In this paper, we address the problem of the ranking of companies based on their diversity and financial performance. The addressed problem is a multiple criteria decision‐making problem where a ...composite measure needs to be obtained to rank firms. Taking as a reference the methodological approach followed by Refinitiv in the construction of their Diversity and Inclusion Index, we propose an alternative ranking framework that overcomes some of the problems identified in the methodological approach of Refinitiv. In particular, the proposed method in this work does not require the a priori establishment of a weighting scheme and is able to incorporate the past behavior of the companies in terms of diversity in their workplaces.
The technique for order preference by similarity to ideal solution (TOPSIS) is a widely used ranking method which provides a composite index representing the relative proximity of each decision ...alternative to an ideal solution. The relative proximity index construction relays on the use of a single criterion aggregation approach. Its output, regardless the certainty or uncertainty nature of the problem’s data, is usually a real number. In TOPSIS classical approach alternatives are ordered based on these numbers. The closer the number to 1, the higher the position of the alternative in the ranking. However, although the relative proximity index can be highly sensible to the weighting scheme, as far as the authors of this work know, the relative proximity index has never been treated as a function. In this work, a new TOPSIS approach is proposed in which weights are not fixed in an exact way a priori. On the contrary, they are handled as decision variables in a set of optimization problems where the objective is to maximize the relative proximity of each alternative to the ideal solution. The only possible a priori information about the weights is that related to the existence of upper and lower bounds in their values. This information is incorporated into the optimization problems as constraints. The result is a new relative proximity index which is a function depending on the values of the weights. This feature of the proposed method could be useful in some decision situations in which the determination of subjective precise weights from decision makers could be problematic.
YouTube is the largest Internet video-sharing site in the world and in the last years it has become an important learning resource making educational contents accessible for hundreds of millions of ...people around the world, from developed and developing countries, allowing students to watch contents on demand. The utility of the performance assessment and ranking of educational videos available in You Tube goes beyond the simple control of the correctness and precision of the instructional contents. It requires considering other important didactical features as waste of time in the exposition, empathy with the user and the degree of adaptation of the contents to the educational context. In this paper a ranking method for instructional videos will be proposed, taking into account decision criteria of different nature: precise and imprecise and a reference solution (
ideal solution
). The decision matrix describing the assessment of videos with respect to each criterion will be formed by data of diverse nature: real numbers, intervals on the real line and/or linguistic or sets of categorical variables. Classical normalization procedures do not always take into account situations where the different nature of the data of the decision matrix could make the ranking of the alternatives quite unstable. A new normalization method will be proposed allowing us to mitigate this problem. Through this normalization procedure, the nature of the transformed normalized data will reflect the similarity of each alternative with the reference solution becoming thus, the decision matrix of homogeneous nature.
Corporate sustainability implies a compromise between the present environmental, social, and economic needs of a firm's stakeholders and their future needs. Corporate sustainability is therefore a ...multidimensional concept. Nowadays, several independent rating agencies rate firms in terms of environmental, social, and governance (ESG) criteria. These ratings are usually used by main sustainability indices such as the Dow Jones Sustainability Index, FTSE4 Good, Stoxx Sustainability Index, or Euronext Vigeo Family to select companies to invest in. Only those firms performing better than the average of their sector are selected. However, although providing linguistic ratings about the performance of the firms in individual ESG criteria with respect to their sector, rating agencies do not usually provide overall ESG rates describing the global performance of the firms in terms of ESG. In this paper, we propose a flexible operator, linguistic ordered weighted geometric aggregating operator (LOWGA), which will allow us to define the fuzzy ESG performance of the firms based on the linguistic labels provided by the rating agencies. Once overall ESG scores have been obtained, we will use them together with financial criteria to rank the firms in terms of their sustainability using a suitable multiple criteria decision aid (MCDA) approach, namely, TOPSIS (technique for order preference by similarity to ideal solution).
•We address the evaluation of mutual funds from the Socially Responsible Investment point of view.•We use a double reference point (reservation–aspiration) scheme to evaluate the funds.•We build ...synthetic indicators (weak, strong and mixed) for each fund, as a result of the study.
Socially Responsible Investing (SRI) is broadly defined as an investment process that integrates not only financial but also social, environmental, and ethical (SEE) considerations into investment decision making. SRI has grown rapidly around the world in the last decades. In the last years, given the causes of the 2008 financial crisis, ethical, social, environmental and governance concerns have become even more relevant investment decision criteria. However, while a diverse set of models have been developed to support investment decision-making based on financial criteria, models including also social responsibility criteria are rather scarce.
