Natalis Christian
Faculty of Business and Management, Universitas Internasional Batam, Indonesia

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Relevant financial distress model for health, technology, transportation, and tourism sectors in the era of Covid-19 Edi Edi; Natalis Christian; Ruby Shafira
Journal of Innovation in Business and Economics Vol. 8 No. 02 (2024): Journal of Innovation in Business and Economics
Publisher : Faculty of Economics and Business, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/jibe.v8i02.29354

Abstract

This research aims to determine the models that are still relevant in predicting financial distress and rank the models from the most to least relevant. The models being compared in this research are Altman, CA-Score, Fulmer, Grover, Ohlson, Springate, Zavgren, and Zmijewski, which are the models for predicting financial distress. The novelty of this research is that it can define the Springate model as the most effective to date, while the Zavgren model is no longer relevant in predicting financial distress. The data sample of this research are companies from the health, technology, transportation, and tourism sectors that were listed on the Indonesia Stock Exchange (IDX) between 2018 and 2021. This research was conducted using purposive sampling to select the research sample. It used the SPSS program to conduct the Spearman Rank Correlation test to measure the correlation between each variable and financial distress. The results of this study show that the Zavgren model is irrelevant due to uncorrelated ratios built within the model. In contrast, Springate, Grover, Fulmer, CA-Score, and Altman models are still relevant in predicting financial distress, and the ratios in those models correlate primarily. These research results will be helpful to the firm’s management and potential