37 research outputs found

    A multiple criteria supplier segmentation using outranking and value function methods

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    [EN] Suppliers play a key role in supply chain management which involves evaluation for supplier selection problem, as well as other complex issues that companies should take into account. The purpose of this research is to develop and test an integrated system, which allows qualifying providers and also supplier segmentation by monitoring their performance based on a multiple criteria tool for systematic decision making. This proposal consists in a general procedure to assess suppliers based mainly on exploiting all reliable databases of the company. Firstly, for each group of products, their evaluation criteria are defined collaboratively in order to determine their critical and strategic performance, which are then integrated with other criteria that are specific of the suppliers and represent relevant aspects for the company, also classified by critical and strategic dimensions. Two multiple criteria methods, compensatory and non-compensatory, are used and compared so as to point out their strengths, weaknesses and flexibility for the supplier evaluation in different contexts, which are usually relevant in the supply chain management. A value function approach is the appropriate method to qualify providers to be included in the panel of approved suppliers of the company as this process depends only on own features of the supplier. On the other hand, outranking methods such as PROMETHEE have shown greater potential and robustness to develop portfolios with suppliers that should be partners of the company, as well as to identify other types of relationships, such as long term contracts, market policies or to highlight those to be removed from their portfolio. These results and conclusions are based on an empirical research in a multinational company for food, pharmaceuticals and chemicals. This system has shown a great impact as it represents the first supplier segmentation proposal applied to industry, in which decision making not only takes into account opinions and judgements, but also integrates historical data and expert knowledge. This approach provides a robust support system to inform operative, tactical and strategic decisions, which is very relevant when applying an advanced management in practice.This research has been partially developed with the support of the Ministry of Economy and Competitiveness (Ref. ECO2011-27369) and Ministry of Education (Marina Segura, scholarship of Training Plan of University Teaching).Segura, M.; Maroto, C. (2017). A multiple criteria supplier segmentation using outranking and value function methods. Expert Systems with Applications. 69:87-100. doi:10.1016/eswa.2016.10.031S871006

    Multiple Criteria Decision Support System for Customer Segmentation using a Sorting Outranking Method

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    [EN] For companies, customer segmentation plays a key role in improving supply chain management by implementing appropriate marketing strategies. The objectives of this research are to design and validate a multicriteria model to support decision making for customer segmentation in a business to business context. First, the model based on the transactional customer behaviour is extended by a hierarchy with three main criteria: Recency, Frequency and Monetary (RFM), customer collaboration and growth rates. Customer collaboration includes quota compliance, variety of products and customer commitment to sustainability (reverse logistics and shared information). Second, the Global Local Net Flow Sorting (GLNF sorting) algorithm is implemented and validated using real company data to classify 8,157 customers of a multinational healthcare company. Third, the SILS quality indicator has been implemented and validated to assess the quality of preference-ordered customer groups and its parameters have been adapted for contexts with thousands of alternatives. The results are also compared with an alternative model based on data mining (K-means). The multicriteria system proposed allows to segment thousands of customers in ordered categories by preferences according to company strategies. The segments generated are more homogeneous, robust and understandable by managers than those from alternative methods. These advantages represent a relevant contribution to automating supply chain management while providing detailed analysis tools for decision making.Barrera, F.; Segura Maroto, M.; Maroto 脕lvarez, MC. (2024). Multiple Criteria Decision Support System for Customer Segmentation using a Sorting Outranking Method. Expert Systems with Applications. 238:1-17. https://doi.org/10.1016/j.eswa.2023.12231011723

    Multicriteria sorting method based on global and local search for supplier segmentation

