Convex-concave effect of financial flexibility on hospitality performance: quantile regression approach

Purpose The purpose of this paper is to study the influence of financial flexibility (FF) on enterprise performance (EP) within Taiwan’s hospitality industry during the COVID-19 shock and explore whether EP varies with hospitality industry characteristics. Design/methodology/approach Secondary data of 39 Taiwan Stock Exchange-listed hospitality firms were collected from the Taiwan Economic Journal databases. Quantile regression analysis was applied to examine the FF-EP relationship Findings The results evidence that there is a U-shaped (convex) FF-EP relationship for hospitality firms in the 10th, 25th and 50th Tobin’s Q quantiles and in asset-heavy firms. For asset-light firms, FF has an inverted U-shaped (concave) effect on EP in the 90th Tobin’s Q quantile Practical implications The empirical results highlight the need for Taiwan’s hospitality industry as a whole to take rolling adjustment and optimization of FF and concentrate on liquidity risk management after the COVID-19 pandemic and for long-term sustainability. Originality/value To the best of the authors’ knowledge, this study is one of the first to examine the nonlinear FF-EP relationship in the hospitality industry of Taiwan, particularly amid the COVID-19 shock. Moreover, this study extends current literature by revealing the hospitality industry’s FF-EP relationship and highlights the importance of the pandemic crisis context.

Capital Structure, Working Capital, and Governance Quality Affect the Financial Performance of Small and Medium Enterprises in Taiwan

This study examines the impact of capital structure, working capital, and governance quality on the financial performance of small- and medium-sized enterprises in Taiwan using a sample of more than 2000 firms from the Taiwan Economic Journal (TEJ) during the 24-year period of 1995–2018. Panel data are used to create statistics for the regression model. The result shows that a firm’s capital structure, represented by the debt ratio, has a significantly negative impact on the firm’s financial measures (return on assets (ROA) and return on equity (ROE)), where the working capital, represented by the cash conversion cycle (CCC), has a negative impact and governance quality, represented by the board size, cash dividend distribution, and the percentage of directors, has different impacts.

Sentiment and Prejudice

This article describes the evolution of Edgeworth’s thought on women’s wages and on the principle of “equal pay for equal work.” We first document Edgeworth’s early works on “exact utilitarianism” as an epistemic basis for his reflections upon women’s wages. Second, we review his first writings on women’s work and wages: early mentions in the 1870s, his book reviews published in the Economic Journal, and the substantial preface he wrote for the British Association for the Advancement of Science 1904 report on Women in Printing Trades. Third, we document his 1922 British Association presidential address in relation to the burgeoning literature on women’s work and wages within political economy at the time. Finally, we show that his 1923 follow-up article on women’s wages and economic welfare constitutes an update of his “aristocratical utilitarianism” in the post–World War I context.

Investigating the Relative Performance of Bricks-and-Mortar, Clicks-and-Mortar, and Pure-Click Firms in Taiwan

The study compares the relative performance among bricks-and-mortar, clicks-and-mortar, and pure-click firms. The research model was tested in the Taiwan service industry using a Taiwan Economic Journal dataset of 1448 firms. Using regression analysis, the study provides empirical evidence that clicks-and-mortar firms outperform pure-click firms in terms of efficiency, but not better in profitability and even worse in efficiency than bricks-and-mortar firms. Pure-click firms need to improve their accounts receivable turnover ratio and total assets turnover. While the findings are not in full congruence with past studies, we provide theoretical explanations. Based on the findings, a strategic guide on going clicks and mortar is provided to practitioners.

En torno al origen del dinero

Carl Menger expuso en sus Principios de Economía Política1 una explicación del origen del dinero que forma parte de las cuatro columnas sobre las que este economista basa su entendimiento de la Economía como ciencia.2 El texto aunque es señero, está poco difundido y a pesar de ello es criticado por otros economistas. Incluso algunos de los trabajos que vamos a reseñar no se refie-ren al libro, sino a un artículo que mantiene las ideas que origi-nalmente publicó en los principios Éste documento se publicó en 1892 en Inglés, partiendo del original en Alemán (1871) en el Economic Journal. En dicho texto, Menger plantea que el dinero es producto de la selección natural, proceso que ocurre para re-solver las complicaciones relacionadas al trueque debido a que éste último requiere la coincidencia de necesidades y está funda-mentado en la valoración de uso3 de los bienes. Debía haber estas coincidencias y además una coincidencia de encuentro entre las dos personas, por lo que la realización del comercio por la vía del trueque era casi imposible. Esa imposibi-lidad, terminaría por convertirse en un serio límite a la división del trabajo, y al proceso evolutivo que se origina producto de este fenómeno que es una de las bases del sistema económico. Por supuesto, Menger está apelando a otro de los pilares de lo que conforma la Escuela Austriaca de Economía, el conocimien-to que es desigualmente distribuido, pero que puede ser trasmi-tido por la colaboración que determina la vida en sociedad. Eso también condiciona que los distintos pueblos usen como moneda diversas mercancías, y el economista austriaco usará varios ejem-plos para dejar en claro esta propuesta.

Using Deep Learning Algorithms for CPAs’ Going Concern Prediction

Certified public accounts’ (CPAs) audit opinions of going concern are the important basis for evaluating whether enterprises can achieve normal operations and sustainable development. This study aims to construct going concern prediction models to help CPAs and auditors to make more effective/correct judgments on going concern opinion decisions by deep learning algorithms, and using the following methods: deep neural networks (DNN), recurrent neural network (RNN), and classification and regression tree (CART). The samples of this study are companies listed on the Taiwan Stock Exchange and the Taipei Exchange, a total of 352 companies, including 88 companies with going concern doubt and 264 normal companies (with no going concern doubt). The data from 2002 to 2019 are taken from the Taiwan Economic Journal (TEJ) Database. According to the empirical results, with the important variables selected by CART and modeling by RNN, the CART-RNN model has the highest going concern prediction accuracy (the accuracy of the test dataset is 95.28%, and the average accuracy is 93.92%).