Enhancing Technical Efficiency in the Oil and Gas Sector: The Role of CEO Characteristics and Board Composition

Abstract

This study investigates how CEO characteristics, board composition, and firm size influence the technical efficiency (TE) of energy firms. We aim to understand how these factors contribute to production inefficiencies, which may help explain fluctuations in oil prices. Using stochastic frontier analysis (SFA), we analyze data from 100 American energy firms over the period from 2006 to 2019. Our results show that inefficiencies in production are primarily driven by specific CEO traits, the size and structure of the board, and the overall size of the firm. Based on the findings of this study, we recommend focusing on the selection of executive managers with specific qualifications, particularly those with extensive experience in managing oil and gas companies. Leadership positions should prioritize seasoned managers with accumulated expertise in this sector, and preference should be given to candidates with advanced educational backgrounds. Encouraging CEOs to acquire equity stakes in the company can significantly boost the technical efficiency of oil and gas firms. Additionally, offering competitive salaries and performance-based bonuses may further enhance managerial effectiveness and drive technical improvements. In addition, expanding the size of boards of directors in oil and gas companies is also anticipated to positively influence their technical efficiency. Finally, pursuing mergers and acquisitions to grow the scale of oil and gas companies represents a strategic approach to improving operational efficiency while contributing to the stability of global energy prices.

1. Introduction

In response to the rapid rise in global energy prices, many countries are looking for ways to make their energy sectors more efficient. A key part of this effort is understanding energy productivity and performance, both of which are essential for optimizing the use of resources in an increasingly competitive market (Abbott & Cohen, 2009; Fang et al., 2009; Gong, 2018). The main goal of any investment is to maximize profit and create value for the firm, and technical efficiency plays a crucial role in this process. Technical efficiency refers to the extent to which a firm optimally utilizes its production inputs to achieve maximum output or minimizes the use of inputs to maintain a specific level of output (Zhang & Deng, 2024). The concept revolves around the proximity between a firm’s actual output and the potential optimal output that could be achieved under ideal conditions. A smaller gap between the two signifies a higher level of technical efficiency, as highlighted by Battese and Coelli (1995). Technical efficiency can be analyzed using two distinct approaches: input-oriented and output-oriented (Fethi & Pasiouras, 2010). According to Coelli et al. (2005), the input-oriented approach focuses on determining the extent to which input quantities can be proportionally reduced without affecting the level of output, whereas the output-oriented approach examines how much output can be proportionally increased without altering the input quantities. When a firm achieves technical efficiency, it minimizes operational costs, maximizes profitability, and enhances competitiveness. This underscores its critical role in optimizing resource utilization and achieving sustainable growth in competitive markets (Yousaf, 2024).

In industries like oil and gas, technical efficiency is particularly critical due to the resource-intensive nature of operations and the environmental challenges they pose. Studies suggest that factors such as managerial quality, innovation in technology, and adherence to environmental regulations significantly affect technical efficiency levels (Zhou et al., 2008; B. Lin & Du, 2013).

It affects important factors such as productivity, profitability, and stock prices, which all influence investment decisions. Firms with lower technical efficiency tend to be less profitable (Sheu & Yang, 2005). In the oil and gas sector, this inefficiency contributes to fluctuations in oil prices (Kesicki, 2010), which has led to a growing interest in understanding the factors that drive technical efficiency in this industry.

The efficiency of petroleum firms is directly linked to how well they manage and use their resources, which in turn affects oil prices. For example, Bodenstein and Guerrieri (2011) found a strong connection between oil supply shocks, efficiency shocks, and changes in oil prices. When oil production and reserves are lower, it is often due to poor technical efficiency in oil and gas firms. However, decisions about production and investment are influenced not only by financial factors but also by behavioral ones. Therefore, analyzing how well these firms use their resources is a critical part of understanding corporate governance in the energy sector.

Despite its importance, the technical efficiency of oil and gas firms remains an underexplored area in the literature. While many studies have investigated efficiency in other industries (e.g., Aggrey et al., 2010; S. F. Yang et al., 2013; Charoenrat & Harvie, 2014; Sahoo & Nauriyal, 2014), relatively few have focused on the oil and gas sector. Most existing research has examined financial performance or broad governance practices, leaving a gap in understanding how specific internal factors, such as CEO characteristics, board dynamics, and firm size, influence technical efficiency. Additionally, the unique challenges faced by the oil and gas industry, such as high production costs and market volatility, necessitate a targeted investigation into these relationships. This study aims to fill this gap by focusing on the impact of CEO characteristics, board composition, and firm size on technical efficiency in American oil and gas firms. Unlike prior research that primarily evaluates governance factors in terms of financial outcomes, this study emphasizes their role in driving operational efficiency. Specifically, it examines how CEO traits, board structure, and firm size collectively shape resource utilization and efficiency within the sector.

The study of this research gap is of utmost importance, as understanding and identifying the factors affecting the technical efficiency of oil and gas companies will significantly contribute to improving their efficiency and sustainability. This, in turn, helps stabilize energy supplies and reduce price volatility.

Previous research highlights that various factors such as a firm’s age, foreign ownership, export activity, sector, location, size, and workforce skills impact technical efficiency. However, this study focuses on three main elements: the characteristics of the Chief Executive Officer (CEO), the composition of the board of directors, and the size of the firm, and how these factors influence technical efficiency in oil and gas companies. Efficient resource management is crucial for maximizing production, and corporate governance plays a key role in this process (Bruce, 2011).

This study is grounded in four fundamental theories to examine the most influential factors on the technical efficiency of oil and gas companies. First, the focus on the characteristics of general managers, such as age, education, and experience, finds its theoretical foundation in the Upper Echelon Theory, which emphasizes the importance of executive characteristics in shaping all corporate decisions, including operational ones, which directly influence resource utilization. Similarly, the Human Capital Theory highlights the significance of the educational level, field of study, and executive experience in decision-making quality and execution capabilities.

On the other hand, when analyzing technical efficiency, it is essential to consider the Resource-Based View (RBV), which posits that a company’s internal resources are the key to achieving sustainable competitive advantage. According to this theory, successful companies are distinguished by their possession of unique resources and strategies that are difficult for competitors to replicate. Thus, focusing on executives as the most influential factor and understanding how their characteristics, such as education and exceptional experience, affect efficiency is a logical choice.

Finally, the Agency Theory, which recognizes the existence of agency problems requiring the implementation of effective corporate governance systems to address them, underscores the importance of studying board characteristics and managerial ownership. This is particularly crucial for understanding the factors influencing the technical efficiency of oil and gas companies, whose operations are highly complex and require decisions that align with the interests of shareholders and owners to ensure the sustainability of these companies.

