theory development or testing? Should academics “think bigger”? Turning to specific research themes, illustrations of how our current thinking can be challenged or broadened by addressing the circular economy, and role of purchasing and innovation. Specifically, the focus on the PSM function as an intrapreneur within the larger organization, and the role of innovation and technology in PSM work. Taken together, we hope the ideas and arguments presented here will inform and inspire ambitious and novel approaches to PSM research with significant and enduring impact on the transformation of business

    Collaboration in multi-tier supply chains for reducing empty running: a case study in the UK retail sector

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    This research aims to explore ways to improve transport efficiency in retail multi-tier supply chains by integrating raw material sourcing of suppliers into the transport network. The performance of the proposed scenario is assessed using a discrete-event simulation (DES) model that includes the additional pick-up and drop-off points of an extended transport network. The results suggest an improvement in the transport network efficiency, evidenced in the reduction of empty running levels and costs. This study supports the idea that the integration of raw material sourcing of suppliers into a retailer's transport network can bring significant benefits

    Paths to Innovation in Supply Chains: The Landscape of Future Research

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    This chapter presents a Strategic Research and Innovation Agenda for supply chain and it is the result of an intensive work jointly performed involving a wide network of stakeholders from discrete manufacturing, process industry and logistics sector to put forward a vision to strengthen European Supply Chains for the next decade. The work is based on matching visions from literature and from experts with several iterations between desk research and workshops, focus groups and interviews. The result is a detailed analysis of the supply chain strategies identified as most relevant for the next years and definition of the related research and innovation topics as future developments and steps for the full implementation of the strategies, thus proposing innovative and cutting-edge actions to be implemented based on technological development and organisational change

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

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    [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

    A conceptual framework for crop-based agri-food supply chain characterization under uncertainty

