Relationship Between Socio-Efficiency, Eco-Efficiency, and Financial Performance of European Companies: A Sector Study

Abstract

This study aims to assess the impact of socio- and eco-efficiency on the financial performance of 180 European companies from 2010 to 2022. Data Envelopment Analysis (DEA) was used to measure the companies’ socio- and eco-efficiency, while their financial performance was assessed using the equitable weighting approach. The analysis revealed a positive relationship between socio-efficiency, eco-efficiency, and financial performance. The findings not only confirm the positive relationship but also provide practical recommendations for integrating sustainability into business strategies without compromising profitability.

1. Introduction

In the contemporary business environment, characterized by mounting environ-mental and social challenges, sustainable business practices have become a fundamental element of corporate strategy, particularly in Europe, where stringent regulatory frameworks and stakeholder expectations compel firms to adopt eco-efficient and socio-efficient practices. The concepts of eco-efficiency, which is the maximization of economic output whilst simultaneously minimizing environmental impact, and socio-efficiency, which is the optimization of social benefits whilst concomitantly reducing negative societal impacts, have gained increased recognition as critical drivers of long-term financial performance (García-Sánchez et al., 2021). Despite the growing body of literature on this topic, there is still a need for more comprehensive studies that examine the relationship between these efficiencies and financial performance across different sectors, particularly in the European context.

This study investigates the impact of eco-efficiency and socio-efficiency on the financial performance of European firms, focusing on three key sectors: industrial, financial, and consumer goods and services. The sample includes 69 industrial firms, 60 financial firms, and 51 consumer goods and services firms from France, Italy, Germany, Spain, Belgium, Poland, and Finland. These countries represent a diverse set of European economies with varying levels of sustainability regulation and stakeholder expectations. The analysis of these sectors is intended to provide insights into how sustainability practices influence financial outcomes in industries with varying resource intensities and social impacts.

In the initial phase, the Data Envelopment Analysis (DEA) methodology is employed to assess eco-efficiency and socio-efficiency. DEA is a non-parametric method that evaluates the efficiency of decision-making units (DMUs) by comparing multiple inputs and outputs without requiring a predefined functional form (Halkos & Petrou, 2019). This flexibility renders DEA particularly suitable for assessing sustainability performance, as it can accommodate the complex and multidimensional nature of eco-efficiency and socio-efficiency (Halkos & Petrou, 2019). Furthermore, DEA effectively handles small sample sizes, which is relevant given the limited number of firms in some sectors of the dataset (e.g., 51 consumer goods and services firms).

In the second stage, the study employs the two-stage GMM approach to estimate the impact of eco-efficiency and socio-efficiency on financial performance. The two-stage GMM approach is deemed appropriate for the present study because it addresses potential endogeneity issues, such as reverse causality and omitted variable bias, which are prevalent in sustainability research (Wintoki et al., 2012). The GMM estimator also permits the incorporation of lagged dependent variables, aiding in capturing dynamic effects and enhancing the robustness of the results.

To ensure the estimates’ stability, the econometric analysis uses the global index (aggregated eco-efficiency and socio-efficiency scores) and the disaggregated dimensions (eco-efficiency and socio-efficiency separately). This methodological approach ensures that the results are not biased by the behavior of a particular dimension and provides a more nuanced understanding of how each dimension contributes to financial performance.

This study makes several contributions to the existing literature on the subject. Firstly, it comprehensively analyzes the relationship between eco-efficiency, socio-efficiency, and financial performance across three key sectors, addressing a gap in the existing literature (Pinheiro et al., 2023). Secondly, it employs rigorous empirical methodologies, namely DEA and GMM, to evaluate these relationships. Thirdly, it offers practical recommendations for managers and policymakers on balancing socio-economic and environmental goals with financial objectives, tailored to the specific realities of each sector (Czerny & Letmathe, 2024).