These variables have also proven their robustness through the results obtained in several previous studies in this field. In fact, studies show that a CEO’s education and experience significantly affect their decision-making and the performance of the firm (S. Wang & Chen, 2019). Similarly, the size and independence of the board of directors have a major impact on a firm’s efficiency (Ramos & Díaz, 2020). To investigate these relationships, this study applies the stochastic frontier approach (SFA), based on the model developed by Battese and Coelli (1995), to analyze how these governance factors influence technical efficiency and resource management in American oil and gas firms.

The structure of this study is as follows: Section 2 reviews the literature on firm-specific factors, governance, and technical efficiency. Section 3 explains our methodology. Section 4 presents the empirical findings, and Section 5 offers an in-depth discussion. Finally, Section 6 provides conclusions and recommendations.

2. Literature Review

An examination of the literature reveals insights into the technical efficiency of firms. Eller et al. (2011) provide empirical evidence regarding the revenue efficiency of oil companies, asserting that differences in structural and institutional features can explain variations in technical efficiency among these firms. While decisions to produce or invest in oil and gas are primarily driven by financial factors, behavioral components also play a significant role. This article aims to investigate the behavior of petroleum enterprises, their production efficiency, and the associated corporate governance. Various studies have focused on the determinants of technical efficiency across different sectors (see

Table 1. Firm efficiency impacting factors as identified in the literature.

Authors/Years	Countries	Sector of the Firm	Approach	Input Variable	Output Variable	The Determinants of Efficiency
Wu et al. (2007)	China	Watch and clock manufacturing firms	DEA	Capital Labor Intermediate inputs	Gross output	- R&D ratio - Size
Aggrey et al. (2010)	East Africa (Ugandan and Tanzania)	Ugandan and Tanzanian manufacturing firms	- DEA - GLS technique	Capital Labor Intermediate inputs (raw materials including energy)	The value of all output produced by the firm	- Firm’s age - Foreign ownership - Export participation - Sector effects - Firm’s location
Admassie and Matambalya (2002)	Tanzania	A total of 148 SMEs (food processing, textile, and tourism firms) located in different parts of Tanzania	A Cobb–Douglas stochastic frontier production function	Labor Material Capital	Sales	- Age in years - Size - Skill—labor - Skill—management
S. F. Yang et al. (2013)	Taiwan	Taiwan’s manufacturing industries	DEA	Number of employees Capital stock	Value added	- R&D expenditures - Age
Charoenrat and Harvie (2014)	Thailand	Manufacturing SMEs	SFA	The net value of fixed assets The total number of employees	Value added	- Firm’s size - Skilled workers - Firm’s location - Ownership type - Shared ownership - Export intensity
Hanousek et al. (2012)	The Czech Republic	Manufacturing industry	The Cobb–Douglas function	The capital Labor	Firm sales	- Ownership effects - Effects of firm characteristics (size, age) - Effects of economic sectors
Fang et al. (2009)	China and the US	Coal industry	CCR and BCC models in the advanced DEA linear programming	Operating costs Total assets Numbers of employees	- Earnings per share - Operating revenue - Net profit before tax	- Ownership - Development stages - Industry concentration - Over-competitiveness - High withdrawal threshold - Rules, regulations
Sahoo and Nauriyal (2014)	India	Software industries	DEA	Employment (labor) Expenses on computer and electronic instruments Operating expenditure Utility expenditure	Sales revenue	- R&D intensity: RDI - Export intensity - Royalty payments: RI - Wages and salaries (W&S) - Firm size: SIZE - Age of the firm: AGE - Ownership
Alvarez and Crespi (2003)	1979–1994	All industrial sectors in the Chilean industry	DEA	Labor and fixed capital	Annual total sales	- Sales per worker - Owner education - Technological innovation - Credit access - Outward orientation - Qualification of workers - Machinery age - Equipment age - Vehicle age - Use of development programs
Erturk and Turut-Asik (2011)	Turkey	Natural gas distribution companies	DEA	Capital costs Operating costs	- Residential consumption and industrial consumption - Total consumption number of customers peak demand	- Getting a license with tenders versus others - New firms versus old firms - Environmental factors - Public versus private companies - Small firms versus large firms
Yao et al. (2007)	China	Insurance companies	DEA	Capital Labor	Payment and benefits Premiums Investment income	- Firm’s size - Ownership structure - Human capital - Mode of business
Fenn et al. (2008)	European countries	Insurance companies	SFA	Labor Real debt capital	Net incurred claims on life and non-life policies	-Firms’size
See and Coelli (2012)	Malaysia	Thermal power plants	SFA	Capital Fuel Labor Other inputs	Electricity sent-out	- Ownership - Plant type - Plant size - Plant age
Setiawan et al. (2012)	Indonesia	Food and beverages industry	DEA	Material Labor Capital	Value of gross output produced by the establishment	- The firm’s size - The technologies used
Suyanto and Salim (2013)	Indonesia	Pharmaceutical sector	DEA	Capital Labor	Value-added	- Foreign Direct Investment (FDI) - Firm’s age
Bhattacharyya and Pal (2013)	India	Commercial banks	SFA	Deposits Labor Capital	Investment loans and advances	- Branches of the bank - Capital adequacy ratio
Servin et al. (2012)	Latin America	Microfinance institutions	SFA	Assets, operating expenses, and personnel	Number of outstanding loans	- Use of technology
Charoenrat et al. (2013)	Thailand	Manufacturing industry	SFA	Capital Labor	Value added	- Firm’s size - Firm’s age - Skill - Location
Castiglione and Infante (2014)	Italy	Manufacturing firms	SFA	ICT capital, non-ICT capital, high-skilled labor, low-skilled labor, and raw materials	The firm’s sales revenue	- Age - Size - Group - Area skill

Source (the authors).

). In our study, we specifically examine the effects of CEO characteristics, board composition (including size and independence), and firm size on technical efficiency, allowing us to develop relevant hypotheses.

Regarding previous studies in the field of TE, we try to include all potential factors that seem to have an impact on firm technical efficiency. In fact, the choice of CEO age as a determinant of technical efficiency (TE) is supported by the extensive literature that links age to critical behavioral and cognitive traits influencing decision-making (Yim, 2013; Adhikari et al., 2015). Managerial education also seems to be a critical determinant of TE because it shapes decision-making frameworks, risk preferences, and strategic resource allocation (Bender et al., 2016). Especially the nature of CEO education, for example, has been linked to better financial reporting and innovation, both of which are pivotal to firm TE (Mario et al., 2019). By analyzing education as an independent variable, this study aims to capture its role in fostering efficient resource utilization and strategic alignment. In addition, managerial career experience is crucial to explain the firm’s TE due to its significant influence on decision-making and performance (Crossland et al., 2014; Huang, 2014).

