Key performance indicators and the balanced scorecard at the Luxury Brand Hotels of Pestana Group

Traditional approaches to evaluate performance in hotels, have mainly used financial measures. Building on Speckbacher et al. (2003), this Work Project aims to design and propose a Balanced Scorecard Type II as a performance measurement/management system for the hospitality industry based on data collected at the Luxury Brand Hotels of Pestana Group. The main contribution is to better align the vision, strategy and financial and non-financial performance measures in this category of hotels, in particular those of Pestana Group, and by doing so, lead their managers to focus on what is really critical and, consequently improve the overall performance.

The relationship between the education level of successor's and the firm performance in German publicly listed family firms- an empirical analysis

The purpose of this thesis is to investigate how far the education level of the second or third generation of publicly traded German family firms affects the post-succession firm performance. By conducting a correlational and regression design, the aim is to examine how several variables influence the performance of family firms. Performance measures, for example ROA and Tobin’s q and variables, like Education level and succession periods, examine analytically that a positive succession trend will occur. However, with the used model, only a less rigid model shows empirical evidence.

Measuring the impact of short and lending practices using the DGTW benchmarks

Mutual fund managers increasingly lend their holdings and/or use short sales to generate higher returns for their funds. This project presents a first look into the impact these practices on performance using the performance measures: i) Characteristic Selectivity (CS), the ability of the fund's managers to choose stocks that outperform their benchmarks; ii) Characteristic Timing (CT), the ability of the manager to time the market; iii) and Average Style (AS), the returns from funds systematically holding stocks with certain characteristics. These returns are computed through the DGTW benchmarks. The effect of other variables that have also been shown to impact fund’s returns – total net assets under management, investment styles, turnover and expense ratios – will also be analyzed. I find that managers who use short-sales do not exhibit better stock picking abilities than those who do not, while mutual funds that lend do present higher CS returns. In addition, while lending is not significant for the total performance of a fund, the employment of short-sales and of both short-sales and lending has a negative impact on the fund’s performance.