The relationship between sustainability practices and financial performance has been extensively debated in the academic literature. While some studies posit that eco-efficiency and socio-efficiency engender cost savings, an enhanced reputation, and improved stakeholder relationships, others contend that the financial benefits may be contingent on the sector and regional context (Czerny & Letmathe, 2024). For instance, industrial firms often achieve immediate financial benefits from eco-efficiency through energy savings and waste reduction. In contrast, financial firms may experience more indirect benefits, such as improved brand reputation and customer trust (Palupi, 2023). Similarly, socio-efficient practices, such as fair labor policies and community engagement, can enhance employee morale and customer loyalty, particularly in sectors with high social visibility (Pinheiro et al., 2023).

Nevertheless, despite the mounting evidence, there remains a necessity for more robust methodologies with which to assess these relationships. Many extant studies have employed single-stage models that do not consider endogeneity or dynamic effects, which can result in biased outcomes (Wintoki et al., 2012). The present study addresses these limitations by employing a two-stage methodology combining Data Envelopment Analysis (DEA) and the Generalized Method of Moments (GMM).

2. Literature Review

2.1. Eco-Efficiency and Socio-Efficiency

In recent years, sustainable business practices, particularly in the context of European companies, have garnered considerable attention, with a marked emphasis on eco-efficiency and socio-efficiency. Eco-efficiency, defined as the ability to deliver goods and services while minimizing environmental impact, has become a cornerstone of corporate sustainability strategies. Recent studies highlight that eco-efficient practices, such as energy efficiency and waste reduction, reduce operational costs and enhance a firm’s competitive advantage in markets with stringent environmental regulations (Majid et al., 2023). A similar phenomenon pertains to socio-efficiency, defined as maximizing social benefits while minimizing negative societal impacts. Evidence suggests that this leads to improved stakeholder relationships and brand reputation. Firms prioritizing socio-efficiency often experience higher levels of employee satisfaction, customer loyalty, and investor confidence, collectively contributing to long-term financial success (García-Sánchez et al., 2021).

The integration of eco-efficiency and socio-efficiency into business models has been particularly pronounced in European companies, driven by regulatory pressures and increasing stakeholder demand for sustainable practices (García-Sánchez et al., 2021). For instance, a study by García-Sánchez et al. (2021) found that European firms adopting eco-efficient and socio-efficient practices outperformed their peers regarding financial performance, particularly in industries with high environmental and social impacts. Nevertheless, the correlation between these efficiencies and financial performance is not uniform across sectors. While industrial firms often see immediate financial benefits from eco-efficiency, service-oriented firms may experience delayed returns due to the intangible nature of their outputs (Majid et al., 2023).

2.2. Eco-Efficiency and Financial Performance

The relationship between eco-efficiency and financial performance has been a focal point of recent research, with mixed findings depending on the sector and regional context. In the manufacturing sector, eco-efficient practices such as resource optimization and waste reduction have significantly improved profitability by lowering production costs and enhancing operational efficiency (Asif, 2023). For instance, a study on European manufacturing firms revealed that companies with higher eco-efficiency scores achieved a 15% reduction in operational costs and a 10% increase in profitability over five years (Asif, 2023). Conversely, the financial sector has exhibited more modest gains from eco-efficiency, primarily due to the low resource intensity of financial activities. Nevertheless, even within this sector, eco-efficient practices such as green financing and sustainable investment strategies have been linked to improved brand reputation and customer trust, contributing to financial performance (Koundouri et al., 2022). Similarly, in the consumer services sector, adopting eco-efficient technologies has been associated with enhanced customer loyalty and market share. However, the initial investment costs can be a barrier for smaller firms (Horváthová, 2020). Recent studies have also explored the role of eco-efficiency in driving innovation and long-term competitiveness. For instance, Majid et al. (2023) found that firms investing in eco-efficient technologies were more likely to develop innovative products and services, boosting their financial performance. These findings underscore the importance of eco-efficiency not only as a cost-saving mechanism but also as a driver of innovation and market differentiation.

2.3. Socio-Efficiency and Financial Performance

The impact of socio-efficiency on financial performance has been a subject of increasing recognition in recent years, particularly in corporate social responsibility (CSR) and stakeholder engagement. Firms prioritizing socio-efficient practices, such as fair labor policies and community development initiatives, often experience improved employee morale, customer loyalty, and investor confidence, all of which contribute to sustained financial success (García-Sánchez et al., 2021). For instance, research on European firms found that companies with high socio-efficiency scores had a 12% higher Return On Equity (ROE) than their peers (García-Sánchez et al., 2021).

However, the benefits of socio-efficiency are not evenly distributed across sectors. In industries with high social impacts, such as retail and healthcare, socio-efficient practices have significantly enhanced financial performance by improving brand reputation and customer trust (Pucheta-Martínez et al., 2021). Conversely, in industries with diminished social visibility, the financial advantages of socio-efficiency may be less evident, though they nevertheless contribute to long-term sustainability and risk mitigation (Guastella et al., 2022).

Recent research has also highlighted the role of socio-efficiency in fostering innovation and resilience. For instance, firms’ adoption of socio-efficient practices is associated with increased attraction and retention of high-caliber personnel, encouraging innovation and competitive advantage (Kafetzopoulos et al., 2024). Furthermore, the ability of socio-efficient firms to navigate social and regulatory risks enhances their long-term financial stability (García-Sánchez et al., 2021).

3. Materials and Methods

This study used an empirical approach to analyze 180 European companies operating in the financial, industrial, and consumer goods and services sectors from 2010 to 2022. The sample includes firms from France, Italy, Germany, Spain, Belgium, Poland, and Finland, representing a diverse set of European economies with varying levels of sustainability regulation and stakeholder expectations. The sample selection was based on data availability, ensuring all firms had complete data on eco-efficiency, socio-efficiency, and financial performance metrics for the study period. The selection of firms was further designed to provide adequate representation across the industrial (69 firms), financial (60 firms), and consumer goods and services (51 firms) sectors, allowing for a robust cross-sectorial analysis. Furthermore, geographic diversity was also considered, with firms chosen from seven European countries to capture regional variations in sustainability practices and financial performance. The study was conducted in three sequential steps. Firstly, eco-efficiency and socio-efficiency scores were calculated using the BCC model from the Data Envelopment Analysis (DEA) method; secondly, the equitable weighting method was used to derive a financial performance score (PFS) based on key financial variables such as Return on Assets (ROA), Return on Equity (ROE), Return on Invested Capital (ROIC), and Tobin’s Q. Finally, a one-step Generalized Method of Moments (GMM) approach was employed to assess the relationship between eco-efficiency, socio-efficiency, and financial performance, capturing both direct and indirect effects across the studied sectors.

3.1. Methodology

3.1.1. Eco-Efficiency and Socio-Efficiency Scores

In this study, we employ the Data Envelopment Analysis (DEA) input-oriented BCC model to assess both eco-efficiency and the socio-efficiency scores. This model is designed to accommodate multiple inputs and outputs while assuming variable returns to scale (VRS), thereby rendering it suitable for evaluating firms of disparate sizes. The BCC model (Banker et al., 1984) offers a distinct advantage over the CCR model in that it can capture non-proportional changes in inputs and outputs.