This study examines corporate governance, with a particular focus on the structure and dynamics of the board of directors, which numerous studies have identified as crucial in explaining technical efficiency (TE). From a theoretical perspective, Agency Theory highlights the necessity of establishing governance mechanisms to curb managerial opportunism, such as the misuse of company assets and resources or making decisions that do not serve stakeholders’ interests (Jensen & Meckling, 1976). For this, we will focus on board compositions and CEO ownership, remuneration, and tenure. Furthermore, Jensen (1993) noted that several characteristics of the board of directors can largely influence its effectiveness, namely CEO duality, board size, independence, and financial expertise of directors. Finally, we propose first that size is a potential variable that can explain TE because it reflects the operational scale and resource capacity, both of which significantly influence TE (Hanousek et al., 2015).

The analysis of Table 1 reveals that firm efficiency is influenced by a wide range of determinants, including firm size, age, ownership type, and innovation activities such as R&D intensity and technological adoption. These factors directly and indirectly shape technical efficiency (TE) by optimizing resource allocation, enhancing productivity, and driving output growth. The determinants outlined in Table 1 not only affect general firm performance but also serve as critical drivers of technical efficiency within specific industries and countries. We also note a large use of the SFA technique for empirical investigations. However, it is worth noting that there is a significant lack of focused research examining these determinants in the context of the oil and gas sector, which represents a key area for further investigation.

2.1. CEO Age and TE

The age of a CEO is widely acknowledged as a determinant of managerial decision-making and strategic vision. Aging induces physiological and cognitive changes that influence risk tolerance and adaptability, both of which are critical to enhancing a firm’s technical efficiency (TE) (Yim, 2013; Adhikari et al., 2015). Therefore, career concerns may make younger CEOs turn out to be slow and unwilling to endanger future earnings and, as a result, avoid intermingling in any risky activities. Older CEO has less mental ability to work hard for a long time and cannot combine different new technologies and information than young CEOs (W. S. Lee & Moon, 2016). As a result, the older top managers tend to be risk-averse (Barker & Mueller, 2002). Yet, as they grow older, their risk-taking option and liability for adopting and accepting new things would gradually fade away. As a result, older CEOs may prove to be less capable of quickly learning and integrating new information.

The CEO’s age is widely considered a proxy for their experience level and risk-taking and change-related options. Young CEOs are assumed to enjoy less experience and knowledge in firm management and control, but they would perfect both as they become older (W. S. Lee & Moon, 2016).

The positive effect of managers’ age on firm TE can be justified because managers are given greater knowledge thanks to past errors. So, older CEOs are considered more highly reliable, efficient, and trustworthy than their younger counterparts (Adhikari et al., 2015).

Hence, the CEO’s age appears to positively influence the oil and gas firms’ TE morning to a noticeable effect on the CEO’s competence level. Thus, any increase noticed to prevail in firm TE would certainly bring about an increase in its productivity (Wolf, 2009; Eller et al., 2011). The relationship between CEO age and TE lies in the trade-off between innovation and stability. While younger CEOs may lack the experience necessary for managing complex organizational structures, their willingness to embrace risk may drive short-term efficiencies. Conversely, older CEOs with refined managerial expertise and a focus on long-term operational stability are more likely to sustain TE over time. The following hypothesis can be drawn:

H₁: 

The CEO’s age positively affects the oil and gas firms’ TE.

2.2. CEO Education and TE

The educational background of a CEO plays a critical role in shaping corporate decisions and influencing the technical efficiency (TE) of a firm. Highly educated CEOs are often better equipped to approach complex problems with systematic thinking and implement strategies that enhance resource acquisition and utilization (Li & Zhang, 2013). For example, CEOs with advanced degrees, particularly in science and engineering, are likely to prioritize R&D investments, thereby driving innovation and improving operational efficiencies (Bender et al., 2016).

MBA programs produce graduates that sound more risk-averse, for MBA programs do not generally help in kindling the development of risk-taking competencies. However, on the other hand, the top manager’s financial education background and skills can play an essential role in elaborating financial reporting (Mun et al., 2020).

Recently, Mario et al. (2019) have studied how CEO training shapes environmental attitudes in business decision-making, and they found a positive association between CEO education and firms’ energy efficiency. Hence, the following set of hypotheses, which help in highlighting the association between the oil and gas firms’ related TE and the CEO’s respective education, is advanced:

H₂: 

The CEO’s education contributes to increasing the oil and gas firms’ TE.

H_2a: 

The CEO’s financial education participates in increasing the oil and gas firms’ TE.

H_2b: 

The CEO’s technical education helps in increasing the oil and gas firms’ TE.

2.3. CEO’s Career Experience and TE

The career experience of a CEO profoundly influences their approach to strategy, risk, and innovation, all of which have implications for a firm’s TE. CEOs with extensive experience in specialized roles (e.g., production, finance, or administration) bring unique perspectives that can drive strategic actions and operational efficiencies (Crossland et al., 2014; G. Wang et al., 2016). For example, CEOs with experience in production-related activities are likely to focus on optimizing processes, reducing inefficiencies, and achieving higher output with minimal resource wastage.

In contrast, CEOs with limited or generalized experience may prioritize short-term gains, potentially compromising long-term investment efficiency (Huang, 2014). This highlights the importance of prior career specialization in shaping a CEO’s ability to implement strategies that align with sustainable TE goals. Empirical evidence suggests that career experience in output-oriented functions such as marketing and sales fosters creativity, enabling CEOs to design innovative approaches to enhance operational outcomes (G. Wang et al., 2016). Consequently, the following hypothesis is proposed to reflect the relationship between CEO career experience and TE:

H₃: 

The CEO’s career experience in production/operational activities positively affects oil and gas T.E.

2.4. CEO’s Duality and TE

From a theoretical perspective, it is important to propose CEO duality as a variable that could explain the technical efficiency of oil and gas companies, as it influences decision-making processes, corporate governance effectiveness, and resource allocation. Based on Agency Theory (Jensen & Meckling, 1976) and the seminal paper of Jensen (1993), CEO duality may reduce board oversight, increasing the likelihood of agency conflicts and inefficiencies. However, from the perspective of the Upper Echelon Theory, combining roles can lead to more coherent and faster decision-making, which is critical in the complex, capital-intensive oil and gas industry. Additionally, the Resource-Based View suggests that effective leadership, shaped by governance structures like CEO duality, is a unique internal resource that can enhance the company’s competitive advantage. This dual impact makes CEO duality a key factor in understanding how leadership structures influence operational efficiency and sustainability, further supported by the Stewardship Theory.

