Review and improvements on OECD better life index

The Organization for Economic Cooperation and Development (OECD) has developed the Better Life Index (BLI) as part of the OECD Better Life initiative to facilitate the better understanding of what drives well-being of people and guide the policy-making. The BLI is a three-level hierarchical composite indicator which covers several socio-economic aspects. In this paper, we depart from the traditional approaches of building composite indices by introducing a hierarchical evaluation methodology for the assessment of BLI. We establish a common basis for fair and democratic evaluation as the aggregation schemes for both first and second level of BLI are determined jointly by the assessed countries through optimization process. We also incorporate into the assessment the public opinion that is captured from the worldwide responses in the web platform of OECD BLI. In addition, we enrich our methodology by incorporating the data from previous years into the normalization process of the indicators, thus smoothing the deviations of indicators’ values among the years. We apply our approach to the data of 38 countries for the year 2017. The robust results obtained from our approach provide insights about the key role that public opinion plays in the evaluation of BLI.info:eu-repo/semantics/publishedVersio

A MIN–MAX GOAL PROGRAMMING APPROACH TO PRIORITY DERIVATION IN AHP WITH INTERVAL JUDGEMENTS

We deal with the problem of priority elicitation in the analytic hierarchy process (AHP) on the basis of imprecise pair-wise comparison judgements on decision elements. We propose a min–max goal programming formulation to derive the AHP priorities in the case that the decision maker provides preference judgements in the form of interval numbers. By applying variable transformations, we formulate a linear programming model that is capable of estimating the priorities from both consistent and inconsistent interval judgements. The proposed method is illustrated by numerical examples.Analytic hierarchy process, priority setting, interval judgements, Goal programming

Reformulation of Network Data Envelopment Analysis models using a common modelling framework

Network Data Envelopment Analysis (network DEA) is an extension of the conventional Data Envelop- ment Analysis (DEA) developed to take into account the internal structure of the Decision Making Units (DMUs). In network DEA, the DMU is considered as a network of interconnected sub-processes, where the connections indicate the flow of the intermediate measures. In this paper, we reformulate some of the basic network DEA methodologies in a common modelling framework. We show that the leader- follower approach, the multiplicative and the additive decomposition methods as well as the recently introduced min-max method and the “weak-link”approach, can all be modelled in a multi-objective programming framework, differentiating only in the definition of the overall system efficiency and the solution procedure adopted. Such a common modelling framework makes the direct comparison of the different methodologies possible and enables us to spot and underline their similarities and dissimilar- ities effectively. We illustrate graphically how the aforementioned methodologies locate their optimal efficiency scores on the Pareto front in the objective functions space, with an example taken from the literature.info:eu-repo/semantics/publishedVersio

Dominance at the divisional efficiencies level in network DEA: the case of two-stage processes

We introduce in this paper the notion of dominance in the divisional efficiencies space in Network Data Envelopment Analysis. We argue that, irrespectively of the method used, a successful efficiency evalua- tion protocol should satisfy the dominance property at the divisional efficiencies level. In particular, there should not exist any other feasible solution in the assessment model, suboptimal in terms of the opti- mality criterion, that provides stage efficiencies scores at least as high as the assessed ones and higher for at least one stage. Then, we investigate the dominance property in different methods for two-stage series processes of various complexity. We prove that the additive efficiency decomposition method and the relational model provide non-dominated divisional efficiencies when they are applied to elemen- tary two-stage processes, where nothing but the external inputs to the first stage enters the system and nothing but the external outputs of the second stage leaves the system. For more complex two-stage structures, however, we provide examples showing that these models do not comply with the dominance requirement at the divisional efficiencies level and lead to controversial results. Finally, we revisit some characteristic NDEA methods for which dominance is an inherent property.info:eu-repo/semantics/publishedVersio

Assessment of OECD Better Life Index by incorporating public opinion

Well-being has a multidimensional nature as it depends on multifaceted factors such as material conditions and quality of life. The Organization for Economic Co-operation and Development (OECD) has developed the Better Life Index (BLI) as part of the OECD Better Life initiative to facilitate the better understanding of what drives well-being of people. The BLI is a three-level hierarchical composite indicator that covers several socio-economic aspects. In this paper, considering the entire hierarchical structure of the index, we introduce a bottom-up procedure for the aggregation of the components at each level. We formulate the assessment of BLI as a multiple objective programming (MOP) problem that facilitates the implementation of different concepts to derive different aggregation schemes. We incorporate the data from previous years into the normalization process of the indicators, to take into account the discrepancy on their observed values and smooth their deviations across the years. Also, we consider the public opinion about well-being that is captured from the worldwide responses in the web platform of OECD BLI. We incorporate the public opinion into the assessment models in the form of weight restrictions. In this way, we reduce the effect of compensation that might be imposed by the adopted modelling approach. We apply our methodology to the data of 38 countries (35 OECD and 3 non-OECD economies) for the year 2017. Our findings illustrate that the public opinion in the form of weight restrictions can effectively drive the optimization process and depict the collective preferences to the BLI scores.N/

A MULTICRITERIA APPROACH TO DYNAMIC REASONING IN AN INTELLIGENT USER INTERFACE

This paper presents the way that the global efficiencies approach has been applied to improve the dynamic reasoning of an intelligent Graphical User Interface (GUI) that is based on the Data Envelopment Analysis (DEA). The GUI provides intelligent help to users during their interaction with an e-mailing system, which is called I-Mailer. For this purpose, I-Mailer constantly reasons about every user action in terms of the user's goals and plans. In case the user is involved in a problematic situation, it transforms the user's problematic action and generates alternative actions to be suggested to the user. The actions suggested should be better than the problematic one in the context of the user's intentions as these are hypothesized by the system. Therefore, DEA is used in order to categorize the candidate alternative actions to be suggested to the user into dominating and dominated ones. However, this process usually results in the production of many alternative actions that could be suggested to the user instead of the one issued. To solve this problem, we have applied the global efficiencies approach to discriminate further among the DEA-efficient alternative actions and select the best alternative action to be suggested to a user. Finally, the system has been evaluated as to the effectiveness of this approach.Intelligent user interface, user modeling, data envelopment analysis