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This paper aims to analyze the impact of intellectual capital disclosure (ICD) and its components on firm performance (FP) while discovering the recent Indian ICD trend and pattern.

Visualizing intellectual capital (IC) through the interpretive lens of the Fourth Industrial Revolution, the study uses agency and signaling theories to elucidate the empirical relationship between ICD and FP of Indian knowledge-sector firms using partial least squares-structural equation modeling (PLS-SEM). Content analysis is used to capture the ICD of 72 NSE-listed firms for five years.

While revealing an increasing ICD trend, the study confirms that the Indian knowledge sector firms strategically design the component-wise ICD in hierarchical alignment with their value creation. Despite human capital disclosures favorably influencing FP, the overall ICD negatively impacts FP. Structural and relational capital disclosure contribute to this negative relationship due to apprehended loss of competitive advantage.

The paper provides information that may assist companies in identifying the specific intellectual capital components that drive financial performance. We suggest firms be strategically responsive in intellectual capital management and disclosure practices considering the value effect due to transparency and loss of competitive advantage.

Contradicting the scanty literature, this study provides a realistic conclusion to the ICD–FP relationship in alignment with ICD trends. The study contributes to the literature by providing a comprehensive and accurate view of ICD in the study setting through improved ICD framework and methodological advancement. It adds value in the contemporary market where the competition is intellectual capital-driven.

The study aims to investigate the mediation effect of the Audit Committee’s (AC) effectiveness on the relationship between knowledge intensity and firm performance (FP) by considering the disparate effect of each AC characteristic on its effectiveness.

The study uses the partial least squares-structural equation model (PLS-SEM) to weigh the AC characteristics for its effectiveness and analyzes the relationships between the variables included in the models. Data was collected from authentic sources for 133 National Stock Exchange (NSE)-listed companies in six industries covering the period 2016 to 2020.

The results indicate that eight out of eleven AC characteristics, namely, nonexecutive directors, independence, expertise, AC-charter, multiple directorships, frequency of AC meetings, attendance of AC meetings and board meetings by AC directors, significantly influence the AC effectiveness while mediating the relationship between knowledge intensity and FP. Further, each characteristic of AC has a disparate effect on AC effectiveness depending on the measurement context.

Apart from guiding the policymakers, management and stakeholders to effectively use AC characteristics in enhancing FP, this study further contributes to the literature by providing a new way to weight AC characteristics based on their individual contributions; and exploring new path models to analyze the multidimensional effect of various AC characteristics.

To the best of the authors’ knowledge, the study is the first to examine the mediation role of AC effectiveness on the relationship between the knowledge intensity of the firms and their performance. It demonstrates improvisation in measuring AC effectiveness using the disparate weights for each AC characteristic, computed based on their relative contribution to AC effectiveness.