10,669 research outputs found

    Research Directions in Information Systems for Humanitarian Logistics

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    This article systematically reviews the literature on using IT (Information Technology) in humanitarian logistics focusing on disaster relief operations. We first discuss problems in humanitarian relief logistics. We then identify the stage and disaster type for each article as well as the article’s research methodology and research contribution. Finally, we identify potential future research directions

    Sustainable strategies for SMEs from traditional, regional industries: The case of Messinian Region, Greece

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    Purpose – Research questions : Products embedded in a region (such as Products of Destinated Origin / PDOs) face significant obstacles to access remote markets, even to domestic ones, since there are a number of inherent difficulties in promoting and managing, in general, such products from the point of production to the market place. This paper addresses to central research questions: ‱ how the sustainability issue relates to regional, traditional industries ‱ what are the prerequisites for sustainability and the corresponding barriers posed to regional food chains ‱ how sustainability relates to the performance of SMEs, operating in a traditional, regional industry ‱ what are the advantages of marketing sustainable products ‱ what region-based strategies could SMEs develop to transform the challenge of sustainability to opportunities ? Design/methodology/approach : Development of a conceptual constructive action framework with reference to regional conditions. Focus on SMEs that produce and/or trade products in the region of Messinia, Greece . Messinian region is well-known for traditional products such as olive oil, olives, raisins, figs, etc. A survey study includes a questionnaire that aims at measuring sustainability, market access, and supply chain performance. Direct contact has been carried out with a number of managing directors of SMEs via semi- structured interviews. Using case study protocol there will be a combination of case analysis and cross-case analysis. Expected Findings : Results will provide insights on how SMEs strategies can achieve sustainability requirements. Originality / Value : Improving know-how by unique focus on the sustainability of regional, traditional products and its effects upon supply chain performance and market access. This study has practical implications for regional-based SMEs in the design of strategies to produce sustainable competitive advantage. Moreover, sustainability has significant direct social, economic and environmental implications

    Strategic and Tactical Crude Oil Supply Chain: Mathematical Programming Models

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    Crude oil industry very fast became a strategic industry. Then, optimization of the Crude Oil Supply Chain (COSC) models has created new challenges. This fact motivated me to study the COSC mathematical programming models. We start with a systematic literature review to identify promising avenues. Afterwards, we elaborate three concert models to fill identified gaps in the COSC context, which are (i) joint venture formation, (ii) integrated upstream, and (iii) environmentally conscious design

    An application of hybrid life cycle assessment as a decision support framework for green supply chains

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    In an effort to achieve sustainable operations, green supply chain management has become an important area for firms to concentrate on due to its inherent involvement with all the processes that provide foundations to successful business. Modelling methodologies of product supply chain environmental assessment are usually guided by the principles of life cycle assessment (LCA). However, a review of the extant literature suggests that LCA techniques suffer from a wide range of limitations that prevent a wider application in real-world contexts; hence, they need to be incorporated within decision support frameworks to aid environmental sustainability strategies. Thus, this paper contributes in understanding and overcoming the dichotomy between LCA model development and the emerging practical implementation to inform carbon emissions mitigation strategies within supply chains. Therefore, the paper provides both theoretical insights and a practical application to inform the process of adopting a decision support framework based on a LCA methodology in a real-world scenario. The supply chain of a product from the steel industry is considered to evaluate its environmental impact and carbon ‘hotspots’. The study helps understanding how operational strategies geared towards environmental sustainability can be informed using knowledge and information generated from supply chain environmental assessments, and for highlighting inherent challenges in this process

    Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model

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    [EN] Lack of homogeneity in the product (LHP) appears in some production processes that confer heterogeneity in the characteristics of the products obtained. Supply chains with this issue have to classify the product in different homogeneous subsets, whose quantity is uncertain during the production planning process. This paper proposes a generic framework for reviewing in a unified way the literature about production planning models dealing with LHP uncertainty. This analysis allows the identification of similarities among sectors to transfer solutions between them and gaps existing in the literature for further research. The results of the review show: (1) sectors affected by LHP inherent uncertainty, (2) the inherent LHP uncertainty types modelled, and (3) the approaches for modelling LHP uncertainty most widely employed. Finally, we suggest a conceptual model reflecting the aspects to be considered when modelling the production planning in sectors with LHP in an uncertain environment.This research was initiated within the framework of the project funded by the Ministerio de EconomĂ­a y Competitividad [Ref. DPI2011-23597] entitled ‘Methods and models for operations planning and order management in supply chains characterised by uncertainty in production due to the lack of product uniformity’ (PLANGES-FHP) already finished. After, the project leading to this application has received funding from the European Union’s research and innovation programme under the H2020 Marie SkƂodowska-Curie Actions with the grant agreement No 691249, Project entitled ’Enhancing and implementing Knowledge based ICT solutions within high Riskand Uncertain Conditions for Agriculture Production Systems’ (RUC-APS).Mundi, I.; Alemany DĂ­az, MDM.; Poler, R.; Fuertes-Miquel, VS. (2019). Review of mathematical models for production planning under uncertainty due to lack of homogeneity: proposal of a conceptual model. International Journal of Production Research. 57(15-16):5239-5283. https://doi.org/10.1080/00207543.2019.1566665S523952835715-16Ahumada, O., Rene Villalobos, J., & Nicholas Mason, A. (2012). Tactical planning of the production and distribution of fresh agricultural products under uncertainty. Agricultural Systems, 112, 17-26. doi:10.1016/j.agsy.2012.06.002Ahumada, O., & Villalobos, J. R. (2009). Application of planning models in the agri-food supply chain: A review. European Journal of Operational Research, 196(1), 1-20. doi:10.1016/j.ejor.2008.02.014AlarcĂłn, F., Alemany, M. M. E., Lario, F. C., & Oltra, R. F. (2011). La falta de homogeneidad del producto (FHP) en las empresas cerĂĄmicas y su impacto en la reasignaciĂłn del inventario. BoletĂ­n de la Sociedad Española de CerĂĄmica y Vidrio, 50(1), 49-58. doi:10.3989/cyv.072011Albornoz, V. M., M. GonzĂĄlez-Araya, M. C. Gripe, and S. V. Rodrıguez. 2014. “A Mixed Integer Linear Program for Operational Planning in a Meat Packing Plant.” Accessed January 15, 2015. http://www.researchgate.net/profile/Victor_Albornoz/publication/268687089_A_Mixed_Integer_Linear_Program_for_Operational_Planning_in_a_Meat_Packing_Plant/links/547382bf0cf29afed60f55c7.pdf.JosĂ© Alem, D., & Morabito, R. (2012). Production planning in furniture settings via robust optimization. Computers & Operations Research, 39(2), 139-150. doi:10.1016/j.cor.2011.02.022Alemany, M. M. E., Lario, F.-C., Ortiz, A., & GĂłmez, F. (2013). Available-To-Promise modeling for multi-plant manufacturing characterized by lack of homogeneity in the product: An illustration of a ceramic case. Applied Mathematical Modelling, 37(5), 3380-3398. doi:10.1016/j.apm.2012.07.022Alemany, M., Ortiz, A., & Fuertes-Miquel, V. S. (2018). A decision support tool for the order promising process with product homogeneity requirements in hybrid Make-To-Stock and Make-To-Order environments. Application to a ceramic tile company. Computers & Industrial Engineering, 122, 219-234. doi:10.1016/j.cie.2018.05.040Alfalla-Luque, R., Medina-Lopez, C., & Dey, P. K. (2012). Supply