Giovanni Mastroleo

Measuring Intellectual Capital in the University Sector Using a Fuzzy Logic Expert System

The main aim of this study is to find a method to measure the intellectual capital (IC) of an organization which is able to combine management and measurement views, to reflect the newest concepts regarding IC, and to take into consideration the ‘vague’ interactions between IC categories. We posit the idea that a fuzzy expert system model can address these issues, since it takes account of the qualitative nature of most IC indicators and the different IC subcategories. The main advantage of an IC score developed through a FES model is to provide a reliable IC index. The model presented in this article applied to data derived from the Austrian universities’ IC reports is a pilot model, sufficiently flexible for individual adaptations and adjustments. The main limitation of the study is that further tests can be carried out only in the presence of available and comparable IC data which are currently not available.

The Use of Fuzzy Logic and Expert Systems for Rating and Pricing Firms: A New Perspective on Valuation

Purpose – The purpose of the paper is to focus on the rating, ranking and valuing of firms.Design/methodology/approach – Fuzzy logic and expert systems are used in order to provide a score for the firm(s) under consideration, representing the firm value‐creating power.Findings – The fuzzy expert system introduced is capable of dealing with both quantitative and qualitative variables and integrates financial, managerial and strategic variables. A sensitivity analysis corroborates the model.Research limitations/implications – The system is apt to rate and rank firms within a sector. Some regression analysis can lead to a determined price for the target firm.Practical implications – The expert system may be used by rating agencies for ranking firms, and by financial analysts and potential buyers to furnish a price for acquisition.Originality/value – The use of a fuzzy expert system for ranking firms within a sector and pricing firms is a first attempt at an alternative way of measuring performance and value.

A Fuzzy Expert System for Solving Real-Option Decision Processes

This paper presents a new approach to real options. The current options-based models have provided new insights into capital-budgeting decisions. Unfortunately they are not widely used by corporate managers and practitioners as they are formally complex, rather difficult to understand and rest on strong implicit assumptions that considerably limit their scope of application. We propose a possible alternative by using a fuzzy expert system, on the basis of Mastroleo, Facchinetti and Magni (2001). We draw up a decision tree with multiple uncertain variables affecting the value of an investment opportunity, consisting of a defer option, a growth option, an abandonment option. Some simulations are conducted to test the economic soundness of the model as well as its consistency with the current models in the literature. A rather refined study can be accomplished by showing how inputs and outputs of the model interrelate one another.

Vagueness evaluation of the crisp output in a fuzzy inference system

Fuzzy models generally provide an output characterized by vagueness, which is expressed through a solution fuzzy set. In many applications, the response of the model is transformed in a crisp value through some defuzzification methods for solution fuzzy region, thus losing its fuzziness. Only to preserve a few indications of its vagueness, some indices summarizing the spread of the output membership function could be used to associate them with the crisp output, such as its standard deviation, the quartile deviation, the coefficients of skewness and kurtosis. The behaviour of such indices is examined in a large number of possible, though unlikely, output solutions and in an application of a fuzzy inference system for evaluating university teaching activity. The results seem to suggest that the 20-80 mid-percentile range could be a good measure of the vagueness dispersion, while the coefficient of skewness could provide a useful indication about the asymmetry of the solutions shape. Moreover, a rough estimate of dispersion was obtained from a triangle approximating the solution fuzzy region because the results were straightforwardly deduced from formulae involving the abscissae of its vertices. The results generally appear to underestimate the true values of the standard deviations; the 15-85 mid-percentile range of the approximating triangle seemed to be a more suitable rough appraisal of fuzzy output dispersion.

International market selection for small firms: a fuzzy-based decision process

Purpose – This study aims to build and test an International Market Selection (IMS) decision process method that is able to capture, within a small firm’s risk-averse setting, the entrepreneurs experience, reduce cognitive biases, and preserve the flexibility of the decision, by combining the advantages of systematic and behavioural-based international market selection approaches. Design/methodology/approach – The unit of analysis is the IMS decision process of a small firm venturing abroad. We adopt a ranking approach based on three-step screening. We assess the markets through a multi-criteria approach with a wider set of variables aggregated within a tree-shaped model. To obtain the ranking, we use a Fuzzy Expert System (FES) as an evaluative tool. Findings – The results show that the proposed decision method is consistent with the entrepreneur’s strategic orientation and experience, while preserving the flexibility requested for decision-making in small firms. Unlike traditional behavioural IMS appro...

Evaluation and interval approximation of fuzzy quantities

In this paper we present a general framework to face the problem of evaluate fuzzy quantities. A fuzzy quantity is a fuzzy set that may be non normal and/or non convex. This new formulation contains as particular cases the ones proposed by Fortemps and Roubens [7], Yager and Filev [12, 13] and follows a completely different approach. It starts with idea of “interval approximation of a fuzzy number” proposed, e.g., in [4, 8, 9].

A fuzzy approach to the geography of industrial districts

Building on Istat [5], Brusco and Paba [4] developed a mathematical algorithm which tries to identify the number and the importance of Italian industrial districts. Unfortunately, this algorithm is too rigid and it rules out some important small-firm, specialized local industries. To solve this problem, we propose a Fuzzy System. We obtain two main results. ( l ) With the fuzzy approach, most of the industrial districts identified in the current literature are still included, but it is now possible to recover some important local production systems ruled out by the crisp approach. (2) The score obtained allows us to rank, sector by sector, all the industrial districts according to their quantitative importance and to their adherence to the characteristics emphasized in the literature, whereas the crisp approach says only yes or not.

Measuring intellectual capital in a firm belonging to a strategic alliance

Purpose – The purpose of this paper is to propose a method to measure intellectual capital (IC) in firms involved in strategic alliances, an area that has received scant attention in the literature, as existing research is focused mainly on organizational level mainly and increasingly on macro-level unit such as regions or nations. There are very few works at the meso-level (i.e. alliances, clusters), and the paper aims to fill this void, by providing researchers and practitioners with a tool capable of combining measurement and management aims, developed at organizational level with the active participation of the researchers. Design/methodology/approach – The method of analysis is based on a model formalized through a fuzzy expert system (FES). The FES are able to merge the capabilities of an expert system to simulate the decision-making process with the vagueness typical of human reasoning, maintaining the ability to still have a numeric value as a response. Its construction requires the participation ...

A Fuzzy Way to Measure Quality of Work in a Multidimensional Perspective

This paper focuses on the definition and measurement of quality of work (QL) by using a multidimensional approach, based on fuzzy logic. The multidimensional nature of quality of work has been widely acknowledged in economic and sociological literature and attempts at measuring its different dimensions can be found at European level in the work carried out by the European Foundation for the Improvement of living and working conditions. The European Commission and the International Labour Office have also identified different dimensions for quality of work and proposed new indicators to measure them. In this paper an attempt is made to maintain the complexity of the quality of work concept by using a technique that allows measurement without introducing too strong assumptions and makes the rules for judging the different dimensions of QL and their interactions explicit.

Capability and Functionings: A Fuzzy Way to Measure Interaction between Father and Child

This paper aims at analyzing the building of social interaction a relevant dimension in the description and conceptualization of child well being by using the capability approach. In this paper we deal with a special dimension of this capability that involves the capability of interaction between father and child. We will try to put in relation and to come to a measure of different factors that can affect its development. We propose a fuzzy expert system to measure this capability both at a theoretical and empirical level. In the applied part of the paper we use a data set based on a ISTAT (Italian National Statistical Office) multipurpose survey on family and on children condition in Italy to recover information on children’s education, the socio-demographic structure of their families, child care provided by relatives and parents according to the type of activities in which the children are involved.