558 research outputs found

    Asymmetric Information Mitigation in Supply Chain: A Systematic Literature Review

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    With the level of competition and consumer demand is changing rapidly, the speed and accuracy of the information flow in the supply chain increasingly necessary. Sharing of information between the parties in a supply chain plays an important role in improving the sustainability of a business, but imperfection information is inevitable because each party in the supply chain has a different objective. This condition increases the importance of a research on the mitigation of asymmetric information in the supply chain, therefore the purpose of this study was to conduct a review of previous studies related to overcoming the asymmetric information and map research trend on mitigating asymmetric information in the supply chain. We used systematic literature review (SLR) methods to analyze the data collected from Web of Science and Scopus database from 2005 to 2016. The results of this study can be used as a guide and a reference for further research related to overcoming the asymmetry of information in the supply chain in every industrial sector

    Opportunities for the digital transformation of the banana sector supply chain based on software with artificial intelligence

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    Artificial intelligence offers great opportunities for the supply chain, being this a competitive advantage for today’s changing market. This article aims to identify the impacts and opportunities that artificial intelligence software can offer to facilitate the operation and improve the performance of the supply chain in the banana sector in Colombia. The work methodology consists of six steps in which a total of 72 investigations were obtained. The sources of information were four databases. As a main conclusion, the supply chain of the banana sector has everything necessary for intelligent software based solutions to be implemented in order to achieve adaptation, flexibility and sensitivity to the context and domain of execution

    Dynamic Pricing for Managing Product Selling on Fruit Supply Chain Management

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    Recently fresh fruit sector is grown not only due to increasing of demand that spirited by healthy lifestyle but also requirement of quality food should be eaten daily. Its complexity make many research considered fruit in certain supply chain, called as Fruit Supply Chain (FSC). In FSC, customers tend to purchase products with a longer remaining lifetime and avoid the ones which give aging signal. Customer willingness to pay decreases once the product start to be deteriorated, which may cause slower demand for aging fruits. Consequently, retailers should enable discounted price for aging fruits products to retain or improve demand rate. Hence, a solution of this is creating price that dynamically following the condition of goods. This research establishes pricing scheme, which is dynamic pricing to FSC. Main purpose of this research is explaining how to maximize supply chain profit by applying dynamic pricing. Remind that there is deterioration that does exist on FSC product and its customer preferences, dynamic pricing will be close to the real life particularly applied by FSC players. A set of mathematical model is optimized on this research. It addresses dynamic pricing for FSC players to achieve better profitability. The result proves that dynamic pricing is urgent to be done. In order to avoid unsold product due to became deteriorated, FSC players can separate selling period into three periods, which are forward buying period, normal price period, and markdown price period. Moreover, there are several parameters involved on optimization has different impact on FSC profitability, where it should be thoroughly focused on by FSC players collaboratively

    Agribusiness supply chain risk management: A review of quantitative decision models

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    Supply chain risk management is a large and growing field of research. However, within this field, mathematical models for agricultural products have received relatively little attention. This is somewhat surprising as risk management is even more important for agricultural supply chains due to challenges associated with seasonality, supply spikes, long supply lead-times, and perishability. This paper carries out a thorough review of the relatively limited literature on quantitative risk management models for agricultural supply chains. Specifically, we identify robustness and resilience as two key techniques for managing risk. Since these terms are not used consistently in the literature, we propose clear definitions and metrics for these terms; we then use these definitions to classify the agricultural supply chain risk management literature. Implications are given for both practice and future research on agricultural supply chain risk management

    Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models

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    This is an Author's Accepted Manuscript of an article published in [include the complete citation information for the final version of the article as published in the International Journal of Production Research (2018) © Taylor & Francis, available online at: http://doi.org/10.1080/00207543.2018.1447706[EN] Agri-food sector performance strongly impacts global economy, which means that developing optimisation models to support the decision-making process in agri-food supply chains (AFSC) is necessary. These models should contemplate AFSC¿s inherent characteristics and sources of uncertainty to provide applicable and accurate solutions. To the best of our knowledge, there are no conceptual frameworks available to design AFSC through mathematical programming modelling while considering their inherent characteristics and sources of uncertainty, nor any there literature reviews that address such characteristics and uncertainty sources in existing AFSC design models. This paper aims to fill these gaps in the literature by proposing such a conceptual framework and state of the art. The framework can be used as a guide tool for both developing and analysing models based on mathematical programming to design AFSC. The implementation of the framework into the state of the art validates its. Finally, some literature gaps and future research lines were identified.This first author was partially supported by the Programme of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport [grant number FPU15/03595]; the partial support of Project 'Development of an integrated maturity model for agility, resilience and gender perspective in supply chains (MoMARGE). Application to the agricultural sector.' Ref. GV/2017/025, funded by the Generalitat Valenciana. The other authors acknowledge the partial support of 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, A.; Alemany Díaz, MDM.; Ortiz Bas, Á. (2018). Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models. International Journal of Production Research. 56(13):4418-4446. https://doi.org/10.1080/00207543.2018.1447706S44184446561

    A rolling horizon simulation approach for managing demand with lead time variability

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    [EN] This paper proposes a rolling horizon (RH) approach to deal with management problems under dynamic demand in planning horizons with variable lead times using system dynamics (SD) simulation. Thus, the nature of dynamic RH solutions entails no inconveniences to contemplate planning horizons with unpredictable demands. This is mainly because information is periodically updated and replanning is done in time. Therefore, inventory and logistic costs may be lower. For the first time, an RH is applied for demand management with variable lead times along with SD simulation models, which allowed the use of lot-sizing techniques to be evaluated (Wagner-Whitin and Silver-Meal). The basic scenario is based on a real-world example from an automotive single-level SC composed of a first-tier supplier and a car assembler that contemplates uncertain demands while planning the RH and 216 subscenarios by modifying constant and variable lead times, holding costs and order costs, combined with lot-sizing techniques. Twenty-eight more replications comprising 504 new subscenarios with variable lead times are generated to represent a relative variation coefficient of the initial demand. We conclude that our RH simulation approach, along with lot-sizing techniques, can generate more sustainable planning results in total costs, fill rates and bullwhip effect terms.This work was supported by the European Commission Horizon 2020 project Diverfarming [grant number 728003].Campuzano Bolarin, F.; Mula, J.; Díaz-Madroñero Boluda, FM.; Legaz-Aparicio, Á. (2020). A rolling horizon simulation approach for managing demand with lead time variability. 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    Supply Chain Management and Management Science: A Successful Marriage

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    The last century has witnessed extant studies on the applications of Management Science (MS) to a diverse set of Supply Chain Management (SCM) issues. This paper provides an overview of the contribution of MS within SCM. A framework is developed in this paper with a sampling of MS contributions to major SCM dimensions. Future research directions are presented

    Supply Chain

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    Traditionally supply chain management has meant factories, assembly lines, warehouses, transportation vehicles, and time sheets. Modern supply chain management is a highly complex, multidimensional problem set with virtually endless number of variables for optimization. An Internet enabled supply chain may have just-in-time delivery, precise inventory visibility, and up-to-the-minute distribution-tracking capabilities. Technology advances have enabled supply chains to become strategic weapons that can help avoid disasters, lower costs, and make money. From internal enterprise processes to external business transactions with suppliers, transporters, channels and end-users marks the wide range of challenges researchers have to handle. The aim of this book is at revealing and illustrating this diversity in terms of scientific and theoretical fundamentals, prevailing concepts as well as current practical applications
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