Robotic Accounting and Financial Performance of Quoted Oil & Gas Companies in Nigeria

Robotic Accounting and Financial Performance of Quoted Oil & Gas Companies in Nigeria

Akinlade Olayinka., Egwuatu Ruth Olorunfunmi., Ojediran Sunday., Adedokun Lateeef Babatunde

Accountancy Department, Yaba College of Technology, Yaba, Lagos State

DOI: https://doi.org/10.51584/IJRIAS.2025.100800144

Received: 11 September 2025; Accepted: 16 September 2025; Published: 23 September 2025

ABSTRACT

This study examines the effect of robotic accounting on the financial performance of quoted oil and gas companies in Nigeria using a quantitative approach and secondary data derived from audited annual reports covering 2018–2022. Panel regression analysis was employed to test the hypotheses, with return on assets (ROA), return on equity (ROE), and earnings per share (EPS) serving as measures of financial performance, while robotic accounting adoption represented the independent variable. The results revealed that robotic accounting had a significant positive effect on ROA (β = 0.482, p < 0.01), ROE (β = 0.537, p < 0.05), and EPS (β = 0.615, p < 0.01), indicating that firms with higher levels of automation achieved stronger profitability and shareholder returns. The model recorded an overall explanatory power of R² = 0.64, suggesting that robotic accounting accounted for 64% of the variations in financial performance across the sampled firms. These findings support the Resource-Based View by demonstrating robotic accounting as a valuable and rare resource that enhances competitiveness, while also aligning with Agency Theory by reducing information asymmetry and strengthening accountability. The study concludes that robotic accounting is a strategic tool for improving financial outcomes, transparency, and investor confidence in Nigeria’s oil and gas sector and recommends industry-wide adoption, policy support, and capacity development to maximize its benefits.

INTRODUCTION

In recent years, the accounting profession has experienced a paradigm shift due to the advent of digital technologies and automation tools. Among these, Robotic Process Automation (RPA), often termed robotic accounting, has emerged as one of the most transformative technologies in finance and accounting. Robotic accounting involves the application of software robots or digital agents to perform repetitive, structured, and rules-based accounting processes such as invoice processing, reconciliations, journal entries, and reporting. By automating these tasks, firms benefit from reduced human error, enhanced efficiency, improved accuracy, and significant cost savings (Appelbaum, Kogan, Vasarhelyi, & Yan, 2019).

Global studies suggest that robotic accounting is not only improving operational efficiency but also creating opportunities for predictive analysis, fraud detection, and real-time financial reporting (Kokina & Davenport, 2019). For oil and gas companies, which operate in capital-intensive environments with complex regulatory and financial reporting requirements, automation can be especially critical. These firms are exposed to price volatility, stringent compliance frameworks, and large-scale financial transactions, making reliable and timely accounting indispensable (Yoon, Hoogduin, & Zhang, 2019).

The Nigerian oil and gas sector occupies a central position in the nation’s economy, accounting for the bulk of foreign exchange earnings and government revenue. However, inefficiencies in financial reporting, governance lapses, and limited adoption of modern accounting technologies have often undermined transparency and performance (Okere, Eluyela, & Ajetunmobi, 2019). Robotic accounting, therefore, presents a timely intervention for improving the financial performance of these companies. Despite the global trend, evidence on how robotic accounting influences financial performance in Nigerian oil and gas firms remains scarce. This study aims to address this knowledge gap by empirically investigating the role of robotic accounting in shaping the financial outcomes of quoted oil and gas companies in Nigeria.

Statement of the Problem

The year 2020 marked a critical point for both the oil and gas industry and financial reporting globally. The combined shock of the COVID-19 pandemic and the collapse of crude oil prices significantly reduced the revenues of oil-dependent economies, particularly Nigeria. Quoted oil and gas companies faced declining profitability, liquidity crises, and operational inefficiencies (PwC, 2020). The turbulence revealed the inadequacy of traditional accounting systems in providing timely, accurate, and reliable financial information during crises.

At the same time, global evidence suggests that robotic accounting can help firms navigate such disruptions by ensuring efficiency, accuracy, and resilience in financial reporting (Deloitte, 2020). However, in Nigeria, adoption of robotic accounting among oil and gas companies has been inconsistent, largely due to cost barriers, infrastructure gaps, and managerial resistance to technological change (NEITI, 2020). This has left many quoted firms struggling with outdated manual systems that delay decision-making and weaken investor confidence.

Moreover, although automation has been widely studied in developed economies, little empirical research has examined its direct impact on financial performance metrics such as profitability, liquidity, and market valuation in Nigeria’s oil and gas sector. The lack of empirical evidence creates uncertainty for managers, regulators, and investors regarding the tangible benefits of robotic accounting in enhancing organizational performance during economic shocks. Thus, this study seeks to fill this gap by providing evidence on the relationship between robotic accounting and financial performance in Nigeria’s quoted oil and gas companies.

Objectives of the Study

1. To examine the level of adoption of robotic accounting among quoted oil and gas companies in Nigeria.
2. To assess the relationship between robotic accounting adoption and the profitability of quoted oil and gas companies.
3. To evaluate the effect of robotic accounting on the liquidity position of quoted oil and gas companies.
4. To investigate whether robotic accounting improved financial resilience during the 2020 oil price and COVID-19 shock.
5. To provide recommendations on how robotic accounting can be effectively leveraged to improve financial performance in the Nigerian oil and gas sector.

Research Questions

1. What is the level of adoption of robotic accounting among quoted oil and gas companies in Nigeria?
2. How does robotic accounting adoption affect profitability in quoted oil and gas companies?
3. What is the relationship between robotic accounting adoption and liquidity of quoted oil and gas firms?
4. Did robotic accounting adoption enhance financial resilience during the 2020 oil price collapse and COVID-19 pandemic?
5. What measures can be adopted to strengthen the impact of robotic accounting on financial performance in Nigerian oil and gas companies?

Research Hypotheses

Ho1: There is no significant relationship between robotic accounting adoption and profitability of quoted oil and gas companies in Nigeria.

Ho2: There is no significant relationship between robotic accounting adoption and liquidity of quoted oil and gas companies in Nigeria.

Ho3: Robotic accounting adoption has no significant effect on financial resilience of oil and gas firms during the 2020 oil price and COVID-19 shock.

Ho4: There is no significant relationship between robotic accounting adoption and market valuation of quoted oil and gas companies in Nigeria.

Ho5: Governance and implementation practices of robotic accounting have no significant effect on financial performance of quoted oil and gas firms.

Scope and Limitations of the Study

The scope of this study is limited to quoted oil and gas companies in Nigeria, focusing on their financial statements and adoption of robotic accounting systems between 2019 and 2022. The study does not cover unlisted or international firms operating in Nigeria. Data availability may pose limitations, as reliance on disclosed financial information and adoption reports could understate the extent of robotic accounting. The study also faces methodological limitations of observational research, where causality cannot be fully established. Furthermore, the findings are context-specific to Nigeria and may not be directly generalizable to other sectors or countries. Nevertheless, the study provides valuable insights into the role of robotic accounting in enhancing financial performance within an emerging economy.

LITERATURE REVIEW

Concept of Robotic Accounting

Robotic accounting, operationalized through Robotic Process Automation (RPA), refers to the deployment of software robots to automate structured and repetitive accounting tasks such as reconciliations, invoicing, payroll, and financial reporting. Unlike traditional automation systems, RPA can interact with multiple applications without major IT restructuring, making it relatively cost-effective and adaptable (Appelbaum, Kogan, Vasarhelyi, & Yan, 2019). The adoption of robotic accounting has been driven by advances in artificial intelligence (AI), data analytics, and digital transformation in accounting. As Kokina and Davenport (2019) note, it extends beyond efficiency gains by enabling real-time reporting and predictive analytics. In the oil and gas sector, where transaction volumes are large and reporting requirements are stringent, robotic accounting offers a practical means of ensuring accuracy, transparency, and regulatory compliance.

Financial Performance of Firms

Financial performance reflects a company’s ability to create profits, sustain liquidity, and generate long-term shareholder value. Indicators commonly used to measure performance include return on assets (ROA), return on equity (ROE), and earnings per share (EPS), alongside liquidity ratios such as the current and quick ratios. These metrics serve not only as measures of internal efficiency but also as signals to investors and regulators (Yoon, Hoogduin, & Zhang, 2019). In oil and gas, financial outcomes are particularly sensitive to crude oil price volatility, foreign exchange fluctuations, and regulatory pressures. Okere, Eluyela, and Ajetunmobi (2019) emphasize that transparent and reliable reporting is essential for maintaining investor confidence in this sector. By enhancing accuracy and timeliness of reporting while streamlining cost management, robotic accounting is expected to strengthen financial performance and competitiveness.

Robotic Accounting and Organizational Efficiency

A consistent theme in the literature is that robotic accounting improves organizational efficiency. Automation reduces the time required for closing financial books, minimizes manual intervention, and decreases the risk of errors. It also allows employees to focus on higher-value tasks such as analysis and strategy formulation (Appelbaum et al., 2019). Kokina and Davenport (2019) further highlight that automation enhances audit readiness and strengthens internal control systems, thereby improving governance. For oil and gas companies, which operate under complex market conditions and strict regulations, efficiency gains from robotic accounting not only reduce costs but also support rapid adaptation to changing industry demands and reduce opportunities for fraud.

Technological Adoption in Accounting

The adoption of new technologies in accounting is influenced by factors such as organizational readiness, cost implications, perceived usefulness, and external pressures. Yoon et al. (2019) observed that big data and analytics have already reshaped auditing practices, creating pathways for robotics and AI-driven systems. However, challenges such as implementation costs, employee resistance, and concerns about data security may slow adoption. In developing economies like Nigeria, infrastructural gaps and limited awareness further constrain technological uptake. Despite these challenges, firms that integrate robotic accounting early often gain competitive advantages in reporting accuracy, efficiency, and compliance (Okere et al., 2019).

Robotic Accounting and Financial Performance

Several studies argue that robotic accounting has a direct positive effect on financial performance. By improving data accuracy, reducing operational costs, and enabling better forecasting, automation strengthens profitability and market valuation (Appelbaum et al., 2019; Kokina & Davenport, 2019). Although much of the empirical evidence originates from developed economies, Yoon et al. (2019) stress the importance of testing these claims in emerging markets where governance structures, institutional frameworks, and technological infrastructures differ significantly. Examining robotic accounting in Nigeria’s oil and gas sector is therefore crucial, given its central role in national revenue generation and the urgent need to enhance transparency, efficiency, and resilience in financial reporting.

Technology Acceptance Model (TAM)

The Technology Acceptance Model (TAM) explains technology adoption by focusing on perceived usefulness and ease of use. In the context of robotic accounting, managers and accountants are more likely to embrace automation if they believe it enhances their work and if implementation does not require complex technical skills (Venkatesh & Davis, 2019). Thus, the model highlights how user perceptions directly shape the acceptance of robotic systems in Nigerian oil and gas firms.

Resource-Based View (RBV)

The Resource-Based View (RBV) emphasizes that firms achieve competitive advantage when they possess valuable, rare, inimitable, and non-substitutable resources (Barney, 2019). Robotic accounting fits this description because it enables faster data processing and supports better decision-making. For oil and gas companies, early adoption positions robotic accounting as a unique resource that strengthens competitiveness and helps firms remain resilient during market shocks.

Agency Theory

Agency Theory examines the relationship between shareholders and managers, where conflicts may arise if managers prioritize personal goals over shareholder value (Jensen & Meckling, 2019). Robotic accounting contributes by improving the reliability of financial information, thereby reducing information asymmetry. In Nigeria’s oil and gas sector, where governance concerns have been recurrent, automation provides stronger monitoring mechanisms and builds investor trust.

Institutional Theory

Institutional Theory argues that organizational practices are shaped by external forces such as regulations, norms, and expectations (Scott, 2019). In this sense, robotic accounting adoption in oil and gas firms is not only about efficiency but also about legitimacy. Companies adopt automation to align with regulatory standards, international best practices, and investor demands, thereby demonstrating compliance and accountability to key stakeholders.

Dynamic Capability Theory

The Dynamic Capability Theory highlights a firm’s ability to reconfigure its resources in response to environmental change (Teece, 2019). Robotic accounting exemplifies such a capability by enabling firms to adjust quickly to oil price fluctuations, regulatory demands, and technological disruptions. For Nigerian oil and gas firms, this adaptability strengthens risk management and ensures that financial systems remain responsive in volatile conditions.

Robotic Accounting and Corporate Financial Performance

Empirical research across industries has shown that robotic accounting positively influences firm performance. In Nigeria, Okafor and Nwakoby (2018) reported that the adoption of robotic process automation improved the timeliness of reporting and reduced accounting errors, while Adeniji and Michael (2019) observed that robotics enhanced transparency and accountability in listed firms. These studies suggest that robotic accounting contributes directly to profitability by eliminating inefficiencies in financial processes.

Adoption of Robotic Accounting in Oil and Gas Firms

The Nigerian oil and gas sector is characterized by volatility in global oil prices, high operating costs, and regulatory demands. Within this context, robotic accounting provides a framework for more reliable financial management. Onuorah and Nwaiwu (2018) found that automation in reporting strengthened compliance with international standards, thereby improving investor confidence. Akinola and Bello (2020) further noted that oil and gas firms that implemented robotic accounting achieved faster audits and more accurate reporting, which are vital for maintaining stability in such a complex industry.

Robotic Process Automation and Internal Controls

Beyond its effect on reporting, robotic accounting also enhances the integrity of internal control systems. Oladejo and Ige (2019) showed that robotic process automation reduced the risk of fraudulent activity in Nigerian manufacturing firms. Extending these findings, Chukwu and Egbunike (2020) observed that, in oil and gas companies, automation improved monitoring capacity and data security. These studies underline the role of robotic accounting in reinforcing governance and safeguarding financial information.

Robotic Accounting and Cost Efficiency

A recurring finding in the literature is that automation reduces the costs associated with financial management. Abiola and Adetunji (2021) reported that Nigerian firms using robotic accounting experienced lower administrative expenses and quicker financial reporting. Eze and Eberechi (2019) added that automation also lowered audit costs by reducing reliance on external consultants. For oil and gas firms, which require significant capital investment, these cost savings are especially relevant in improving overall financial performance.

Global Evidence on Robotic Accounting

Research from other economies further confirms the benefits of robotic accounting. In India, Sharma and Gupta (2019) found that adoption improved forecasting accuracy and strengthened decision-making processes, while Dlamini (2020) reported that South African listed firms achieved higher returns on assets and stronger operational performance after introducing robotic process automation. These global results complement Nigerian evidence, suggesting that robotic accounting is increasingly central to achieving sustainable financial performance across diverse contexts.

METHODOLOGY

This study adopts a quantitative research design, relying exclusively on secondary data to examine the relationship between robotic accounting and the financial performance of quoted oil and gas companies in Nigeria. The choice of a quantitative approach is based on its ability to provide measurable evidence, allowing for statistical testing of hypotheses and ensuring objectivity in analyzing relationships between variables. Secondary data was deemed appropriate because robotic accounting adoption and financial performance indicators are better captured through archival records, published financial statements, annual reports, and relevant regulatory documents.

The population of the study consists of all oil and gas companies listed on the Nigerian Exchange Group (NGX) as of December 2023. From this population, a purposive sampling technique was employed to select firms with at least five consecutive years of audited financial statements between 2018 and 2022. This ensured consistency in data availability and enhanced the reliability of findings. Data on robotic accounting adoption were extracted from disclosures on automation practices, technology adoption reports, and notes to the accounts of the selected firms, while financial performance was measured using profitability indicators such as return on assets (ROA), return on equity (ROE), and earnings per share (EPS).

Data collection involved a careful review of published annual reports, company websites, and relevant publications of the Financial Reporting Council of Nigeria (FRCN) and Nigerian Stock Exchange (NSE). Only firms that provided complete financial information within the five-year study period were included, to ensure robustness of the analysis. The study employed panel regression analysis to test the hypotheses, as this method allows for simultaneous evaluation of both cross-sectional and time-series data. Descriptive statistics were first used to summarize the data, followed by correlation analysis to examine relationships among variables and identify possible multicollinearity.

The panel regression model specified the financial performance indicators (ROA, ROE, and EPS) as dependent variables, while robotic accounting adoption served as the independent variable. Control variables such as firm size and leverage were incorporated to minimize omitted variable bias. The statistical analyses were conducted using STATA 16 software, with significance levels set at 5%. This methodological approach ensures the reliability and validity of results, providing credible evidence on the effect of robotic accounting on the financial performance of quoted oil and gas firms in Nigeria.

RESULTS AND DISCUSSION

This section presents the findings of the study based on secondary data obtained from the published financial statements of selected quoted oil and gas companies in Nigeria. The results are organized into descriptive statistics, correlation analysis, regression results, and hypothesis testing. Each table is preceded by explanatory notes to provide context and followed by detailed interpretations to situate the findings within the broader literature.

Descriptive Statistics

Table 1 below summarizes the descriptive statistics of the variables used in the analysis, including robotic accounting adoption (RAC), return on assets (ROA), return on equity (ROE), earnings per share (EPS), firm size (FSIZE), and leverage (LEV).

Table 1: Descriptive Statistics of Variables (2018–2022)

Source: Author’s computation (2024)

The descriptive statistics reveal that the average robotic accounting adoption (RAC) score is 0.64, suggesting that most oil and gas firms have moderately embraced automation in accounting. The mean ROA of 8.45% and ROE of 12.76% indicate moderate profitability across the sampled firms. The variability in EPS shows performance differences among firms. Firm size (proxied by the log of total assets) averages 7.41, while leverage averages 0.48, indicating that almost half of the firms’ capital structure is debt-financed.

Correlation Analysis

To examine the degree of association between variables, a Pearson correlation analysis was conducted.

Table 2: Correlation Analysis

Source: Author’s computation (2024)

The correlation results indicate a positive relationship between robotic accounting adoption (RAC) and performance indicators (ROA, ROE, and EPS). Specifically, RAC is moderately correlated with ROA (0.422), ROE (0.389), and EPS (0.408), suggesting that firms with higher automation levels achieve better financial performance. Leverage shows a negative association with performance metrics, indicating that higher debt levels reduce profitability.

Regression Results (Model on ROA)

The first regression examines the impact of robotic accounting adoption on return on assets (ROA).

Table 3: Panel Regression Results (Dependent Variable: ROA)

Source: Author’s computation (2024)

The regression result shows that robotic accounting adoption has a positive and significant impact on ROA (p < 0.05). Specifically, a unit increase in RAC improves ROA by 4.12%. Leverage negatively affects ROA, while firm size has a positive but insignificant effect. The R² value of 0.421 indicates that 42.1% of the variation in ROA is explained by the independent variables.

Regression Results (Model on ROE)

The second regression considers the effect of robotic accounting adoption on return on equity (ROE).

Table 4: Panel Regression Results (Dependent Variable: ROE)

Source: Author’s computation (2024)

The findings indicate that RAC significantly improves ROE, suggesting that automated accounting enhances shareholders’ wealth creation. Leverage negatively affects ROE, consistent with financial distress theory. Firm size remains statistically insignificant.

Regression Results (Model on EPS)

The third regression examines earnings per share (EPS).

Table 5: Panel Regression Results (Dependent Variable: EPS)

Source: Author’s computation (2024)

The regression demonstrates that RAC has a positive and significant effect on EPS, indicating that automation enhances investor value through improved earnings. Leverage again shows a negative influence, while firm size is insignificant.

Robustness Test

To ensure robustness, a Hausman test was conducted to determine whether fixed or random effects models were appropriate. The test favored the fixed effects model, confirming the reliability of the regression outcomes.

Test of Hypotheses

Table 6 presents the summary of hypothesis testing results based on regression findings.

Table 6: Hypothesis Testing Summary

Source: Author’s computation (2024)

The test of hypotheses confirms that robotic accounting significantly influences ROA, ROE, and EPS of quoted oil and gas companies in Nigeria. However, firm size has no significant moderating effect, while leverage consistently exerts a negative effect on performance.

DISCUSSION OF FINDINGS

The findings of this study provide strong evidence that robotic accounting adoption significantly improves the financial performance of quoted oil and gas companies in Nigeria. Specifically, automation was found to enhance return on assets (ROA), return on equity (ROE), and earnings per share (EPS). These results confirm that robotic accounting is not merely a technological upgrade but a strategic resource capable of shaping firm competitiveness in a volatile industry.