The aim of this paper, in which we focus on the environmental dimension, is to assist individual investors in their investment decisions providing them with a synthetic indicator of mutual funds’ environmental responsibility, which is by nature a multicriteria concept and therefore multicriteria techniques are to be used to measure it.
The proposed approach is based on the double (reservation–aspiration) Reference Point Method. This scheme is applied to each fund of a randomly selected set of U.S. equity mutual funds, in order to determine, on the basis of a given set of indicators, a pair of synthetic indicators that measure the weak and the strong environmental responsibility degree of each mutual fund, relying on the particular preferences of the investor.
Abstract
ESG criteria are becoming increasingly important for institutional and retail investors with a consequent growing demand of reliable and transparent ESG data to support their decisions. ...Several ESG rating agencies assess companies providing ratings and rankings. However, their rating methodologies are subject to some criticisms. One of the main weaknesses is the determination of the relative importance of the ESG criteria involved in the rating process. In this work, we propose the use of a MCDM rating and ranking approach with which the decision maker can rank firms based on their ESG global performance without the elicitation of aggregation weights. The approach, UW-TOPSIS, provides three outputs: the global ESG rating of the firms, a ranking based on the ratings and, for each alternative, a vector of weights describing the discriminatory power of the ESG criteria on the alternative, thus overcoming one of the criticisms to the methodologies of ESG rating agencies. However, UW-TOPSIS has a limitation as it does not provide a global vector of weights valid for all the alternatives in the ranking, expressing the overall role or contribution of each criteria to the componsition of the ranking. The acknowledge and analysis of this situation and the proposal of a solution, is the main objective of this paper.
Real decision problems usually consider several objectives that have parameters which are often given by the decision maker in an imprecise way. It is possible to handle these kinds of problems ...through multiple criteria models in terms of possibility theory.
Here we propose a method for solving these kinds of models through a fuzzy compromise programming approach.
To formulate a fuzzy compromise programming problem from a possibilistic multiobjective linear programming problem the fuzzy ideal solution concept is introduced. This concept is based on soft preference and indifference relationships and on canonical representation of fuzzy numbers by means of their
α-cuts. The accuracy between the ideal solution and the objective values is evaluated handling the fuzzy parameters through their expected intervals and a definition of discrepancy between intervals is introduced in our analysis.
This paper proposes a crisp two-objective logarithmic programming model to help companies decide their advertising campaigns on TV networks for mature products. Both objectives are: (a) to achieve ...the highest audience impact and (b) to reduce advertising costs as much as possible. Information input is fuzzily elaborated from statistical data, the fuzzy variables being defuzzified to introduce them into the crisp model. This fuzzy information is elicited by TV experts (often independent consultants). Although these experts know statistical information on audience in the past, they do not fully trust its predictive ability. The approach leads to the strategic advertisement (ad) placement among different broadcasts. Users (often managers of big companies) should inform the analyst about their advertising campaign budget. From Weber and Fechner-based psychological research, the ad impact during the advertising campaign is measured depending on the logarithm of ad repetitions. The crisp two-objective problem is solved by a tradeoff method subject to TV technical constraints. A case study with real world data is developed.
Abstract
Minimizing travel in the urban environment facilitates the development of sustainable cities. A key aspect is that there is a wide supply of amenities and facilities in the neighbourhoods: ...if most of the needs of families, goods and services can be covered from the sub-centers of the residential areas, it will be possible to reduce daily intra-urban mobility. The objective of this work is to propose a ranking multicriteria method that facilitates the choice of an ideal residential location in terms of neighbourhood characteristics, especially in the search of sustainable mobility for each family characteristics. One of the main problems in several Multiple Criteria Decision Making methods is the assignment of criteria weights in the aggregation process. The proposed methodology in this paper, Un-weighted TOPSIS (UW-TOPSIS) is able to overcome that problem. In this Multiple Criteria Decision Making (MCDM) method the relative proximity of each decision alternative to an ideal solution is minimized for the un-known weights of the criteria which are the variables in the corresponding mathematical programming program. Thus, a ranking based on the relative proximity of each alternative to an ideal alternative is obtained without the a priori establishment of the criteria weights. The use of subjective weights in real decision making contexts, where for instance a ranking of alternatives is required, is subject to important criticisms. This could be the case of the ranking of neighbourhoods based on their sustainability.
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