Ukuran Perusahaan Di Dalam Memoderasi Struktur Modal Terhadap Kinerja Perusahaan: Studi Pada Perusahaan Sektor Transportasi Dan Logistik Di Bursa Efek Indonesia
UKURAN PERUSAHAAN DI DALAM MEMODERASI STRUKTUR MODAL TERHADAP KINERJA PERUSAHAAN: STUDI PADA PERUSAHAAN SEKTOR TRANSPORTASI DAN LOGISTIK DI BURSA EFEK INDONESIA
Abstract
ABSTRACTThe transportation and logistics sector is a strategic part of the Indonesian economy, characterized by high asset intensity and a high fixed-cost structure. In the post-COVID-19 period (2021–2025), most publicly listed companies in this sector continued to bear debt burdens resulting from crisis-era restructuring, while global inflationary pressures and fuel price fluctuations impacted their financing structures. This study aims to analyze the impact of capital structure (Debt-to-Equity Ratio/DER and Debt-to-Assets Ratio/DAR) on corporate performance (Return on Assets/ROA and Return on Equity/ROE), using firm size (natural logarithm of total assets) as a moderating variable and the Current Ratio (CR) as a control variable. The sample comprises 33 transportation and logistics companies listed on the Indonesia Stock Exchange during the 2021–2025 period, selected via purposive sampling. Data Were analyzed using panel data regression with a Moderated Regression Analysis (MRA) approach. The results indicate that capital structure, firm size, the moderation interaction, and CR do not collectively have a significant effect on ROA, yet they do significantly affect ROE. Individually, DER has a significant negative effect on ROE but not on ROA, whereas DAR shows no significant effect on either performance metric. Firm size acts as a pure moderator, intensifying the negative impact of DAR on ROA and DER on ROE, and reversing the direction of DAR's impact on ROE from negative to positive for large firms. These findings highlight the importance of managing leverage with due regard for business scale in this capital-intensive sector.
Keywords: capital structure; corporate performance; firm size; panel data regression; transportation and logistics sector
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