Stable financial operation is the essential factor for the sustainable development of the cruise tourism industry. The cruise industry was one of the fastest growing before the COVID-19 pandemic. The industry is capital intensive, has an enormous supply chain, serves to improve many ports-of-call economies, hires an immense quantity of people worldwide, and has a substantial economic contribution worldwide, especially in coastal countries or areas. COVID-19 has disrupted what had been an unending development of growth and success for the cruise industry. This study aims to analyze the financial performance of the worldwide cruise industry and realize the trends in the cruise tourism industry. The study examines the statistical data of the top three cruise companies that account for nearly 74.6–91.8% of the worldwide cruise tourism for 2015–2021. The financial analysis includes economic structure, solvency, operating ability, profitability, and financial leverage. We also analyze the economic indicators of the top three cruise companies with frequency analysis, correlation analysis, regression analysis, and the financial management risks of the top three cruise companies with the Z-Score Model. In addition, the study organizes and summarizes the impact of the COVID-19 pandemic on global cruise tourism. The study found that from mid-March 2020 until July 2021, the temporary suspension decreased passenger numbers, operating losses, and stock price losses. The research results confirm that the COVID-19 pandemic has caused the suspension of cruise ships worldwide. The break has led to a sharp drop in the number of cruise passengers, resulting in a significant decrease in operating income and profits of cruise companies, and the debt-to-assets ratio and leverage ratio have increased significantly. The excessive debt ratio will affect the sustainable operation of cruise companies and the sustainable development of the cruise industry. Because of the enormous impact and damage caused to the cruise industry by the COVID-19 pandemic, it is suggested that the cruise industry should take effective preventive strategies against highly contagious infectious diseases, deploy these strategies ahead of time, and strengthen the resilience and pandemic prevention ability of the cruise industry, to achieve the goal of sustainably developing the cruise industry.

The consumer price index (CPI) is one of the most important macroeconomic indicators for determining inflation, and accurate predictions of CPI changes are important for a country's economic development. This study uses multivariate linear regression (MLR), support vector regression (SVR), autoregressive distributed lag (ARDL), and multivariate adaptive regression splines (MARS) to predict the CPI of the United States. Data from January 2017 to February 2022 were randomly selected and divided into two stages: 80 % for training and 20% for testing. The US CPI was modeled for the observed period and relied on a mix of elements, including crude oil price, world gold price, and federal fund effective rate. Evaluation metrics—mean absolute percentage value, mean absolute error, root mean square error, R-squared, and correlation of determination—were employed to estimate forecasted values. The MLR, SVR, ARDL, and MARS models attained high accuracy parameters, while the MARS algorithm generated higher accuracy in US CPI forecasts than the others in the testing phase. These outputs could support the US government in overseeing economic policies, sectors, and social security, thereby boosting national economic development.

Due to its unpredictability, the novel coronavirus (COVID-19) pandemic has changed the global business climate and commercial management practices in unprecedented ways. As a direct result of the pandemic, the hospitality and tourism sectors have shut down, and business failure rates have occurred exponentially. The franchise hospitality industry has experienced significant impact and challenged a basic understanding of knowledge management (KM) implementation in the face of the COVID-19 outbreak. A strategic KM implementation practice can not only guide a large-scale operation, but also adjust an organization’s performance and competitiveness. The purpose of this study is to examine the influential criteria of success through effective KM implementation and to predict the probability of successful KM in a post-pandemic era. The conceptual framework for KM applies an analytic hierarchical prediction model reliant upon consistent fuzzy preference relations to assist the franchise hospitality sector’s consciousness of the influential criteria. An empirical case study is used to apply pairwise comparisons used to determine the priority weights and two possible outcomes. The case study will assist franchise organizations to analyze whether or not to implement KM, interdict application, or adopt revised actions. This assistance will enhance the success possibility of KM implementation within such a crisis environment. This study uses a case setting by assessing 15 franchises hospitality experts’ opinions in Taiwan relevant to KM implementation.

This study aims to examine the asymmetric relationship between trade openness and FDI (foreign direct investment) inflows to Vietnam by using NARDL (nonlinear autoregressive distributed lag) during the period from 1997 to 2019. Our findings show that the influence of FDI on trade openness is asymmetric in the short-run and long-run. But the influence of trade openness on FDI is symmetric in the short-run and asymmetric in the long run.

This study proposes the use of consistent fuzzy preference relations to evaluate the structure of hotel sustainable business model (HSBM) dimensions and the corresponding hierarchy of evaluation indicators, and predict the overall probability of success. As fuzzy preference relations require, a group of hotel professionals in Taiwan was asked to process pairwise comparisons using linguistic variables to determine the weights of dimensions and indicators. According to the results, finances were found to be the most important dimension, followed by human capital. The number of local cultural events in the hotel was identified as the most important indicator. The predictive values revealed the possibility for successful HSBM implementation, shedding light on the vision of sustainability for the hotel industry. The results of the present study contribute to the literature on sustainability by determining the importance and weights of dimensions and indicators for hotel business models, providing an example of the use of this strategic tool in generating and modifying sustainable business models for the hotel industry.

Crude oil price volatility impacts the global economy in general, as well as the economies of Europe and the United States in particular; it is supremely difficult to describe its tendency precisely, hence it leads to a forecasting methodology. This study aims to use the autoregressive integrated moving average (ARIMA), and seasonal autoregressive integrated moving average (SARIMA) approaches to cope with this problem in the United States and Europe. The data was gathered from the U.S. Energy Information Administration and federal research economic data (FRED) from January 2017 to September 2021. Simultaneously, values from January 2017 to March 2021, with 51 observations accounting for 90% of the total samples, were employed for the training phase, and the rest were used for the testing phase. The forecast result also indicated that the root mean square error (RMSE) and mean absolute percentage error (MAPE) values, applied by ARIMA models in Europe and the United States, have higher accurate indicators than SARIMA models. As a result, the ARIMA model achieved the best accuracy in both Europe and the USA, with ${\mathrm{MAPE}}_{\mathrm{Europe}-\mathrm{ARIMA}}$ = 0.05, and ${\mathrm{MAPE}}_{\mathrm{USA}-\mathrm{ARIMA}}=0.05$. Based on these accuracy parameters, the forecasting models appear incredibly reliable; similarly, the study results might assist governing bodies in making significant decisions, thereby accelerating socio-economic development in the world’s two largest economies.