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    [EN] The aim of this research is to develop a robust multicriteria method to classify suppliers into ordered cate-gories and its validation in real contexts. The proposed technique is based on a property of net flows of thePROMETHEE method and uses global and local search concepts, which are common in the optimisationfield. The results obtained are compared to those from the most cited sorting algorithm, and an empiricalvalidation and sensitivity analysis is performed using real supplier evaluation data. Furthermore, it does notrequire additional information from decision-makers as other sorting algorithms do for assigning incompa-rable or indifferent alternatives to groups. An extension of the silhouette concept from data mining is alsocontributed to measure the quality of ordered classes. Both contributions are easy to apply and integrate intodecision support systems for automated decisions in the supply chain management. Finally, this practicalapproach is also useful to classify customers and any type of alternatives or actions into ordered categories,which have an increasing number of real applications.Barrera, F.; Segura Maroto, M.; Maroto 脕lvarez, MC. (2023). Multicriteria sorting method based on global and local search for supplier segmentation. International Transactions in Operational Research. 1-27. https://doi.org/10.1111/itor.1328812

    Food market segmentation based on consumer preferences using outranking multicriteria approaches

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    [EN] Market segmentation is a key concept in marketing that groups consumers by their needs, characteristics, or purchasing behavior. The objectives of this research are to develop outranking multicriteria models based on preference ranking organization method for enrichment evaluation (PROMETHEE) in order to segment food consumers and apply them to a survey of healthy and sustainable meat. The models consider two categories of purchasing criteria; one related to product and another to the distributor process. One model generates ordered segments of consumers, while the other obtains four segments according to consumer performance in both criteria categories. An extension of FlowSort method for the sorting problems with Likert scale data is also contributed. The profile of segments shows the significance level of variables such as gender, but mainly those related to food-related lifestyles, when characterizing the consumer groups. This proposal represents a robust approach, which is useful in the effective design of marketing campaigns and policies.This research was funded by the Regional Ministry of Education, Research, Culture and Sport of the Autonomous Government of the Valencian Region, Spain, grant number AICO/2017/066: Sustainability of the food value chain from production to responsible consumption. We also thank the editors and reviewers for their suggestions on improving the paper.Casas-Rosal, JC.; Segura Maroto, M.; Maroto 脕lvarez, MC. (2023). Food market segmentation based on consumer preferences using outranking multicriteria approaches. International Transactions in Operational Research. 30(3):1537-1566. https://doi.org/10.1111/itor.129561537156630

    Sustainable Technology Supplier Selection in the Banking Sector

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    Sustainable supplier selection is a key strategic problem in supply chain management. The aim of this research is to provide a new hybrid multicriteria model for evaluating technology suppliers and validate it with a case study in the banking sector. This approach allows companies to perform qualification, selection, ranking and sorting of suppliers on a sustainable basis. Integration of several techniques is necessary to address this complex decision problem with conflicting economic, environmental and social criteria. Analytic hierarchy process (AHP) is useful for problem structuring and weighting criteria collaboratively. Multi-attribute utility theory (MAUT) is applied to obtain indicators for product quality and supplier risks, whose utility functions are derived by data-driven models that favour evaluation objectivity and transparency. Preference ranking organisation method for enrichment evaluation (PROMETHEE) is suitable for supplier selection due to its discriminant power among alternatives. Finally, FlowSort is proposed to classify suppliers into ordered groups and the outcomes are compared with results from MAUT. Results show its applicability by increasing process transparency and reducing operational risks in practice

    Improving Food Supply Chain Management by a Sustainable Approach to Supplier Evaluation

