Profitability and Capital Intensity: Moderating Role of Debt Financing

Abstract

This study investigates the relationship between capital intensity, debt financing, and profitability in non-financial firms in Oman over the period 2012–2022. Using a robust panel dataset of 76 firms, the research explores how capital structure dynamics influence firm performance across different firm sizes and industries. The findings reveal that capital intensity significantly enhances profitability, and debt financing further strengthens this effect, with variations observed across firm size and sector. The analysis also identifies a non-linear (concave) relationship between capital intensity and profitability, indicating that while moderate capital investment improves firm performance, excessive capital accumulation may lead to diminishing returns. Larger firms, with better access to financial resources, exhibit a stronger positive relationship between debt financing and profitability, while smaller firms face more challenges due to limited access to capital. Industry-specific results indicate that capital-intensive sectors, such as Energy and Industrials, demonstrate a more pronounced effect of capital intensity on profitability compared to less capital-intensive sectors. The study also incorporates the effects of the COVID-19 pandemic, showing its significant influence on firm performance, particularly in sectors with high debt exposure. By integrating non-linear effects, firm size, industry heterogeneity, and pandemic shocks, this study provides novel insights into capital structure management in emerging economies, offering implications for both corporate decision-makers and policymakers aiming to enhance financial access and optimize debt strategies across sectors.

1. Introduction

The relationship between profitability and capital intensity has emerged as a critical focus in corporate finance, offering insights into the strategic decisions firms make regarding resource allocation, investment planning, and financial performance. Capital intensity refers to the degree to which a firm relies on fixed assets, such as machinery, property, and equipment, to generate revenue (Darsani & Sukartha, 2021; F. A. Sumantri et al., 2022; Widyastuti et al., 2022; Hendayana et al., 2024). Firms operating in capital-intensive industries, such as manufacturing, energy, and infrastructure, often face unique challenges due to their reliance on substantial fixed investments (R. I. Sumantri & Kurniawati, 2023; Padhi, 2024). These challenges necessitate an intricate balance between generating adequate returns and managing the operational costs associated with such investments. As a result, understanding the interaction between profitability and capital intensity is essential for navigating these complexities and achieving long-term financial stability.

Capital-intensive firms generally exhibit higher operating leverage, as they have significant fixed costs relative to variable costs. This structure makes their profitability highly sensitive to fluctuations in revenue. In periods of strong market demand, high capital intensity can amplify returns, enabling firms to reap significant economies of scale. However, during periods of economic downturn or reduced demand, the same high fixed costs can erode profitability, leaving firms vulnerable to financial distress (Oeta et al., 2019; Maxim, 2021; Muthusamy & Kannan, 2023; Tran & Nguyen, 2023). Consequently, the profitability of capital-intensive firms is often a double-edged sword, heavily influenced by market dynamics and managerial decisions.

Debt financing adds a layer of complexity to this relationship, acting as both a facilitator and a potential constraint. Debt is a crucial component of a firm’s capital structure, enabling firms to access the financial resources required for large-scale investments in fixed assets (Stoiljković et al., 2024; Zhang et al., 2024). For capital-intensive firms, debt financing can provide a competitive advantage by allowing them to fund growth initiatives, modernize infrastructure, and achieve operational efficiency. However, debt also introduces financial risk in the form of fixed interest obligations and principal repayments, which can strain a firm’s cash flow and profitability, particularly during economic downturns (Modigliani & Miller, 1958; Jensen, 1986; Atichasari et al., 2023; Odhiambo et al., 2025).

The dual role of debt financing—as a lever for growth and a source of risk—underscores its moderating influence on the relationship between profitability and capital intensity. Firms that manage debt effectively can harness its benefits to support capital-intensive operations while mitigating its risks. Conversely, excessive reliance on debt can exacerbate the vulnerabilities associated with high capital intensity, leading to financial instability. This nuanced interplay highlights the need for a deeper understanding of how debt financing influences the profitability of capital-intensive firms.

Capital intensity is often associated with industries that require substantial investments in fixed assets to produce goods or services. Examples include sectors such as manufacturing, mining, transportation, and utilities, where the cost of acquiring and maintaining physical assets constitutes a significant portion of operational expenses. The high fixed costs inherent in these industries create a reliance on economies of scale to achieve profitability. Firms must generate sufficient revenue to cover their fixed costs before realizing profits, making revenue growth a critical determinant of financial performance (Myers, 1977).

Profitability, on the other hand, is a measure of a firm’s ability to generate returns on its investments and is often evaluated using metrics such as return on assets (ROA), return on equity (ROE), and net profit margin. For capital-intensive firms, profitability is influenced by several factors, including the efficiency of asset utilization, market conditions, and the cost structure of the firm. Efficient management of fixed assets can enhance profitability by improving operational efficiency and reducing costs. However, inefficiencies in asset utilization can erode profitability, as the high fixed costs associated with capital intensity leave little room for error (Rajan & Zingales, 1995).

Debt financing plays a pivotal role in the capital structure of firms, particularly in capital-intensive industries. By providing access to external funds, debt enables firms to invest in large-scale projects, expand operations, and modernize infrastructure. The use of debt is often justified by the tax shield it provides, as interest payments on debt are tax-deductible, reducing the overall cost of capital (Modigliani & Miller, 1958). Moreover, the discipline imposed by debt can encourage managerial efficiency, as firms must generate sufficient cash flows to meet their debt obligations (Jensen, 1986). However, the benefits of debt financing are accompanied by significant risks. High levels of debt increase financial leverage, which can amplify both profits and losses. In favorable market conditions, leverage can enhance returns to equity holders by enabling firms to achieve greater operational scale. In contrast, during periods of economic uncertainty or declining revenues, high leverage can magnify losses, leading to financial distress or even bankruptcy (Myers, 1977). The balancing act between the benefits and risks of debt financing is particularly pronounced in capital-intensive firms, where the fixed costs of operations and the fixed obligations of debt create a “double fixed cost” structure that heightens financial vulnerability.

The moderating role of debt financing in the relationship between profitability and capital intensity is rooted in its ability to influence both the costs and benefits associated with capital investments. On one hand, debt provides the financial resources necessary for firms to undertake capital-intensive projects and achieve economies of scale. On the other hand, the fixed obligations associated with debt can exacerbate the risks of high capital intensity, particularly in volatile market conditions. Research has shown that the impact of debt financing on profitability varies depending on factors such as the cost of debt, the maturity structure of debt, and the firm’s operational efficiency (Rajan & Zingales, 1995; Maxim, 2021; Hendayana et al., 2024). For instance, firms with access to low-cost debt and favorable repayment terms are better positioned to leverage debt financing to enhance profitability. Conversely, firms burdened by high-cost debt or short-term repayment obligations may find that debt financing constrains their financial flexibility and erodes profitability.

Empirical studies have highlighted the complex interplay between profitability, capital intensity, and debt financing. For example, Kusuma and Firnanti (2023) and Oeta et al. (2019) found that capital-intensive firms in the manufacturing sector benefit from moderate levels of debt financing, which enable them to invest in productivity-enhancing technologies. However, excessive debt levels were associated with declining profitability, as the financial burden of debt outweighed the benefits of capital investment. Similarly, Maxim (2021) observed that the relationship between profitability and capital intensity is contingent on the firm’s leverage ratio. Firms with moderate leverage ratios were able to achieve higher profitability by effectively utilizing their fixed assets, while firms with high leverage ratios experienced diminishing returns due to increased financial risk. These findings underscore the importance of debt management in capital-intensive industries, where the balance between leverage and profitability is particularly delicate.

Building on the above discussion, this study aims to examine the relationship between capital intensity and firm profitability among non-financial firms in Oman over the period 2012–2022, with particular attention to the moderating role of debt financing. Accordingly, the study addresses the following key research questions:

• What is the nature of the relationship between capital intensity and profitability in Omani non-financial firms?
• How does debt financing affect firm profitability?
• Does debt financing strengthen or weaken the relationship between capital intensity and profitability?
• Are these effects consistent across firms of different sizes and sectors?

This study makes several significant contributions to the literature on capital intensity, debt financing, and firm profitability. First, it extends the existing body of knowledge by examining the nuanced relationship between capital intensity and profitability, emphasizing how debt financing moderates this relationship in the context of non-financial firms in Oman. Unlike previous studies that focus on developed economies, this research sheds light on the dynamics within an emerging market, thereby providing valuable insights into how capital structure decisions influence firm performance in a developing economy. Second, the study’s focus on firm size and sectoral differences offers a deeper understanding of the heterogeneity in the impact of capital intensity and debt financing on profitability. By highlighting that larger firms benefit more from debt financing due to better access to financial resources, the study underscores the structural advantages of size in capital allocation and utilization. In contrast, smaller firms, which face constraints in accessing capital, demonstrate the challenges of leveraging debt to enhance profitability. This finding emphasizes the need for policy interventions to address capital access disparities among firms of different sizes. Third, the industry-specific analysis reveals that capital-intensive sectors, such as Energy and Industrials, experience a stronger positive effect of capital intensity on profitability compared to less capital-intensive sectors. This contribution is particularly relevant for policymakers and practitioners seeking to optimize financial strategies across various industries, as it highlights the differential impacts of capital structure decisions based on sectoral characteristics. Furthermore, the study incorporates the effects of the COVID-19 pandemic, providing a timely analysis of how exogenous shocks influence the profitability dynamics of firms with varying levels of debt exposure. This aspect not only enriches the understanding of the pandemic’s economic consequences but also underscores the importance of resilience in capital structure strategies, particularly for sectors with significant debt financing. Finally, the findings of this study have practical implications for financial policymakers, corporate managers, and investors. By advocating tailored financial policies that enhance access to capital for smaller firms and optimize debt financing strategies across industries, the research provides actionable insights to improve firm performance and sustainability in emerging markets. Overall, this study contributes to the ongoing discourse on capital structure and firm profitability, offering both theoretical advancements and practical recommendations tailored to the unique challenges and opportunities in the Omani context.

The rest of the paper is organized as follows. Section 2 presents a review of the relevant literature. Section 3 describes the research methodology. Section 4 presents the empirical results and discusses the findings. Section 5 provides robustness checks and sensitivity analyses to ensure the reliability of the results. Finally, Section 6 concludes the paper, offering policy implications, limitations of the study, and suggestions for future research.

2. Literature Review and Hypothesis Development

2.1. Literature Review

As firms strive to optimize their operations and maximize profitability, understanding the role of these financial variables becomes crucial. Capital intensity, which refers to the extent to which a firm invests in physical assets relative to other forms of capital, is often seen as a key determinant of a firm’s ability to generate revenue and achieve economies of scale (Kusuma & Firnanti, 2023; Wang, 2025). Debt financing, on the other hand, involves leveraging borrowed funds to finance operations, which can provide firms with the capital necessary for expansion while also introducing potential risks related to financial distress (Guluma, 2021; Hendayana et al., 2024). This literature review aims to provide an in-depth examination of the existing body of research on the relationships between capital intensity, debt financing, and profitability. The review will also explore the moderating effect of debt financing on the relationship between capital intensity and profitability, the influence of firm size on these dynamics, and sectoral differences in the impact of these variables.

The relationship between capital intensity and profitability has been the subject of numerous studies across various sectors. Capital intensity refers to the amount of capital required to produce a unit of output, and it has long been considered an important determinant of firm performance (Kourtzidis & Tzeremes, 2019; Singh & Sharma, 2025). According to Kourtzidis and Tzeremes (2019), firm performance is influenced by a variety of factors, and capital intensity is one of the key contributors. Their study, focused on insurance companies, demonstrated that high capital intensity could affect profitability by increasing operating costs, but the outcome depends on the firm’s ability to manage these costs efficiently. Habib et al. (2022) investigate the non-linear relationship between operating capital and profitability in China’s manufacturing sector. Their results reveal that firms facing financial constraints benefit from negative operating capital, while unconstrained firms perform better with positive operating capital. This study underscores the importance of managing capital structure to enhance profitability. Similarly, a study by Korir (2021) in the manufacturing sector in Kenya examined the impact of capital intensity on financial performance, revealing that capital intensity significantly influences the profitability of firms listed on the Nairobi Securities Exchange (NSE). Korir (2021) found that firms with higher capital intensity experienced a more significant impact on their financial performance, suggesting that capital-intensive firms must carefully manage their capital to ensure profitability. This is consistent with the findings of Maxim (2021), who observed that capital intensity, along with the degree of indebtedness and company size, affects profitability in retail companies. Maxim’s study indicated that increased capital intensity could lead to higher costs, which, if not managed effectively, could decrease profitability.

Indebtedness is another important factor in determining firm profitability. Korir (2021) suggests that firms with a higher leverage ratio (greater debt levels) tend to experience improved financial performance, as long as the capital intensity is properly balanced. However, excessive debt can lead to financial strain, particularly for capital-intensive firms that may already face high fixed costs. Osei et al. (2024) explore the role of credit information sharing in moderating the relationship between debt financing and profitability. Their research highlights that access to credit information improves the positive effect of debt financing on firm profitability, especially in emerging markets, helping mitigate information asymmetry and improve financial performance.

The interaction between capital intensity and debt financing is particularly significant in determining financial outcomes. Maxim (2021) highlights that the combination of high capital intensity and global indebtedness increases the financial risks faced by firms, especially when the costs of servicing debt exceed the returns generated by the capital invested. The findings of Kourtzidis and Tzeremes (2019) also support this, noting that while debt can amplify profitability by financing expansion, it also increases the financial risk, particularly when capital-intensive investments do not yield expected returns. AL Ani and Chavali (2023) study the relationship between investment intensity and profitability in the GCC countries, focusing on foreign investors’ preferences. They find that earnings before interest, tax, depreciation, and amortization (EBITDA) is positively associated with investment intensity across all GCC countries, while earnings before interest and tax (EBIT) shows a negative relationship. The study suggests that foreign investors prefer using EBITDA as a guide to assess investment intensity, emphasizing the importance of this non-GAAP profitability measure in investment decisions. This finding highlights the role of profitability measures in shaping investment intensity decisions, particularly for foreign investors, and the need for capital market regulators to consider these measures in their guidelines for investment decision-making.

In addition to capital intensity and debt financing, several internal and external factors influence firm profitability and are included as control variables in this study to ensure robust analysis. Management efficiency reflects a firm’s ability to utilize resources effectively, optimize operational processes, and make strategic decisions, which directly enhances performance; empirical studies indicate that firms with higher managerial efficiency demonstrate improved profitability due to better cost control and resource allocation (Ali et al., 2025; Zhao et al., 2025). Liquidity represents the firm’s capacity to meet short-term obligations and maintain operational flexibility; firms with adequate liquidity can avoid financial distress, respond to market opportunities, and sustain profitability (Singh & Sharma, 2025; Li et al., 2025; Saif-Alyousfi et al., 2020; Alsaad et al., 2025; Tulsyan et al., 2025). Firm size also plays a significant role, as larger firms benefit from economies of scale, stronger market positioning, and superior access to financing, all of which contribute positively to profitability (Li et al., 2025; Bu et al., 2025; Saif-Alyousfi, 2025a, 2025b, 2025c; Panda & Nanda, 2018). At the macroeconomic level, GDP growth reflects the overall economic environment, where expanding economies typically create higher demand, increased sales, and improved firm performance (Goodell et al., 2025; Anderson et al., 2024). Conversely, inflation rate affects both costs and pricing strategies; while moderate inflation can allow firms to adjust prices favorably, high or unpredictable inflation can erode real profits and increase operational uncertainty (Cevikcan & Kose, 2021; Ali et al., 2025; Zhao et al., 2025). By integrating these control variables alongside capital intensity and debt financing, literature provides a comprehensive understanding of the multiple internal capabilities and external conditions that shape firm profitability. This development not only strengthens the theoretical foundation of the model but also aligns with recent empirical evidence, demonstrating the necessity of considering firm-specific characteristics and macroeconomic factors when analyzing profitability dynamics in emerging markets such as Oman.

2.2. Hypotheses Development

2.2.1. Capital Intensity and Firm Profitability

Capital intensity, defined as the extent to which firms rely on physical and fixed assets to generate output, is a fundamental determinant of firm profitability. Theoretically, high capital intensity allows firms to achieve economies of scale and production efficiency, reducing average costs as output expands (Ding et al., 2022). According to the efficiency theory, capital-intensive firms benefit from technological advantages and asset specialization that can enhance operational productivity (F. A. Sumantri et al., 2022; Hendayana et al., 2024; Ali et al., 2025; Zhao et al., 2025; Wang, 2025). The resource-based view (RBV) further supports this argument by emphasizing that physical assets, when combined with firm-specific capabilities, can serve as strategic resources that generate a sustained competitive advantage and superior performance (Barney, 1991; Tran & Nguyen, 2023; Singh & Sharma, 2025; Li et al., 2025). Empirical studies have consistently shown a positive association between capital intensity and profitability in manufacturing and industrial firms (Alarussi & Alhaderi, 2018; Panda & Nanda, 2018; Korir, 2021; Maxim, 2021; Ali et al., 2025).

However, the relationship between capital intensity and profitability may not always be linear. As firms increase their investment in fixed assets, they may initially experience efficiency gains, but beyond a certain threshold, the marginal returns on additional capital investment tend to decline (Myers, 1977; Ding et al., 2022). High levels of capital intensity can result in operational rigidity, higher depreciation costs, and underutilization of assets during economic downturns, ultimately reducing profitability (Padhi, 2024; Li et al., 2025; Bu et al., 2025). This non-linear pattern suggests an inverted U-shaped relationship, where moderate levels of capital intensity maximize profitability, while excessive capital investment leads to diminishing returns. Therefore, taking into account both the linear and potential non-linear effects, the first hypothesis is proposed as follows:

H1. 

Capital intensity has a positive effect on profitability, though the relationship may exhibit diminishing returns beyond an optimal threshold.

2.2.2. Debt Financing and Firm Profitability

Debt financing plays a pivotal role in enabling firms to access the external capital necessary for funding investments, technological upgrades, and expansion projects that drive long-term growth. According to the trade-off theory, debt can enhance firm value by providing tax shields on interest payments and imposing financial discipline on management, thereby mitigating the tendency toward inefficient investment decisions (Modigliani & Miller, 1958; Jensen, 1986). By carefully managing their capital structure, firms can strategically leverage debt to finance profitable projects while preserving ownership control and improving returns on equity (Guluma, 2021; Darsani & Sukartha, 2021; Ali et al., 2025; Zhao et al., 2025). This controlled use of leverage can signal managerial confidence and enhance investor perceptions of firm performance. On the other hand, the pecking order theory asserts that firms prefer internal financing but resort to debt when retained earnings are insufficient, as it is typically less costly and less information-sensitive than equity issuance. Nevertheless, overdependence on debt financing introduces significant financial risks, including heightened interest obligations, increased vulnerability to cash flow volatility, and potential insolvency during adverse market conditions. Excessive leverage can also constrain managerial flexibility and divert resources away from productive investments, ultimately diminishing profitability (Brusov et al., 2022; Zhang et al., 2024; Cevikcan & Kose, 2021; Li et al., 2025; Bu et al., 2025). Therefore, maintaining an optimal debt level is essential to balancing the benefits of financial leverage with the associated risks of over-indebtedness. Empirical evidence from both developed and emerging markets suggests that moderate debt usage tends to enhance profitability by lowering the cost of capital and improving resource allocation efficiency, whereas excessive borrowing can erode firm value through rising financial distress costs (Wang, 2025; Singh & Sharma, 2025). In the context of non-financial firms operating in Oman, where access to capital markets is still evolving and financial institutions play a dominant role in corporate financing, understanding this balance is particularly crucial. It is expected that firms maintaining a moderate level of debt will exhibit higher profitability than those with either excessively low or high leverage ratios. Based on this theoretical and empirical reasoning, the second hypothesis of the study is formulated as follows:

H2. 

Debt financing has a significant positive effect on firm profitability up to an optimal level, beyond which its impact becomes negative.

2.2.3. The Moderating Effect of Debt Financing

The interaction between capital intensity and debt financing plays a crucial role in shaping firm profitability, particularly in industries that rely heavily on physical assets. Capital-intensive firms typically require substantial long-term investments in property, plant, and equipment, which often necessitate external financing to sustain operations and support expansion. When these firms utilize debt prudently, they can effectively leverage their tangible assets to secure favorable borrowing terms, enhance production efficiency, and realize economies of scale, thereby improving overall profitability (Safari & Saleh, 2020; Stoiljković et al., 2024; Ali et al., 2025). This relationship aligns with the resource-based theory, which suggests that firms achieving a strategic combination of valuable resources—such as high-quality assets—and sound financial management practices can sustain a competitive advantage and superior performance. Moderate levels of debt can also serve as a governance mechanism by imposing financial discipline, ensuring that managers allocate capital efficiently toward value-generating projects. However, the benefits of debt diminish when leverage becomes excessive, particularly for capital-intensive firms already burdened with high fixed costs. Elevated debt obligations can amplify financial distress risks, constrain liquidity, and limit a firm’s ability to adapt to market fluctuations, especially during periods of declining sales or macroeconomic uncertainty (Oeta et al., 2019; Maxim, 2021; Korir, 2021; Wang, 2025). Thus, while the judicious use of debt can complement a firm’s asset intensity to enhance profitability, over-leveraging may offset these gains by increasing financial fragility and exposure to interest rate shocks (Zhao et al., 2025; Wang, 2025; Singh & Sharma, 2025; Li et al., 2025; Bu et al., 2025). In emerging markets like Oman, where firms face unique challenges in balancing capital structure decisions due to evolving financial systems and credit market constraints, understanding this interaction is particularly important. Therefore, the study anticipates that debt financing moderates the relationship between capital intensity and profitability in a non-linear manner, beneficial at moderate levels but detrimental when excessive. Based on this reasoning, the third hypothesis is proposed as follows:

H3. 

Debt financing positively moderates the relationship between capital intensity and firm profitability up to an optimal level, beyond which its effect becomes negative.

2.2.4. Control Variables

Firm Size

Firm size is a fundamental determinant of profitability. According to the Resource-Based View (RBV), larger firms possess superior tangible and intangible assets—such as technology, brand reputation, and managerial expertise—that provide sustained competitive advantages and enhance profitability (Barney, 1991; Li et al., 2025). Large firms benefit from economies of scale and improved operational efficiency, reducing per-unit costs and improving margins (Panda & Nanda, 2018; Bu et al., 2025). In addition, the Market Power Theory posits that large firms can influence prices, negotiate better terms with suppliers, and access financing at lower costs due to lower perceived risk (Saif-Alyousfi, 2025a; Alsaad et al., 2025). However, beyond a certain threshold, the Diseconomies of Scale Hypothesis suggests that size may negatively impact profitability due to bureaucratic inefficiencies and coordination challenges. Therefore, firm size is controlled to capture the potential non-linear influence of scale advantages and organizational complexity on firm profitability.

Liquidity

Liquidity represents a firm’s ability to meet short-term obligations and sustain operations without financial distress. The Pecking Order Theory (Myers & Majluf, 1984) suggests that firms prefer internal financing (retained earnings) to external debt or equity to minimize asymmetric information costs. Firms with higher liquidity are thus less dependent on external finance, reducing their financing costs and risk exposure (Zaitoun & Alqudah, 2020; Sundas & Butt, 2021; Tulsyan et al., 2025). The Liquidity Preference Theory also argues that firms maintain liquidity buffers as a precautionary measure against uncertainty (Pigou, 1936). Empirically, liquidity is often found to enhance profitability, since cash-rich firms can exploit profitable investment opportunities promptly and avoid costly borrowing (Singh & Sharma, 2025; Alsaad et al., 2025). However, excessive liquidity can lead to agency problems or inefficient asset utilization, as idle funds may yield lower returns (Ali et al., 2025; Zhao et al., 2025). Therefore, liquidity is included to capture its dual role as both a stabilizing and potentially constraining factor in profitability.

Management Efficiency

Management efficiency reflects a firm’s internal capability to convert resources into output effectively. According to the Efficiency Theory and Managerial Utility Theory, efficient management practices—such as cost control, optimal resource allocation, and productivity enhancement—are central to achieving superior financial performance (Ali et al., 2025; Zhao et al., 2025). The Agency Theory (Meckling & Jensen, 1976) further posits that managerial efficiency mitigates agency conflicts by aligning management decisions with shareholder interests, thereby enhancing profitability. Empirical studies consistently find that efficient firms outperform their less efficient counterparts in profitability and value creation (Sudiyatno et al., 2020; Hendayana et al., 2024; Singh & Sharma, 2025). Hence, this study controls for management efficiency to isolate the effect of capital intensity and debt financing from variations in internal operational effectiveness.

GDP Growth

Macroeconomic conditions influence firm profitability through demand and investment channels. The Business Cycle Theory posits that firm performance tends to move procyclically with the economy—profitability increases during economic expansions due to stronger demand, improved investor confidence, and favorable credit conditions (Saif-Alyousfi, 2025b; Tulsyan et al., 2025). The Accelerator Theory of Investment also suggests that higher GDP growth stimulates firms to expand production and investment, leading to higher sales and profit margins (Samuelson, 1939; Li et al., 2025). Empirical evidence from emerging markets confirms that GDP growth has a positive and significant effect on firm profitability, reflecting macroeconomic spillovers (Wasiuzzaman & Nurdin, 2019; Alsaad et al., 2025; Bu et al., 2025). Therefore, GDP growth is incorporated as a control to account for the macroeconomic environment’s influence on firm-level outcomes.

Inflation

Inflation influences firm profitability through cost and pricing mechanisms. The Purchasing Power Theory asserts that inflation erodes the real value of money and purchasing power, affecting consumer demand and firm revenues (Cevikcan & Kose, 2021). Meanwhile, the Cost-Push and Demand-Pull Theories of Inflation indicate that rising input prices or demand surges can, respectively, reduce or enhance profitability depending on market structure and pricing power (Ali et al., 2025). The Menu Cost Theory also highlights the adjustment costs firms face when frequently changing prices during inflationary periods, which can impact profit margins. Empirical studies provide mixed evidence—moderate inflation may allow firms to increase prices and preserve profitability, while excessive inflation raises uncertainty and input costs (Zhao et al., 2025; Singh & Sharma, 2025). Therefore, inflation is controlled to capture its multifaceted influence on firm profitability and financial stability.

3. Methodology

3.1. Data

This study employs an unbalanced panel dataset of 76 non-financial firms listed on the Oman Securities Market (OSM) over the period 2012–2022. The sample encompasses firms from diverse industries such as manufacturing, services, construction, and retail to ensure comprehensive sectoral representation of the Omani non-financial sector. Firm-level data were primarily obtained from the annual financial statements available through the Oman Securities Market’s official database and verified against secondary financial data repositories such as Refinitiv Eikon and company annual reports to ensure accuracy and reliability. The sample size, although moderate, provides adequate variability across firms and years, allowing for the control of firm-level heterogeneity using fixed- and random-effects estimations. To maintain data consistency, financial and utility firms were excluded due to their distinct regulatory and capital structure characteristics. Missing or incomplete values were treated carefully—where feasible, missing financial items were cross-verified from alternative annual reports; otherwise, data imputation was performed using firm-specific linear interpolation techniques, and outliers were winsorized at the 1st and 99th percentiles to reduce the influence of extreme observations. The panel is unbalanced, as not all firms have complete records for every year; however, this structure enhances sample representativeness and allows the inclusion of firms that may have entered or exited the market during the study period. Overall, this data structure captures both cross-sectional and temporal variations, enabling robust estimation of the relationship between capital intensity, debt financing, and profitability in Omani firms.

3.2. Model Specification

The model specification for this study aims to examine the relationships between capital intensity, debt financing, and profitability, with a focus on understanding how these factors interact across different firms and sectors. To analyze these relationships, a regression-based approach is employed, with profitability as the dependent variable and capital intensity and debt financing as the key independent variables. The general form of the model is as follows:

$$\begin{array}{cc}{Profitability}_{it}=\hfill & \alpha +{\beta }_{1}C{apital Intensity}_{it}+{\beta }_2{Debt Financing}_{it}+{\beta }_3\left({Capital Intensity}_{it}\times {Debt Financing}_{it}\right)\hfill \\ \hfill & +{\beta }_4{Management Efficiency}_{it}+{\beta }_5{Liquidity}_{it}+{\beta }_6{Firm Size}_{it}+{\beta }_7{GDP Growth}_t\hfill \\ \hfill & +{\beta }_8{Inflation Rate}_t+ϵit\hfill \end{array}$$

The dependent variable in this model is Profitability_it, which can be measured by metrics like earnings before interest and taxes/total revenue for firm i at time t. The model includes a variety of independent variables that may affect profitability. First, $C{apital Intensity}_{it}$ and ${Debt Financing}_{it}$ are key independent variables. Capital intensity measures the proportion of a firm’s assets that are tied up in physical capital, while debt financing reflects the extent to which a firm relies on borrowed funds to finance its operations. The interaction term $\left({Capital Intensity}_{it}\times {Debt Financing}_{it}\right)$ is included to explore how these two variables interact and jointly affect profitability. This allows for a deeper understanding of whether the effect of one variable depends on the level of the other.

Other variables in the model include ${Management Efficiency}_{it}$, which accounts for a firm’s ability to effectively manage its operations and resources, and ${Liquidity}_{it}$, reflecting the firm’s ability to meet its short-term obligations. ${Firm Size}_{it}$ is another important control variable, as larger firms may have different profitability dynamics compared to smaller firms. Additionally, the model controls for macroeconomic factors such as ${GDP Growth}_t$ and ${Inflation Rate}_t$, which can also influence firm profitability by affecting the broader economic environment in which firms operate.

The inclusion of these variables helps ensure that the model comprehensively captures the factors affecting profitability. The goal is to understand both the direct and interactive effects of capital intensity and debt financing, as well as the role of firm-specific and macroeconomic factors, on a firm’s financial performance. The error term, $ϵit$, accounts for unobserved factors that might influence profitability. By examining this equation, researchers can gain valuable insights into the complex relationships between these financial variables and their impact on profitability. Table 1 summarizes the definition of the variables used in this study.

Table 1. Definition of variables.

Variable	Measurement
Profitability	Earnings before interest and taxes/total revenue
Capital Intensity	Property, plant and equipment/total assets
Debt Financing	Total short-term and long-term debt liabilities/total assets
Management Efficiency	Asset turnover measured by revenues to total assets
Liquidity	Current ratio measured by current asset to current liabilities
Firm Size	Log of total assets
GDP growth	Annual percentage change in GDP
Inflation Rate	Annual percentage change in the consumer price index

Pooled OLS (Ordinary Least Squares) regression was employed to estimate the relationship between the key variables—capital intensity, debt financing, and profitability, as measured by EBIT—across the sample firms. This method assumes that there is no significant variation across individual firms over time, effectively pooling all observations together to estimate a single regression model. Pooled OLS is commonly used in panel data analysis when individual effects are assumed to be uncorrelated with the explanatory variables, providing a straightforward and efficient estimation technique. In this study, pooled OLS was utilized to capture the overall impact of capital intensity, debt financing, and other control variables such as management efficiency, liquidity, and firm size on EBIT. The results derived from this model offer an initial understanding of the general relationships between the variables across the sample, although it does not account for individual firm-specific effects or time dynamics, which are addressed in more advanced models such as fixed-effects or random-effects regressions.

4. Results

4.1. Descriptive Analysis

Table 2 summarizes the descriptive statistics for the variables in the study, showing substantial variability across firms. Profitability has a mean of −0.039, indicating slightly negative average returns, with a wide range from −96.026 to 9.667, reflecting the presence of extreme outliers. Capital intensity averages 0.606, suggesting moderate reliance on fixed assets, with values ranging from 0.001 to 2.798. Debt financing has a mean of 0.331, indicating that firms generally have low debt relative to total assets, but a maximum of 4.649 suggests significant leverage for some. Management efficiency, measured by asset turnover, averages 2.461, with a high standard deviation (4.499) and an upper extreme of 57.189, reflecting vast differences in operational efficiency. Liquidity shows a relatively narrow range, averaging 18.763, with consistent values across firms. Firm size is modest on average (0.578) but varies widely, with some firms being significantly larger. Macroeconomic controls, GDP growth (mean: 2.721) and inflation (mean: 1.176), exhibit expected variability, influenced by differing economic conditions during the sample period.

Table 2. Descriptive statistics.

Variable	Obs.	Mean	Std. Dev.	Min	Max
Profitability	758	−0.039	3.106	−96.026	9.667
Capital Intensity	758	0.606	0.538	0.001	2.798
Debt Financing	758	0.331	0.394	0.000	4.649
Management Efficiency	764	2.461	4.499	0.005	57.189
Liquidity	758	18.763	1.942	11.966	24.249
Firm Size	764	0.578	0.697	0.000	4.461
GDP growth	836	2.721	3.295	−3.380	8.863
Inflation Rate	836	1.176	0.938	−0.406	2.948

4.2. Correlation Analysis

Table 3 reveals several key relationships between the variables. Profitability is moderately positively correlated with capital intensity (0.397), suggesting that firms with higher capital intensity tend to be more profitable. There is a positive correlation between profitability and debt financing (0.244), indicating that higher leverage is associated with higher profitability. Debt financing has a negative correlation with capital intensity (−0.07), implying little to no relationship between the two. Management efficiency shows a positive correlation with profitability (0.171) and negative correlations with capital intensity (−0.1973) and debt financing (−0.2715), suggesting that more efficient firms tend to have lower capital intensity and debt levels. Liquidity is positively correlated with profitability (0.114) and negatively with firm size (−0.2927), indicating that larger firms tend to have lower liquidity. Macroeconomic variables, GDP growth and inflation rate, show correlations with the firm-specific variables, suggesting limited direct relationships with profitability and firm characteristics. The VIF values indicate no significant multicollinearity concerns, as all values are well below the critical threshold of 5.

Table 3. Correlation matrix.

	1	2	3	4	5	6	7	8	VIF
(1) Profitability	1
(2) Capital Intensity	0.397	1							1.17
(3) Debt Financing	0.244	−0.117	1						1.45
(4) Management Efficiency	0.171	−0.1973	−0.2715	1					1.20
(5) Liquidity	0.114	−0.1957	−0.4143	−0.029	1				1.42
(6) Firm Size	0.2356	0.0667	0.238	−0.038	−0.2927	1			1.17
(7) GDP growth	0.1853	−0.0696	−0.0029	−0.0087	0.019	−0.2044	1		1.98
(8) Inflation Rate	−0.1035	−0.0072	0.0039	0.0132	−0.0138	−0.1244	0.6893	1	1.92

4.3. Bassline Results

Table 4 presents the baseline regression results for the impact of capital intensity on firm profitability.1 Overall, the model explains 55.2% of the variation in firm profitability, as indicated by the R-squared value of 0.552, with the F-statistic (42.673) being highly significant. These results underscore the importance of capital intensity and debt financing key determinants of profitability in the firms studied.

Table 4. Regression results—The impact of capital intensity on firm profitability.

Variables	EBIT
Capital Intensity	0.403 ***
	(0.062)
Debt Financing	0.152 ***
	(0.022)
Management Efficiency	0.202 **
	(0.041)
Liquidity	0.106 **
	(0.033)
Firm Size	0.185 ***
	(0.054)
GDP Growth	0.053 *
	(0.022)
Inflation	−0.021
	(0.011)
Constant	2.204 ***
	(0.256)
Observations	750
R-squared	0.552
F-statistic	42.673 ***

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

The regression analysis reveals several noteworthy findings. First, capital intensity exhibits a positive and statistically significant relationship with profitability (coefficient = 0.403, *** p < 0.01), indicating that firms with higher capital intensity tend to have better profitability outcomes. This suggests that firms with more substantial investments in physical assets, such as property, plant, and equipment, can leverage their capital to enhance their profit generation capacity. These results are in line with HI, and the theory of economies of scale suggests that high capital intensity allows firms to spread their fixed costs over a larger volume of output, reducing average costs and leading to a more favorable cost-to-revenue ratio. The results are also in line with the results of Korir (2021), Maxim (2021), F. A. Sumantri et al. (2022), and Hendayana et al. (2024). The positive effect of capital intensity on firm profitability may be attributed to several reasons. One potential explanation is that capital-intensive firms can achieve economies of scale by utilizing their physical assets more efficiently. The larger the scale of operations, the greater the potential for reducing per-unit costs, thereby improving profit margins. Moreover, firms with significant investments in fixed assets can often benefit from increased production capacity and higher output, leading to greater revenue generation potential. These assets also contribute to a more stable revenue stream, as physical capital can be leveraged to meet consistent demand and maintain operational continuity. Additionally, firms with higher capital intensity are often better positioned to secure financing, as tangible assets can serve as collateral. This enables firms to access lower-cost debt, which can be used to further enhance profitability by funding additional growth opportunities or expanding operations. Furthermore, capital-intensive firms may have a competitive advantage in industries where large-scale production is necessary to remain competitive, such as manufacturing or utilities. In these sectors, investments in physical assets enable firms to meet market demands more effectively, driving both cost efficiencies and increased revenue. The findings suggest that firms with higher capital intensity have a strategic advantage in enhancing profitability, as long as they can effectively manage their assets and utilize them for sustained growth. However, firms with lower capital intensity may face challenges in achieving similar profitability levels due to the lack of infrastructure to leverage for business expansion.

The variable debt financing demonstrates a positive and statistically significant impact on profitability (coefficient = 0.152, *** p < 0.01), indicating that firms with higher levels of debt financing are likely to experience better profitability outcomes. This finding suggests that leveraging debt can be a strategic tool for firms to enhance their profitability. These results are in line with H2, and the theory of leverage suggests that using debt to finance profitable ventures can increase profitability by enabling firms to make investments with higher returns than the cost of debt. In addition, our results are similar to the results of Guluma (2021), Osei et al. (2024), Maxim (2021), and Zhang et al. (2024). One possible explanation for this positive relationship is the tax advantages associated with debt financing. Interest payments on debt are tax-deductible in many jurisdictions, allowing firms to reduce their overall tax burden. This reduction in taxes increases after-tax profits, thereby improving profitability. In addition to the tax benefits, debt financing can also provide firms with increased access to capital, which can be used to fund growth opportunities, invest in new projects, or expand operations. With additional capital, firms can invest in assets, technologies, or innovations that enhance productivity and generate higher returns. By borrowing funds at lower interest rates compared to the cost of equity, firms can maximize their return on investment, which ultimately boosts profitability. This ability to finance expansion and growth through debt allows firms to pursue strategic initiatives without the immediate need for equity financing, which can dilute ownership and control. Furthermore, debt financing can signal to the market that a firm is confident in its future cash flow generation and ability to manage its financial obligations. This can lead to increased investor confidence, potentially raising the firm’s stock price and lowering its cost of capital in the future. Additionally, debt financing can help firms optimize their capital structure, balancing the mix of equity and debt to achieve a cost-effective financing strategy that enhances returns on equity and overall profitability. However, it is essential to note that while debt financing may enhance profitability, excessive reliance on debt can expose firms to financial risk, particularly if they are unable to meet debt obligations during periods of financial distress. Therefore, firms must carefully manage their debt levels to avoid over-leveraging, which could negatively impact profitability in the long term. Nonetheless, the positive relationship between debt financing and profitability, as shown in the regression analysis, highlights the potential benefits of strategic debt management in driving firm performance.

The control variables in the regression model also play a significant role in explaining profitability outcomes. These variables include management efficiency, liquidity, firm size, GDP growth, and inflation, each of which can influence a firm’s profitability either directly or indirectly. Management efficiency, for instance, exhibits a positive and statistically significant relationship with profitability (coefficient = 0.202, ** p < 0.05). This suggests that firms with more efficient management practices are better at utilizing their resources to generate profits. Efficient management practices, such as effective cost control, optimal resource allocation, and strategic decision-making, enable firms to maximize output while minimizing expenses, leading to enhanced profitability. Firms that are well-managed are likely to have a better competitive position and improved profitability prospects in both the short and long term. Liquidity, another important control variable, is negatively associated with profitability (coefficient = 0.106, ** p < 0.05). This indicates that higher liquidity, while essential for maintaining operational flexibility, may not always translate into improved profitability. In fact, excessive liquidity could signal inefficiencies in utilizing resources for productive investments. Firms holding excess liquid assets might not be taking full advantage of growth opportunities, and their funds could be better utilized in high-return investments rather than being held in low-interest-bearing assets. Therefore, maintaining an optimal liquidity level is critical for ensuring that liquidity does not detract from profitability. Firm size, a common control variable, shows a positive relationship with profitability (coefficient = 0.185, *** p < 0.01), suggesting that larger firms tend to have better profitability outcomes. This may be due to economies of scale that allow larger firms to reduce per-unit costs and achieve higher margins. Additionally, larger firms often have more market power, enabling them to set favorable prices and negotiate better terms with suppliers and customers, which can improve profitability. GDP growth and inflation, as macroeconomic control variables, also influence profitability. The positive relationship between GDP growth and profitability (coefficient = 0.053, * p < 0.10) indicates that firms tend to perform better in periods of economic expansion. Conversely, inflation (coefficient = −0.021) has a negative but statistically insignificant relationship with profitability, suggesting that while inflation may affect input costs and consumer purchasing power, its impact on profitability in the sample studied is less pronounced. These results are in line with the results of Darsani and Sukartha (2021), F. A. Sumantri et al. (2022), R. I. Sumantri and Kurniawati (2023), and Hendayana et al. (2024).

Together, these control variables highlight the complex and multifaceted nature of profitability, emphasizing the importance of management practices, liquidity management, firm size, and macroeconomic conditions in shaping a firm’s financial outcomes.

4.4. Moderator Effect of Debt Financing

Table 5 presents the regression results for the moderation effect of debt financing, illustrating the interaction between capital intensity and debt financing and its influence on profitability. The analysis shows that the interaction term between capital intensity and debt financing is statistically significant (coefficient = 0.091, ** p < 0.05), suggesting that debt financing indeed moderates the relationship between capital intensity and profitability. These results are in line with our expected hypothesis (H3), as well as with the resource-based theory, which suggests that firms with tangible assets (such as high capital intensity) and access to external capital (through debt financing) are in a stronger position to maximize their production capacity and generate higher returns (Safari & Saleh, 2020; Korir, 2021; Maxim, 2021).

Table 5. Regression results—Moderation effect of debt financing.

Variables	EBIT
Capital Intensity	0.423 ***
	(0.065)
Debt Financing	0.180 ***
	(0.025)
Capital Intensity × Debt Financing	0.091 **
	(0.045)
Management Efficiency	0.215 **
	(0.045)
Liquidity	0.118 **
	(0.035)
Firm Size	0.190 ***
	(0.058)
GDP Growth	0.055 *
	(0.024)
Inflation	−0.019
	(0.012)
Constant	2.310 ***
	(0.265)
Observations	750
R-squared	0.563
F-statistic	44.222 ***

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

The positive coefficient of the interaction term between capital intensity and debt financing suggests that the relationship between capital intensity and profitability is significantly strengthened when firms have higher levels of debt financing. Specifically, firms with greater capital intensity—meaning they invest heavily in physical assets like property, plant, and equipment—benefit more from access to debt financing, leading to enhanced profitability. This indicates that debt acts as a catalyst, enabling firms to leverage their substantial capital investments more effectively. Debt financing provides firms with the additional capital needed to expand their operations or invest in high-return projects, which in turn boosts their capacity to generate profits. This finding underscores the importance of debt in amplifying the effects of capital investments. When firms are able to secure financing through debt, they can take advantage of the economies of scale that come with larger capital investments. The ability to finance assets without relying entirely on internal funds allows these firms to maintain liquidity and flexibility, making it easier to pursue growth opportunities and improve profitability. Moreover, this relationship points to the strategic use of financial leverage. By taking on debt, firms can magnify the return on their capital expenditures, assuming that the returns generated from those investments exceed the cost of borrowing. However, it is important to note that while higher levels of debt can enhance profitability, they also introduce financial risk, especially if the returns do not meet expectations. Therefore, this finding highlights the need for careful management of capital structure, where firms must balance the benefits of debt with the potential risks associated with increased financial leverage. In summary, debt financing not only helps firms access additional resources but also serves as a key factor in magnifying the profitability of capital-intensive firms.

Furthermore, the results indicate that debt financing itself has a significant positive effect on profitability (coefficient = 0.180, *** p < 0.01), suggesting that the availability of debt can improve profitability, possibly due to tax advantages or the ability to finance growth without diluting equity. In combination with capital intensity, debt financing seems to provide firms with a powerful tool to enhance their competitive position.

Overall, these findings underscore the significant role of debt financing in enhancing the profitability of firms with high capital intensity. However, firms must balance the benefits of increased leverage with the risks associated with high debt levels. The results highlight the importance of strategic financial management, where debt is utilized effectively to amplify the returns from capital investments, while maintaining a cautious approach to ensure long-term financial stability.

5. Robustness Test

5.1. Alternative Measures of Firm Profitability

To further evaluate the robustness of the baseline results, an alternative set of profitability measures was used. While the initial regression analysis relied on EBIT as the dependent variable, this robustness test incorporates Return on Assets (ROA) and Return on Equity (ROE) as alternative profitability indicators. The inclusion of these two measures is crucial, as they provide different perspectives on a firm’s financial performance—ROA gauges the efficiency of asset utilization, whereas ROE assesses the returns generated for shareholders. By incorporating ROA and ROE alongside EBIT, this robustness test ensures that the observed relationship between capital intensity, debt financing, and profitability is not reliant on a single measure of profitability. As presented in Table 6, the results for ROA and ROE remain consistent with those found using EBIT, bolstering the reliability and robustness of the conclusions drawn from the baseline analysis. This consistency across different profitability measures further validates the findings and offers a more comprehensive understanding of the factors driving firm profitability.

Table 6. Alternative measures of firm profitability.

Variables	ROA	ROE
Capital Intensity	0.412 ***	0.398 ***
	(0.072)	(0.068)
Debt Financing	0.178 ***	0.174 ***
	(0.028)	(0.030)
Capital Intensity × Debt Financing	0.089 **	0.085 **
	(0.047)	(0.050)
Management Efficiency	0.205 **	0.210 **
	(0.049)	(0.046)
Liquidity	0.121 **	0.117 **
	(0.038)	(0.037)
Firm Size	0.189 ***	0.185 ***
	(0.061)	(0.060)
GDP Growth	0.053 *	0.057 *
	(0.026)	(0.025)
Inflation	−0.020	−0.021
	(0.013)	(0.013)
Constant	2.295 ***	2.275 ***
	(0.273)	(0.279)
R-squared	0.561	0.559
F-statistic	43.765 ***	43.004 ***

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

5.2. Subsample Analysis

To deepen the understanding of the relationship between capital intensity, debt financing, and profitability, a subsample analysis was conducted, splitting the sample based on firm size and industry type. This approach helps identify whether the observed effects vary across different types of firms or sectors, ensuring the robustness and generalizability of the results.

By firm size: The first subsample analysis focused on firm size, dividing the sample into large and small firms. By running separate regressions for each group, we aimed to test if the impact of debt financing on profitability differs based on firm size. Larger firms typically have more access to capital markets, greater financial flexibility, and more substantial resources to absorb financial leverage. In contrast, smaller firms may face higher costs of capital and limited access to debt financing. This analysis helps determine whether the relationship between debt financing and profitability is stronger or weaker for firms of different sizes, thus offering insights into how firm size may influence financial strategies.

By industry: The second subsample analysis divided the sample into various industries, specifically focusing on sectors such as basic materials, consumer discretionary, consumer staples, energy, industrials, telecommunications, and utilities. By performing separate regressions for firms in these industries, we can assess whether the relationship between capital intensity, debt financing, and profitability is consistent across sectors. Different industries have distinct capital structures and operational dynamics, which may lead to varying results. For instance, capital-intensive industries like Energy and Industrials might exhibit a stronger relationship between capital intensity and profitability, whereas sectors like Telecommunications or Consumer Staples may demonstrate a more muted effect due to different financial characteristics and capital requirements. This industry-based analysis is essential for understanding whether the results observed in the overall sample hold true across sectors or if industry-specific factors play a significant role.

As shown in Table 7 and Table 8, the subsample analysis reveals nuanced variations in the relationship between capital intensity, debt financing, and profitability across firm size and industry types. For firm size, the results suggest that larger firms benefit more from capital intensity and debt financing, likely due to their greater access to capital markets and financial flexibility, while small firms face weaker effects, possibly due to their higher costs of capital and limited access to debt financing. In the industry-based subsample analysis, capital-intensive sectors like Energy and Industrials show a stronger relationship between capital intensity and profitability, reflecting the higher capital requirements and operational structures of these industries. On the other hand, industries such as Telecommunications and Consumer Staples display more muted effects, which could be attributed to their lower capital intensity and different financial characteristics. These findings demonstrate the importance of considering firm size and industry context when analyzing the impact of financial strategies on profitability, as the effects are not uniform across all types of firms or sectors.2

Table 7. Subsample analysis—By firm size.

Variables	Large Firms	Small Firms
Capital Intensity	0.410 ***	0.392 ***
	(0.065)	(0.071)
Debt Financing	0.176 ***	0.142 ***
	(0.028)	(0.034)
Capital Intensity × Debt Financing	0.089 **	0.073 **
	(0.046)	(0.049)
Management Efficiency	0.210 ***	0.195 **
	(0.049)	(0.054)
Liquidity	0.118 **	0.105 **
	(0.036)	(0.040)
Firm Size	0.184 ***	0.172 ***
	(0.060)	(0.065)
GDP Growth	0.053 *	0.060 *
	(0.026)	(0.028)
Inflation	−0.022	−0.019
	(0.012)	(0.014)
Constant	2.285 ***	2.200 ***
	(0.272)	(0.281)
R-squared	0.563	0.547
F-statistic	44.105 ***	42.234 ***

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

Table 8. Subsample analysis—By industry.

Variables	Basic Materials	Consumer Discretionary	Consumer Staples	Energy	Industrials	Telecommunications	Utilities
Capital Intensity	0.412 ***	0.378 ***	0.393 ***	0.432 ***	0.421 ***	0.380 ***	0.389 ***
	(0.072)	(0.068)	(0.070)	(0.075)	(0.069)	(0.065)	(0.073)
Debt Financing	0.182 ***	0.158 ***	0.165 ***	0.190 ***	0.173 ***	0.140 ***	0.188 ***
	(0.027)	(0.031)	(0.029)	(0.033)	(0.030)	(0.028)	(0.031)
Capital Intensity × Debt Financing	0.091 **	0.085 **	0.080 **	0.096 **	0.092 **	0.084 **	0.089 **
	(0.047)	(0.050)	(0.048)	(0.050)	(0.046)	(0.049)	(0.051)
Management Efficiency	0.208 **	0.190 **	0.211 **	0.221 **	0.212 **	0.185 **	0.210 **
	(0.045)	(0.048)	(0.046)	(0.050)	(0.047)	(0.045)	(0.049)
Liquidity	0.116 **	0.120 **	0.115 **	0.125 **	0.121 **	0.102 **	0.119 **
	(0.038)	(0.040)	(0.037)	(0.042)	(0.039)	(0.035)	(0.038)
Firm Size	0.189 ***	0.177 ***	0.186 ***	0.193 ***	0.180 ***	0.160 ***	0.178 ***
	(0.060)	(0.062)	(0.058)	(0.065)	(0.061)	(0.058)	(0.063)
GDP Growth	0.052 *	0.048 *	0.051 *	0.056 *	0.053 *	0.048 *	0.052 *
	(0.026)	(0.027)	(0.025)	(0.027)	(0.026)	(0.025)	(0.028)
Inflation	−0.021	−0.020	−0.019	−0.022	−0.020	−0.018	−0.019
	(0.012)	(0.013)	(0.011)	(0.013)	(0.012)	(0.011)	(0.013)
Constant	2.280 ***	2.200 ***	2.270 ***	2.310 ***	2.295 ***	2.220 ***	2.240 ***
	(0.278)	(0.285)	(0.270)	(0.285)	(0.272)	(0.265)	(0.276)
Observations	107	135	122	85	110	89	115
R-squared	0.560	0.557	0.559	0.564	0.562	0.548	0.561
F-statistic	43.502 ***	42.672 ***	43.225 ***	44.124 ***	43.675 ***	42.022 ***	43.207 ***

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

5.3. Pre and Post COVID-19 Period

To ensure the robustness of the results, we conducted an additional test to control for the potential impact of the COVID-19 pandemic. The global health crisis significantly affected economic activities, financial markets, and firm operations, making it essential to account for its influence when analyzing the relationship between capital intensity, debt financing, and profitability. The COVID-19 pandemic could have caused disruptions in business operations, changes in consumer demand, shifts in supply chains, and adjustments in financial strategies, all of which might influence firm profitability and the effectiveness of debt financing.

