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- Determinants of firm profitability: the case of portuguese meat manufacturing sector between 2014 – 2020Publication . Nguyen, Le Quyen; Alves, Jorge; Fernandes, António B.; Nunes, Alcina; Pereira, João Paulo; Ribeiro, Nuno A.; Fernandes, Paula OdeteThe research attempts to provide insights into the profitability of Portuguese meat manufacturing sector and its determining factors. A balanced data panel of 233 Portuguese firms between 2014 – 2020 is examined using static and dynamic panel estimators. Return on Assets is a proxy of firm profitability. Explanatory variables involve the firm characteristics, industrial attributes, and external environment. The results show that the average profitability of the Portuguese meat manufacturing sector is relatively low with a significant disparity in performance across the firms. Next, the paper reveals influencing factors associated with the sector´s success, making meat manufacturing the most valued activity in Portuguese agricultural production. Firm characteristics are highly related to profitability while macro factors show no significant impacts on the firms´ performance. Hence, the study provides useful information for policymakers and business managers in introducing measures and policies to improve the firms´ profitability.
- Analysing and forecasting tourism demand in Vietnam with artificial neural networksPublication . Nguyen, Le Quyen; Fernandes, Paula O.; Teixeira, João PauloVietnam has experienced a tourism boom over the last decade with more than 18 million international tourists in 2019, compared to 1.5 million twenty-five years ago. Tourist spending has translated into rising employment and income for the tourism sector, making it the key driver to the socio-economic development of the country. Facing the COVID-19 pandemic, Vietnam´s tourism has suffered extreme economic losses. However, the number of international tourists is expected to reach the pre-pandemic levels in the next few years after the COVID-19 pandemic subsides. Forecasting tourism demand plays an essential role in predicting future economic development. Accurate predictions of tourism volume would facilitate decision-makers and managers to optimize resource allocation as well as to balance environmental and economic aspects. Various methods to predict tourism demand have been introduced over the years. One of the most prominent approaches is Artificial Neural Network (ANN) thanks to its capability to handle highly volatile and non-linear data. Given the significance of tourism to the economy, a precise forecast of tourism demand would help to foresee the potential economic growth of Vietnam. First, the research aims to analyse Vietnam´s tourism sector with a special focus on international tourists. Next, several ANN architectures are experimented with the datasets from 2008 to 2020, to predict the monthly number of international tourists traveling to Vietnam including COVID-19 lockdown periods. The results showed that with the correct selection of ANN architectures and data from the previous 12 months, the best ANN models can forecast the number of international tourists for next month with a MAPE between 7.9% and 9.2%. As the method proves its forecasting accuracy, it would serve as a valuable tool for Vietnam´s policymakers and firm managers to make better investment and strategic decisions to promote tourism after the COVID-19 situation.
- Analyzing and forecasting tourism demand in Vietnam with artificial neural networksPublication . Nguyen, Le Quyen; Fernandes, Paula Odete; Teixeira, João PauloVietnam has experienced a tourism expansion over the last decade, proving itself as one of the top tourist destinations in Southeast Asia. The country received more than 18 million international tourists in 2019, compared to only 1.5 million twenty-five years ago. Tourist spending has translated into rising employment and incomes for Vietnam’s tourism sector, making it the key driver to the socio-economic development of the country. Following the COVID-19 pandemic, only 3.8 million international tourists visited Vietnam in 2020, plummeting by 78.7% year-on-year. The latest outbreak in early summer 2021 made the sector continue to hit bottom. Although Vietnam’s tourism has suffered extreme losses, once the contagion is under control worldwide, the number of international tourists to Vietnam is expected to rise again to reach pre-pandemic levels in the next few years. First, the paper aims to provide a summary of Vietnam’s tourism characteristics with a special focus on international tourists. Next, the predictive capability of artificial neural network (ANN) methodology is examined with the datasets of international tourists to Vietnam from 2008 to 2020. Some ANN architectures are experimented with to predict the monthly number of international tourists to the country, including some lockdown periods due to the COVID-19 pandemic. The results show that, with the correct selection of ANN architectures and data from the previous 12 months, the best ANN models can be forecast for next month with a MAPE between 7.9% and 9.2%. As the method proves its forecasting accuracy, it would serve as a valuable tool for Vietnam’s policymakers and firm managers to make better investment and strategic decisions.
- Exploring factors influencing firm profitability: the case of the meat industry in PortugalPublication . Nguyen, Le Quyen; Fernandes, António B.; Nunes, Alcina; Pereira, João Paulo; Ribeiro, Nuno A.; Fernandes, Paula Odete; Alves, JorgeThe study examines the profitability of the meat industry in Portugal and its determining factors. Annual financial data of the Portuguese firms are col- lected from the database Analysis System of Iberian Balance Sheets from 2014 to 2020. Based on 1,631 observations, one dependent variable and four groups of independent variables are tested using estimation methods, i.e., Pooled Ordinary Least Square and Fixed Effects and Generalised Method of Moments. The empir- ical evidence shows that firm size and tangible assets have significant impacts on firm profitability. Besides, profitability is persistent, implying that the continuous nature of profitability over time provides a firm with an advantage in capturing new opportunities to improve its performance. However, external factors show no effects on firm profitability. In general, the capability to manage assets and liabili- ties flexibly is highly related to profitability, enabling the firms to prosper after the financial crisis. Therefore, the paper provides useful information for stakeholders in considering solutions to improve firms ́ resilience and profitability while facing unfavourable economic conditions.