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    [EN] Increasing food supply chain sustainability means having to deal with many conflicting aspects and involves producers, several departments in distribution companies, and consumers. The objectives of this research are to develop models to solve real-world supplier evaluation problems and validate them with real data on fresh fruits in a supermarket chain. Literature review and results from a survey with managers from purchasing, logistics, and quality departments of a food distribution company are used to establish criteria, to first model the assessment of products and, second, to model supplier evaluation. A multicriteria hybrid approach is proposed, using multi-attribute utility theory (MAUT) to assess the quality of products and Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) to complete their evaluation with strategic criteria to be included in the second phase. The results allow companies to rank suppliers by product and classify them according to the main criteria categories, such as product strategy, food safety, economic, logistic, commercial, green image and corporate social responsibility. A sorting approach is also applied to obtain ordered groups of suppliers. Finally, the models proposed can form the core of a decision support system in order to create and monitor the supplier base in food distribution companies, as well as to inform sustainable decision making.This research was funded by the Regional Ministry of Education, Research, Culture and Sport of the Autonomous Government of the Valencian Region, Spain, grant number AICO/2017/066.Segura Maroto, M.; Maroto 脕lvarez, MC.; Segura Garc铆a Del R铆o, B.; Casas-Rosal, JC. (2020). Improving Food Supply Chain Management by a Sustainable Approach to Supplier Evaluation. Mathematics. 8(11):1-23. https://doi.org/10.3390/math8111952S123811Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16-24. doi:10.1016/j.ejor.2009.05.009Zimmer, K., Fr枚hling, M., & Schultmann, F. (2015). Sustainable supplier management 鈥 a review of models supporting sustainable supplier selection, monitoring and development. International Journal of Production Research, 54(5), 1412-1442. doi:10.1080/00207543.2015.1079340Aouadni, S., Aouadni, I., & Reba茂, A. (2019). A systematic review on supplier selection and order allocation problems. Journal of Industrial Engineering International, 15(S1), 267-289. doi:10.1007/s40092-019-00334-yChai, J., Liu, J. N. K., & Ngai, E. W. T. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872-3885. doi:10.1016/j.eswa.2012.12.040Chai, J., & Ngai, E. W. T. (2020). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, 140, 112903. doi:10.1016/j.eswa.2019.112903Wetzstein, A., Hartmann, E., Benton jr., W. C., & Hohenstein, N.-O. (2016). A systematic assessment of supplier selection literature 鈥 State-of-the-art and future scope. International Journal of Production Economics, 182, 304-323. doi:10.1016/j.ijpe.2016.06.022Ansari, Z. N., & Kant, R. (2017). A state-of-art literature review reflecting 15 years of focus on sustainable supply chain management. Journal of Cleaner Production, 142, 2524-2543. doi:10.1016/j.jclepro.2016.11.023Schramm, V. B., Cabral, L. P. B., & Schramm, F. (2020). Approaches for supporting sustainable supplier selection - A literature review. Journal of Cleaner Production, 273, 123089. doi:10.1016/j.jclepro.2020.123089Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98, 66-83. doi:10.1016/j.jclepro.2013.06.046Rajeev, A., Pati, R. K., Padhi, S. S., & Govindan, K. (2017). Evolution of sustainability in supply chain management: A literature review. Journal of Cleaner Production, 162, 299-314. doi:10.1016/j.jclepro.2017.05.026Demir, L., Akp谋nar, M. E., Araz, C., & Ilg谋n, M. A. (2018). A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT. Expert Systems with Applications, 114, 479-487. doi:10.1016/j.eswa.2018.07.071Diaz-Balteiro, L., Gonz谩lez-Pach贸n, J., & Romero, C. (2017). Measuring systems sustainability with multi-criteria methods: A critical review. European Journal of Operational Research, 258(2), 607-616. doi:10.1016/j.ejor.2016.08.075Thies, C., Kieckh盲fer, K., Spengler, T. S., & Sodhi, M. S. (2019). Operations research for sustainability assessment of products: A review. European Journal of Operational Research, 274(1), 1-21. doi:10.1016/j.ejor.2018.04.039Konys. (2019). Green Supplier Selection Criteria: From a Literature Review to a Comprehensive Knowledge Base. Sustainability, 11(15), 4208. doi:10.3390/su11154208Segura, M., Maroto, C., & Segura, B. (2019). Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies. Sustainability, 11(21), 5875. doi:10.3390/su11215875Memari, A., Dargi, A., Akbari Jokar, M. R., Ahmad, R., & Abdul Rahim, A. R. (2019). Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. Journal of Manufacturing Systems, 50, 9-24. doi:10.1016/j.jmsy.2018.11.002Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 62, 273-283. doi:10.1016/j.eswa.2016.06.030Chang, L., Ouzrout, Y., Nongaillard, A., Bouras, A., & Jiliu, Z. (2014). Multi-criteria decision making based on trust and reputation in supply chain. International Journal of Production Economics, 147, 362-372. doi:10.1016/j.ijpe.2013.04.014Ekici, A. (2013). An improved model for supplier selection under capacity constraint and multiple criteria. International Journal of Production Economics, 141(2), 574-581. doi:10.1016/j.ijpe.2012.09.013Lin, R.-H. (2012). An integrated model for supplier selection under a fuzzy situation. International Journal of Production Economics, 138(1), 55-61. doi:10.1016/j.ijpe.2012.02.024Amid, A., Ghodsypour, S. H., & O鈥橞rien, C. (2011). A weighted max鈥搈in model for fuzzy multi-objective supplier selection in a supply chain. International Journal of Production Economics, 131(1), 139-145. doi:10.1016/j.ijpe.2010.04.044Chen, Y.-J. (2011). Structured methodology for supplier selection and evaluation in a supply chain. Information Sciences, 181(9), 1651-1670. doi:10.1016/j.ins.2010.07.026Zeydan, M., 脟olpan, C., & 脟obano臒lu, C. (2011). A combined methodology for supplier selection and performance evaluation. Expert Systems with Applications, 38(3), 2741-2751. doi:10.1016/j.eswa.2010.08.064艦en, C. G., Bara莽l谋, H., 艦en, S., & Ba艧l谋gil, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Applications, 36(3), 5272-5283. doi:10.1016/j.eswa.2008.06.070Bottani, E., & Rizzi, A. (2008). An adapted multi-criteria approach to suppliers and products selection鈥擜n application oriented to lead-time reduction. International Journal of Production Economics, 111(2), 763-781. doi:10.1016/j.ijpe.2007.03.012Segura, M., & Maroto, C. (2017). A multiple criteria supplier segmentation using outranking and value function methods. Expert Systems with Applications, 69, 87-100. doi:10.1016/j.eswa.2016.10.031Trapp, A. C., & Sarkis, J. (2016). Identifying Robust portfolios of suppliers: a sustainability selection and development perspective. Journal of Cleaner Production, 112, 2088-2100. doi:10.1016/j.jclepro.2014.09.062Araz, C., & Ozkarahan, I. (2007). Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. International Journal of Production Economics, 106(2), 585-606. doi:10.1016/j.ijpe.2006.08.008Boran, F. E., Gen莽, S., Kurt, M., & Akay, D. (2009). A multi-criteria intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363-11368. doi:10.1016/j.eswa.2009.03.039Zopounidis, C., & Doumpos, M. (2002). Multicriteria classification and sorting methods: A literature review. European Journal of Operational Research, 138(2), 229-246. doi:10.1016/s0377-2217(01)00243-0Brans, J. P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The Promethee method. European Journal of Operational Research, 24(2), 228-238. doi:10.1016/0377-2217(86)90044-5Nemery, P., & Lamboray, C. (2007). 鈩眑ow S\mathcal{S} ort: a flow-based sorting method with limiting or central profiles. TOP, 16(1), 90-113. doi:10.1007/s11750-007-0036-xLau, H., Nakandala, D., & Shum, P. K. (2018). A business process decision model for fresh-food supplier evaluation. Business Process Management Journal, 24(3), 716-744. doi:10.1108/bpmj-01-2016-0015D-Sight CDM http://www.d-sight.com/solutions/d-sight-cdmNemery, P., Lidouh, K., & Mareschal, B. (2011). On the usefulness of taking the weights into account in the GAIA visualisations. International Journal of Information and Decision Sciences, 3(3), 228. doi:10.1504/ijids.2011.041585Nemery, P., Ishizaka, A., Camargo, M., & Morel, L. (2012). Enriching descriptive information in ranking and sorting problems with visualizations techniques. Journal of Modelling in Management, 7(2), 130-147. doi:10.1108/17465661211242778Xu, Z. (2000). On consistency of the weighted geometric mean complex judgement matrix in AHP. European Journal of Operational Research, 126(3), 683-687. doi:10.1016/s0377-2217(99)00082-xOrtiz鈥怋arrios, M., Miranda鈥怐e la Hoz, C., L贸pez鈥怣eza, P., Petrillo, A., & De Felice, F. (2019). A case of food supply chain management with AHP, DEMATEL, and TOPSIS. Journal of Multi-Criteria Decision Analysis, 27(1-2), 104-128. doi:10.1002/mcda.169

    Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies

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    [EN] Supplier evaluation is a relevant task of supply chain management where multicriteria methods make great contributions to manufacturing industries. This is not the case in food distribution companies, which have a key role in providing safe and affordable food to society. The purpose of this research is to measure the sustainability of products and suppliers in food distribution companies through a multiple criteria approach. Firstly, the system proposed provides indicators to qualify products and assess the food quality, using the compensatory Multi-Attribute Utility Theory (MAUT) model. Secondly, these indicators are included in supplier evaluation, which takes economic, environmental, and social criteria into account. MAUT and Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE), a non-compensatory method, are used for supplier evaluation. This approach has been validated for fresh food in a supermarket chain, mainly using historical data. Partial indicators, such as food safety scores, together with global indicators of suppliers, inform the most appropriate decisions and the most appropriate relations between companies and providers. Poor performance in food safety can lead to the disqualification of some suppliers. MAUT is good for qualifying products and is easy to apply at the operational level in logistic platforms, while PROMETHEE is more suitable for supplier segmentation, as it helps to identify supplier strengths and weaknesses.This research was funded by the Regional Ministry of Education, Research, Culture and Sport of the Autonomous Government of the Valencian Region, Spain, grant number AICO/2017/066.Segura Maroto, M.; Maroto 脕lvarez, MC.; Segura Garc铆a Del R铆o, B. (2019). Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies. Sustainability. 11(21):1-18. https://doi.org/10.3390/su11215875S1181121Thies, C., Kieckh盲fer, K., Spengler, T. S., & Sodhi, M. S. (2019). Operations research for sustainability assessment of products: A review. European Journal of Operational Research, 274(1), 1-21. doi:10.1016/j.ejor.2018.04.039Diaz-Balteiro, L., Gonz谩lez-Pach贸n, J., & Romero, C. (2017). Measuring systems sustainability with multi-criteria methods: A critical review. European Journal of Operational Research, 258(2), 607-616. doi:10.1016/j.ejor.2016.08.075Zimmer, K., Fr枚hling, M., & Schultmann, F. (2015). Sustainable supplier management 鈥 a review of models supporting sustainable supplier selection, monitoring and development. International Journal of Production Research, 54(5), 1412-1442. doi:10.1080/00207543.2015.1079340Chai, J., & Ngai, E. W. T. (2020). Decision-making techniques in supplier selection: Recent accomplishments and what lies ahead. Expert Systems with Applications, 140, 112903. doi:10.1016/j.eswa.2019.112903Chai, J., Liu, J. N. K., & Ngai, E. W. T. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872-3885. doi:10.1016/j.eswa.2012.12.040Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: a literature review. Journal of Cleaner Production, 98, 66-83. doi:10.1016/j.jclepro.2013.06.046Ansari, Z. N., & Kant, R. (2017). A state-of-art literature review reflecting 15 years of focus on sustainable supply chain management. Journal of Cleaner Production, 142, 2524-2543. doi:10.1016/j.jclepro.2016.11.023Ho, W., Xu, X., & Dey, P. K. (2010). Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. European Journal of Operational Research, 202(1), 16-24. doi:10.1016/j.ejor.2009.05.009Rajeev, A., Pati, R. K., Padhi, S. S., & Govindan, K. (2017). Evolution of sustainability in supply chain management: A literature review. Journal of Cleaner Production, 162, 299-314. doi:10.1016/j.jclepro.2017.05.026Demir, L., Akp谋nar, M. E., Araz, C., & Ilg谋n, M. A. (2018). A green supplier evaluation system based on a new multi-criteria sorting method: VIKORSORT. Expert Systems with Applications, 114, 479-487. doi:10.1016/j.eswa.2018.07.071Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 62, 273-283. doi:10.1016/j.eswa.2016.06.030Chang, L., Ouzrout, Y., Nongaillard, A., Bouras, A., & Jiliu, Z. (2014). Multi-criteria decision making based on trust and reputation in supply chain. International Journal of Production Economics, 147, 362-372. doi:10.1016/j.ijpe.2013.04.014Ekici, A. (2013). An improved model for supplier selection under capacity constraint and multiple criteria. International Journal of Production Economics, 141(2), 574-581. doi:10.1016/j.ijpe.2012.09.013Lin, R.