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Journal : International Journal of Business, Economics, and Social Development

Determination of Financial Distress: Firm Size as Moderating Variable Febiana, Herlin Dwi; Febriyanti, Irva Tri; Parlina, Nurhana Dhea
International Journal of Business, Economics, and Social Development Vol 5, No 4 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v5i4.666

Abstract

This study aims to test and analyze financial ratios to predict a company's financial distress, which is moderated by company size with a research population from the property and real estate sub-sector listing on the IDX. The method used was purposive sampling involving 14 companies that became data processing samples with a research range of 2020-2022. In this study, 42 data were obtained, but outliers were made, so the number of samples was 37. The SEM-PLS-based Structural Equation Model with SmartPLS 4.1.0.1 was used to analyze the data. The results of data processing state that CR, ROA, and DAR significantly affect financial distress. At the same time, company size moderates ROA and DAR regarding financial distress. However, company size does not moderate CR in terms of financial distress. Therefore, financial ratios are a benchmark to predict financial stress. Businesses can use the findings of this study to predict financial crises. The earlier the signs of financial distress can be identified; the company management will have the opportunity to find solutions to the problems faced immediately.
Determination of Financial Distress: Firm Size as Moderating Variable Febiana, Herlin Dwi; Febriyanti, Irva Tri; Parlina, Nurhana Dhea
International Journal of Business, Economics, and Social Development Vol. 5 No. 4 (2024)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v5i4.666

Abstract

This study aims to test and analyze financial ratios to predict a company's financial distress, which is moderated by company size with a research population from the property and real estate sub-sector listing on the IDX. The method used was purposive sampling involving 14 companies that became data processing samples with a research range of 2020-2022. In this study, 42 data were obtained, but outliers were made, so the number of samples was 37. The SEM-PLS-based Structural Equation Model with SmartPLS 4.1.0.1 was used to analyze the data. The results of data processing state that CR, ROA, and DAR significantly affect financial distress. At the same time, company size moderates ROA and DAR regarding financial distress. However, company size does not moderate CR in terms of financial distress. Therefore, financial ratios are a benchmark to predict financial stress. Businesses can use the findings of this study to predict financial crises. The earlier the signs of financial distress can be identified; the company management will have the opportunity to find solutions to the problems faced immediately.