A methodology for project portfolio selection under criteria prioritisation, uncertainty and projects interdependency – combination of fuzzy QFD and DEA

© 2018 Elsevier Ltd Resources of an organisation (people, time, money, equipment, etc) are never endless. As such, a constant and continuous challenge for decision makers is to decide which projects should be given priority in terms of receiving critical resources in a way that the organisation's productivity and profitability is best guaranteed. Previous literature has already developed a plenitude of project portfolio selection methodologies ranging from simple scoring to complex mathematical models. However, most of them too often fail to propose one integrated and seamless method that can simultaneously take into account three important elements: (1) prioritisation of selection criteria over each other, (2) uncertainty in decision-making, and (3) projects interdependencies. This paper aims to fill this gap by proposing an integrated method that can simultaneously address all these three aspects. The proposed method combines Quality Function Development (QFD), fuzzy logic, and Data Envelopment Analysis (DEA) to accounts for prioritisation, uncertainty and interdependency. We then apply this method in a numerical example from a real world case to illustrate the applicability and efficacy of the proposed methodology

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

Multiple Attribute Decision Making Based on Cross-Evaluation with Uncertain Decision Parameters

Multiple attribute decision making (MADM) problem is one of the most common and popular research fields in the theory of decision science. A variety of methods have been proposed to deal with such problems. Nevertheless, many of them assumed that attribute weights are determined by different types of additional preference information which will result in subjective decision making. In order to solve such problems, in this paper, we propose a novel MADM approach based on cross-evaluation with uncertain parameters. Specifically, the proposed approach assumes that all attribute weights are uncertain. It can overcome the drawback in prior research that the alternatives’ ranking may be determined by a single attribute with an overestimated weight. In addition, the proposed method can also balance the mean and deviation of each alternative’s cross-evaluation score to guarantee the stability of evaluation. Then, this method is extended to a more generalized situation where the attribute values are also uncertain. Finally, we illustrate the applicability of the proposed method by revisiting two reported studies and by a case study on the selection of community service companies in the city of Hefei in China

A state-of-art survey on TQM applications using MCDM techniques

In today’s competitive economy, quality plays an essential role for the success business units and there are considerable efforts made to control and to improve quality characteristics in order to satisfy customers’ requirements. However, improving quality is normally involved with various criteria and we need to use Multi Criteria Decision Making (MCDM) to handle such cases. In this state-of the-art literature survey, 45 articles focused on solving quality problems by MCDM methods are investigated. These articles were published between 1994 and 2013.Seven areas were selected for categorization: (1) AHP, Fuzzy AHP, ANP and Fuzzy ANP, (2) DEMATEL and Fuzzy DEMATEL, (3) GRA, (4) Vikor and Fuzzy Vikor, (5) TOPSIS, Fuzzy TOPSIS and combination of TOPSIS and AHP, (6) Fuzzy and (7) Less frequent and hybrid procedures. According to our survey, Fuzzy based methods were the most popular technique with about 40% usage among procedures. Also AHP and ANP were almost 20% of functional methods. This survey ends with giving recommendation for future researches

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. 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Impact of Lean and Sustainability Oriented Innovation on Sustainability Performance of Small and Medium Sized Enterprises: A Data Envelopment Analysis-based framework

Lean and Sustainability Oriented Innovation both enhance competitiveness of small and medium enterprises (SMEs) in a sustainable way. Lean is efficiency focused, whereas Sustainability Oriented Innovation emphasizes on responsiveness. Although lean and sustainability oriented innovation have been separately researched, there is a gap in knowledge on the combined effect of lean and sustainability oriented innovation (SOI) on SMEs Supply Chain sustainability. SMEs have limited resources and face numerous competition. Therefore, their supply chain sustainability can only be achieved through most appropriate trade-off between economic, environment and social aspects of business. The purpose of this paper is to understand the combined effect of sustainability oriented innovation and lean practices, on supply chain sustainability performance of SMEs. The study uses a Data Envelopment Analysis (DEA) based framework and applies this to a group of SMEs within the Eastern part of India. Lean and sustainability oriented innovation are considered as input criteria, and economic, operational, environmental and social aspects are considered as output criteria of the proposed framework. DEA segregates inefficient SMEs and suggests at least a SME to benchmark. Subsequently, the study undertakes qualitative approach to suggest improvement measures for the inefficient SMEs. The results reveal that combined lean and SOI helps achieve SMEs' supply chain sustainability. The findings are useful for policy makers and Individual SMEs' owners and managers to undertake measures for improving sustainability. Theoretically this research contributes a DEA-based framework to study the effect of combined lean and SOI on sustainability that helps improving SMEs’ sustainability performance

A New Approach for Evaluating the Order Fulfillment Process Options of B2C Horizontal Portals Using DEA (Data Envelopment Analysis)

By using the traditional statistical or operations research methods for deciding the product-delivery logistics, the portal companies are not using their competitive advantages on being more e-enabled, informed and computationally able than their traditional counterparts. In this paper, we show some typical characteristics of the portals like their handling of a huge range of goods in terms of transactional values or volumes. Subsequently, we have identified three types of generic product-delivery logistics of the portals with various intermediate entities or trading partners. Then, a completely different approach using an extreme point method rather than the traditional central-tendency-based statistical methods has been suggested

An Integrated Fuzzy Clustering Cooperative Game Data Envelopment Analysis Model with application in Hospital Efficiency

Hospitals are the main sub-section of health care systems and evaluation of hospitals is one of the most important issue for health policy makers. Data Envelopment Analysis (DEA) is a nonparametric method that has recently been used for measuring efficiency and productivity of Decision Making Units (DMUs) and commonly applied for comparison of hospitals. However, one of the important assumption in DEA is that DMUs must be homogenous. The crucial issue in hospital efficiency is that hospitals are providing different services and so may not be comparable. In this paper, we propose an integrated fuzzy clustering cooperative game DEA approach. In fact, due to the lack of homogeneity among DMUs, we first propose to use a fuzzy C-means technique to cluster the DMUs. Then we apply DEA combined with the game theory where each DMU is considered as a player, using Core and Shapley value approaches within each cluster. The procedure has successfully been applied for performances measurement of 288 hospitals in 31 provinces of Iran. Finally, since the classical DEA model is not capable to distinguish between efficient DMUs, efficient hospitals within each cluster, are ranked using combined DEA model and cooperative game approach. The results show that the Core and Shapley values are suitable for fully ranking of efficient hospitals in the healthcare systems

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