-H. (2012). An integrated model for supplier selection under a fuzzy situation. International Journal of Production Economics, 138(1), 55-61. doi:10.1016/j.ijpe.2012.02.024Amid, A., Ghodsypour, S. H., & O鈥橞rien, C. (2011). A weighted max鈥搈in model for fuzzy multi-objective supplier selection in a supply chain. International Journal of Production Economics, 131(1), 139-145. doi:10.1016/j.ijpe.2010.04.044Chen, Y.-J. (2011). Structured methodology for supplier selection and evaluation in a supply chain. Information Sciences, 181(9), 1651-1670. doi:10.1016/j.ins.2010.07.026Zeydan, M., 脟olpan, C., & 脟obano臒lu, C. (2011). A combined methodology for supplier selection and performance evaluation. Expert Systems with Applications, 38(3), 2741-2751. doi:10.1016/j.eswa.2010.08.064艦en, C. G., Bara莽l谋, H., 艦en, S., & Ba艧l谋gil, H. (2009). An integrated decision support system dealing with qualitative and quantitative objectives for enterprise software selection. Expert Systems with Applications, 36(3), 5272-5283. doi:10.1016/j.eswa.2008.06.070Bottani, E., & Rizzi, A. (2008). An adapted multi-criteria approach to suppliers and products selection鈥擜n application oriented to lead-time reduction. International Journal of Production Economics, 111(2), 763-781. doi:10.1016/j.ijpe.2007.03.012Govindan, K., Kadzi艅ski, M., & Sivakumar, R. (2017). Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega, 71, 129-145. doi:10.1016/j.omega.2016.10.004Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49-57. doi:10.1016/j.omega.2014.11.009Rezaei, J., & Ortt, R. (2013). Multi-criteria supplier segmentation using a fuzzy preference relations based AHP. European Journal of Operational Research, 225(1), 75-84. doi:10.1016/j.ejor.2012.09.037Segura, M., & Maroto, C. (2017). A multiple criteria supplier segmentation using outranking and value function methods. Expert Systems with Applications, 69, 87-100. doi:10.1016/j.eswa.2016.10.031Bloemhof, J. M., & Soysal, M. (2016). Sustainable Food Supply Chain Design. Springer Series in Supply Chain Management, 395-412. doi:10.1007/978-3-319-29791-0_18Grimm, J. H., Hofstetter, J. S., & Sarkis, J. (2014). Critical factors for sub-supplier management: A sustainable food supply chains perspective. International Journal of Production Economics, 152, 159-173. doi:10.1016/j.ijpe.2013.12.011Lau, H., Nakandala, D., & Shum, P. K. (2018). A business process decision model for fresh-food supplier evaluation. Business Process Management Journal, 24(3), 716-744. doi:10.1108/bpmj-01-2016-0015Beske, P., Land, A., & Seuring, S. (2014). Sustainable supply chain management practices and dynamic capabilities in the food industry: A critical analysis of the literature. International Journal of Production Economics, 152, 131-143. doi:10.1016/j.ijpe.2013.12.026Schmitt, E., Galli, F., Menozzi, D., Maye, D., Touzard, J.-M., Marescotti, A., 鈥 Brunori, G. (2017). Comparing the sustainability of local and global food products in Europe. Journal of Cleaner Production, 165, 346-359. doi:10.1016/j.jclepro.2017.07.039Behzadian, M., Kazemzadeh, R. B., Albadvi, A., & Aghdasi, M. (2010). PROMETHEE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200(1), 198-215. doi:10.1016/j.ejor.2009.01.021The PROMETHEE Bibliographical Databasehttp://www.promethee-gaia.net/bibliographical-database.htmlChen, Y.-H., Wang, T.-C., & Wu, C.-Y. (2011). Strategic decisions using the fuzzy PROMETHEE for IS outsourcing. Expert Systems with Applications, 38(10), 13216-13222. doi:10.1016/j.eswa.2011.04.137Araz, C., & Ozkarahan, I. (2007). Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. International Journal of Production Economics, 106(2), 585-606. doi:10.1016/j.ijpe.2006.08.008Dulmin, R., & Mininno, V. (2003). Supplier selection using a multi-criteria decision aid method. Journal of Purchasing and Supply Management, 9(4), 177-187. doi:10.1016/s1478-4092(03)00032-3Seuring, S. (2013). A review of modeling approaches for sustainable supply chain management. Decision Support Systems, 54(4), 1513-1520. doi:10.1016/j.dss.2012.05.053Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2014). Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 233(2), 299-312. doi:10.1016/j.ejor.2013.09.032Xu, Z. (2000). On consistency of the weighted geometric mean complex judgement matrix in AHP. European Journal of Operational Research, 126(3), 683-687. doi:10.1016/s0377-2217(99)00082-xKonys. (2019). Green Supplier Selection Criteria: From a Literature Review to a Comprehensive Knowledge Base. Sustainability, 11(15), 4208. doi:10.3390/su11154208D-Sight CDMhttp://www.d-sight.com/solutions/d-sight-cd

