Cost of Capital, Corporate Reputation and Human Capital Disclosure: A Study of Companies in Indonesia

The purpose of this study is to test and analyze the cost of capital and reputation of companies on the Human Resources disclosure. The sample in this study consisted of 318 companies the sample criteria. This research data was analyzed using a regression model of ordinary least square (OLS) estimation technique. Based on testing, researchers found that debt costs and equity costs negatively affect human resource disclosure, while company reputation is positively related to human resource disclosure. In addition, research findings from Indonesia's largest categorized industries show that debt costs and equity costs have a significant negative impact on human capital disclosure. Meanwhile, industries that are not categorized as the largest companies in Indonesia do not show significant results in both debt costs and equity costs. This study got results cost of debt and the cost of equity to human capital disclosure is driven by companies engaged in large-scale industries. This research provides contribution, insight and reference to companies in Indonesia through the HR disclosure index as a benchmark to improve HR disclosure in the future. Also, for policymakers, this research can be a consideration for making policies that HR disclosure practices as mandatory disclosures for companies.

Authors

Institutions

Publication Details

Journal
Asian Journal of Applied Business and Management
Published
2024-11-26
DOI
https://doi.org/10.55927/ajabm.v3i4.11629
Primary Topic
Corporate Governance and Financial Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Cost of Capital, Corporate Reputation and Human Capital Disclosure: A Study of Companies in Indonesia

Setu Setyawan, Ahmad Juanda, Lia Candra Inata
Asian Journal of Applied Business and Management
Corporate Governance and Financial Management
article

Cost of Capital, Corporate Reputation and Human Capital Disclosure: A Study of Companies in Indonesia

Setu Setyawan, Ahmad Juanda, Lia Candra Inata
article en

Abstract

The purpose of this study is to test and analyze the cost of capital and reputation of companies on the Human Resources disclosure. The sample in this study consisted of 318 companies the sample criteria. This research data was analyzed using a regression model of ordinary least square (OLS) estimation technique. Based on testing, researchers found that debt costs and equity costs negatively affect human resource disclosure, while company reputation is positively related to human resource disclosure. In addition, research findings from Indonesia's largest categorized industries show that debt costs and equity costs have a significant negative impact on human capital disclosure. Meanwhile, industries that are not categorized as the largest companies in Indonesia do not show significant results in both debt costs and equity costs. This study got results cost of debt and the cost of equity to human capital disclosure is driven by companies engaged in large-scale industries. This research provides contribution, insight and reference to companies in Indonesia through the HR disclosure index as a benchmark to improve HR disclosure in the future. Also, for policymakers, this research can be a consideration for making policies that HR disclosure practices as mandatory disclosures for companies.

Asian Journal of Applied Business and ManagementVol. 3(4)
Universitas Muhammadiyah Jember (ID)
Openalex Percentile: Top 62%
Corporate Governance and Financial Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.