chain integration framework using literature review. Production Planning & Control, 24(8-9), 800-817. doi:10.1080/09537287.2012.666870Al-Othman, W. B. E., Lababidi, H. M. S., Alatiqi, I. M., & Al-Shayji, K. (2008). Supply chain optimization of petroleum organization under uncertainty in market demands and prices. European Journal of Operational Research, 189(3), 822-840. doi:10.1016/j.ejor.2006.06.081Al-Shammari, A., & Ba-Shammakh, M. S. (2011). Uncertainty Analysis for Refinery Production Planning. Industrial & Engineering Chemistry Research, 50(11), 7065-7072. doi:10.1021/ie200313rAmaro, A. C. S., & Barbosa-PĂłvoa, A. P. F. D. (2009). The effect of uncertainty on the optimal closed-loop supply chain planning under different partnerships structure. Computers & Chemical Engineering, 33(12), 2144-2158. doi:10.1016/j.compchemeng.2009.06.003ARAS, N., BOYACI, T., & VERTER, V. (2004). The effect of categorizing returned products in remanufacturing. IIE Transactions, 36(4), 319-331. doi:10.1080/07408170490279561Aydin, R., Kwong, C. K., Geda, M. W., & Okudan Kremer, G. E. (2017). Determining the optimal quantity and quality levels of used product returns for remanufacturing under multi-period and uncertain quality of returns. The International Journal of Advanced Manufacturing Technology, 94(9-12), 4401-4414. doi:10.1007/s00170-017-1141-0Bakhrankova, K., Midthun, K. T., & Uggen, K. T. (2014). Stochastic optimization of operational production planning for fisheries. Fisheries Research, 157, 147-153. doi:10.1016/j.fishres.2014.03.018Banasik, A., Kanellopoulos, A., Claassen, G. D. H., Bloemhof-Ruwaard, J. 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Risk Management in the Oil Supply Chain: A CVaR Approach. Industrial & Engineering Chemistry Research, 49(7), 3286-3294. doi:10.1021/ie901265nChakraborty, M., & Chandra, M. K. (2005). Multicriteria decision making for optimal blending for beneficiation of coal: a fuzzy programming approach. Omega, 33(5), 413-418. doi:10.1016/j.omega.2004.07.005LUO, C., & RONG, G. (2009). A Strategy for the Integration of Production Planning and Scheduling in Refineries under Uncertainty. Chinese Journal of Chemical Engineering, 17(1), 113-127. doi:10.1016/s1004-9541(09)60042-2Davoli, G., Gallo, S., Collins, M., & Melloni, R. (2011). A stochastic simulation approach for production scheduling and investment planning in the tile industry. International Journal of Engineering, Science and Technology, 2(9). doi:10.4314/ijest.v2i9.64006Denizel, M., Ferguson, M., & Souza, G. (2010). Multiperiod Remanufacturing Planning With Uncertain Quality of Inputs. IEEE Transactions on Engineering Management, 57(3), 394-404. doi:10.1109/tem.2009.2024506Dong, M., Lu, S., & Han, S. (2011). Production Planning for Hybrid Remanufacturing and Manufacturing System with Component Recovery. Advances in Electrical Engineering and Electrical Machines, 511-518. doi:10.1007/978-3-642-25905-0_66Dubois, D., Fargier, H., & Fortemps, P. (2003). Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge. European Journal of Operational Research, 147(2), 231-252. doi:10.1016/s0377-2217(02)00558-1DUENYAS, I., & TSAI, C.-Y. (2000). Control of a manufacturing system with random product yield and downward substitutability. IIE Transactions, 32(9), 785-795. doi:10.1080/07408170008967438Esteso, A., Alemany, M. M. E., & Ortiz, A. (2018). Conceptual framework for designing agri-food supply chains under uncertainty by mathematical programming models. International Journal of Production Research, 56(13), 4418-4446. doi:10.1080/00207543.2018.1447706French, M. L., & LaForge, R. L. (2005). Closed-loop supply chains in process industries: An empirical study of producer re-use issues. Journal of Operations Management, 24(3), 271-286. doi:10.1016/j.jom.2004.07.012Gallo, M., R. Grisi, G. Guizzi, and E. Romano. 