    Multicriteria sorting method based on global and local search for supplier segmentation

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    The aim of this research is to develop a robust multicriteria method to classify suppliers into ordered categories and its validation in real contexts. The proposed technique is based on a property of net flows of the PROMETHEE method and uses global and local search concepts, which are common in the optimisation field. The results obtained are compared to those from the most cited sorting algorithm, and an empirical validation and sensitivity analysis is performed using real supplier evaluation data. Furthermore, it does not require additional information from decision-makers as other sorting algorithms do for assigning incomparable or indifferent alternatives to groups. An extension of the silhouette concept from data mining is also contributed to measure the quality of ordered classes. Both contributions are easy to apply and integrate into decision support systems for automated decisions in the supply chain management. Finally, this practical approach is also useful to classify customers and any type of alternatives or actions into ordered categories, which have an increasing number of real applications

    Sustainable Forest Management in a Mediterranean region: Social preferences

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    Forest Systems is an Open Access Journal. All articles are distributed under the terms of the Creative Commons Attribution License (CC by-nc/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.[EN] Aim of study: There is a lack of empirical research that deals with sustainable forest management in Mediterranean regions, among the most vulnerable ecosystems. The main purpose of this work is to define the strategic criteria and objectives for sustainable forest management and aggregate the preferences of stakeholders in a Mediterranean region, using AHP and Goal Programming. Area of study: Valencian Community (Spain). Material and Methods: Firstly, we identified forest stakeholders and structured a decision hierarchy. Then a workshop was carried out to test and validate the proposed criteria and objectives, as well as a survey to determine social preferences. Secondly, another survey was conducted amongst experts to prioritize action plans. Main results: Stakeholders preferences gave the greatest importance to the environmental criteria (hydrological regulation and erosion, climate change mitigation and biodiversity) with an average weight of 40%. Social criteria (employment, recreational activities and landscape) had a weight of 38% and 22% the economic criteria case (wood, hunting and fishing, livestock, renewable energies, rural tourism and mining). The results showed that new products and services such as tourism, renewable energies, landscape, hydrological regulation and erosion control, biodiversity or climate change mitigation are very relevant objectives. We also prioritized action plans comparing them with the distribution of the administration budget. Research highlights: The environmental and social criteria are much more important than the economic ones in the regional planning of the Mediterranean forest, regardless of the method used to aggregate the social preferences and if the forest is public or private.The authors acknowledge the support received from the Ministry of Science and Innovation through the research projects Ref. ECO2008-05895-C02-01/ECON and ECO2011-27369, as well as the time and expert judgments from all the stakeholders involved in workshop and surveys we have carried out.Maroto 脕lvarez, MC.; Segura Maroto, M.; Ginestar Peiro, CM.; Uriol Batuecas, J.; Segura Garc铆a Del R铆o, B. (2013). Sustainable Forest Management in a Mediterranean region: Social preferences. Forest Systems. 22(3):546-558. https://doi.org/10.5424/fs/2013223-04135S54655822