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    [EN] Crop-based Agri-food Supply Chains (AFSCs) are complex systems that face multiple sources of uncertainty that can cause a significant imbalance between supply and demand in terms of product varieties, quantities, qualities, customer requirements, times and prices, all of which greatly complicate their management. Poor management of these sources of uncertainty in these AFSCs can have negative impact on quality, safety, and sustainability by reducing the logistic efficiency and increasing the waste. Therefore, it becomes crucial to develop models in order to deal with the key sources of uncertainty. For this purpose, it is necessary to precisely understand and define the problem under study. Even, the characterisation process of this domains is also a difficult and time-consuming task, especially when the right directions and standards are not in place. In this chapter, a Conceptual Framework is proposed that systematically collects those aspects that are relevant for an adequate crop-based AFSC management under uncertainty.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015Alemany Díaz, MDM.; Esteso, A.; Ortiz Bas, Á.; Hernández Hormazabal, JE.; Fernández, A.; Garrido, A.; Martin, J.... (2021). A conceptual framework for crop-based agri-food supply chain characterization under uncertainty. Studies in Systems, Decision and Control. 280:19-33. https://doi.org/10.1007/978-3-030-51047-3_2S1933280Taylor, D.H., Fearne, A.: Towards a framework for improvement in the management of demand in agri-food supply chains. Supply Chain Manage. 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 Manage. 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)Iakovou, E., Vlachos, D., Achillas, C., Anastasiadis, F.: A methodological framework for the design of green supply chains for the agrifood sector. Paper presented at the 2nd international conference on supply chains, Katerini, 5–7 Oct 2012Manzini, R., Accorsi, R.: The new conceptual framework for food supply chain assessment. J. Food Eng. 115, 251–263 (2013)Shukla, M., Jharkharia, S.: Agri-fresh produce supply chain management: a state-of-the-art literature review. Int. J. Oper. Prod. Manage. 33, 114–158 (2013)Lemma, Y., Kitaw, D., Gatew, G.: Loss in perishable food supply chain: an optimization approach literature review. Int. J. Sci. Eng. Res. 5, 302–311 (2014)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)Hernandez, J., Mortimer, M., Patelli, E., Liu, S., Drummond, C., Kehr, E., Calabrese, N., Iannacone, R., Kacprzyk, J., Alemany, M.M.E., Gardner, D.: RUC-APS: enhancing and implementing knowledge based ICT solutions within high risk and uncertain conditions for agriculture production systems. In: 11th International Conference on Industrial Engineering and Industrial Management, Valencia, Spain (2017)Miles, M.B., Huberman, A.M.: Qualitative Data Analysis: An Expanded Sourcebook. Sage Publications, Thousand Oaks (1994)Alemany, M.M.E., Alarcón, F., Lario, F.C., Boj, J.J.: An application to support the temporal and spatial distributed decision-making process in supply chain collaborative planning. Comput. Ind. 62, 519–540 (2011)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)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)Zhang, W., Wilhelm, W.E.: OR/MS decision support models for the specialty crops industry: a literature review. Ann. Oper. Res. 190, 131–148 (2011)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)Blanco, A.M., Masini, G., Petracci, N., Bandoni, J.A.: Operations management of a packaging plant in the fruit industry. J. Food Eng. 70, 299–307 (2005)Grillo, H., Alemany, M.M.E., Ortiz, A., Fuertes-Miquel, V.S.: Mathematical modelling of the order-promising process for fruit supply chains considering the perishability and subtypes of products. Appl. Math. Model. 49, 255–278 (2017)Verdouw, C.N., Beulens, A.J.M., Trienekens, J.H., Wolferta, J.: Process modelling in demand-driven supply chains: a reference model for the fruit industry. Comput. Electron. Agric. 73, 174–187 (2010)Amorim, P., Günther, H., Almada-Lobo, B.: Multi-objective integrated production and distribution planning of perishable products. Int. J. Prod. Econ. 138, 89–101 (2012)Nahmias, S.: Perishable inventory theory: a review. Oper. Res. 30, 680–708 (1982)Mowat, A., Collins, R.: Consumer behavior and fruit quality: supply chain management in an emerging industry. Supply Chain Manage. 5, 45–54 (2000)Kazaz, B., Webster, S.: The impact of yield-dependent trading costs on pricing and production planning under supply uncertainty. M&SOM Manuf. Serv. Oper. Manage. 13, 404–417 (2011)Van der Vorst, J.G.: Effective food supply chains: generating, modelling and evaluating supply chain scenarios (2000)Fuertes-Miquel, V.S., Cuenca, L., Boza, A., Guyon, C., Alemany, M.M.E.: Conceptual framework for the characterization of vegetable breton supply chain sustainability in an uncertain context. In: 12th International Conference on Industrial Engineering and Industrial Management, XXII Congreso de Ingeniería de Organización, Girona, Spain, 12–13 July 2018Kummu, M., de Moel, H., Porkka, M., Siebert, S., Varis, O., Ward, P.J.: Lost food, wasted resources: global food supply chain losses and their impacts on freshwater, cropland, and fertiliser use. Sci. Total Environ. 438, 477–489 (2012)Hoekstra, S., Romme, J.: Integral Logistic Structures: Developing Customer-Oriented Goods Flow. Industrial Press Inc., New York (1992)Borodin, V., Bourtembourg, J., Hnaien, F., Labadie, N.: Handling uncertainty in agricultural supply chain management: a state of the art. Eur. J. Oper. Res. 254, 348–359 (2016)Handayati, Y., Simatupang, T.M., Perdana, T.: Agri-food supply chain coordination: the state-of-the-art and recent developments. Logist. Res. 8, 1–15 (2015)Mintzberg, H.: The Structuring of Organisations. Prentice-Hall, Upper Saddle River (1979)Keuning, D.: Grondslagen Van Het Management. Stenfert Kroese, Houten (1995) (in Dutch)Esteso, A., Alemany, M.M.E., Ortiz, A.: Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models. Int. J. Prod. Res. (2018)Backus, G.B.C., Eidman, V.R., Dijkhuizen, A.A.: Farm decision making under risk and uncertainty. Neth. J. Agr. Sci. 45, 307–328 (1997)Esteso, A., Alemany, M.M.E., Ortiz, A.: Conceptual framework for managing uncertainty in a collaborative agri-food supply chain context. In: IFIP Advances in Information and Communication Technology, vol. 506, pp. 715–724 (2017)Mundi, I., Alemany, M.M.E., Poler, R., Fuertes-Miquel, V.S.: Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model. Int. J. Prod. Res. (2019)Grillo, H., Alemany, M.M.E., Ortiz, A., De Baets, B.: Possibilistic compositions and state functions: application to the order promising process for perishables. Int. J. Prod. Res. (2019)Soto-Silva, W.E., Nadal-Roig, E., González-Araya, M.C., Pla-Aragones, L.M.: Operational research models applied to the fresh fruit supply chain. Eur. J. Oper. Res. 251, 345–355 (2016)Farahani, R.Z., Rezapour, S., Drezner, T., Fallah, S.: Competitive supply chain network design: an overview of classifications, models, solution techniques and applications. Omega 45, 92–118 (2014)Banasik, A., Bloemhof-Ruwaard, J.M., Kanellopoulos, A., Claassen, G.D.H., van der Vorst, J.G.: Multi-criteria decision making approaches for green supply chains: a review. Flex. Serv. Manuf. J. 1–31 (2016)Paam, P., Berretta, R., Heydar, M., Middleton, R.H., García-Flores, R., Juliano, P.: Planning models to optimize the agri-fresh food supply chain for loss minimization: a review. In: Reference Module in Food Science (2016)Soysal, M., Bloemhof-Ruwaard, J.M., Meuwissen, M.P., van der Vorst, J.G.: A review on quantitative models for sustainable food logistics management. Int. J. Food Syst. Dyn. 3, 136–155 (2012
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