The sustainability balanced scorecard as a framework for selecting socially responsible investment: an effective MCDM model

In recent years, sustainable development and social responsibility have become important issues around the globe. Investors are interested in the so-called ‘socially responsible investment’ (SRI), an investment strategy that employs criteria other than financial risk and return when selecting firms in which to invest. The practice of SRI shows that there are growing numbers of investors who want to take account of more criteria. Given this worldwide trend, the question arises how these issues can be incorporated into the investment decision process. This paper proposes a novel integrated model for selecting SRI stocks and illustrates the practical application of such a model through a case study. This model first applied the decision making trial and evaluation laboratory (DEMATEL) approach to deal with the interdependencies existing among the criteria of organization requires, and then integrated the DEMATEL, the analytic network process, and the zero-one goal programming method to select an optimal portfolio of SRI. Additionally, we used the sustainability balanced scorecard as a multi-criteria framework for SRI evaluation. This integrated model enables the management to obtain the fitting SRI portfolio and achieves the desired spiritual value.     

Toward professional development for teachers grounded in a theory of decision making

There is now robust evidence that teachers’ and others’ in-the-moment decision making can be modeled and explained as a function of the following: their knowledge and other intellectual, social, and material resources; their goals; and their orientations (their beliefs, values, and preferences). The role of beliefs as they affect teachers’ behavior can thus be described at a level of mechanism—but of necessity in interaction with resources and goals. This paper outlines and exemplifies how resources, goals, and orientations shape teachers’ behavior. It indicates how they are interconnected, and why their evolution is necessarily slow. It then suggests how these understandings can be used as a foundation for mathematics teachers’ professional development, and describes how they are being used to shape a course of participatory professional development for middle school mathematics teachers.     

Using compromise programming for macroeconomic policy making in a general equilibrium framework: theory and application to the Spanish economy

This paper aims to show how Compromise Programming, linked with some results connecting this approach with classic utility optimization, can become a useful analytical tool for designing and assessing macroeconomic policies. The functioning of the method is illustrated through an application to the Spanish economy. In this way, starting from a Computable General Equilibrium Model, a frontier of growth–inflation combinations is determined. After that, several Pareto-efficient policies that represent compromises between economic growth and inflation rate are established and interpreted in economic terms.     

Reserving relief supplies for earthquake: a multi-attribute decision making of China Red Cross

Earthquake usually causes grievous damages especially in the earthquake prone areas. Building a fast and effective relief system is very important. China Red Cross is the largest humanitarian organizations in China. To improve its disaster response system, reserving relief supplies gets more and more attentions. In this article, a decision making programming based on the data envelopment analysis method is proposed in the construction of reserve network for China Red Cross with three factors, including cost, risk and utility. Four warehouses are selected and the optimal allocation strategies are obtained under the principles of equity and effectiveness which should be obeyed in humanitarian assistance.     

Conditions for the existence of decision horizons for discounted problems in a stochastic environment: A note

In this note, we extend the sufficiency conditions obtained by Bean and Smith for the existence of decision and forecast horizons in discounted deterministic problems to a stochastic environment. Also developed are some examples for illustration of the results and the need for the development of necessary and sufficient conditions for undiscounted problems.     

Rough set theory: a novel approach for extraction of robust decision rules based on incremental attributes

Rough set theory is a new data mining approach to manage vagueness. It is capable to discover important facts hidden in the data. Literature indicate the current rough set based approaches can’t guarantee that classification of a decision table is credible and it is not able to generate robust decision rules when new attributes are incrementally added in. In this study, an incremental attribute oriented rule-extraction algorithm is proposed to solve this deficiency commonly observed in the literature related to decision rule induction. The proposed approach considers incremental attributes based on the alternative rule extraction algorithm (AREA), which was presented for discovering preference-based rules according to the reducts with the maximum of strength index (SI), specifically the case that the desired reducts are not necessarily unique since several reducts could include the same value of SI. Using the AREA, an alternative rule can be defined as the rule which holds identical preference to the original decision rule and may be more attractive to a decision-maker than the original one. Through implementing the proposed approach, it can be effectively operating with new attributes to be added in the database/information systems. It is not required to re-compute the updated data set similar to the first step at the initial stage. The proposed algorithm also excludes these repetitive rules during the solution search stage since most of the rule induction approaches generate the repetitive rules. The proposed approach is capable to efficiently and effectively generate the complete, robust and non-repetitive decision rules. The rules derived from the data set provide an indication of how to effectively study this problem in further investigations.     

Realization of constructive set theory into explicit mathematics: a lower bound for impredicative Mahlo universe

We define a realizability interpretation of Aczel's Constructive Set Theory CZF into Explicit Mathematics. The final results are that CZF extended by Mahlo principles is realizable in corresponding extensions of T₀, thus providing relative lower bounds for the proof-theoretic strength of the latter.     

Math MOOC UniTo : an Italian project on MOOCs for mathematics teacher education,and the development of a new theoretical framework

This paper focuses on MOOCs (massive open online courses), a fairly recent paradigm in e-learning educational projects. Despite the high dropout rate, and