2009. “A Comparison of Production Policies in Remanufacturing Systems,” Proceedings of the 8th WSEAS International Conference on System Science and Simulation in Engineering, ICOSSSE ‘09, pp. 334.Goodfellow, R., & Dimitrakopoulos, R. (2017). Simultaneous Stochastic Optimization of Mining Complexes and Mineral Value Chains. Mathematical Geosciences, 49(3), 341-360. doi:10.1007/s11004-017-9680-3Graves, S. C. (2010). Uncertainty and Production Planning. Planning Production and Inventories in the Extended Enterprise, 83-101. doi:10.1007/978-1-4419-6485-4_5Grillo, H., Alemany, M. M. E., Ortiz, A., & Fuertes-Miquel, V. S. (2017). Mathematical modelling of the order-promising process for fruit supply chains considering the perishability and subtypes of products. Applied Mathematical Modelling, 49, 255-278. doi:10.1016/j.apm.2017.04.037Guan, Z., & Philpott, A. B. (2011). A multistage stochastic programming model for the New Zealand dairy industry. International Journal of Production Economics, 134(2), 289-299. doi:10.1016/j.ijpe.2009.11.003Guide, V. D. R. (2000). Production planning and control for remanufacturing: industry practice and research needs. Journal of Operations Management, 18(4), 467-483. doi:10.1016/s0272-6963(00)00034-6Gupta, V., & Grossmann, I. E. (2011). Solution strategies for multistage stochastic programming with endogenous uncertainties. Computers & Chemical Engineering, 35(11), 2235-2247. doi:10.1016/j.compchemeng.2010.11.013Gupta, S., and Z. Nan. 2006. “‘Multiperiod Planning of Refinery Operations Under Market Uncertainty,’ AIChE Annual Meeting.” Conference Proceedings.Heckmann, I., Comes, T., & Nickel, S. (2015). A critical review on supply chain risk – Definition, measure and modeling. Omega, 52, 119-132. doi:10.1016/j.omega.2014.10.004Heydari, J., & Ghasemi, M. (2018). A revenue sharing contract for reverse supply chain coordination under stochastic quality of returned products and uncertain remanufacturing capacity. Journal of Cleaner Production, 197, 607-615. doi:10.1016/j.jclepro.2018.06.206Hovelaque, V., Duvaleix-TrĂ©guer, S., & Cordier, J. (2009). Effects of constrained supply and price contracts on agricultural cooperatives. European Journal of Operational Research, 199(3), 769-780. doi:10.1016/j.ejor.2008.08.005Hsieh, S., & Chiang, C.-C. (2001). Manufacturing-to-Sale Planning Model for Fuel Oil Production. The International Journal of Advanced Manufacturing Technology, 18(4), 303-311. doi:10.1007/s001700170070Igarashi, M., de Boer, L., & Fet, A. M. (2013). What is required for greener supplier selection? A literature review and conceptual model development. Journal of Purchasing and Supply Management, 19(4), 247-263. doi:10.1016/j.pursup.2013.06.001Jamshidi, M., & Osanloo, M. (2019). Reliability analysis of production schedule in multi-element deposits under grade-tonnage uncertainty with multi-destinations for the run of mine material. International Journal of Mining Science and Technology, 29(3), 483-489. doi:10.1016/j.ijmst.2018.04.016Jin, X., Hu, S. J., Ni, J., & Xiao, G. (2013). Assembly Strategies for Remanufacturing Systems With Variable Quality Returns. IEEE Transactions on Automation Science and Engineering, 10(1), 76-85. doi:10.1109/tase.2012.2217741Jindal, A., & Sangwan, K. S. (2016). Multi-objective fuzzy mathematical modelling of closed-loop supply chain considering economical and environmental factors. Annals of Operations Research, 257(1-2), 95-120. doi:10.1007/s10479-016-2219-zJohnson, P., G. Evatt, P. Duck, and S. Howell. 2010. “The Derivation and Impact of an Optimal Cut-off Grade Regime Upon Mine Valuations,” Proceedings of the World Congress on Engineering 2010 Vol I.Junior, M. L., & Filho, M. G. (2011). Production planning and control for remanufacturing: literature review and analysis. Production Planning & Control, 23(6), 419-435. doi:10.1080/09537287.2011.561815Kamrad, B., & Ernst, R. (2001). An Economic Model for Evaluating Mining and Manufacturing Ventures with Output Yield Uncertainty. Operations Research, 49(5), 690-699. doi:10.1287/opre.49.5.690.10610Kannegiesser, M., GĂŒnther, H.-O., van Beek, P., Grunow, M., & Habla, C. (2008). Value chain management for commodities: a case study from the chemical industry. 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    Supply Chain Management Concepts Applied in the Oil & Gas Industry ñ€“ A review of literature

