Quantifying the Sustainability of Products and Suppliers in Food Distribution Companies

[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 Álvarez, MC.; Segura García Del Río, 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., Kieckhäfer, 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., González-Pachón, 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., Fröhling, M., & Schultmann, F. (2015). Sustainable supplier management – 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., Akpınar, M. E., Araz, C., & Ilgın, 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’Brien, C. (2011). A weighted max–min 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., Çolpan, C., & Çobanoğlu, C. (2011). A combined methodology for supplier selection and performance evaluation. Expert Systems with Applications, 38(3), 2741-2751. doi:10.1016/j.eswa.2010.08.064Şen, C. G., Baraçlı, H., Şen, S., & Başlıgil, 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—An application oriented to lead-time reduction. International Journal of Production Economics, 111(2), 763-781. doi:10.1016/j.ijpe.2007.03.012Govindan, K., Kadziński, 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., … 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

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

[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 Álvarez, MC.; Segura García Del Río, 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., Fröhling, M., & Schultmann, F. (2015). Sustainable supplier management – 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., & Rebaï, 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 – 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., Akpınar, M. E., Araz, C., & Ilgın, 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., González-Pachón, 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., Kieckhäfer, 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’Brien, C. (2011). A weighted max–min 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., Çolpan, C., & Çobanoğlu, C. (2011). A combined methodology for supplier selection and performance evaluation. Expert Systems with Applications, 38(3), 2741-2751. doi:10.1016/j.eswa.2010.08.064Şen, C. G., Baraçlı, H., Şen, S., & Başlıgil, 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—An 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., Genç, 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). ℱlow $\mathcal{S}$ 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‐Barrios, M., Miranda‐De la Hoz, C., López‐Meza, 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

A regional information-based multi-attribute and multi-objective decision-making approach for sustainable supplier selection and order allocation

Although extant studies proposed various models and frameworks for sustainable supplier selection problems, they paid limited attention to the incorporation of regional economic, social, and environmental factors simultaneously for global supply chain design due to the difficulty in reflecting varies dimensions of the global business environment and their associated risk in a decision model. Existing supplier selection models also tend to focus on the formulation of a simplified supply chain structure rather than considering more realistic supply chain operations under multiple sourcing and product designs. To facilitate the complex decision-making process of global supplier selection problems, this study proposes an integrated approach that consists of two phases to effectively reflect the multi-perspectives of global supply chain design for sustainability. The first phase identifies sustainable supplier regions through multi-attribute utility theory, considering four regional sustainability indices for economic and social factors in global business and logistics, to reflect the decision maker\u27s risk attitudes on global business opportunities. In the second phase, a multi-objective integer linear programming model for multiple sourcing and multiple product designs that minimizes economic and environmental objectives is applied to find optimal suppliers in the regions selected from the first phase and their order quantities. The proposed approach is illustrated through a bicycle supplier selection case study. The results show that the multi-objective sustainable decision under a multiple sourcing strategy for different product designs leads to a supply chain that is significantly different from the single-objective non-sustainable decisions. The case study under different decision scenarios shows that a decision maker should hold a balanced perspective under the multi-objective decision environment for sustainable supply chain design

Supplier evaluation and selection in fuzzy environments: a review of MADM approaches

In past years, the multi-attribute decision-making (MADM) approaches have been extensively applied by researchers to the supplier evaluation and selection problem. Many of these studies were performed in an uncertain environment described by fuzzy sets. This study provides a review of applications of MADM approaches for evaluation and selection of suppliers in a fuzzy environment. To this aim, a total of 339 publications were examined, including papers in peer-reviewed journals and reputable conferences and also some book chapters over the period of 2001 to 2016. These publications were extracted from many online databases and classified in some categories and subcategories according to the MADM approaches, and then they were analysed based on the frequency of approaches, number of citations, year of publication, country of origin and publishing journals. The results of this study show that the AHP and TOPSIS methods are the most popular approaches. Moreover, China and Taiwan are the top countries in terms of number of publications and number of citations, respectively. The top three journals with highest number of publications were: Expert Systems with Applications, International Journal of Production Research and The International Journal of Advanced Manufacturing Technology

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective