The basic materials and industrial sector sits at the heavy end of the Indonesian economy: chemicals, metals, cement, and heavy manufacturing, all capital-intensive, all tied closely to commodity cycles and global industrial demand. Between 2018 and 2022, firms in this sector lived through a full stress cycle. Conditions were relatively stable in 2018 and 2019, then came a sharp market dislocation in early 2020 when the IDX Composite dropped roughly 37% in a matter of weeks, followed by an uneven recovery through 2021 and 2022.

That sequence created wide dispersion in how individual stocks moved relative to the market. Some firms barely flinched; others tracked the index crash almost point for point. Beta, the coefficient that measures this co-movement, varied substantially across the sector. What explains that variation is the central question of this study.

Systematic risk is market-wide by definition. No portfolio can diversify it away because it reflects forces that hit all firms simultaneously, among them interest rate changes, exchange rate shocks, commodity supercycles, and geopolitical disruptions (Cordes et al., 2023; Malliaris & Malliaris, 2021). But market-wide does not mean uniform. A firm carrying heavy debt amplifies the impact of a credit squeeze on its equity; a firm whose balance sheet is dominated by intangible assets faces a different kind of problem when investor uncertainty spikes, since markets struggle to price what they cannot see, and the result is wider return swings. Firm-level characteristics do not create systematic risk, but they shape how much of it a given stock absorbs (Artikis & Alexopoulos, 2016; Handini, 2023; Tudose et al., 2022). The literature agrees on this in principle. It is far less settled on which characteristics matter most, and in what direction.

Several candidates have been studied, including leverage, size, liquidity, and profitability (Arora, 2020; Sujana, 2017; Yusuf, 2019). Three variables have received comparatively little attention in the Indonesian setting despite strong theoretical reasons to include them. The first is Economic Value Added. Unlike conventional accounting profit, EVA asks whether a firm's returns actually cover the full cost of the capital used to generate them, including equity. A firm posting positive net income can still be destroying shareholder value if those returns fall short of what investors could have earned elsewhere. That gap matters for systematic risk because investors who trust a firm's capital efficiency may treat its stock as less vulnerable during market downturns (Li, 2023; Tudose et al., 2022).

Capital gearing is the second. When a firm funds its operations largely through fixed-cost debt, its equity returns become mechanically more volatile: interest must be paid whether revenues are strong or not, so when conditions deteriorate, shareholders absorb the residual loss in amplified form. Trade-off theory has long predicted that this amplification should show up in beta (Yusuf, 2019), though how strongly depends on the industry and the economic cycle.

The third is intellectual capital, measured here through Pulic's VAICTM framework. Human expertise, proprietary systems, and relational networks are the kinds of assets that drive competitive advantage in modern industry, but they are also the hardest for outside investors to evaluate. There is no market for a firm's internal knowledge base, no standard price for accumulated organisational know-how. That opacity creates information asymmetry, and when uncertainty rises market-wide, stocks whose value rests heavily on intangibles tend to see wider return swings as investors struggle to hold a stable estimate of what they are actually worth (Anhar et al., 2021; Persulessy et al., 2022; Vafaei et al., 2011). All three have been examined in relation to firm performance. Their relationship with systematic risk, particularly in Indonesian manufacturing and industrial firms, is another matter entirely.

There is a second gap, less obvious but arguably more interesting. Corporate value, measured here as the market-to-book ratio of assets, is not just an outcome variable. It aggregates investor beliefs about a firm's future growth potential, and those beliefs are themselves shaped by EVA, by capital structure decisions, and by whatever the market can infer about a firm's intellectual resources. If corporate value is a downstream product of these characteristics, it may also be the mechanism through which they influence beta. Prior work has shown that EVA and intellectual capital affect firm valuation (Berzkalne & Zelgalve, 2014; Otuya et al., 2023), and that high market premiums are associated with greater stock price sensitivity (Subekti & Kusuma, 2001). What remains untested is whether corporate value formally mediates the EVA-beta, gearing-beta, and IC-beta relationships. No published panel study on the Indonesian basic materials and industrial sector has examined this question.