    Preferencias y rendimiento de los alumnos en el aprendizaje de Investigaci贸n Operativa con videos

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    [EN] The increasing supply of videos as an online resource has changed the performance of students who study degrees based on face-to-face learning. The objectives of this paper are to elicit current preferences for different types of learning resources, especially videos, developed to teach Operations Research in Business Administration and Management degree, as well as analysing the relation between the videos use and students鈥 performance. The methodology is based on a survey using the Likert scale and the multicriteria method AHP. While all available resources are used to learn the subject, the results show a predominant preference for exam answers and videos, although more than one third of the students also use books and slides. Detailed exam answers improve learning and decrease tutorial appointments. There are significant differences in the use of learning resources among groups and resources affect students鈥 behaviour and performance. The videos with teaching modules decrease face-to-face class attendance, while the videos with interactive case studies affect performance positively. Therefore, we think that moving forward in this line would improve effective learning.[ES] La creciente oferta de videos como recurso online ha modificado el comportamiento de los alumnos que cursan titulaciones con docencia presencial. Los objetivos de este trabajo son cuantificar las preferencias actuales por los diversos tipos de materiales, y en particular los videos, elaborados para la docencia de Investigaci贸n Operativa en el Grado en Administraci贸n y Direcci贸n de Empresas, as铆 como analizar la relaci贸n entre el uso de videos y el rendimiento de los alumnos. La metodolog铆a se basa en una encuesta con la escala de Likert y la t茅cnica AHP. Si bien todos los recursos disponibles se utilizan para preparar la materia, los resultados muestran una preferencia mayoritaria por los ex谩menes resueltos y videos, aunque m谩s de un tercio de los alumnos tambi茅n utilizan libros y presentaciones. Los ex谩menes resueltos mejoran el aprendizaje y reducen las tutor铆as. Se han encontrado diferencias significativas en el uso de los recursos por grupo y los medios utilizados tambi茅n afectan al comportamiento y al rendimiento de los alumnos. Los videos con unidades did谩cticas reducen la asistencia a clase presencial, mientras que los videos de casos pr谩cticos interactivos afectan positivamente al rendimiento. Por tanto, creemos que avanzar en esta 煤ltima l铆nea mejorar铆a el aprendizaje efectivo.Segura Maroto, M.; Maroto 脕lvarez, MC.; Ginestar Peiro, CDM.; Navarro Cerd谩n, JR. (2018). Preferencias y rendimiento de los alumnos en el aprendizaje de Investigaci贸n Operativa con videos. En IN-RED 2018. IV Congreso Nacional de Innovaci贸n Educativa y Docencia en Red. Editorial Universitat Polit猫cnica de Val猫ncia. 126-140. https://doi.org/10.4995/INRED2018.2018.862112614
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