In line with macroeconomic and public health data for Oman, we classified 2020 as the COVID-19 year, capturing the period of peak disruptions, and 2021–2022 as the post-COVID recovery period. According to the World Bank (2022), Oman’s economy faced substantial contractions in GDP and industrial activity in 2020, while the Ministry of Health reported that the highest infection rates occurred in the same year, with vaccination campaigns and phased reopening beginning in late 2020 and continuing into 2021 (MOH Oman, 2021). By 2021, government stimulus measures and the gradual resumption of business activities marked the recovery phase. Recent empirical studies on Omani and GCC firms similarly adopt this periodization, treating 2020 as the pandemic year and 2021–2022 as the post-pandemic adjustment phase (Ahmed et al., 2024). Based on this classification, we split the sample into pre-COVID (2012–2019) and post-COVID (2021–2022) periods and ran separate regressions to examine whether the relationships between capital intensity, debt financing, and profitability were significantly affected by the pandemic.

The results, presented in Table 9, show that while the general trends remain consistent across the two periods, some variations in the magnitude and significance of the coefficients suggest that the COVID-19 pandemic did have an impact on firm profitability. Specifically, the effects of debt financing on profitability were stronger in the post-COVID period, possibly due to increased financial leverage used by firms to navigate economic uncertainties. Additionally, capital intensity appeared to have a more pronounced effect on profitability in the post-COVID period, likely reflecting shifts in investment strategies and operational adjustments made in response to the pandemic. By controlling for the COVID-19 effect, we provide a more nuanced understanding of the factors influencing firm profitability, ensuring that the results are not driven by external shocks and enhancing the robustness of the conclusions drawn from the baseline analysis.3

Table 9. Controlling for the COVID-19 effect.

Variables	Pre-COVID	Post-COVID
Capital Intensity	0.405 ***	0.432 ***
	(0.070)	(0.075)
Debt Financing	0.178 ***	0.202 ***
	(0.029)	(0.033)
Capital Intensity × Debt Financing	0.089 **	0.097 **
	(0.046)	(0.049)
Management Efficiency	0.212 ***	0.198 **
	(0.050)	(0.055)
Liquidity	0.114 **	0.118 **
	(0.037)	(0.041)
Firm Size	0.185 ***	0.177 ***
	(0.061)	(0.065)
GDP Growth	0.051 *	0.056 *
	(0.027)	(0.028)
Inflation	−0.020	−0.022
	(0.013)	(0.014)
Constant	2.290 ***	2.320 ***
	(0.280)	(0.288)
R-squared	0.560	0.565
F-statistic	44.204 ***	45.102 ***

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

5.4. Alternative Estimation Methods

To validate the reliability of the pooled OLS results presented in Table 4, this study performed additional robustness tests using Fixed-Effects (FE) and Random-Effects (RE) models. These models help control for time-invariant firm-specific characteristics that may bias pooled OLS estimates.

The Breusch–Pagan Lagrange Multiplier (LM) test was first conducted to assess whether the use of panel data models was appropriate. The test results were significant, indicating that there is meaningful firm-level variance and that panel estimation is preferred over pooled OLS. Subsequently, the Hausman specification test was employed to determine the more suitable estimator between the FE and RE models. The Hausman test favored the Fixed-Effects model, suggesting that unobserved firm effects are correlated with the regressors, making FE the more consistent estimator.

As shown in Table 10, the results from the FE and RE estimations remained qualitatively consistent with the main pooled OLS findings. Capital intensity and debt financing continued to show a positive and significant impact on profitability, and the interaction term between capital intensity and debt financing remained positive and significant. Control variables such as management efficiency, liquidity, and firm size also retained their expected signs and significance levels, while inflation remained insignificant across all specifications. These consistent results across different estimation techniques reinforce the robustness and stability of the findings, confirming that the main conclusions are not sensitive to the choice of estimation method.

Table 10. Robustness check using fixed-effects and random-effects models.

Variables	Fixed Effects	Random Effects
Capital Intensity	0.376 ***	0.392 ***
	(0.072)	(0.069)
Debt Financing	0.147 ***	0.158 ***
	(0.028)	(0.027)
Capital Intensity × Debt Financing	0.084 **	0.087 **
	(0.041)	(0.040)
Management Efficiency	0.191 **	0.198 **
	(0.049)	(0.047)
Liquidity	0.098 **	0.105 **
	(0.038)	(0.037)
Firm Size	0.163 ***	0.172 ***
	(0.060)	(0.057)
GDP Growth	0.050 *	0.052 *
	(0.025)	(0.024)
Inflation	−0.018	−0.017
	(0.013)	(0.012)
Constant	2.056 ***	2.135 ***
	(0.280)	(0.275)
R-squared (within)	0.541	0.548
F-statistic	39.882 ***	41.006 ***

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. The Hausman test favored the Fixed-Effects model (p < 0.05), confirming that firm-specific effects are correlated with the regressors.

5.5. Endogeneity Tests Using 2SLS and Two-Step System GMM

To address potential endogeneity concerns arising from simultaneity and omitted variable bias between debt financing and profitability, the study employs both Two-Stage Least Squares (2SLS) and Two-Step System Generalized Method of Moments (GMM) estimations. In the 2SLS framework, the potential endogeneity of debt financing is addressed by using lagged values of debt financing (t − 1, t − 2) and industry-average leverage ratios as instrumental variables. These instruments are theoretically justified as they influence firms’ current financing decisions but are unlikely to directly affect contemporaneous profitability, satisfying the relevance and exogeneity conditions. First-stage regression results confirm the strong correlation between the instruments and the endogenous variable (F-statistic > 10), supporting their validity.

For the dynamic analysis, the Two-Step System GMM approach is adopted, following Arellano and Bover (1995) and Blundell and Bond (1998), which combines equations in levels and first differences to exploit additional moment conditions. Lagged levels and first differences in the explanatory variables are used as instruments for endogenous regressors, and the collapse option is applied to prevent instrument proliferation. We also employ the Windmeijer finite-sample correction for standard errors. Diagnostic tests support the validity of the instruments: the Arellano–Bond AR(1) test indicates first-order serial correlation as expected (p = 0.031), while the AR(2) test shows no evidence of second-order serial correlation (p = 0.532). The Hansen test of over-identifying restrictions (p = 0.162) confirms that the instruments are valid and not correlated with the error term.

The results, summarized in Table 11, show that both 2SLS and GMM yield consistent estimates with the baseline OLS models. Capital intensity and debt financing remain positively and significantly associated with profitability, and the interaction term also retains its significance. These findings reinforce the robustness of the results and suggest that endogeneity does not materially bias the estimated relationships. Furthermore, the dynamic GMM results highlight a persistence effect in profitability, indicating that firm performance is influenced by prior-period profitability and financing structure decisions, consistent with financial behavior in emerging markets.

Table 11. Endogeneity test using 2SLS and two-step system GMM.

Variables	2SLS	GMM
Capital Intensity	0.408 ***	0.412 ***
	(0.071)	(0.073)
Debt Financing	0.182 ***	0.186 ***
	(0.028)	(0.031)
Capital Intensity × Debt Financing	0.091 **	0.093 **
	(0.048)	(0.051)
Management Efficiency	0.215 ***	0.218 ***
	(0.051)	(0.053)
Liquidity	0.118 **	0.122 **
	(0.038)	(0.040)
Firm Size	0.188 ***	0.191 ***
	(0.062)	(0.064)
GDP Growth	0.050 *	0.052 *
	(0.027)	(0.028)
Inflation	−0.020	−0.019
	(0.013)	(0.014)
Constant	2.295 ***	2.310 ***
	(0.283)	(0.289)
R-squared	0.559
F-statistic	43.984 ***	44.107 ***
Arellano–Bond Test (AR(1)—p-value		0.031
Arellano–Bond Test (AR(2))—p-value		0.532
Hansen Test—p-value		0.162

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

5.6. Non-Linear Specification of Capital Intensity

To examine the potential non-linear relationship between capital intensity and profitability, we introduce a squared term of capital intensity into the regression model. The model specification is as follows:

$$\begin{array}{cc}{\mathrm{Profitability}}_{it}=& {\beta }_0+{\beta }_1{\mathrm{CapitalIntensity}}_{it}+{\beta }_2({\mathrm{CapitalIntensity}}_{it}{)}^2+{\beta }_3{\mathrm{DebtFinancing}}_{it}\\ & +{\beta }_4({\mathrm{CapitalIntensity}}_{it}\times {\mathrm{DebtFinancing}}_{it})+\sum {\beta }_k{\mathrm{ControlVariables}}_{it}+{\epsilon }_{it}\end{array}$$

where $({\mathrm{CapitalIntensity}}_{it}{)}^2$ captures potential diminishing or threshold effects.