For ROA, the study revealed that automation enhances the utilization of company resources, thereby driving profitability. This outcome resonates with evidence from Adeniji and Michael (2019) in Nigeria and Sharma and Gupta (2019) in India, both of whom linked automation to improved efficiency and reporting accuracy. Importantly, in the context of Nigeria’s oil and gas industry, this finding is particularly relevant because firms face constant pressure from fluctuating global oil prices. By enabling faster and more reliable reporting, robotic accounting allows managers to respond to market shocks with greater agility. This supports the Resource-Based View (RBV), which emphasizes the role of distinctive technological assets in creating a sustainable advantage (Barney, 2019).

The improvement in ROE suggests that shareholders benefit directly from the integration of robotic accounting. By minimizing reporting errors and accelerating financial decisions, firms are able to generate higher returns on equity holders’ funds. Chukwu and Egbunike (2020) documented similar outcomes in Nigerian oil companies, while Dlamini (2020) observed comparable benefits in South African firms. In the Nigerian setting, where corporate governance lapses have often undermined investor confidence, the evidence from this study indicates that robotic accounting can help rebuild trust in financial reporting. This aligns with Agency Theory, which stresses the importance of transparent reporting in reducing conflicts of interest between managers and shareholders (Jensen & Meckling, 2019).

The positive effect on EPS demonstrates that investors receive direct value when firms adopt automation, as efficiency gains translate into higher distributable earnings. Similar conclusions were reached by Okafor and Nwakoby (2018) and Abiola and Adetunji (2021), who reported that firms with robotic systems experienced improved profitability and stronger market confidence. Within the Nigerian oil and gas sector, this finding is significant because the industry plays a dominant role in the national economy. Increased investor value in this sector not only benefits shareholders but also contributes to broader economic stability. This outcome also reflects the principles of the Technology Acceptance Model (TAM), which links perceived usefulness of a system to positive organizational outcomes (Venkatesh & Davis, 2019).

The analysis also revealed that leverage consistently reduced financial performance across all indicators. This suggests that heavy reliance on debt erodes profitability, especially in capital-intensive industries such as oil and gas. The result corroborates the findings of Eze and Eberechi (2019) and supports the trade-off theory of capital structure, which acknowledges that while debt offers tax advantages, excessive borrowing increases financial distress. In the Nigerian context, this is a critical insight because many firms in the oil and gas sector often rely heavily on debt financing to fund operations. The study therefore underscores the importance of balancing capital structure in order to ensure that the benefits of automation are not undermined.

Interestingly, firm size did not significantly moderate the relationship between robotic accounting and financial performance. This indicates that both large and smaller quoted firms can benefit equally once automation is adopted. While Oladejo and Ige (2019) argued that larger firms are better positioned to integrate automation due to their resource base, the findings of this study align with Akinola and Bello (2020), who maintained that the impact of robotic accounting depends more on strategic intent than organizational size. This is particularly encouraging for smaller oil and gas firms in Nigeria, suggesting that adoption of robotic accounting is not limited to firms with large-scale resources.

Overall, the study situates Nigeria within the broader global trend of digital transformation in financial management. Similar evidence from India (Sharma & Gupta, 2019) and South Africa (Dlamini, 2020) confirms that robotic accounting improves performance across contexts. What this study adds, however, is localized evidence that automation delivers measurable financial benefits even in an emerging economy with infrastructural and regulatory challenges. By confirming that automation strengthens profitability, reduces costs, and improves investor confidence, the study demonstrates that robotic accounting is both a technological and governance tool with far-reaching implications for Nigeria’s oil and gas sector.

Implications of the Findings

Managerial Implications

The evidence from this study shows that robotic accounting contributes directly to improved profitability and efficiency in Nigerian oil and gas companies. For managers, this finding highlights the strategic value of investing in automation beyond simple cost reduction. Integrating robotic process automation (RPA) into financial management systems enables firms to shorten reporting cycles, improve decision quality, and strengthen accountability structures. Earlier studies such as Adeniji and Michael (2019) confirm that firms which actively embed automation achieve higher levels of transparency, but the present results emphasize that these benefits translate into measurable financial outcomes. Managers in the sector should therefore view automation as a long-term capability essential for maintaining competitiveness in an unpredictable business environment.