The specific DEA model is structured in the following manner:

$$\min \theta$$

(1)

subject to:

$${\sum }_{j=1}^n{\lambda }_j{x}_{ij}\le \theta x_{i0} \mathrm{for} \mathrm{all} \mathrm{inputs} i$$

(2)

$${\sum }_{j=1}^n{\lambda }_j{y}_{rj}\ge y_{r0} \mathrm{for} \mathrm{all} \mathrm{outputs} r$$

(3)

$${\sum }_{j=1}^n{\lambda }_j=1 , {\lambda }_j\ge 0$$

(4)

where

• $\theta is the efficiency score, with \theta \le 1 indicating inefficiency.$
• $x_{ij} and y_{rj} represent inputs and outputs for decision-making units\left(DM{U}^{\mathrm{’}}s\right).$
• ${\lambda }_j are weights for each DMU.$
• $The constraint {\sum }_j^n{\lambda }_j=1 ensure VRS$

Despite the limitations of DEA, particularly in the analysis of time-varying phenomena, it was selected over SFA for several reasons. Firstly, DEA does not require a predefined functional form, thus rendering it more flexible for modeling the complex relationships between inputs and outputs in sustainability performance (Halkos & Petrou, 2019). Secondly, DEA is better suited for small sample sizes, which is relevant given the limited number of firms in some sectors of the dataset (e.g., 51 consumer goods and services firms). Thirdly, DEA provides a clear benchmarking framework, enabling firms to compare their performance against industry peers. Conversely, SFA necessitates larger sample sizes and particular functional forms, which may not accurately reflect the heterogeneity of sustainability practices across sectors.

3.1.2. Financial Performance Score

The equitable weighting method was used to derive a financial performance score (PFS) based on key financial variables, including Return on Assets (ROA), Return on Equity (ROE), Return on Invested Capital (ROIC), and Tobin’s Q.

The typical process for calculating the financial performance score (PFS) involves using the following formula:

$$PFS={\sum }_{k=1}^n{\omega }_K\times R_k$$

(5)

$R_K$ indicates financial metrics, including Return on Assets (ROA), Return on Equity (ROE), Return on Invested Capital (ROIC), or Tobin’s Q.

${\omega }_k$ represents the weight assigned to each ratio $({\omega }_k={\displaystyle \frac{1}{n}})$, and n is the total number of ratios used.

In this study, we adopt an approach that assigns equal weight to each financial ratio. This method ensures that no single metric dominates the Performance Financial Score (PFS). This approach aligns with previous studies, such as those by Buallay et al. (2020), who explored the trade-offs between sustainability reporting and financial performance in MENA banks, and AL-Akheli et al. (2025), who conducted a systematic literature review on corporate social responsibility and the cost of capital.

The calculation process involves standardizing each financial ratio by subtracting the mean and dividing by the standard deviation. This allows us to assign equal weight to each standardized ratio before aggregating them to produce the PFS. This method facilitates a balanced financial performance evaluation, as it prevents excessive reliance on any single metric and acknowledges the multidimensional nature of financial health.

The equitable weighting method has several advantages, including flexibility, transparency, and robustness, making it suitable for evaluating financial performance across various sectors and contexts.

3.1.3. Relationship Between Eco-Efficiency, Socio-Efficiency, and Financial Performance

We use the one-step GMM method to explore the relationship between eco-efficiency, socio-efficiency, and financial performance. The GMM (Generalized Method of Moments) is well suited for addressing endogeneity, autocorrelation, and heteroskedasticity in panel data, as Arellano and Bond (1991) demonstrated. This method uses instrumental variables to reduce biases arising from endogenous regressors (Blundell & Bond, 1998). The approach involves estimating a dynamic panel model in which financial performance is regressed on eco-efficiency and socio-efficiency while controlling for other influential variables. The one-step GMM estimator ensures consistent and efficient parameters even when endogenous variables are present (Roodman, 2009).

The model is specified as follows:

$${FPS}_{it}={\beta }_0+{\beta }_1{FPS}_{i,t-1}+{\beta }_2{BCCeco}_{it}+{\beta }_3{BCCsoc}_{it}+\sum {\beta }_k{CONTROL}_{it}+{ϵ}_{it}$$

(6)

• ${FPS}_{it }$ represents financial performance for firm $i$ in year $t.$
• ${FPS}_{i,t-1}$ represents the lagged financial performance score.
• ${BCCeco}_{it}$ represents eco-efficiency score.
• ${BCCsoc}_{it}$ represents socio-efficiency score.
• ${ϵ}_{it}$ is the error term.