The stewardship theory argues that intrinsic satisfaction emanating from achievement, recognition, respect, and reputation is likely to induce the CEO further to promote firm efficiency. In effect, dual leadership allows firms to make prompt decisions and respond swiftly and quickly to new information regarding separate leadership. The CEO is endowed with the most accurate and fit knowledge of the firm’s strategic challenges and opportunities. Duality helps in discarding an unnecessary additional chain of command. Still, an advanced counter-argument stipulates that separating both functions will help reduce agency costs and optimize firm performance.

The positive effect of dual leadership proves to be rather pronounced concerning companies characterized by high information costs than those witnessing low information costs (T. Yang & Zhao, 2014). Dual-structure characterized firms are usually associated with a rather effective accounting performance and, consequently, more highly improved efficiency. More recently, a study by Abiad et al. (2025) found that the impact of CEO duality is mixed. Subsequently, the following hypothesis can be developed:

H₄: 

CEO duality positively affects the oil and gas firm’s overall TE.

2.5. CEO’s Ownership and TE

The agency problem questions whether managers could pursue other targets than the owners aspire. Too great managerial ownership would help the managers to become entrenched and enjoy their private benefits of control. Consequently, large owners may engage in self-dealing, likely to attenuate efficiency. Insider ownership is one of the key parameters used to judge and assess the extent of firm efficiency level. Sheu and Yang (2005) argue that the owner holding a large proportion of shares (blockholders) is not entitled to take part in the daily operations and running of the company. The Agency Theory suggests that increased wealth may induce top managers to have long-term oriented vision and targets. By the joint means of management and supervisory boards, ownership may favor an enhanced form of direct executive control within the company (Hanousek et al., 2012).

Thus, higher rates of executive stock ownership may be viewed as a means whereby managers are provided with adequately enhancing incentives likely to ensure higher managerial efficiency levels coupled with greater firm value. In this way, it seems clear that managerial ownership may stand as a real effective enhancer of productivity (Chung & Pruitt, 1996). So, it follows that the following baseline hypothesis seems worth formulating:

H₅: 

CEO ownership positively affects the oil and gas firms’ production efficiency.

2.6. CEO’s Remuneration and TE

The CEO’s remuneration framework is a highly important determinant critically useful in evaluating firm efficiency. However, the perceived effectiveness of the CEO relating compensation plans harmoniously maintaining a mutual alignment of both the managers’ and shareholders’ interests turns out to be a controversial topic.

According to Matolcsy and Wright (2011), an efficient CEO compensation structure is reckoned to be highly dependent on the underlying economic characteristics of the firm and sounds, therefore, helpful in minimizing agency costs. For Amornkitvikai and Harvie (2011), the CEO remuneration schemes are discovered to have a significantly positive correlation with the technical efficiency of listed manufacturing enterprises.

Executive remuneration may take several forms, such as salary, employee benefits, and perquisites. Still, the CEO compensation scale depends on the firm’s characteristics and performance. According to Murphy (1999), the CEO’s pay proves to be remarkably higher in large firm cases. This is because the large firms’ operational complexity, characterized by growth opportunities and riskier operations, entails the designation of high-level performing executives. Therefore, the CEO would acquire a corresponding higher compensation, and some portion of his bonus should depend on his proper individual performance (Murphy, 1999). More recently, Firth et al. (2015) have examined the relative pay effect (manager’s pay in relevance to the average worker’s pay) on firm productivity. They have discovered that relative pay is negatively associated with high productivity. They have founded their results on the fact that workers prove to be alienated once their incomes turn out to be far lower than those of the top management, which is likely to culminate in lower productivity.

As for Amornkitvikai and Harvie (2011), the rate of executive remuneration is documented as being significantly and positively correlated with the listed manufacturing enterprises’ respective technical efficiency. This argument paves the way for the following hypothesis:

H₆: 

The CEO’s remuneration affects the oil and gas firm’s TE positively.

2.7. CEO’s Tenure and TE

CEO tenure, defined as the duration of a CEO’s service within the firm, is an important indicator of their experience, persistence, and adaptability. While longer tenure can provide CEOs with a deeper understanding of the firm’s operations and strategic environment, it may also lead to entrenchment and resistance to change, particularly in rapidly evolving industries like oil and gas (G. Wang et al., 2016). This duality of tenure effects is critical in industries that demand continuous innovation, operational flexibility, and responsiveness to external pressures.

In the oil and gas sector, where firms operate under high capital intensity, complex technological processes, and volatile commodity markets, a CEO’s tenure can significantly influence their strategic decisions. Longer-tenured CEOs may prioritize stability and operational efficiency over innovation, potentially resulting in underinvestment in critical areas such as R&D (Barker & Mueller, 2002). While this conservative approach may benefit firms in the short term by reinforcing technical efficiency, it could hinder long-term adaptability and growth. Furthermore, older CEOs may face declining motivation to pursue aggressive strategies as their career approaches its end, instead focusing on maintaining the status quo (Murphy, 1999; Brickley, 2003).

On the other hand, shorter-tenured CEOs may lack the accumulated power and firm-specific knowledge required to withstand external pressures from stakeholders. This can lead to higher turnover rates, especially in smaller firms, where CEO performance is more closely scrutinized (Jenter & Kanaan, 2015). For oil and gas firms, where decision-making requires a balance of deep industry expertise and forward-looking innovation, the impact of tenure is particularly pronounced. CEOs who fail to align their strategies with the industry’s evolving challenges may be replaced, further influencing technical efficiency. Considering these dynamics, the relationship between CEO tenure and TE in the oil and gas sector highlights a potential trade-off between experience and adaptability, leading to the following hypothesis:

H₇: 

The CEO’s tenure negatively affects the petroleum firms’ TE.

2.8. Financial Expertise and TE

It seems worth highlighting, in this regard, that firms are often in urgent need to obtain and gain outsider financial expertise and aspire more knowledgeable directors in a bid to improve both the corporate governance quality as well as the overall efficiency (Jeanjean & Stolowy, 2009).

In general, boards of directors incorporating more outside directors are likely to take different decisions, rather more advantageous than the usual ones that could improve the board’s efficiency. Financial executives are expected to provide knowledge of a specific nature to the corporate board members and demonstrate a significant financial performance imprint. Yet, extra financial expertise may result in unnecessary costs, though very scarcely, if the company does not highly request it. In effect, financial experts might well-exert significant influence that could not necessarily favor the shareholders’ interests (Güner et al., 2008). In this sense, one may presume that financial expertise could turn out to have an impact on firm technical efficiency, for a financial director (e.g., investment bankers) usually detains a thorough and timely knowledge of the prevalent conditions predominating the financial markets such as for instance information concerning the least costly and most prudent way for acquiring long-term or working capital (Y. S. Lee et al., 1999). At this level, the following hypothesis can be put forward:

H₈: 

Financial expertise positively affects oil and gas production efficiency.

