Browsing by Issue Date, starting with "2023-11-08"
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- Future travel intentions in light of risk and uncertainty: An extended theory of planned behaviorPublication . Erul, Emrullah; Woosnam, Kyle Maurice; Salazar, John; Uslu, Abdullah; Santos, José António C.; Sthapit, EroseCOVID-19 has affected travel and will undoubtedly impact how people view travel and future intentions to travel as we adjust to life moving forward. Understanding how people arrive at these travel intentions will be paramount for managers and planners in determining how best to reactively and proactively plan for tourism, especially considering perceived risk and uncertainty related to COVID-19. By extending the theory of planned behavior, this study aims to examine the relationship between perceived risk, perceived uncertainty, subjective norms, attitudes about future travel, and perceived behavioral control in explaining individuals’ intentions to travel in the near future. This study employed a quantitative research method, and data were gathered using an online questionnaire distributed through Qualtrics from a sample of 541 potential travelers (representing residents of 46 US states) from 23 June 2020 to 1 July 2020. Of the eight hypotheses tested, four were supported. Surprisingly, neither perceived risk nor uncertainty were significant within the model. Subjective norms significantly predicted both attitudes about traveling and perceived behavioral control. Subjective norms and perceived behavioral control, in turn, explained a moderate degree of variation in individuals’ intentions to travel. Study implications, limitations, and future research suggestions are offered. One of the main managerial implications includes the need for destinations to be proactive and focus on intentional planning for sustainable tourism.
- Fuzzy algorithm applied to factors influencing competitiveness: A case study of Brazil and Peru through affinities theoryPublication . Barcellos-Paula, Luciano; Rezende, Aline; Alvares, Daniela FantoniInnovation plays a crucial role in the economy of nations worldwide. In Latin America, countries foster competitiveness through public and private incentives to support innovation. Moreover, entrepreneurship incentives seek to improve countries’ performance, although factors such as low business growth rates and informality can compromise it. Despite the efforts, there are several difficulties in achieving competitiveness, and few studies in developing countries. Therefore, the article explores the relationship between the factors that influence competitiveness, especially the role of innovation and entrepreneurship in Brazil and Peru. The research uses quantitative-qualitative methodology through modeling and simulation and a case study. The authors use the Affinities Theory to verify the relationship between the indicators that make up the competitiveness landscape and its most significant and attractive factors, adapting the methodology established by the International Institute for Management Development (IMD) World Competitiveness ranking. As a result, this algorithm allows us to know the relationships between five factors of economic attractiveness and four competitiveness indicators. As its main contributions, the study advances the frontier of knowledge about innovation and entrepreneurship, as few studies explore competitiveness in developing countries. Also, it offers a detailed explanation of the application of this algorithm, allowing researchers to reproduce this methodology in other scenarios. Practically, it might support policymakers in formulating development strategies and stimuli for business competitiveness. In addition, academic and business leaders can strengthen university-business collaboration with applied research in innovation and entrepreneurship. One limitation would be the number of countries participating in the research. The authors suggest future lines of research.
- Modelling risk for commodities in Brazil: An application for live cattle spot and futures pricesPublication . Alcoforado, Renata G.; Egídio dos Reis, Alfredo D.; Bernardino, Wilton; Santos, José António C.This study analyses a series of live cattle spot and futures prices from the Boi Gordo Index (BGI) in Brazil. The objective is to develop a model that best portrays this commodity’s behaviour to estimate futures prices more accurately. The database created contains 2010 daily entries in which trade in futures contracts occurs, as well as BGI spot sales in the market, from 1 December 2006 to 30 April 2015. One of the most important reasons why this type of risk needs to be measured is to set loss limits. To identify patterns in price behaviour in order to improve future transaction results, investors must analyse fluctuations in asset values for longer periods. Bibliographic research reveals that no other study has conducted a comprehensive analysis of this commodity using this approach. Cattle ranching is big business in Brazil given that in 2021, this sector moved BRL 913.14 billion (USD 169.29 billion). In that year, agribusiness contributed 26.6% of Brazil’s total gross domestic product. Using the proposed risk modelling technique, economic agents can make the best decision about which options within these investors’ reach produce more effective risk management. The methodology is based on Holt–Winters exponential smoothing algorithm, autoregressive integrated moving-average (ARIMA), ARIMA with exogenous inputs, generalised autoregressive conditionally heteroskedastic and generalised autoregressive moving-average (GARMA) models. More specifically, five different methods are applied that allow a comparison of 12 different models as ways to portray and predict the BGI commodity behaviours. The results show that GARMA with order c(2,1) and without intercept is the best model. Investors equipped with such precise modelling insights stand at an advantageous position in the market, promoting informed investment decisions and optimising returns.