Andrea Ellero

The optimal level solutions method

Abstract In this paper the method of optimal level solutions, introduced by Cambini and Martein for fractional programming problems [5, 8], is developed in a general framework. In such a framework all the algorithms based on the optimal level solutions approach stated so far in literature can be easily embedded and their properties proved at once.

Short-medium term tourist services demand forecasting with Rough Set Theory

Abstract The need to understand more in depth tourism demand trends and the aim to provide the tourist operators and the policy makers with innovative predicting tools are the key points of our research. In tourism literature predicting tourist demand has become a flourishing theme of research at a macroeconomic level, while the study is still lacking at a microeconomic level. Our attention is focused on analyzing Italian tourists’ behaviours on the basis of statistical surveys on households, life conditions, incomes, consumptions, travels and holidays. Data analysis is performed by means of Rough Sets Theory, a Data Mining technique which, unlike more traditional time-series and econometric models, can easily manage categorical variables. Data were provided by GfK Eurisko and concern social, cultural and behavioural trends in Italy, collected by means of a psychographic survey. Some interesting relations between consumer behaviours and corresponding tourism consumption choices are obtained in terms of decision rules.

The role of retailer's performance in optimal wholesale price discount policies

The main goal of this paper is to model the effects of wholesale price control on manufacturers profit, taking explicitly into account the retailers sales motivation and performance. We consider a stylized distribution channel where a manufacturer sells a single kind of good to a single retailer. Wholesale price discounts are assumed to increase the retailers motivation thus improving sales. We study the manufacturers profit maximization problem as an optimal control model where the manufacturers control is the discount on wholesale price and retailers motivation is one of the state variables. In particular in the paper we prove that an increasing discount policy is optimal for the manufacturer when the retailer is not efficient while efficient retailers may require to decrease the trade discounts at the end of the selling period. Computational experiments point out how the discount on wholesale price passed by the retailer to the market (pass-through) influences the optimal profit of the manufacturer.

Minimization of communication expenditure for seasonal products

We consider a firm that sells seasonal goods. The firm seeks to reach a fixed level of goodwill at the end of the selling period, with the minimum total expenditure in promotional activities. We consider the linear optimal control problem faced by the firm which can only control the communication expenditure rate; communication is performed by means of advertising and sales promotion. Goodwill and sales levels are considered as state variables and word-of-mouth effect and saturation aversion are taken into account. The optimal control problem is addressed by means of the classical Pontryagin Maximum Principle and the solution can be easily found solving, in some cases numerically, a system of two non linear equations. Moreover, a parametric analysis is performed to understand how the total expenditure in communication should be divided between advertising and sales promotion.

Are traditional forecasting models suitable for hotels in Italian cities

Purpose – The aim of this paper is to assess the performance of different widely-adopted models to forecast Italian hotel occupancy. In particular, the paper tests the different models for forecasting the demand in hotels located in urban areas, which typically experience both business and leisure demand, and whose demand is often affected by the presence of special events in the hotels themselves, or in their neighborhood. Design/methodology/approach – Several forecasting models that the literature reports as most suitable for hotel room occupancy data were selected. Historical data on occupancy in five Italian hotels were divided into a training set and a test set. The parameters of the models were trained and fine-tuned on the training data, obtaining one specific set for each of the five Italian hotels considered. For each hotel, each method, with corresponding best parameter choice, is used to forecast room occupancy in the test set. Findings – In the particular Italian market, models based on bookin...

Checking financial markets via Benford's law: the S&P 500 case

In general, in a given financial market, the probability distribution of the first significant digit of the prices/returns of the assets listed therein follows Benford’s law, but does not necessarily follow this distribution in case of anomalous events. In this paper we investigate the empirical probability distribution of the first significant digit of S&P 500’s stock quotations. The analysis proceeds along three steps. First, we consider the overall probability distribution during the investigation period, obtaining as result that it essentially follows Benford’s law, i.e., that the market has ordinarily worked. Second, we study the day-by-day probability distributions. We observe that the majority of such distributions follow Benford’s law and that the non-Benford days are generally associated to events such as the Wall Street crash on February 27, 2007. Finally, we take into account the sequences of consecutive non-Benford days, and find that, generally, they are rather short.

The Small World of Pheromone Trails

In this paper we consider

A model for the marketing of a seasonal product with different goodwills for consumer and retailer

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A computational comparison between algorithms for linear fractional programming

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Monotonicity and Symmetry of IFPD Bayesian Confirmation Measures

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