The incorporation of eco-efficiency and socio-efficiency is founded on sustainability and stakeholder theory principles. These variables encapsulate the firm’s capacity to curtail environmental and social ramifications while optimizing economic yield. To ensure the results’ stability and avoid bias from the behavior of a particular dimension, the econometric estimates are presented with the global index (aggregated eco-efficiency and socio-efficiency scores) and the disaggregated dimensions (eco-efficiency and socio-efficiency separately). Robustness checks, incorporating techniques such as bootstrapping, sensitivity tests, and the incorporation of lagged values of eco-efficiency and socio-efficiency, are conducted to verify the reliability of the estimates. This is particularly important given the limited sample size and the broad set of variables spanning 12 years (2010–2022). The findings offer actionable insights for managers and policymakers, such as prioritizing energy efficiency and waste reduction in industrial firms or focusing on green financing in financial firms, tailored to the specific realities of each sector and supported by recent studies such as Buallay et al. (2020) and AL-Akheli et al. (2025).

3.2. Data

3.2.1. Dependent Variable

The Financial Performance Score (PFS) construction has reached a relatively mature stage. Insights have been drawn from existing research, including studies by Ricca et al. (2023), and consideration has been given to the availability of financial data. The FPS has been formulated using an equitable weighting method.

The score is defined as follows:

$$PFS=\omega ROA\times ROA+\omega ROIC\times ROIC+\omega ROE\times ROE+\omega Q\times Q$$

(7)

Each ratio indicates a critical aspect of financial performance. Specifically, Return on Assets (ROA) evaluates the efficiency with which a firm utilizes its assets, Return on Invested Capital (ROIC) assesses the profitability generated from capital investments, and Return on Equity (ROE) measures the return generated for shareholders. Q represents the market’s assessment of the firm’s growth potential. Equal weights $({\omega }_{ROA}={\omega }_{ROE}={\omega }_{ROIC}={\omega }_Q=0.25)$ are assigned to each ratio to ensure a balanced evolution, as supported by Ricca et al. (2023), who compared four techniques for synthesizing accounting-based performance scores. The equal weighting methods provide a robust and transparent approach to aggregating financial metrics. The calculation process involves standardizing each ratio by subtracting the mean and dividing by the standard deviation, assigning equal weights, and aggregating the weighted ratios to produce the PFS, which offers a comprehensive measure of financial performance. The equitable weighting method ensures flexibility, transparency, and robustness, making it suitable for evaluating financial performance across diverse sectors.

3.2.2. Independent Variables

The Banker, Charnes, Cooper (BCC) model in Data Envelopment Analysis (DEA) was utilized to calculate environmental and social efficiency scores. The eco-efficiency score is determined by the following outputs: the environmental pillar score, the environmental innovation score, and the renewable energy score. The inputs considered include total CO₂ emissions, waste, water emissions, and resource use. These variables are crucial for assessing a firm’s ability to minimize environmental resource consumption while maximizing environmental performance, as demonstrated in recent studies like Wang et al. (2021), which applied a dynamic network DEA approach to evaluate eco-efficiency in China’s industrial sectors. Calculating the socio-efficiency score involves using outputs such as the social pillar score, the CSR score, and the human rights score, alongside inputs like employee turnover, involuntary turnover, and salary gap. This reflects a firm’s ability to optimize social benefits while minimizing negative societal impacts, as emphasized in research by Zhu et al. (2021). These researchers employed the SBM-DEA model to analyze green innovation and sustainable development performance. These variables are selected based on sustainability and stakeholder theory, highlighting the importance of balancing environmental and social performance with financial objectives. For instance, the widely acknowledged significance of total CO₂ emissions and waste as key environmental impact indicators is complemented by a firm’s commitment to sustainable practices through its investment in renewable energy and environmental innovation. Moreover, employee turnover and the salary gap are critical social performance indicators affecting employee satisfaction and organizational stability. While numerous studies have examined the correlation between environmental performance and financial outcomes, fewer have incorporated environmental innovation and renewable energy as outputs, marking this study as a novel contribution to the existing literature. Additionally, including involuntary turnover and salary in the study’s scope enhances its comprehensiveness.