2.9. The Board’s Size and TE

The board’s size comes among the director’s board, relating characteristics that sound likely to affect firm efficiency. Its importance stems from the diversity and wide range of studies appearing in the literature that prove to deal with its influence on firm performance and value (Maka & Kusnadi, 2005; Coles et al., 2008).

The main reason behind the board’s size effect is the increasingly surging and recurrent problems of communication and coordination that prove to occur. As the number of board members registers an increase, its ability to control would decrease. This is likely to bring about a noticeable rise in agency problems owing mainly to the separation of management and control (Yermack, 1996; Bozec & Dia, 2007; Ramos & Díaz, 2020). Large boards may render communication and decision-making more cumbersome than the smaller ones. As a result, directors would be less effective or unable to control the managers. Bozec and Dia (2007) document that board size, firm performance, and value negatively correlate. It follows that large boards turn out to affect firm efficiency and point to the difficulties it brings about while trying to solve the agency problem among the board members. Indeed, smaller groups usually prove to be more cohesive, more productive, and more liable to monitor the firm in a rather effective way.

Conversely, however, a larger board is likely to engender higher coordination costs and further sophisticate the decision-making process (Coles et al., 2008; Ramdani & Witteloostuijn, 2010; He et al., 2015). With respect, the decisions taken by larger boards would often turn out to be less extreme, yielding less corporate efficiency and lower productivity. In this context, the following hypothesis seems worth developing:

H₉: 

The board’s size negatively affects the oil and gas firm’s TE.

2.10. Board’s Independence and TE

It is generally maintained by the previously elaborated kinds of literature that independence represents the fittest key determinant of the council board’s effectiveness and that companies prove to perform highly better once their boards appear to involve a greater number of outsiders (Bozec & Dia, 2007; Ramos & Díaz, 2020).

The stewardship theory argues that the insiders’ dominated boards turn out to be a lot more efficient than those dominated by outsiders. Furthermore, the inside directors who enjoy a great deal of information regarding their firms are more liable to sustain effective decision-making strategies and assess the top managers’ performance. Inversely, however, the outside directors, who are most often appointed part-time, appear unable to recognize business-related complexities. As a result, the board’s independence is certainly discovered to be negatively associated with corporate efficiency (Bozec & Dia, 2007; Ramdani & Witteloostuijn, 2010).

On the other hand, the Agency Theory assumes that managers are predominantly opportunistic and self-serving, which entails much control from independent boards. In this respect, independent directors play a remarkable role in constraining insider self-dealing and improving investment efficiency (Y. Liu et al., 2015; Rajkovic, 2020; Ramos & Díaz, 2020).

Hence, and given the fact that the board’s independence contributes a great deal to enhancing investment efficiency and operational performance, one can well state that the proportion of independent directors within the board does participate in positively affecting the firm’s overall efficiency (Y. Liu et al., 2015; Bozec & Dia, 2007). So, it also follows that the hypothesis below can be established:

H₁₀: 

The board’s independence positively affects the oil and gas firm’s TE.

2.11. Firm Size and TE

A major determinant aspect of the firm’s specific factors, likely to help greatly in reducing its ability to operate at the most optimum level of technical efficiency, is the firm’s size.

Various evidence and explanations related to the firm’s size influence its technical or production efficiency in the associated literature. In this respect, two trends or lines of thought can be distinguished. The first vein of thought argued that as firms grow larger, they may lose focus and become more complacent and prone to agency problems (Hanousek et al., 2015). However, on the other hand, small firms could prove to be more efficient owing mainly to the fact that they have flexible, non-hierarchical structures and do not usually suffer from acute agency problems (Halkos & Tzeremes, 2007). Additionally, according to Aggrey et al. (2010), the proprietor’s direct participation in productive activities helps greatly lessen or mitigate agency costs within the small firms relative to the large size ones, where delegation gives rise to intense issues of potential adverse selection and moral hazard.

Actually, the environment may also favor small firms relative to the large ones, which are more likely to encounter deliberate restrictions. It is also argued that much of the large firms’ focus of interest seems to be directed to these matters relating mainly to the overall process, form, and bureaucracy rather than results and earnings-oriented. In this way, the size–efficiency associated relationship is negative for large-sized firms and positive concerning smaller ones (Aggrey et al., 2010; Karbhari et al., 2018).

As for the second line of thought, as perceived in the literature dealing with firm growth, it mainly the idea that it is only the efficient firms that can manage to grow and survive over time, whereas the inefficient enterprises turn out to stagnate and fail (Lundvall & Battese, 2007; Aggrey et al., 2010). According to Edjigu (2016), production in some sectors proves to be predominantly constrained by the small and average size of the firms. At this level, the following hypothesis can be constructed:

H₁₁: 

Firm size positively affects the firm’s TE.

3. The Empirical Approach

3.1. Empirical Model

To measure technical efficiency, this study employs Stochastic Frontier Analysis (SFA), a method that is particularly suited for the oil and gas sector due to its ability to account for statistical noise caused by factors beyond the control of firms, such as price volatility, environmental shocks, and measurement errors (Battese & Coelli, 1995). Unlike Data Envelopment Analysis (DEA), which is a non-parametric method that assumes all deviations from the frontier are due to inefficiency, SFA distinguishes between inefficiency and random error, providing a more realistic representation of firm performance in contexts like oil and gas, where external factors significantly affect outcomes.

Moreover, SFA allows for the incorporation of firm-specific characteristics (e.g., CEO characteristics, board composition, and firm size) into the efficiency estimation, enabling the analysis of how these governance factors influence technical efficiency (Zaabouti et al., 2016). While DEA has been widely used in other sectors, its deterministic nature may overstate inefficiency in the presence of stochastic variations, making it less suitable for industries prone to high external variability, such as oil and gas.

It is worth highlighting that the stochastic frontier production function helps account for the stochastic errors due mainly to the persistence of statistical noise or measurement errors. Thus, it decomposes the error terms into two components: the random effect lying outside the firm’s control and the component that captures the firm’s efficiency aspect (Admassie & Matambalya, 2002).

In the context of the present work, the stochastic frontier production function subject of estimation looks as follows:

$$Ln Y_{it}={\beta }_0+{\beta }_{1}Ln {OE}_{it}+{\beta }_{2}Ln K_{it}+{\beta }_3 Ln L_{it}+V_{it}-U_{it}$$

(1)

Under this new formulation, $Y_{it}$ stands for the output produced by the American energy firm i(i = 1, 2,…, N) in period t(t = 1, 2,…, T); K_it, L_it, and OE_it denote the row input vectors of firm i during period t, with K_it,, L_it, and OE_it representing the operating expenses, capital, and labor, respectively. V_it is the random error term and U_it denotes the technical inefficiency pertaining to the American oil and gas firm i in period t.