Three research questions organise the investigation. Do EVA, capital gearing, and intellectual capital each exert a significant direct effect on the systematic risk of IDX-listed basic materials and industrial firms? Does corporate value itself affect beta in this context? And does corporate value mediate the path from each of the three main predictors to systematic risk? The study draws on a panel of 21 firms across 2018 to 2022, yielding 205 firm-year observations, estimated through a fixed effects model identified via sequential Chow and Hausman tests. The period is analytically valuable precisely because it is not calm: the COVID-19 shock of 2020 and the subsequent recovery create the kind of variation in systematic risk that makes it possible to distinguish which firm characteristics genuinely matter from those that appear relevant only in stable conditions.

Agency Theory and Economic Value Added

Shareholders rarely run the firms they own. They delegate that task to managers, and in doing so, they introduce a problem: managers may not always act in shareholders' best interest. Agency Theory, developed principally by Jensen and Meckling (1976), formalises this conflict. Managers are agents with their own career concerns, risk preferences, and time horizons, all of which can diverge from the goal of maximising firm value. Designing performance metrics that pull managerial behaviour back toward shareholder interests is therefore one of the central preoccupations of corporate governance. Economic Value Added was developed precisely for this purpose. It is calculated as NOPAT minus the product of invested capital and WACC the idea being that a firm only genuinely creates value when its operating returns exceed the full cost of the capital used to generate them, including the opportunity cost of equity (Joorboonyan et al., 2015; Li, 2023). This is not how conventional accounting profit works. A company can report positive net income while simultaneously destroying shareholder value if its returns fall short of what investors could have earned elsewhere. EVA closes this gap.

Resource-Based Theory and Intellectual Capital

Not all competitive advantages are visible on a balance sheet. The Resource- Based View holds that sustained outperformance comes from internal resources that competitors cannot easily copy or buy resources that are valuable, rare, and difficult to substitute (Barney, 1991). Physical assets rarely qualify on all these dimensions. Intellectual capital often does. Intellectual capital comprises three interrelated components. Human capital is the productive capacity embedded in people their expertise, judgment, and experience. Structural capital is what remains when employees leave: the systems, databases, processes, and organisational routines that encode accumulated knowledge. Relational capital covers the external dimension client relationships, supplier networks, and reputational assets that took years to build (Anhar et al., 2021; Persulessy et al., 2022). Together, these intangibles shape a firm's ability to innovate, operate efficiently, and adapt to changing conditions. Studies across several markets confirm the performance benefits. Achim et al. (2023) found positive intellectual capital effects on firm performance in Romania; Hatane et al. (2019) documented similar dynamics among Indonesian service firms; Rusa et al. (2022) extended the picture to European Union data. The consensus is fairly robust: IC matters for value creation. The systematic risk question is more complicated. Intangible assets are hard to price. Investors cannot inspect a firm's internal knowledge base the way they can inspect a factory, so they estimate and those estimates carry uncertainty. Firms investing heavily in R&D, talent, or proprietary systems operate in domains where payoffs are uncertain and timelines are long. When market sentiment shifts downward, ambiguity about intangible asset values can trigger disproportionate sell-offs, pushing these stocks into sharper co-movement with the broader market. This study tests that hypothesis using VAIC™ as the IC measurement instrument.

The Mediating Role of Corporate Value

The hypotheses above treat each variable as a separate pathway to systematic risk. But corporate value is not independent of EVA, gearing, or intellectual capital it is partly a product of them. A firm generating strong EVA will, other things equal, attract higher market valuations. A firm with intellectual capital that the market can observe and price will command a premium over its book assets. Capital structure decisions signal financial prudence or recklessness, and markets price that signal into valuations accordingly. If these dynamics hold, then corporate value is not just another predictor of beta; it is a channel through which the other variables operate. This mediation story draws directly on signalling theory. The market cannot monitor EVA calculations or audit intellectual capital quarterly. What it can observe is the market valuation multiple a noisy but accessible aggregate of investor beliefs about firm quality. EVA, gearing, and IC feed into those beliefs, which are compressed into a price-to-book ratio, which then influences how sensitively the stock moves with the market. The mediation pathway is: firm fundamentals shape valuation, and valuation shapes systematic risk. Berzkalne and Zelgalve (2014) and Otuya et al. (2023) have both pointed to firm value as a conduit between corporate characteristics and market outcomes, though neither tested this formally as a mediation pathway within a systematic risk model. The present study fills that gap using panel data and the Baron and Kenny (1986) mediation procedure supplemented by Sobel tests, within a fixed effects framework that accounts for unobserved firm-level heterogeneity.