The specific definitions of these variables are listed in

Table 1. Index system for eco-efficiency and socio-efficiency scores.

	Indicators	Variables	Variable Description
Eco-efficiency	outputs	Environment Pillar score	A company’s weighted average relative rating based on the reported environmental information and the resulting three environmental category scores.
		Environmental innovation score	Reflects a company’s capacity to reduce its customers’ environmental costs and burdens, creating new market opportunities.
		Energy renewable	Total primary renewable energy purchased in gigajoules.
	Inputs	Total emission CO2	The percentage change year on year of total CO2 equivalent emissions.
		Waste Total	The total amount of waste produced in tones.
		Water Emission	Total weight of water pollutant emissions in tones.
		Resource use	The resource use category score reflects a company’s performance and capacity to reduce its resource use.
Socio-efficiency	Outputs	Human rights score	Measures a company’s effectiveness towards respecting the fundamental human rights conventions.
		CSR score	Reflects a company’s practices to communicate that it integrates the economic (financial), social, and environmental dimensions.
		Social Pilar score	A company’s weighted average relative rating based on the reported social information.
	Inputs	Turnover of employees	Includes employees who left the company for any reason (voluntary or involuntary).
		Involuntary turnover of employees	Refers to the rate at which employees leave an organization against their will or without their consent.
		Salary gap	The CEO’s total salary (or the highest) is divided by average wages and benefits.

.

3.2.3. Control Variables

Based on the existing literature, the regression model includes three control variables—inflation rate, firm size, and total debt.

Inflation has been demonstrated to influence financial performance and eco–socio-efficiency by impacting cost structures and profitability. A rise in inflation can lead to increased operational expenses, potentially reducing investments in sustainability initiatives. However, in some instances, firms may seek efficiency improvements to counteract these rising costs.

Firm size is a critical factor in determining eco–socio-efficiency, as larger firms often benefit from economies of scale and greater access to resources, which can enhance both eco-efficiency and socio-efficiency. However, research also suggests that firm size plays a role in financial fragility, particularly in emerging markets, where larger firms may face more significant financial vulnerabilities (Alfaro et al., 2018). Furthermore, the inclusion of total debt is warranted, as it serves as an indicator of a firm’s leverage. High levels of indebtedness can constrain a company’s capacity to invest in sustainability and efficiency initiatives, thereby impacting financial performance and risk management. Empirical studies indicate that the relationship between debt and firm performance is influenced by institutional factors, with short-term debt having a more positive effect than long-term debt (Forte & Tavares, 2019). These variables are crucial for controlling external economic conditions and firm-specific factors when analyzing the relationship between eco- and socio-efficiency and financial performance.

The specific definitions of these variables are listed in

Table 2. Definition and description of the variables.

Variables	Indicator	Indicator Description
Independent variables	Socio-efficiency (BCCsoc)	Measurement of social efficiency score, which comes from the DEA model with an input focus and BCC formulation.
	Eco-efficiency (BCCeco)	Measurement of the environmental efficiency score, derived from the DEA model with input orientation and BCC formulation.
Dependent variable	Financial performance (PFS)	The financial performance score, determined by weighting, evaluates a company’s overall financial well-being and effectiveness.
Control variables	Total Debt	It refers to the total money a company owes to its creditors or lenders.
	Size	A standardized measure of the size of a company refers to the logarithm of total assets.
	Inflation	Measure of how the prices of goods and services rise within an economy.

.

