Business Performance Evaluation for Tourism Factory: Using DEA Approach and Delphi Method

Abstract

The tourism industry contributes more than 10% of global GDP, and creates than 330 million jobs. Since the outbreak of COVID-19, tourism has been one of the hardest hit areas, and one of the most explosive growth sectors, in the post-COVID-19 era. This study analyses the operational efficiency of tourism factories, before and after the COVID-19 outbreak. This study develops a PADME (Product, Aesthetic, Digitalization, Management and Experience) efficiency evaluation model for the non-financial components of tourism factories. This study has also successfully developed the evaluation scale of the PADME model. In addition, with reference to studies on the operational efficiency of financial components, two output variables (turnover and net profit after tax), and three input variables (assets, R&D expenses, and employees) were set, and the efficiency of the PADME model was calculated. The data envelopment analysis (DEA) approach was used to measure the operational efficiency of tourism factories. The empirical research goals of this study are focused on 12 listed companies in Taiwan, with operational efficiency before and after COVID-19 analyzed in relation to their general and individual analyses. The conclusions of this study lead to both enlightening and practical management implications. Academically, this study fills a gap in the research on operational efficiency of tourism factories in the tourism industry.