Recognizing whether firms are technically inefficient might not prove to stand as a useful proceeding unless an extra effort intended to identify the sources of the inefficiencies is made (Admassie & Matambalya, 2002). Hence, as a second phase of the analysis, we investigate the sources of firm-level technical inefficiencies for the oil and gas firms’ subject of our study sample.

According to Eller et al. (2011), who provide empirical evidence concerning the oil companies’ revenue earnings’ efficiency, inefficiency may explain the differences persisting within the firms’ structural and institutional features. The authors argue that “many factors can influence the relative ability of such a wide variety of firms to generate revenue from given inputs.” According to Admassie and Matambalya (2002), technical inefficiency-associated effects are discovered to be definable in terms of modeling the mean of $U_{it}$ as a function of a host of firm-specific and managerial characteristics.

In this regard, and concerning the present study’s context dealing with a selection of American oil and gas operating firms, several explanatory variables are investigated, namely the CEO’s age, education, career experience, duality, ownership, remuneration, tenure, financial expertise, the board size, and independence as well as the firm’s size. To this end, the package Frontier 4.1 is implemented to model these energy-specializing firms’ technical inefficiency. This package of variables, we reckon, would serve as a practical tool that would help in relatively facilitating the inefficiency modeling task. In this way, and in conformity with Battese and Coelli (1995) as well as Sheu and Yang (2005) and Zaabouti et al.’s (2016) undertaken strategy, the potential firm’s specific factors, likely to help influence technical efficiency, turn out to be liable to modelization on conformingly with an inefficiency functional form, as follows:

$$\begin{array}{c}{\mu }_{it}={\delta }_0+{\delta }_1({firm size)}_{it}+{\delta }_2({Board size)}_{it}+{\delta }_3({Board independence)}_{it}+{\delta }_4({financial expertise)}_{it}\hfill \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}+{\delta }_5({CEO education level)}_{it}+{\delta }_6({CEO financial education)}_{it}\hfill \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}+{\delta }_7({CEO technical education)}_{it}+{\delta }_8({CEO career experience)}_{it}+{\delta }_9({CEO Age)}_{it}\hfill \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}+{\delta }_{10}({CEO tenure)}_{it}+{\delta }_{11}({CEO owner)}_{it}{+\delta }_{12}({CEO remuneration)}_{it}\hfill \\ \hspace{1em}\hspace{1em}\hspace{1em}\hspace{1em}+{\delta }_{13}({CEO duality)}_{it}+W_{it} \hfill \end{array}$$

(2)

According to this formulation, $({CEO Age)}_{it}$ represents the CEO’s age as directly measured by CEO age; the $({CEO education level)}_{it}$ variable is measured on a four-point scale reflecting the highest level of education attained; $({CEO duality)}_{it}$ denotes the CEO’s dual functions, which take the value 1 in case the CEO is simultaneously the firm’s chairman, and 0 otherwise; $({CEO career experience)}_{it}$ stands for the number of the CEO’s years of experience; $({Board size)}_{it}$ signifies the number of members making up the directors’ board; $({Board independence)}_{it}$ represents the percentage of outside directors in the council; $({firm size)}_{it}$ is measured through the log of total assets. Finally, Wit stands for the error term.

Table 2. The variables definition.

Variables	Definition and Measure	Data Source
Sales	- The total sales	Full company’s report Thomson One Banker (TOB)
Capital	- Measured by the total assets (Charoenrat et al., 2013)	Full company’s report (TOB)
Labor	- Number of employees (Fang et al., 2009; Servin et al., 2012; Charoenrat et al., 2013; S. F. Yang et al., 2013)	Full company’s report (TOB)/report 10-k
Operating expenses	- Total operating expenses	Full company’s report (TOB)
CEO's age	- The age of the Chief Executive Officer. CEO’s age is measured in years (Vintila & Gherghina, 2012; Ben Fatma et al., 2024)	Proxy statement
CEO education	- The CEO’s education level is measured on a four-point scale reflecting the highest level of education attained (0 = no college degree, 1 = undergraduate degree, 2 = master’s degree or JD, 3 = Ph.D. degree) (Barker & Mueller, 2002) - Financial education is a dummy variable that equals 1 if the CEO of firm i has a graduate degree in an MBA or finance and 0 otherwise - Technical education is a dummy variable that equals 1 if the CEO of firm i has a graduate degree other than an MBA or law degree and 0 otherwise (Gottesman & Morey, 2010)	Proxy statement
CEO’s remuneration	- Total compensation (SALFIX + BONUS + OPTIONS + SHARES) (Chalmers et al., 2006)	Proxy statement
CEO’s tenure	- CEO tenure is the number of years the person has been in the CEO position. Ahn and Shrestha (2013)	Proxy statement
CEO’s career experience	- The number of years of experience that specialist CEOs have in their specialized divisions and how close chronologically the experience is to their succession to CEO (Wilson et al., 2001; Sheng Huang, 2014)	Proxy statement
Firm’s size	- Firm size is defined as the log of total assets (Ahn & Shrestha, 2013)	Full company’s report (TOB)
Board’s size	- The number of the members that compose the board of directors (Ben Mohamed & Jarboui, 2017)	Proxy statement
Independence of the board	- The percentage of outside directors (Ben Mohamed, 2021)	Proxy statement
CEO’s duality	- Duality equals 1 when the CEO is also a chairman and 0 otherwise (Ahn & Shrestha, 2013)	Proxy statement
CEO’s own	- CEO’s ownership as a percentage of total outstanding shares (Ahn & Shrestha, 2013)	Proxy statement
Financialexpertise	- The number of outside directors with expertise in financial industries identified with keywords “Financ”, “Bank”, “Invest”, “Capital”, and “Insurance” (Ahn & Shrestha, 2013) - Jeanjean and Stolowy (2009) define “financial expertise” as the sum of management education and financial experience - Following Güner et al. (2008), we classify an independent director as a financial expert if he or she works within a banking institution or a non-bank financial institution or has a finance-related role within a non-financial firm (e.g., CFO, accountant, treasurer, or VP finance) or academic institution (e.g., professor in finance, accounting, economics, or business), or a professional investor (e.g., hedge fund, private equity)	Proxy statement

Source (the authors).

gives details of the measurement of each variable.

3.2. Data Description

The production function analysis output was proxied by annual sales. The conventional key input variables are capital, labor, and operation expenses. Capital (K) is defined as the capital stock recorded at the beginning of the production year and estimated as the value of registered assets. Similarly, labor input, referred to as L, is measured in terms of the number of employees. Apart from the above-cited conventional key input variables, some firm and personal-specific attributes have been expected to impact firms’ technical efficiency levels remarkably and, therefore, comprise the model. Among the factors considered useful for explaining the inter-firm technical efficiency differentials are the company-specific characteristics, including the firm size and the associated management variables involving the CEO’s characteristics and board composition.

