The economic, social and environmental crises of recent years have caused a global concern for the need to find mechanisms that enable efficient development processes and that lead countries towards sustainability. In particular, emerging countries have specific characteristics that force them to face the issue of sustainable development under a very particular vision about how actions should be taken to generate public policies and programmes that suit their own needs and the well-being of their citizens. With this perspective, our study presents a methodology based on the model of forgotten effects developed by Kaufmann and Gil Aluja. This methodology quantifies (using expert groups) the relationship between the indicators of Mexico’s social progress index and its sustainability to determine the incidence of the components of this index in the country’s sustainability activities, with the objective of providing elements for better decision-making in the design of strategies, actions and public policies aimed at the sustainable development of the nation

During the last decades, global climate change has led to serious impacts on nature, environment and socio-economic development in several places, especially in coastal zones. Vietnam is one of the countries, which was significantly affected by climate change. Hence, establishing an integrated framework to analysis climate change impacts for 28 coastal provinces in the country is necessary. Determining the key effects of climate change requires an appropriate method. To solve this issue, this study aims to utilize the fuzzy analytic hierarchy process (Fuzzy-AHP) technique to evaluate the weight of criteria and sub-criteria of climate change. The results found that 3/28 provinces are highly vulnerable to climate change compared to 17/28 of medium areas and 8/28 of the lowest group. Especially, Ho Chi Minh City is the most vulnerable province by the influence of climate change since the area has a low terrain, concentrated population, and a key economic province in Vietnam. Furthermore, the Fuzzy-AHP technique was integrated into climate change vulnerability index to assist policymakers in deciding an effective adaptation planning

The objective of the paper is to demonstrate the effectiveness of a model which fuses econometric models and Heavy Ordered Weighted Moving Average (HOWMA) operators. The evaluation of the methodology is validated with a forecast exercise of the monthly USD / MXN parity for 2015-2017. Within the results, it is identified that the use of HOWMA operators decreases the forecast error in contrast to the time series. The limitation lies in obtaining the weights of the operator, since a change generates different results, however, this becomes its main advantage, since it allows to incorporate expectations and knowledge of market experts. The originality of the article is the presentation of a fuzzy econometric model based on information aggregation operators

For attaining an entrepreneurial development of Mexico, particularly in the state of Michoacan, it is of the utmost importance to know what are the factors and elements that influence in a relevant way to generate a regional, national and international development and the positioning of the MIPYMEs (micro, small and medium enterprises, declared as -MSMEs) in the market. For this reason, in the present work, a study that incorporates the Forgotten Effects Theory (FET) is made. This theory, originally proposed by professors Kaufmann and Gil-Aluja in 1988, studies the sustainability and the good economic development of the enterprise and thus, finds all those factors that employing the classical theory are not possible to know precisely. Once determined with the FET it is possible to design more efficient and effective development plans, which will enable the sustainability of the enterprise and self-sustained development of regions and countries based on entrepreneurial development.

This paper proposes a new procedure for enriching investment and real option analysis performed with the fuzzy pay-off method by decomposing the pay-off distribution into multiple sub-distributions that correspond to different investment scenarios. This creates more information about the importance of the effect of selected factors to investment profitability. Furthermore, based on the proposed procedure, we show how a fuzzy inference system to support investment decision-making can be constructed. The proposed new procedure and the application of a fuzzy inference system are illustrated with a numerical case analysis of a power generation investment. The results show that the proposed new procedure reveals actionable information about the analyzed investment that may otherwise remain uncovered and enhances the decision-making ability of investment managers. The application of a fuzzy inference system to investment decision-support and real option analysis is a rather new approach. The obtained results highlight how the construct of a fuzzy inference system must be adapted to the perspective of the application for which it is used.

Model-building professionals are often facing a very difficult choice of selecting relevant variable/s from a set of several similar variables. All those variables are supposedly representing the same factor but are measured differently. They are based on different methodologies, baselines, conversion/comparability methods, etc., thus leading to substantial differences in numerical values for essentially the same things (from the perspective of the modeler). In this study, we introduce a method for modeling, capable of utilizing ranges (intervals) of values and thus enabling to utilize inclusive approach, which includes all the relevant variables that represent the same factor. This approach has numerous advantages in terms of efficient data utilization, reliability of conclusions and simplification of process to summarize results (due to reduction in the number of necessary regression runs). We also introduce an interval reduction algorithm, designed to reduce excessive size of intervals, thus bringing them closer to their central tendency cluster. The algorithm also allows to identify exceptional cases where such reduction is not possible. The modeling method used in this study is Soft Regression (based on Fuzzy Logic).

This study provides new evidence on anomaly interactions, as well as on the cross-section of returns in all-but-microcap universe of U.S. stocks over the 42-year sample period from 1971 to 2013. The five anomalies being examined are size, value, profitability, investment/asset growth, and momentum. We form 5x5 conditional double-sort portfolios for each pair of anomaly variables, resulting in 20 different 5x5 sorts when using each variable in the first-stage sorting and the remaining four in the second-stage sorting. The interrelation between each pair of anomaly variables is evaluated on the basis of the monotonic relation (MR) test of Patton and Timmermann (2010) for portfolio raw returns, and in addition, by means of the Sharpe ratio comparisons. Moreover, we run Fama-MacBeth (1973) cross-sectional regressions to compare the relative explanatory power of each variable in the presence of the others. The results show that investment/asset growth and momentum dimensions capture the cross-sectional return patterns better than size, value, or profitability. The relative efficacy of momentum is higher in all-but-microcap universe than previously documented for the corresponding unlimited market-cap samples of U.S. stocks.

In many applications of real options there is an assumption of complete capital markets. For the perpetual timing option this means that if the underlying asset does not pay out any cash flows, the ...

Guest’s satisfaction in the hotel industry cannot be easily measured because these constructs depend on multiple intangible attributes that can be evaluated very differently by distinct market segments. In this paper, the satisfaction experienced by different market segments based on age and gender is evaluated by the use of a hybrid method built from the fuzzy logic and optimal solutions. Fuzzy set theory has become a standard technique to resolve in part the uncertain information provided by guests. The results show that age and gender affect the satisfaction experienced by the hotel guests, and that not all the attributes are equally important when satisfaction is studied. The analysis of the elasticities show that the guest satisfaction is quite inelastic with respect to the 32 attributes included in the study, but the elasticity is higher for these four attributes: (1) welcome gifts in the room; (2) furniture/decoration in restaurants and bars; (3) furniture/decoration in public areas; and (4) welcome gifts in the bathroom.

This paper outlines the application of non-additive measures and Choquet integral in the construction of a composite indicator to assess the performance of international climate think tanks and evaluate their influence in shaping climate policies and raising awareness among the general public. The composite index consists of 15 carefully selected indicators according to the feedback provided by Experts within the field and structured into three main pillars: Activities, Publications and Dissemination. In order compare Think Tanks of different size and hence to measure their efficiency, the standardized ranking is also computed dividing the Think Tank outcome in each criterion by the number of its researchers. The application of fuzzy measures and Choquet integral, allowing to take into account potential interactions existing among criteria, increases substantially the model capability both in eliciting effectively Experts’ preferences and in aggregating indicators. Moreover, we present a novel technique for the aggregation of Experts’ preferences where Decision Makers’ weights have been set proportionally to their consistency in evaluating the specific questionnaire.