Internationalization, firm performance, and capital structure: an empirical study in Indonesia

Abstract

The objective of this study is to examine the impact of internationalization, firm perfo rmance, and capital structure: an empirical study in Indonesia. This research used industrial manufacturing companies listed on the Indonesian Stock Exchange over the 2012 -2016 period. The dependent variable in this study is the capital structure. Independent variables used are internationalization an d firm performance, Control variables used are size, age current ratio, tangibility, and total asset turn over. This study used multiple linear regression analysis models (two -stage least square) to test the hypothesis with a sample of 57 manufacturing companies listed on the Indonesian Stock Exchange over the 2012-2016 period. The number of observations used in this study was 285 observations at first by using classical. The study findings suggest that internationalization has a significant positive effect on relative performance based on historical target, and a significant negative effect on relative p erformance based on the industrial target. While relative performance based on historical target and relative performance based on industrial target has a significant positive effect on short term debt and private debt and also has a significant negative effect on long term debt, total debt, and public debt.

The Importance of Interfirm Networks in Enhancing Innovation Capability and Exporting in High-Tech Industry

“…Exports are expected to increase the achievement of firm performance. From research conducted in Indonesia on the manufacturing industry listed on the Indonesia Stock Exchange from 2012 to 2016, exports had a significant positive impact on firm performance based on the achievement of the firm's historical targets [45]. However, other studies have found the negative effect of exports on firm performance due to the costs of internationalization that arise [46].…”

How green credit policy shapes financial performance: Evidence from Chinese listed construction energy-saving enterprise

“…To solve the bias problems that may be caused by the omission of variables in the equation of the model, as much as possible, this study controls the effects of these variables. Ten control variables are selected: stock returns (Ret) (Wang G et al, 2021), liquid ratio (Lr) (Zhang et al, 2015), enterprise total profit growth ratio (Np) (Huo and Zhang, 2017), enterprise age (Age) (Carnahan et al, 2010), enterprise liabilities to assets (L/A) ratio (Lev) (Díaz-Fernández et al, 2015), enterprise total asset turnover ratio (Tato) (Edward and Marciano, 2019), the enterprise growth rate of net profit (Profit) (Gao et al, 2021), enterprise operating growth ratio (Revenue) (Fu and Shen, 2020), equity nature (State) (Li, 2011), and Tobin's q (Tq) (Lee et al, 2021) as control variables, and selects assets scale (Size) (Goll et al, 2008) and return on equity (Roe) (He et al, 2020) as replacement variables for the robustness test. Ret, Lr, Np, Lev, Tato, Profit, Revenue, Tq, Roe are collected from the financial annual reports of the enterprises.…”

“…The enterprise age is measured as the reporting period minus the number of years that the enterprise has been in the market (measured in months). Younger enterprises tend to be aggressive and innovative, while older enterprises usually experience organizational rigidity and reduced efficiency (Loderer and Waelchli, 2011;Edward and Marciano, 2019). Thus, enterprise age may affect financial performance by influencing the strategic decisions of the enterprise.…”