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- The Relevance of Tourism in Financial Sustainability of HotelsPublication . Mucharreira, Pedro Ribeiro; Antunes, Marina Godinho; Abranja, Nuno; Texeira Fernandes Justino, Maria Do Rosário; Texeira Quirós, JoaquíntThe macroeconomic context is an extremely important factor for the growth and development of compa-nies, and for the hotel sector, being expected that the performance of hotel companies should be stronglydependent on the conditions and the macroeconomic environment where they are inserted.Using a panel data methodology, this research analyzed the growth of hotel companies, the size ofhotel companies, total number of guests in the sector, total revenues, and total income of the sector, withthe corporate indebtedness variable, given by total liabilities/total assets ratio. It is concluded that 91.5%of the average variation in the corporate indebtedness is determined by the remaining variables of thestudy, with the remaining 8.5% variation explained by other factors not specified. It is also concluded thatthere is no statistically significant difference between the values of the corporate size variable throughoutthe study, existing a negative relation between this variable and the variables corporate size, number ofguests, and tourism revenue, and a positive relation with the variables corporate growth rate and totalincome of the hospitality industry.This research provides a great contribution and enrichment of existing literature because with adetailed knowledge concerning these topics, managers’ can base their decision making on these causeand effect relationships, looking for the best decisions that will provide the highest profitability.
- Survey data preprocessing for optimal modelling through ANNs applied to management environmentsPublication . Texeira Quirós, Joaquín; Texeira Justino, Maria do Rosário; Gonçalves, António José; Godinho Antunes, Marina; Ribeiro Mucharreira, PedroSurveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.
- The role of management accounting indicators in performance assessment of Portuguese higher education institutionsPublication . Mucharreira, P. R.; Godinho Antunes, Marina; Justino, M; Texeira Quirós, JoaquínThe assessment of quality and performance in Higher Education Institutions (HEIs) is a multifaceted task, which needs a holistic approach that encompasses various dimensions. This article focuses on the role of some management accounting indicators, namely, the relevance of both financial and nonfinancial indicators when evaluating the quality and performance of HEIs. In today's era of globalization, HEIs continually grapple with ongoing challenges. Competitive landscapes are increasingly taking shape across various markets, elevating the creation of value and financial sustainability as critical objectives within their purview. HEIs performance has undergone significant transformation, given that these educational establishments are now compelled to seek alternative funding sources, aligning more closely with the characteristics of a competitive market. As such, HEIs aspiring to establish a strong presence in these markets must direct their attention toward strategic objectives that ensure financial sustainability, much like organizations in other sectors. For this purpose, HEIs must develop an in-depth understanding of their business processes, adopting a management approach that allows them to assess their quality and performance, both at the national and international levels. These institutions aim to bolster their competitiveness by implementing management strategies centered on quality and financial sustainability. These strategies incorporate performance measurement systems encompassing a wide array of financial and non-financial metrics. The literature highlights the advantages of nonfinancial performance measures, emphasizing their particular focus on long-term perspectives, which contribute to enhanced organizational performance. Such measures facilitate comprehension of the interplay between various strategic objectives, enhance communication between employee actions and defined goals, and aid in resource allocation and priority setting relative to those objectives. Regarding the methodology, the data were obtained through an online survey developed by the authors to evaluate the different dimensions of the proposed research model, using for this purpose a sample of convenience constituted by members of the management boards of Portuguese universities and polytechnics. In the treatment of quantitative data, a structural equation model (SEM) was used through the SPSS software (Statistical Package for the Social Sciences), to investigate the possible relationships between the different dimensions incorporated in the model. The main conclusions of the study, considering the conceptions of the respondents, point towards that the use of financial indicators significantly improves the financial performance of HEIs (B=0.199, p=0.006) and, on the other hand, the use of non-financial indicators significantly improves the operational (B=0.487, p <0.001), financial (B=0.265, p <0.001) and market (B=0.479, p <0.001) performance of HEIs.