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    The recent trends in the oil gas has shown volatility in this market and the low oil prices has influenced this industry in a big way. The researchers and practitioners in this field have realized the importance of efficient Supply Chain Management (SCM) to have competitive edge in this industry. The dynamic nature of the supply as well as the demand has contributed to the unique challenges in managing the supply chain in this sector. The main objective of this study is to understand the application of different SCM concepts in the Oil and Gas industry. The study involved the systematic literature review of the various articles published by prominent researchers in this field in reputed journals and databases like Scopus, Web of Science (WOS). The findings have identified 52 different models of SCM which are used in the oil gas industry. This study is a contribution to the body of knowledge regarding the use of SCM concepts in oil and gas industry. Future studies can use this as a reference to understand the existing SCM concept in this industry and base their empirical study the suitability and influence of these concepts on the efficient supply chain management in Oil gas industry

    Social, environmental and economic impacts of alternative energy and fuel supply chains

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    Energy supply nowadays, being a vital element of a country’s development, has to independently meet diverse, sustainability criteria, be it economic, environmental and social. The main goal of the present research work is to present a methodological framework for the evaluation of alternative energy and fuel Supply Chains (SCs), consisting of a broad topology (representation) suggested, encompassing all the well-known energy and fuel SCs, under a unified scheme, a set of performance measures and indices as well as mathematical model development, formulated as Multi-objective Linear Programming with the extension of incorporating binary decisions as well (Multi-objective Mixed Integer-Linear programming). Basic characteristics of the current modelling approach include the adaptability of the model to be applied at different levels of energy SCs decisions, under different time frames and for multiple stakeholders. Model evaluation is carried for a set of Greek islands, located in the Aegean Archipelagos, examining both the existing energy supply options as well future, more sustainable Energy Supply Chains (ESCs) configurations. Results of the specific research work reveal the social and environmental costs which are underestimated under the traditional energy supply options' evaluation, as well as the benefits that may be produced from renewable energy based applications in terms of social security and employment

    A proposed framework for supply chain analytics using customer data

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    Thesis (PhD (Business Management))--University of Pretoria, 2022.The COVID-19 pandemic and recent geopolitical events have called for a need to re-evaluate methodologies for Supply Chain Risk management. Significant investment in supply chain technology has resulted in data being generated throughout the value chain. Customer data, specifically, is of interest in order to establish customer-centricity and an enhanced customer journey. However, the transformation of this data to insight is not obvious for some organisations. Forecasting models are typically used to inform decision-making, mitigate risks and enlighten policymakers. This thesis aims to address this challenge by proposing a set of capabilities that will enhance the integration of the supply chain network to its customer data. Given this context, two methodologies were used to address the research problem; (i) multinational petrochemicals company was considered for our case study and a web-based survey was distributed among key stakeholders at their head offices in South Africa. A structured equation model (SEM) was constructed to empirically test the proposed relationships among the constructs, specifically: People, Process and Technology capabilities; (ii) The macro-economic factors that drive customer demand also considered. Increasing crude oil prices have increased logistics costs and have incited the deglobalization of supply chain operations. A novel petroleum forecasting model is also proposed, particularly focusing on the forecasting on South Africa’s petrol and diesel consumptions. The model uses indices for Brent crude oil price (ZAR), Gross Domestic Product (GDP), Rand to Dollar exchange rate, Consumer Confidence Index (CCI) and Business Confidence Index (BCI) data as input data. Overall, this study suggests that in order to effectively serve their customers, organisations need to establish a culture of customer centricity that is underpinned by appropriate supply chain analytics techniques. The predictive model further highlights the need to establish the relationship between the organisation’s supply chain and micro and macro-economic drivers.Business ManagementPhD (Business Management)Unrestricte
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