Using data envelopment analysis for supplier evaluation with environmental considerations

With the proliferation of outsourcing in global market place, supplier selection has become a key strategic consideration in forming a competitive supply chain. Supplier selection has been recognized as a multi-criteria decision making problem in which suppliers are evaluated according to multiple criteria such as price, quality, delivery and service simultaneously. Facing with excessive pressures from government and customers, increasing number of companies are beginning to consider environmental issues in the procurement and supplier selection process to practice the sustainable development. It is therefore necessary to measure a supplier’s environmental performance. This paper aims to find out what kind of environmental criteria can be applied to assess suppliers overall performances. The multicriteria decision making approach data envelopment analysis (DEA) is applied to help companies to evaluate suppliers’ various environmental performance and other capabilities simultaneously. © 2013 IEEE.published_or_final_versio

Green supplier selection problems with data scaling and production frontier estimations in a DEA model

Considering ecological issues in supplier evaluation and management alongside business considerations is getting more recognition among firms. Data envelopment analysis (DEA) is one of those methods, which is frequently suggested by the literature to support management decisions. However, the data requirements of the method should be an important consideration. The literature often addresses the issue of desirable outputs and undesirable input as an important data related problem in case of the ecological use of DEA. This paper will present a new solution to manage these data problems along with connecting the evaluation of management criteria, environmental criteria and total cost aspects. The proposed environmental supplier selection problem is an extension of a former paper. The new model examines the effect of inventory related costs, such as EOQ costs of inventory holding or ordering costs on the selected supplier, extended with newly introduced scaled values of input and output indicators. The usage of scaled values is motivated by the problem of invariance to data alteration. In addition to the uncertainty of the data, the paper looks for a functional relationship between the input and output criterion values and the efficiency that can be assigned to them using DEA

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Food Supply without Risk: Multicriteria Analysis of Institutional Conditions of Exporters

[EN] International trade in food knows no borders, hence the need for prevention systems to avoid the consumption of products that are harmful to health. This paper proposes the use of multicriteria risk prevention tools that consider the socioeconomic and institutional conditions of food exporters. We propose the use of three decision-making methods-Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS), Elimination et Choix Traduisant la Realite (ELECTRE), and Cross-Efficiency (CE)-to establish a ranking of countries that export cereals to the European Union, based on structural criteria related to the detection of potential associated risks (notifications, food quality, corruption, environmental sustainability in agriculture, and logistics). In addition, the analysis examines whether the wealth and institutional capacity of supplier countries influence their position in the ranking. The research was carried out biannually over the period from 2012-2016, allowing an assessment to be made of the possible stability of the markets. The results reveal that suppliers' rankings based exclusively on aspects related to food risk differ from importers' actual choices determined by micro/macroeconomic features (price, production volume, and economic growth). The rankings obtained by the three proposed methods are not the same, but present certain similarities, with the ability to discern countries according to their level of food risk. The proposed methodology can be applied to support sourcing strategies. In the future, food safety considerations could have increased influence in importing decisions, which would involve further difficulties for low-income countries.Ministry of Science and Innovation (Spain) and European Commission-ERDF. Project "Strengthening innovation policy in the agri-food sector" (RTI2018-093791-B-C22).Puertas Medina, RM.; Martí Selva, ML.; García Alvarez-Coque, JM. (2020). Food Supply without Risk: Multicriteria Analysis of Institutional Conditions of Exporters. International Journal of Environmental research and Public Health. 17(10):1-21. https://doi.org/10.3390/ijerph17103432S1211710Walker, E., & Jones, N. (2002). An assessment of the value of documenting food safety in small and less developed catering businesses. Food Control, 13(4-5), 307-314. doi:10.1016/s0956-7135(02)00036-1Sun, Y.-M., & Ockerman, H. W. (2005). A review of the needs and current applications of hazard analysis and critical control point (HACCP) system in foodservice areas. Food Control, 16(4), 325-332. doi:10.1016/j.foodcont.2004.03.012Rohr, J. R., Barrett, C. B., Civitello, D. J., Craft, M. E., Delius, B., DeLeo, G. A., … Tilman, D. (2019). Emerging human infectious diseases and the links to global food production. 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Strategic supplier performance evaluation::a case-based action research of a UK manufacturing organisation