Figure 1. Conceptual Framework

This study employs a quantitative explanatory design using secondary panel data sourced from audited annual financial reports and stock price records on the Indonesia Stock Exchange website (www.idx.go.id). The observation period covers 2018 to 2022, a window selected because it encompasses a full market cycle including the pre-pandemic expansion, the 2020 contraction, and the subsequent recovery, producing meaningful variation in beta estimates across firm-years. The target population comprised all basic materials and industrial companies listed continuously on the IDX throughout the study period. Purposive sampling applied four criteria: continuous listing from 2018 to 2022, positive earnings in each observation year, financial statements denominated in Indonesian Rupiah, and complete audited data across all five years. The resulting sample consists of 21 companies and 205 firm-year observations.

Variables are measured as follows. Systematic risk (beta) is estimated via market model regression of monthly firm returns against the IDX Composite Index over a 60-month window. EVA is computed as NOPAT minus invested capital multiplied by WACC. Capital gearing is long-term interest-bearing debt divided by total invested capital. Intellectual capital uses Pulic's (1998) VAIC™, aggregating capital employed efficiency, human capital efficiency, and structural capital efficiency. Corporate value is the market-to-book value of assets ratio. Control variables are the current ratio, debt-to-equity ratio, and the natural logarithm of total assets as a proxy for firm size. Three panel regression equations are estimated to capture direct effects of the independent variables on systematic risk, their effects on corporate value, and the role of corporate value in transmitting those effects to beta. Mediation is assessed using the Baron and Kenny (1986) procedure with Sobel tests. Panel model selection follows a sequential Chow-Hausman-Lagrange Multiplier testing procedure. Prior to interpretation, classical assumption tests were conducted covering normality (Jarque-Bera), multicollinearity (correlation matrix), autocorrelation (Breusch-Godfrey), and heteroskedasticity (Breusch- Pagan-Godfrey). All analysis was performed in EViews 13.

Normality Test

The histogram and associated descriptive statistics of standardised residuals confirm approximate normality. The mean residual is near zero and the median is –0.002, suggesting a symmetric distribution. The skewness value of – 0.14 is negligible, and the kurtosis value of 2.89 is close to the normal benchmark of 3. The Jarque-Bera statistic (0.763; p = 0.683) indicates no significant departure from normality, supporting the adequacy of the regression model.

Figure 2. Normality Test

Autocorrelation Test

The Breusch-Godfrey Serial Correlation LM Test (Table 2) yields an F- statistic p-value of 0.685 and a chi-square p-value of 0.677, both well above the 0.05 threshold. The null hypothesis of no serial correlation is therefore retained, confirming that the residuals are independent over time.

EVA and Systematic Risk (H1 Rejected)

The non-significant effect of EVA on systematic risk (p = 0.157) is consistent with the view that value-based performance metrics operate at a different analytical level from market-wide risk. EVA is an internal, accounting-derived measure of economic profit; it captures how efficiently management has deployed capital relative to its cost, but it does not directly reflect the co- movement of firm returns with market returns that defines beta. This distinction aligns with Artikis & Alexopoulos (2016), who note that EVA's explanatory power is strongest for cross-sectional differences in stock returns rather than for systematic risk per se. Furthermore, the calculation of WACC a key input in EVA involves assumptions (cost of equity, capital structure weights) that vary across firms and analysts, introducing measurement error that attenuates any relationship with beta (Delis et al., 2023; Li, 2023). In capital-intensive industries like basic materials and industrials, where systematic risk is heavily driven by commodity price cycles and macroeconomic demand, internal efficiency metrics such as EVA may be too firm-specific to explain co-movement with the broad market.