3.3. Sample

This study utilizes data from 2010 to 2022 sourced from LSEG-Datastream and the World Bank. LSEG-Datastream provides firm-level financial and ESG data, while the World Bank offers relevant macroeconomic variables, such as inflation rates and economic growth indicators. The final sample comprises 180 European companies1 across three sectors: 69 in industrial, 60 in financial, and 51 in consumer goods and services, from France, Italy, Germany, Spain, Belgium, Poland, and Finland.

The selection criteria ensured data consistency, sectorial representation, and geographical diversity. Only firms with complete data on eco-efficiency, socio-efficiency, financial indicators, and debt levels were included, while smaller firms and those lacking robust sustainability reporting were excluded. Focusing on significant sectors and countries with strong ESG practices further enhances the sample’s relevance. Only mid- to large-sized firms with substantial market activity and compliance with recognized financial and ESG reporting standards were considered. This approach ensures a representative sample of European firms engaged in sustainability practices while maintaining methodological rigor.

4. Results

4.1. Efficiency Analysis of Environmental and Social Systems in European Companies

Our results in

Table 3. Socio-efficiency and eco-efficiency scores.

	Industrial Sector		Financial Sector		Consumer Goods and Services Sector
Efficiency Range	Environmental System	Social System	Environmental System	Social System	Environmental System	Social System
0 ≤ E < 0.1	1.0%	1.0%	-	-	-	-
0.1 ≤ E < 0.2	3.3%	18.6%	-	6.2%	6.6%	4.4%
0.2 ≤ E < 0.3	5.9%	25.9%	0.64%	11.4%	9.2%	11.0%
0.3 ≤ E < 0.4	11.6%	18.4%	4.23%	13.6%	9.7%	19.0%
0.4 ≤ E < 0.5	11.5%	10.4%	7.31%	9.2%	13.3%	15.5%
0.5 ≤ E < 0.6	11.5%	6.8%	13.46%	13.6%	9.0%	14.6%
0.6 ≤ E < 0.7	9.6%	5.5%	13.85%	7.8%	9.0%	10.1%
0.7 ≤ E < 0.8	12.2%	2.5%	15.26%	6.0%	7.1%	8.4%
0.8 ≤ E < 0.9	11.6%	1.8%	20.13%	6.4%	10.0%	4.7%
0.9 ≤ E < 1	10.5%	2.1%	9.87%	5.0%	9.7%	3.3%
E = 1	11.4%	7.1%	15.26%	20.8%	16.4%	8.9%
Mean	0.64279	0.40213	0.7451	0.6053	0.6324	0.5418
Minimum	0.06511	0.05631	0.2028	0.1141	0.1310	0.1205
Maximum	1.00000	1.00000	1.0000	1.0000	1.00000	1.00000
Median	0.66190	0.31857	0.7673	0.5546	0.6324	0.5000

show that the efficiency of the environmental and social systems of the European companies in the industrial, financial, and consumer goods and services sectors varies considerably. A notable trend in the industrial sector is the substantial social performance at lower efficiency levels, with a peak of 25.9% for 0.2 ≤ E < 0.3, suggesting that even less efficient companies have significant social impacts.

On the other hand, the financial sector shows strong environmental performance at higher efficiency levels, with a peak environmental efficiency of 20.13% for 0.8 ≤ E < 0.9, and the highest social performance at total efficiency (20.8%). This is an indication that highly efficient financial companies are better at the management of both environmental and social responsibilities.

Consumer goods and services show a balanced approach with consistent environmental performance across efficiency ranges and significant social performance, particularly at 0.3 ≤ E < 0.4 (19.0%). This highlights the different strategic focuses: industrial companies may prioritize incremental social improvements, financial companies may aim for high-end efficiency, and consumer goods companies may balance environmental and social efficiency.

4.2. Descriptive Statistics and Correlation

4.2.1. Descriptive Statistics

Table 4. Descriptive statistics.