The main aim of this research is to demonstrate strategic supplier performance evaluation of a UK-based manufacturing organisation using an integrated analytical framework. Developing long term relationship with strategic suppliers is common in today׳s industry. However, monitoring suppliers׳ performance all through the contractual period is important in order to ensure overall supply chain performance. Therefore, client organisations need to measure suppliers׳ performance dynamically and inform them on improvement measures. Although there are many studies introducing innovative supplier performance evaluation frameworks and empirical researches on identifying criteria for supplier evaluation, little has been reported on detailed application of strategic supplier performance evaluation and its implication on overall performance of organisation. Additionally, majority of the prior studies emphasise on lagging factors (quality, delivery schedule and value/cost) for supplier selection and evaluation. This research proposes both leading (organisational practices, risk management, environmental and social practices) and lagging factors for supplier evaluation and demonstrates a systematic method for identifying those factors with the involvement of relevant stakeholders and process mapping. The contribution of this article is a real-life case-based action research utilising an integrated analytical model that combines quality function deployment and the analytic hierarchy process method for suppliers׳ performance evaluation. The effectiveness of the method has been demonstrated through number of validations (e.g. focus group, business results, and statistical analysis). Additionally, the study reveals that enhanced supplier performance results positive impact on operational and business performance of client organisation

A contribution to supply chain design under uncertainty

Dans le contexte actuel des chaînes logistiques, des processus d'affaires complexes et des partenaires étendus, plusieurs facteurs peuvent augmenter les chances de perturbations dans les chaînes logistiques, telles que les pertes de clients en raison de l'intensification de la concurrence, la pénurie de l'offre en raison de l'incertitude des approvisionnements, la gestion d'un grand nombre de partenaires, les défaillances et les pannes imprévisibles, etc. Prévoir et répondre aux changements qui touchent les chaînes logistiques exigent parfois de composer avec des incertitudes et des informations incomplètes. Chaque entité de la chaîne doit être choisie de façon efficace afin de réduire autant que possible les facteurs de perturbations. Configurer des chaînes logistiques efficientes peut garantir la continuité des activités de la chaîne en dépit de la présence d'événements perturbateurs. L'objectif principal de cette thèse est la conception de chaînes logistiques qui résistent aux perturbations par le biais de modèles de sélection d'acteurs fiables. Les modèles proposés permettent de réduire la vulnérabilité aux perturbations qui peuvent aV, oir un impact sur la continuité des opérations des entités de la chaîne, soient les fournisseurs, les sites de production et les sites de distribution. Le manuscrit de cette thèse s'articule autour de trois principaux chapitres: 1 - Construction d'un modèle multi-objectifs de sélection d'acteurs fiables pour la conception de chaînes logistiques en mesure de résister aux perturbations. 2 - Examen des différents concepts et des types de risques liés aux chaînes logistiques ainsi qu'une présentation d'une approche pour quantifier le risque. 3 - Développement d'un modèle d'optimisation de la fiabilité afin de réduire la vulnérabilité aux perturbations des chaînes logistiques sous l'incertitude de la sollicitation et de l'offre

