Computerized management of tourism marketing information

This article discusses the benefits of applying computers to the management of marketing Information by the tourism industry. It looks at the role of regional tourism associations, and the monitoring of promotional programmes and details how such a system operates and draws together its potential applications.     

Retail Leasing: The Determinants of Shopping Center Rents

The determinants of lease rentals are of fundamental importance to real estate researchers and practitioners. Retail leases are unique in that they typically have two rental components: a base rent and an "overage" rent equal to a percentage of the tenant's gross sales above some threshold level. In this paper, we develop and test a simple cash flow model of retail lease valuation that predicts that base rents are lower with higher percentage rent rates and are higher with greater threshold levels of sales. Using a sample of shopping center leases, regression analysis indicates that these tradeoffs are observed in the market.     

Financial distress,financial constraint and investment decision: Evidence from Brazil

This paper analyses the presence of financial constraint in the investment decisions of 367 Brazilian firms from 1997 to 2004, using a Bayesian econometric model with group-varying parameters. The motivation for this paper is the use of clustering techniques to group firms in a totally endogenous form. In order to classify the firms we used a hybrid clustering method, that is, hierarchical and non-hierarchical clustering techniques jointly. To estimate the parameters a Bayesian approach was considered. Prior distributions were assumed for the parameters, classifying the model in random or fixed effects. Ordinate predictive density criterion was used to select the model providing a better prediction. We tested thirty models and the better prediction considers the presence of 2 groups in the sample, assuming the fixed effect model with a Student t distribution with 20 degrees of freedom for the error. The results indicate robustness in the identification of financial constraint when the firms are classified by the clustering techniques.