Concerning our analysis, it rests on a study sample made up of 100 U.S.-based oil and gas firms observed over the periods between 2006 and 2019. After the sample collection process, we gather information relevant to the corporate governance variable. The corporate governance mechanisms and CEO-associated characteristics are obtained from the proxy statement report and the firms’ published annual report. Other data directly extracted from the Thomson Financial Database are drawn from the full company’s report (concerning mainly the total sales assets, total operating expenses, and the number of employees). Moreover, an appeal has also been made to the 10-K report for some missing variables to be filled.

Table 3. Summary statistics.

Variables	Observations	Mean	Std. Dev.	Min	Max
lnsales	1400	18.86	4.85	0	26.79
Lnk	1400	20.29	2.91	0	26.57
Lnl	1400	5.78	2.94	0	11.71
Firm size	1400	20.29	2.91	0	26.57
Board size	1400	8.19	2.47	2	18
CEO education level	1400	1.69	0.61	1	3
CEO age	1400	55.91	8.97	31	88
Board independence	1400	0.71	1,796,009	0	1
CEO careerexperience	1400	20.44	11.30	0	43
CEO duality	1400	0.64	0.47	0	1
CEO financial education	1400	0.50	0.50	0	1
CEO technical education	1400	0.55	0.49	0	1
Financial expertise	1400	3.20	2.02	0	11
CEO tenure	1400	15.29	9.21	0	46
CEO remuneration	1400	4,304,795	8,764,984	−3,975,950	1.42 × 108
CEO owner	1400	12.63	82.08	0.0015365	2855

Source (the authors).

gives details about our sample.

4. Results

Table 4. Estimation results.

Variables	Parameters	Coefficients (Estimated Values)
Constant	β0	4.732 (10.325) ***
OE	β1	0.821 (29.586) ***
K	β2	−0.098 (1.825)
L	β3	−2.355 (1.399)
Constant	δ0	18.729 (13.257) ***
Firm size	δ1	−0.782 (−8.703) ***
Board size	δ2	−0.977 (−5.585) ***
Board independence	δ3	−0.625 (−0.723)
Financial expertise	δ4	0.871 (6.102) ***
CEO education level	δ5	−0.436 (−4.125) ***
CEO financial education	δ6	2.012 (6.235) ***
CEO technical education	δ7	1.367 (3.022) ***
CEO career experience	δ8	−0.0701 (3.861) ***
CEO age	δ9	−0.045 (1.638) **
CEO tenure	δ10	0.207 (−1.133)
CEO owner	δ11	−0.065 (4.756) ***
CEO remuneration	δ12	−0.781 (5.485) ***
CEO duality	δ13	−0.775 (−3.210) ***
Sigma-Squared	Wit = vi − uj	2.985 (7.114) ***
Gamma		0.787 (43.356) ***
LogLikelihood Function		−1829.142

** indicates significance at the 5% level. *** indicates significance at the 1% level.

presents the estimated parameters of the production function frontier and the determinants of inefficiency, analyzed using Frontier 4.1 (Battese & Coelli, 1995). The results offer valuable insights into the factors influencing technical efficiency (TE) in the oil and gas sector.

In the first model, the coefficient for total operating expenses is statistically significant at the 1% level, while the coefficient for the number of employees is not. This finding underscores the critical role of operating expenses in driving sales and, by extension, TE. It highlights the capital-intensive nature of the oil and gas sector, where high production costs are inherent. These results suggest that firms must prioritize optimizing operating expenses to achieve better efficiency.

The results also suggest that firm size positively influences technical efficiency (coefficient = −0.782; t-statistic = −8.703). This finding supports the theory of firm growth, which posits that larger firms benefit from economies of scale and resource optimization, leading to higher efficiency. Efficient firms are more likely to grow, while inefficient ones stagnate or decline, as noted by Lundvall and Battese (2007). This insight is particularly relevant for policymakers and firms aiming to sustain growth in a competitive market by scaling operations strategically.

Moreover, the CEO’s managerial abilities and competencies appear to play a crucial role in enhancing oil production. Interestingly, the negative sign associated with the CEO’s age (coefficient = −0.045; t-statistic = 1.638) suggests that firms led by older CEOs tend to perform more efficiently. This finding supports the conclusions of Lambarraa and Kallas (2009), who argue that CEOs accumulate valuable knowledge from past experiences, which can improve the decision-making abilities of older executives. However, it is essential to balance this with fostering innovation and adaptability within executive teams, as these qualities are equally crucial for long-term success in dynamic industries like oil and gas.

In terms of executive ownership, the estimated coefficient is negative and highly significant (coefficient = −0.065; t-statistic = 4.756). This finding highlights the alignment of interests between shareholders and executives when CEOs hold a significant ownership stake, which confirms the theoretical predictions of the Agency Theory and the corporate governance approach. By reducing agency costs, executives are incentivized to make strategic decisions that enhance operational performance. In the oil and gas sector, this alignment is particularly beneficial, as executives often possess deep industry knowledge, which can be leveraged to improve efficiency.

Similarly, the negative and significant coefficient related to CEO remuneration (coefficient = −0.781; t-statistic = 5.485) indicates that higher compensation enhances production efficiency. Large firms with greater growth potential and higher operational risks typically require skilled executives who demand competitive pay. Compensation packages that link bonuses to individual performance (Murphy, 1999; Chung & Pruitt, 1996; Chalmers et al., 2006) further incentivize executives to maximize efficiency. These findings underscore the importance of linking executive pay to long-term efficiency objectives.

The results also suggest that CEOs with advanced education drive firms towards greater efficiency over time, narrowing performance gaps (coefficient = −0.436; t-statistic = −4.125). A high level of education enhances a CEO’s ability to access and apply knowledge, positively influencing efficiency regardless of workforce capabilities. In fact, the Human Capital Theory emphasizes that education is one of the most influential factors in individual decision-making. Empirical validations have proven the importance of managerial education in supporting their ability to make decisions that benefit the company (Almaiman et al., 2024).

However, the results indicate that managerial financial education has a negative impact on production efficiency (coefficient = 2.012; t-statistic = 6.235). This could be due to the conservative, risk-averse mindset often associated with MBA graduates, which may conflict with the high-risk nature of the oil and gas industry.

The CEO’s professional experience also significantly affects the firm’s technical efficiency (TE) by promoting the use of effective strategies and the discovery of new oil and gas fields. The coefficient related to career experience is negative and highly significant (coefficient = −0.0701; t-statistic = 3.861). This indicates that an increase in managerial professional experience will be associated with an increase in firm technical efficiency. Additionally, the influence of financial experts on boards appears to exacerbate inefficiencies by increasing reliance on debt financing (coefficient = 0.871; t-statistic = 6.102). This trend, evident during the 2014–2015 oil price collapse, emphasizes the need for a balanced board composition, integrating both technical and financial expertise to reduce vulnerabilities.