Strategic sourcing:a combined QFD and AHP approach in manufacturing

Purpose – This paper aims to develop an integrated analytical approach, combining quality function deployment (QFD) and analytic hierarchy process (AHP) approach, to enhance the effectiveness of sourcing decisions. Design/methodology/approach – In the approach, QFD is used to translate the company stakeholder requirements into multiple evaluating factors for supplier selection, which are used to benchmark the suppliers. AHP is used to determine the importance of evaluating factors and preference of each supplier with respect to each selection criterion. Findings – The effectiveness of the proposed approach is demonstrated by applying it to a UK-based automobile manufacturing company. With QFD, the evaluating factors are related to the strategic intent of the company through the involvement of concerned stakeholders. This ensures successful strategic sourcing. The application of AHP ensures consistent supplier performance measurement using benchmarking approach. Research limitations/implications – The proposed integrated approach can be principally adopted in other decision-making scenarios for effective management of the supply chain. Practical implications – The proposed integrated approach can be used as a group-based decision support system for supplier selection, in which all relevant stakeholders are involved to identify various quantitative and qualitative evaluating criteria, and their importance. Originality/value – Various approaches that can deal with multiple and conflicting criteria have been adopted for the supplier selection. However, they fail to consider the impact of business objectives and the requirements of company stakeholders in the identification of evaluating criteria for strategic supplier selection. The proposed integrated approach outranks the conventional approaches to supplier selection and supplier performance measurement because the sourcing strategy and supplier selection are derived from the corporate/business strategy

An Investigation into Factors Affecting the Chilled Food Industry

With the advent of Industry 4.0, many new approaches towards process monitoring, benchmarking and traceability are becoming available, and these techniques have the potential to radically transform the agri-food sector. In particular, the chilled food supply chain (CFSC) contains a number of unique challenges by virtue of it being thought of as a temperature controlled supply chain. Therefore, once the key issues affecting the CFSC have been identified, algorithms can be proposed, which would allow realistic thresholds to be established for managing these problems on the micro, meso and macro scales. Hence, a study is required into factors affecting the CFSC within the scope of Industry 4.0. The study itself has been broken down into four main topics: identifying the key issues within the CFSC; implementing a philosophy of continuous improvement within the CFSC; identifying uncertainty within the CFSC; improving and measuring the performance of the supply chain. However, as a consequence of this study two further topics were added: a discussion of some of the issues surrounding information sharing between retailers and suppliers; some of the wider issues affecting food losses and wastage (FLW) on the micro, meso and macro scales. A hybrid algorithm is developed, which incorporates the analytic hierarchical process (AHP) for qualitative issues and data envelopment analysis (DEA) for quantitative issues. The hybrid algorithm itself is a development of the internal auditing algorithm proposed by Sueyoshi et al (2009), which in turn was developed following corporate scandals such as Tyco, Enron, and WorldCom, which have led to a decline in public trust. However, the advantage of the proposed solution is that all of the key issues within the CFSC identified can be managed from a single computer terminal, whilst the risk of food contamination such as the 2013 horsemeat scandal can be avoided via improved traceability

Selection of Production Mix in the Agricultural Machinery Industry considering Sustainability in Decision Making

[EN] Competition among companies is growing globally, with the need to increase productivity and efficiency in the product sector. However, there is also a growing concern about global warming and the depletion of natural resources, as well as their effects on human health. In this context, all human activities that involve intense usage of resources must take into account sustainability as one of the decision criteria. This work presents the application of decision-making methods to define the best product mix in the agricultural machinery industry. With this objective, the current schedule of the production line was identified, along with the production flow, by performing an inventory analysis and an environmental impact study (endpoint). A total of seven alternatives for the production mix of grain trailers were defined, considering different materials and production processes. The selection of the best schedule according to the different criteria was performed through the analytic hierarchy process (AHP) and data envelopment analysis (DEA) to evaluate the managerial implications for decision making. The results obtained through AHP identified a single alternative as being the best, which facilitates the decision making. The DEA method identified two alternatives as the most efficient, and in this case the manager can choose between a product mix that generates lesser environmental impact or greater profitability. Although applied to agricultural industry, the presented methodology can be easily adapted to other activities related to the built environment, such as construction industry.The authors acknowledge the financial support the Spanish Ministry of Science and Innovation (Project: PID2020-117056RB-I00), along with FEDER funding to the second author, and the financial support of the Brazilian National Council for Scientific and Technological Development (CNPq) to the last author.Hoose, A.; Yepes, V.; Kripka, M. (2021). Selection of Production Mix in the Agricultural Machinery Industry considering Sustainability in Decision Making. Sustainability. 13(16):1-14. https://doi.org/10.3390/su13169110S114131