0000000000175213
AUTHOR
Giacomo Di Tollo
Neural Networks to Determine the Relationships Between Business Innovation and Gender Aspects
Gender aspects of management, innovation and entrepreneurship are gaining more and more importance as cross-cutting issues for researchers, practitioners and decision makers. Extant literature pays a growing attention to the hypothesis that there exists a correlation between the gender diversity of corporate boards of directors and the business attitude to innovation. In this paper we introduce a working framework to test the aforementioned hypothesis and to examine the correlation between board diversity and innovation perception of a business. This framework is based on correlation computation and feed-forward neural networks, and it is used to evaluate whether the gender component may be…
A heuristic fuzzy algorithm for assessing and managing tourism sustainability
“Smartness” and “sustainability” are gaining growing attention from both practitioners and policy makers. “Smartness” and “sustainability” assessments are of crucial importance for directing, in a systemic perspective, the decision-making process toward sustainability and smart growth objectives. Sustainability assessment is a major challenge due to the multidisciplinary aspects involved that make the evaluation process complex and hinder the effectiveness of available monitoring tools. To achieve the assessment objective, we introduce an enhanced fuzzy logic-based framework for handling the inherent uncertainty and vagueness of the involved variables: we apply our approach to Italy, and we…
An Empirical Investigation of Heavy Tails in Emerging Markets and Robust Estimation of the Pareto Tail Index
In this work we analyze and compare the performances of VaR-based estimatorswith respect to three different classes of distributions, i.e., Gaussian, Stable and Pareto, and to different emerging markets, i.e., Egypt, Qatar and Mexico. This is motivated by the evidence that there are points of distinction between emerging and developed markets mainly relating to the speed and reliability of information available to investors.We propose a computational Threshold Accepting-VaR based algorithm (TAVaR) for optimally estimating the Pareto tail index. A Monte Carlo bias estimation analysis is also carried out by comparing our proposed methodology with the Hill estimator and a variant of it.
A fuzzy evaluation of tourism sustainability
For many years the sustainability assessment of tourist destinations has been based on the carrying capacity, which is a measure that takes into account the preservation of a geographical area (by measuring the number of tourists, the visitor flow and the environmental thresholds) along with its tourist fruition (by assessing the quality of the experience perceived by visitors). Unfortunately, its definition lacks clarity, and its dependence upon qualitative variables makes it unable to provide a unique criterion for its assessment. In this paper we propose a fuzzy approach that takes into account the inherent uncertainty and vagueness of the involved variables to assess a destination’s sus…
Detection of local tourism systems by threshold accepting
Despite the importance of tourism as a leading industry in the development of a country’s economy, there is a lack of criteria and methodologies for the detection, promotion, and governance of local tourism systems. We propose a quantitative approach for the detection of local tourism systems the size of which is optimal with respect to geographical, economic, and demographical criteria: we formulate the problem as an optimisation problem and we solve it by a metaheuristic approach; then we compare the obtained results with standard clustering approaches and with an exact optimisation solver. Results show that our approach requires low computational times to provide results that are better …
The Problem of Time Arrow in Financial Time Series
According to the efficient market hypothesis, future movements of the market cannot be predicted. This introduces an intrinsic time asymmetry of the financial time series as there are no laws forbidding “predicting” past based on the current market fluctuations. This clear time asymmetry in the basic laws of finance raises a question which we shall be referring to as the problem of time arrow: are there any noticeable statistical differences between forward-in-time and reverse-in-time market data. Majority of the statistical methods used for financial time series are time-symmetric and hence, not usable for our purposes. The first method used in our study is the analysis of the length-distr…
Gender analysis and attention to gender: An experimental framework
Gender aspects are gaining more and more attention for policy makers, practitioners and faculties. They also have a great importance for funding purposes, since many calls for proposals by national and international agencies require a gender plan and/or an analysis of the gender aspect, especially referring to the extent to which a candidate research project affects differently men and women. In this context, we want to understand whether there exists a relationship between the gender diversity of corporate boards of directors and the way a business articulates gender aspects on their corporate communications and activities on the Internet. To achieve this goal, we created a set of meaningf…
The predictive power of power-laws: An empirical time-arrow based investigation
The efficient market hypothesis forbids any predictability towards future, but there is no such restriction in the case of reversed-looking approaches. We analyze if this asymmetry in non-predictability is reflected in the statistical features of financial time series. Our study is based on the analysis of the length-distribution of periods with high variability, and introduces time-asymmetric modifications of the method which are capable of revealing differences of the time series in forward and reversed time. We show that the future and reversed-looking time-series possess very similar properties, with some features being distinguishable with our method. Our findings give also evidence of…
Clustering local tourism systems by threshold acceptance
Despite the importance of tourism as a leading industry in the development of a country’s economy, there is a lack of criteria and methodologies for the detection, promotion and governance of local tourism systems. We propose a quantitative approach for the detection of local tourism systems that are optimal with respect to geographical, economic, and demographical criteria. To this end, we formulate the issue as an optimization problem, and we solve it by means of Threshold Acceptance, a meta-heuristic algorithm which does not require us to predefine the number of clusters and also does not require all geographic areas to belong to a cluster.
Fuzzy Multi-Criteria Decision Making: An entropy-based approach to assess tourism sustainability
In this article, we propose a method for ranking tourist destinations and evaluating their performances under a sustainability perspective: a fuzzy multiple criteria decision-making method is applied for determining sustainability performance values and ranking destinations accordingly. We select a set of sustainability evaluation criteria and use a fuzzy analytic hierarchy process to weight the selected criteria. We also optimize each evaluator’s membership function support by means of a fuzzy entropy maximization criteria. A case study is illustrated and results are compared with two data envelopment analysis–based models. The simplicity of the proposed approach along with the easy reada…
Propagation of Bankruptcy Risk over Scale-Free Economic Networks.
The propagation of bankruptcy-induced shocks across domestic and global economies is sometimes very dramatic; this phenomenon can be modelled as a dynamical process in economic networks. Economic networks are usually scale-free, and scale-free networks are known to be vulnerable with respect to targeted attacks, i.e., attacks directed towards the biggest nodes of the network. Here we address the following question: to what extent does the scale-free nature of economic networks and the vulnerability of the biggest nodes affect the propagation of economic shocks? We model the dynamics of bankruptcies as the propagation of financial contagion across the banking sector over a scale-free network…
Distance Measures for Portfolio Selection
The classical Markowitz approach to the portfolio selection problem (PSP) consists of selecting the portfolio that minimises the return variance for a given level of expected return. By solving the problem for different values of this expected return we obtain the Pareto efficient frontier, which is composed of non-dominated portfolios. The final user has to discriminate amongst these points by resorting to an external criterion in order to decide which portfolio to invest in. We propose to define an external portfolio that corresponds to a desired criterion, and to assess its distance from the Markowitz frontier in market allowing for short-sellings or not. We show that this distance is ab…