Additionally, the results highlight the negative impact of CEO duality on inefficiencies score and so positively influences TE (coefficient = −0.775; t-statistic = −3.210). Dual leadership, where the CEO also serves as the board chair, enables quicker decision-making due to the CEO’s superior understanding of the firm’s strategic challenges. Firms with dual leadership tend to exhibit stronger financial performance and greater efficiency. This finding contradicts the predictions of the Agency Theory and corporate governance, which view duality as undesirable because it reduces the effectiveness of the board of directors.

The results show that board independence has a positive impact on the company’s ability to achieve high levels of technical efficiency, but the result is insignificant (coefficient = −0.625; t-statistic = −0.723). As predicted in the literature review section, board independence is considered one of the most important corporate governance mechanisms and has a direct impact on the majority of the company’s decisions. These findings align with Jensen (1993), who stated that independent directors act as experts providing unbiased opinions and guiding the board’s decisions to serve the interests of shareholders and stakeholders in general. The CEO tenure, as predicted, negatively influences the gas and oil firms’ technical efficiency, but the result is not significant (coefficient = 0.207; t-statistic = −1.133).

Finally, the size of the board is also found to positively influence inefficiency (coefficient = −0.977; t-statistic = −5.585). This indicates that the technical efficiency scores of gas and oil firms increase with the board size. Larger boards are generally better equipped to navigate complex business environments, as they provide diverse expertise and perspectives that enhance strategic decision-making.

5. Discussion

This study discusses the significance of the characteristics of executive managers, corporate governance mechanisms and firm size in American oil and gas companies over a relatively long period, spanning from 2016 to 2019. The importance of this study lies in addressing a gap in the energy literature, where insufficient attention is given to internal factors that influence the efficiency of these companies, such as executive characteristics, corporate governance systems, and company size.

The study is grounded in the Upper Echelon Theory, which emphasizes the crucial role of executive characteristics in decision-making processes of various types, directly impacting firms’ efficiency in utilizing their resources. This, in turn, has a direct effect on technical efficiency levels.

Our findings reveal that age positively influences the technical efficiency of oil companies, as statistical evidence indicates a negative relationship between an increase in executives’ age and the inefficiency term. This can be attributed to the accumulation of experience and enhanced decision-making skills, which are particularly valuable in a sector known for its rapid changes. Additionally, experience in managing oil and gas companies positively influences operational efficiency.

These findings also align with the Human Capital Theory, which highlights the importance of education and experience in improving the quality of human capital. This improvement reflects positively on various decision-making processes and the technical efficiency of firms.

Our findings indicate that corporate governance mechanisms, in general, can influence the technical efficiency of oil and gas companies. This is primarily because corporate governance mechanisms, especially the structure and composition of the board of directors, as well as managerial ownership, can serve as effective solutions to mitigate agency problems within these large corporations. The results of this study support both the Agency Theory and the governance approach as solutions to encourage executive management to act in the interests of shareholders and other stakeholders.

One controversial finding of this research is that the financial and technical education of the CEO negatively impacts the company’s technical efficiency. This contradicts the results of most empirical studies, which emphasize the positive effect, particularly of financial education. Consequently, further research is needed to explore the conditions under which financial education becomes beneficial for the company. This also leads us to propose a hypothesis that the impact of financial education for CEOs is positive only under specific conditions that need to be identified.

On the other hand, the study’s results confirm that company size is an important factor in achieving technical efficiency. This finding is expected, as discussed earlier in the literature review section. Oil and gas companies require significant investments and expertise, making it natural for larger companies to have a greater capacity to achieve higher levels of technical efficiency. This leads us to discuss the importance of mergers and acquisitions operations in the oil and gas sector.

6. Conclusions and Recommendations

This study serves as an initial exploration into the key determinants of technical efficiency among American oil and gas firms, as well as the underlying causes of fluctuations in their sales and production, which may contribute to oil price volatility. The findings reveal significant insights that enhance our understanding of the internal factors driving fluctuations in oil production and sales, ultimately leading to notable changes in oil prices.

Regarding the study results and to increase technical efficiency scores within production processes, oil and gas firms are invited to focus on optimizing resource allocation, including labor, capital, and operating expenses. In fact, this strategy will foster further investment and sales, enabling firms to implement new technologies and best practices that enhance operational performance. It seems that larger firms tend to exhibit higher technical efficiency scores due to their ability to leverage economies of scale. This underlines the importance of planned expansion, where firms can capitalize on increased size to drive cost efficiencies, improve operational workflows, and ultimately sustain long-term growth.

Moreover, the study highlights the role of the CEO in driving technical efficiency. The findings prove that the managerial competencies of the CEO, namely their experience, have a direct impact on production efficiency. Interestingly, the age of the CEO also plays a significant role. It seems that older CEOs, who have normally accumulated more experience, tend to lead their companies to greater efficiency. This suggests that seasoned leadership is an asset to companies aiming to maintain high levels of operational performance, particularly in the complex and dynamic oil and gas industry. To this end, oil and gas firms should focus on selecting executives who not only have deep industry experience but also have the ability to navigate the challenges and complexities of the oil and gas sector.

To further enhance the technical efficiency of oil and gas firms, it is suggested that CEOs increase their ownership participation in the company. This alignment of interests between executives and shareholders encourages executives to make decisions that optimize the company’s long-term performance. Additionally, offering competitive salaries and performance-based bonuses tied to specific efficiency goals can further incentivize executives to maximize the company’s operational output. By linking executive compensation to performance, firms can create a culture of accountability and productivity that drives higher levels of efficiency.

Our findings also suggest that the board size has a positive influence on technical efficiency. A larger board brings diverse perspectives, expertise, and insights that can contribute to better strategic decision-making. Therefore, oil and gas firms should consider expanding their boards to include directors with a range of skills and backgrounds. This diversity can enhance the firm’s ability to navigate challenges, make informed decisions, and improve overall performance.

Finally, the strategic pursuit of mergers and acquisitions should be considered as a means of driving growth and improving operational efficiency. In fact, mergers and acquisitions allow firms to increase their scale, streamline operations, and access new technologies or markets. By expanding their reach, firms can also improve their bargaining power in the global energy market, contributing to the stability of energy prices while simultaneously enhancing their own competitiveness. This approach provides oil and gas firms with the opportunity to position themselves for long-term success in an increasingly competitive and volatile industry.

In summary, firms that prioritize the selection of experienced CEOs, incentivize executive performance, expand their boards, and consider strategic growth through mergers and acquisitions will be well-positioned to improve technical efficiency. These efforts will not only optimize their operations but also contribute to the broader stability and sustainability of the oil and gas sector.