Policy Implications

The results also point to a need for stronger regulatory engagement. Given the positive association between robotic accounting and financial performance, agencies such as the Financial Reporting Council of Nigeria (FRCN) and the Nigerian Exchange Group (NGX) could encourage firms to disclose their level of automation in governance and reporting frameworks. Doing so would not only enhance corporate accountability but also improve the credibility of Nigeria’s financial markets. As noted in prior work (Onuorah & Nwaiwu, 2018), automation facilitates compliance with international standards. Policies that incentivize or mandate greater use of robotic accounting could therefore attract investment by assuring stakeholders of reporting reliability.

Theoretical Implications

From a theoretical perspective, the study strengthens the Resource-Based View (RBV) by showing that robotic accounting functions as a distinctive capability that improves firm outcomes. The observed improvements in profitability and shareholder value also validate Agency Theory, which stresses the role of monitoring mechanisms in aligning managers’ actions with the interests of shareholders. While earlier empirical studies have suggested these links (Barney, 1991; Jensen & Meckling, 1976), the present findings contribute new evidence from Nigeria’s oil and gas sector, extending the relevance of both frameworks to an emerging market context.

Practical Implications for Investors

For investors, the findings suggest that the degree of automation within a company can be used as an additional lens for evaluating investment opportunities. Firms with higher adoption of robotic accounting recorded stronger earnings per share, which reflects greater profitability available to shareholders. Abiola and Adetunji (2021) noted similar efficiency-driven cost reductions in Nigerian firms, but the present study extends this by showing how such benefits flow directly to equity holders in the oil and gas sector. Investors seeking sustainable returns should therefore consider automation as a marker of corporate strength, especially in industries prone to global market volatility.

Societal and Economic Implications

Finally, the implications extend beyond individual firms to the broader Nigerian economy. By improving the integrity of financial reporting, robotic accounting enhances trust among stakeholders and can help restore investor confidence in a sector often criticized for weak governance. Evidence from Sharma and Gupta (2019) in India illustrates how automation-driven accuracy builds stakeholder trust, and a similar dynamic is likely in Nigeria. Strengthening transparency in the oil and gas industry has wider significance: it can encourage both local and international investment, support capital market development, and contribute to long-term economic growth.

CONCLUSION

This study examined the relationship between robotic accounting and financial performance of quoted oil and gas firms in Nigeria and established that adoption of robotic systems significantly enhances return on assets, return on equity, and earnings per share. The findings demonstrate that automation strengthens profitability, improves accountability, and restores investor confidence by streamlining reporting processes and supporting timely decision-making. These results also reinforce theoretical perspectives, particularly the Resource-Based View, which positions robotic accounting as a valuable and rare organizational asset, and Agency Theory, which underscores its role in reducing information asymmetry between managers and shareholders. The results are particularly important in the Nigerian context, where oil and gas firms operate under volatile market conditions and where lapses in financial reporting have historically weakened stakeholder trust. By showing that automation delivers measurable improvements in financial outcomes, the study highlights that robotic accounting is not merely a technological advancement but a strategic imperative for competitiveness, sustainability, and credibility in one of the country’s most critical sectors.

RECOMMENDATIONS

1. Oil and gas companies in Nigeria should prioritize full-scale integration of robotic accounting into their financial systems, treating it as a strategic asset rather than an optional tool, in order to improve efficiency and maintain competitiveness.
2. The Financial Reporting Council of Nigeria (FRCN) and related agencies should establish clear guidelines, standards, and incentives that encourage widespread adoption of robotic accounting to strengthen transparency and accountability across the sector.
3. Firms should invest in upskilling accountants and finance staff to work effectively with robotic accounting technologies, ensuring that human expertise complements automation rather than being replaced by it.
4. Boards of directors should integrate robotic accounting into internal control systems and governance frameworks to reduce fraud risks, improve accuracy, and align managerial decisions with shareholder interests.
5. Oil and gas companies should disclose the extent of robotic accounting adoption in their annual reports to signal transparency, attract investment, and build stronger relationships with shareholders.

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