Intellectual Capital and Systematic Risk (H3 Accepted)

The significant positive effect of intellectual capital on systematic risk (p = 0.0001) is consistent with theoretical predictions from the resource-based view and information asymmetry arguments. Firms with high VAIC scores are characterised by substantial investments in human expertise, proprietary systems, and innovation processes activities whose value is inherently uncertain and difficult for the market to assess with precision (Anhar et al., 2021; Persulessy et al., 2022). This information asymmetry increases investor uncertainty about the firm's true risk-return profile, manifesting as higher beta. Additionally, IC- intensive firms in the industrial sector tend to pursue ambitious technological upgrading strategies that, while potentially value-creating, expose them to execution risk and the possibility of rapid obsolescence. When market-wide downturns occur, such firms may face disproportionate investor sell-offs as uncertainty about their intangible asset values rises, amplifying co-movement with the market index (Arora, 2020; Sujana, 2017). These findings align with Hatane et al. (2019), who document that intellectual capital intensity is associated with higher return volatility in Indonesian service firms.

Mediation by Corporate Value (H5 and H6 Rejected; H7 Accepted

The mediation results reveal an important asymmetry. Corporate value does not mediate the relationships between EVA and systematic risk (p = 0.152) or between capital gearing and systematic risk (p = 0.171). These null mediation findings are coherent with the direct effect results: if EVA and capital gearing do not significantly affect systematic risk directly, there is little theoretical basis to expect that corporate value would carry their influence indirectly (Berzkalne & Zelgalve, 2014; Otuya et al., 2023; Vafaei et al., 2011). Moreover, corporate value as measured by MV/BVA is a market-based aggregate that responds to a broad array of signals beyond EVA or gearing; the specific information content of these variables may be too diluted to trace a mediation path. By contrast, corporate value significantly mediates the intellectual capital– systematic risk relationship (p = 0.0003). The mediation chain is theoretically coherent and empirically supported: IC investment enhances organisational capabilities and drives innovation, which the market rewards with higher valuations (higher MV/BVA). However, high valuations also embed elevated performance expectations that increase the firm's sensitivity to market-wide shocks when those expectations are revised. The intellectual capital–corporate value–systematic risk pathway thus represents a double-edged mechanism: IC creates value but simultaneously amplifies market risk through the channel of elevated investor expectations. This finding contributes to the literature by establishing corporate value as a significant mediator in this specific pathway, a relationship that has been theorised but rarely tested with Indonesian panel data (Persulessy et al., 2022; Rusa et al., 2022).

The findings do not tell a single story. EVA and capital gearing, despite their theoretical relevance, show no significant relationship with beta in this sample. That result is worth sitting with rather than dismissing. In a sector where revenues track commodity cycles closely, the factors driving stock co-movement with the market appear to operate at a different level than internal capital efficiency or leverage ratios. Macroeconomic conditions during 2018 to 2022, including the COVID-19 shock and the commodity price swings that followed, likely dominated whatever signal EVA or gearing might otherwise have sent.

Intellectual capital and corporate value tell a different story. Both show significant positive effects on systematic risk, and corporate value carries the intellectual capital effect partly as a mediator. Firms with stronger knowledge- based assets attract higher market valuations, and those valuations bring greater sensitivity to market-wide sentiment shifts. The mechanism is essentially one of expectations: the market prices IC-intensive firms generously, and generous pricing means sharper corrections when conditions deteriorate. Investors holding stocks in this sector would do well to treat high VAIC scores not only as a performance indicator but as a risk signal. The mediation finding narrows things further. Corporate value does not transmit the effects of EVA or capital gearing to beta, only those of intellectual capital. This suggests that the market does not consistently reprice firms based on their EVA performance or leverage position, at least not in ways that feed through to systematic risk in this sector and period. What the market does appear to price, and price in ways that matter for beta, is the intangible asset intensity of a firm.