Does intellectual capital reduce the probability of default?

IF 4.7 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-04-02 DOI:10.1108/jfrc-10-2023-0162
Sakshi Khurana, Meena Sharma
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Abstract

Purpose This study aims to examine the impact of intellectual capital (IC) on default risk in Indian companies listed on the National Stock Exchange. Design/methodology/approach This study applies panel data regression analysis to derive a relationship between IC and default risk for the sample period 2013–2022. The value-added intellectual coefficient (VAIC) of Pulic (2000) has been applied to measure IC performance, and default risk is estimated using the revised Z-score model of Altman (2000). Findings The results revealed a positive association between Z-score and VAIC. It implies that a higher value of VAIC improves financial stability and leads to a lower likelihood of default. The findings further suggest that new default forecasting models can be experimented with IC indicators for better default prediction. Practical implications The findings can have implications for investors and banks. This paper provides evidence of IC performance in improving the financial solvency of firms. Investors and financial institutions should invest their resources in a healthy firm that effectively manages and invests in their IC. It will eventually award investors and creditors high returns through efficient value-creation processes. Originality/value This study provides evidence of IC performance in improving the financial solvency of Indian high-defaulting firms, which lacks sufficient evidence in this domain of research. Numerous studies exist examining the relationship between firm performance and IC value, but this area is inadequately focused and underresearched. This study, therefore, fills the research gap from an Indian perspective.
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知识资本能否降低违约概率?
本研究采用面板数据回归分析法,得出 2013-2022 年样本期间智力资本与违约风险之间的关系。采用 Pulic(2000 年)的智力增值系数(VAIC)来衡量集成电路性能,并使用 Altman(2000 年)的修订 Z 分数模型估算违约风险。这意味着 VAIC 值越高,财务稳定性越好,违约可能性越低。研究结果进一步表明,可以尝试使用集成电路指标建立新的违约预测模型,以更好地预测违约情况。本文提供了集成电路在改善企业财务偿付能力方面表现的证据。投资者和金融机构应将资源投入到有效管理和投资集成电路的健康企业中。本研究提供了集成电路在改善印度高违约企业财务偿付能力方面的表现的证据,而这一研究领域缺乏足够的证据。已有大量研究探讨了公司业绩与集成电路价值之间的关系,但这一领域的研究重点不够突出,而且研究不足。因此,本研究从印度的角度填补了这一研究空白。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
期刊介绍: ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.
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