The Influence of Liquidity Ratios, Leverage, Profitability and Activity on Financial Distress of Infrastructure Companies in the Building Construction Subsector for the Period 2018 – 2022

Siti Ruhanni Ummayah, Dede Hertina
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Abstract

This research aims to determine the effect of liquidity, leverage, profitability and activity ratios on the financial distress of infrastructure companies in the building construction subsector listed on the Indonesia Stock Exchange in 2018 - 2022. The approach used is quantitative research. This research uses secondary data accessed through the official website of the Indonesia Stock Exchange with a population of 22 companies and a sample of 16 companies selected using the purposive sampling method and obtaining a sample of 80 observations. The data analysis technique uses panel data regression analysis with the Eviews9 test tool. The research results show that the Liquidity Ratio as proxied by the Current Ratio has a positive effect on financial distress, the Leverage Ratio as measured by the Debt to Asset Ratio (DAR) has a negative effect on financial distress, the Profitability Ratio as measured by Return on Assets (ROA) has a positive effect on financial distress, while the Activity Ratio which is proxied by Total Asset Turnover (TATO) does not affect financial distress. The calculation technique uses the Altman Z-Score method and financial ratio calculations. Therefore, researchers recommend utilizing this test model to predict financial distress because the accuracy that can be given is quite good so that companies can anticipate financial difficulties.
2018 - 2022 年期间流动性比率、杠杆率、盈利能力和活动对建筑施工子行业基础设施公司财务困境的影响
本研究旨在确定流动性、杠杆率、盈利能力和活动比率对 2018 - 2022 年在印度尼西亚证券交易所上市的建筑施工子行业基础设施公司财务困境的影响。采用的方法是定量研究。本研究使用通过印尼证券交易所官方网站获取的二手数据,研究对象为 22 家公司,采用目的性抽样法选取 16 家公司作为样本,获得 80 个观测值。数据分析技术使用 Eviews9 测试工具进行面板数据回归分析。研究结果表明,用流动比率(Current Ratio)表示的流动比率对财务困境有正向影响,用资产负债率(DAR)表示的杠杆比率对财务困境有负向影响,用资产收益率(ROA)表示的盈利比率对财务困境有正向影响,而用总资产周转率(TATO)表示的活动比率对财务困境没有影响。计算技术采用 Altman Z 评分法和财务比率计算法。因此,研究人员建议利用这一测试模型来预测财务困境,因为其准确性相当高,企业可以提前预知财务困境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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