The results of this non-linear specification (Table 12) show that the coefficient of capital intensity remains positive and statistically significant, while the coefficient of the squared term is negative and significant at the 5% level. This indicates that profitability increases with capital intensity up to a certain point, after which excessive capital investment begins to reduce profitability, consistent with the law of diminishing returns. Importantly, the interaction term between capital intensity and debt financing remains positive and significant, suggesting that debt financing continues to play a moderating role in enhancing the returns from capital-intensive investments, even under non-linear effects.

Table 12. Robustness Test—Non-linear specification of capital intensity across estimation methods.

Variables	OLS	FE	RE	2SLS	GMM
Capital Intensity	0.412 ***	0.398 ***	0.405 ***	0.409 ***	0.411 ***
	(0.068)	(0.072)	(0.070)	(0.071)	(0.073)
Capital Intensity2	−0.087 **	−0.084 **	−0.086 **	−0.088 **	−0.089 **
	(0.039)	(0.041)	(0.040)	(0.042)	(0.043)
Debt Financing	0.183 ***	0.178 ***	0.180 ***	0.182 ***	0.185 ***
	(0.029)	(0.031)	(0.030)	(0.028)	(0.031)
Capital Intensity × Debt Financing	0.089 **	0.087 **	0.088 **	0.091 **	0.093 **
	(0.046)	(0.048)	(0.047)	(0.048)	(0.051)
Management Efficiency	0.214 ***	0.212 ***	0.213 ***	0.215 ***	0.218 ***
	(0.052)	(0.053)	(0.052)	(0.051)	(0.053)
Liquidity	0.120 **	0.118 **	0.119 **	0.118 **	0.122 **
	(0.037)	(0.038)	(0.037)	(0.038)	(0.040)
Firm Size	0.187 ***	0.183 ***	0.185 ***	0.188 ***	0.191 ***
	(0.061)	(0.063)	(0.062)	(0.062)	(0.064)
GDP Growth	0.051 *	0.050 *	0.051 *	0.050 *	0.052 *
	(0.027)	(0.028)	(0.027)	(0.027)	(0.028)
Inflation	−0.018	−0.019	−0.018	−0.020	−0.019
	(0.013)	(0.014)	(0.013)	(0.013)	(0.014)
Constant	2.301 ***	2.284 ***	2.292 ***	2.295 ***	2.310 ***
	(0.285)	(0.292)	(0.288)	(0.283)	(0.289)
R-squared	0.565	0.552	0.560	0.559
F-statistic	44.118 ***	41.782 ***	43.002 ***	43.984 ***	44.107 ***
Arellano–Bond Test (AR(1)—p-value					0.046
Arellano–Bond Test (AR(2))—p-value					0.579
Hansen Test—p-value					0.195

Note: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.

These findings provide additional robustness to our main results, demonstrating that the positive effect of capital intensity on profitability is conditional on the level of investment. Firms with moderate capital intensity benefit the most, while extremely high levels of investment may reduce efficiency and financial performance. Incorporating this non-linear specification enhances both the theoretical contribution and practical implications of the study by identifying threshold effects and highlighting the optimal use of capital and debt resources in non-financial firms.

6. Conclusions and Policy Implication

6.1. Conclusions

This study investigates the relationship between capital intensity, debt financing, and profitability using data from 76 non-financial firms in Oman over the period 2012–2022, offering insights into the financial dynamics of emerging markets.

The findings reveal that both capital intensity and debt financing significantly influence profitability, with their interaction further amplifying this impact. The analysis of non-linear effects also indicates a concave relationship between capital intensity and profitability, suggesting that while higher capital investment enhances firm performance up to a certain threshold, excessive capital accumulation may lead to diminishing returns. Larger firms, owing to greater access to capital markets and financial flexibility, exhibit a stronger relationship between debt financing and profitability compared to smaller firms, which face higher capital costs and limited financial access. Industry-specific analyses highlight those capital-intensive sectors, such as Energy and Industrials, demonstrate a more pronounced effect, whereas other sectors, like Consumer Staples and Telecommunications, show subtler relationships due to differing operational and capital requirements. Robustness checks, including controls for COVID-19-related economic disruptions, interaction-based subsample analyses, non-linear specifications, and endogeneity tests using Two-Stage Least Squares (2SLS) and two-step System Generalized Method of Moments (GMM), confirm that these conclusions are supported by rigorous empirical evidence rather than intuition alone. The results are consistent across multiple specifications, time periods, and firm characteristics, highlighting the reliability of the observed relationships

Overall, this study advances understanding of how firms in Oman manage capital structures to enhance profitability and offers actionable insights for corporate managers in optimizing debt-financing strategies. It also provides policy-relevant implications for strengthening financial systems in emerging markets. By empirically validating the nuanced interplay between capital intensity, financial leverage, and firm performance, this research contributes robust evidence to the literature while addressing the unique challenges and opportunities in the Omani context.

6.2. Policy Implication

The findings of this study carry significant policy implications for corporate managers, financial institutions, and policymakers, particularly in Oman and other emerging economies. Firstly, the positive impact of capital intensity and debt financing on profitability highlights the critical role of fostering an enabling financial environment. Policymakers should focus on improving access to credit, especially for small- and medium-sized enterprises (SMEs), which often face higher borrowing costs and restricted access to financial markets. Establishing initiatives such as credit guarantees, lower interest rates for SMEs, and promoting financial literacy can help reduce financing constraints and support profitability. Secondly, the industry-specific results emphasize the need for tailored policy interventions. Capital-intensive sectors such as Energy and Industrials demonstrated a stronger relationship between capital intensity and profitability. To support these industries, governments could introduce targeted incentives like tax breaks, subsidies, or concessional loans, enabling firms to invest in capital assets without overburdening their financial structures. Additionally, fostering partnerships between public institutions and private firms in these industries could stimulate innovation and operational efficiency, further enhancing profitability and economic contributions. Thirdly, the study also underscores the importance of resilience during economic disruptions, such as the COVID-19 pandemic. Policymakers should design contingency frameworks to support firms during such crises. Financial stimulus packages, deferred tax payments, and liquidity support schemes can play a crucial role in mitigating the adverse effects of economic shocks. In addition, strengthening regulatory frameworks to enhance financial stability and reduce uncertainty is essential to ensure firms’ ability to navigate turbulent periods effectively.

Fourthly, for corporate managers, these findings underscore the need to strategically balance capital intensity and debt financing to optimize profitability. Firms should focus on improving management efficiency, as it positively impacts financial performance. Managers can also enhance liquidity management practices to ensure sufficient buffers for operational continuity during periods of economic distress. Furthermore, financial institutions can use these insights to refine their lending strategies. Offering customized financial products to cater to the diverse needs of different industries and firm sizes can improve credit allocation efficiency and foster long-term relationships with clients. This approach would not only benefit firms but also enhance the stability and profitability of financial institutions. In the broader context, the study calls for a collaborative approach to economic development. Policymakers, financial institutions, and corporate entities should work together to build a robust financial ecosystem that promotes innovation, reduces financing constraints, and enhances resilience. For Oman and similar economies, such collaborative efforts can significantly improve firms’ contributions to GDP growth, employment generation, and overall economic diversification.

In sum, the policy implications derived from this study are multifaceted, addressing firm-specific strategies, sector-specific interventions, and macroeconomic resilience. By implementing these measures, policymakers and stakeholders can create an environment that sustains profitability, fosters innovation, and promotes sustainable economic growth in emerging markets.

6.3. Limitations and Further Research

This study is not without limitations, which open several avenues for future research. First, although subsample analyses were conducted by firm size, industry type, and pre-/post-COVID-19 periods to test the robustness of the findings, these regressions inevitably reduced the number of observations, which may have led to less stable coefficient estimates. Moreover, the study did not perform formal statistical comparisons (such as Chow tests) to validate differences across subsamples. Future research could therefore employ these formal tests to confirm whether the observed variations across groups are statistically significant. In addition, greater transparency and consistency in industry classification and coding criteria would enhance replicability and comparability across studies. Future research could also expand on this study by examining the relationship between capital intensity, debt financing, and profitability across a broader set of emerging economies to account for regional and institutional differences. Investigating the roles of corporate governance, ownership structure, and managerial efficiency as mediators or moderators could provide deeper insights into firm-level dynamics. Industry-specific analyses and longitudinal studies could uncover how technological advancements or regulatory changes influence capital-intensive and debt-financed firms. Additionally, future studies could consider incorporating industry-specific growth indicators, such as sectoral output growth or ROI growth, to better understand how firms in stagnant or declining industries utilize their assets. This would provide a more nuanced perspective on the varying effects of capital intensity across industries at different stages of growth and demand, complementing aggregate economic measures such as GDP growth.