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All Journal Journal of Governance Risk Management Compliance and Sustainability
Zulkarnain, Abdul Malik
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Environmental Science Social Sciences Other

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Cigarette Company Classification and Environmental Uncertainty with Risk Management Mediation in Predicting Excise Tax Returns Zulkarnain, Abdul Malik; Wati, Lela Nurlaela; Wibowo, Martino
Journal of Governance Risk Management Compliance and Sustainability Vol. 4 No. 1 (2024): April Volume
Publisher : Center for Risk Management & Sustainability and RSF Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31098/jgrcs.v4i1.2247

Abstract

This research was conducted on the basis of the fact that the amount of excise returns as a deduction from state revenues from the excise sector is fluctuating and tends to increase over the last five years from 2018 to 2022. This research aims to conduct an analysis and obtain empirical evidence regarding the influence of Cigarette Company Classification on excise returns through the implementation of management. risks and the influence of Environmental Uncertainty on excise returns through the application of Risk Management. This research falls into the realm of quantitative research that adheres to a causality approach, the focus of which is testing cause-and-effect relationships between variables. Data collection and analysis were performed using quantitative methods, with a statistical testing approach through path analysis. The source of information used in this research comes from secondary data, namely financial report data from the Directorate General of Customs and Excise and Risk Management Values in the form of profiling tobacco products companies from 2015 to 2022. This research is different from previous research and shows a higher level of originality. because it uses Risk Management variables as mediators and utilizes a unique unit of analysis by adopting indicators of tobacco production capacity and the size of cigarette company capital ownership as a method for measuring company size variables.
Co-Authors Martino Wibowo Wati, Lela Nurlaela