Variables	Observations	Mean	Std.Div	Min	Max
PFS	2.340	8.852728	24.35325	−356.3875	521.5447
BCCeco	2.340	0.659375	0.2445269	0.06511	1
BCCsoc	2.340	0.422378	0.258661	0.05631	1
Size	2.340	14.48901	2.370814	2.639057	21.26202
Ln(debt)	2.340	13.31113	2.93179	2.639057	22.39792
Inflation	2.340	2.421836	1.382462	0.8469055	6.594097

shows that European companies’ socio-efficiency and eco-efficiency averages are low and less than 1 (0.67; 0.46). These results demonstrate that eco–socio-efficiency is a priority for European companies. However, we noted that the average financial performance score is relatively high (8.89). These results confirm Ehrenfeld et al.’s (2018) findings, which suggest that eco–socio-efficiency positively affects financial performance. However, the high standard deviations of eco-efficiency, socio-efficiency, and economic performance scores show that these are unstable and disparate.

4.2.2. Relation Between Eco-Efficiency Score, Socio-Efficiency, and Financial Performance

Table 5. Correlation between variables.

Variables	1	2	3	4	5	6
1. PFS	1.000
2. BCCeco	0.0035	1.000
3. BCCsoc	0.0963	0.1167	1.000
4. Size	−0.1060	0.1190	0.0907	1.000
5. Lndebt	−0.0367	0.0818	0.1362	0.2646	1.000
6. Inflation	0.0280	0.0367	0.0102	0.0310	0.0227	1.000

presents connections between factors in our model. We noticed a correlation between environmental scores (BCCeco, BCCsoc) and financial performance (PFS). Specifically, BCCsoc is positively linked to PFS (0.0963), while size correlates (0.1060) with PFS. This indicates an essential connection between factors and financial performance. Furthermore, debt ln(debt) correlates with performance, suggesting that companies with higher debt levels may experience lower financial performance. On the other hand, inflation shows an insignificant relationship with financial performance. We did not identify any issues related to multicollinearity.

4.3. Estimation of the GMM Model

After the heteroskedasticity test of Breusch–Pagan and Cook–Weisberg to choose between the GMM method and the method of instrumental variables (IV), the presence of heteroskedasticity was confirmed by the rejection of the null hypothesis H0 (the variance of the errors is a constant) with a probability Prob > Chi² = 0.000 as shown in

Table 6. Heteroskedasticity test.

chi (1)	1697.13
Prob > chi2	0.0000

. For this reason, we decided to work with the Generalized Method of Moments (GMM) on a dynamic panel, which is recommended in this case. This model is proposed by Arellano and Bond (1991), Arellano and Bover (1995), and Blundell and Bond (1998).

The over-identification and autocorrelation tests show the instruments’ validity and the absence of second-order autocorrelation (AR2) of the difference equation’s residuals.

GMM Estimation

Our results in

Table 7. GMM estimation.

System GMM
Variables	Industrial Sector	Financial Sector	Consumer Goods and Services
	Financial Performance
${PF}_{t-1}$	0.039 ***	−0.297 ***	0.080 ***
BCCsoc	21.510 **	−10.498 **	22.199 **
BCCeco	−1.471 **	29.955	5.306 **
Size	−0.491 **	5.340	0.135 ***
Ln(debt)	−1.469 **	−8.254 **	−2.662 ***
inflation	0.944 **	−0.167	0.800 **
Sargan test	Prob > chi2 = 0.114	Prob > chi2 = 0.181	Prob > chi2 = 0.126
AR (1)	Pr > z = 0.002	Pr > z = 0.018	Pr > z = 0.008
AR (2)	Pr > z =0.482	Pr > z = 0.102	Pr > z = 0.771
Hansen	Pr > chi2 = 0.338	Pr > chi2 = 0.255	Pr > chi2 = 0.253
Number of Obs	897	780	663

Note: * Statistically significant at 10% level. ** Statistically significant at level 5%. *** Statistically significant at level 1%.

show a negative relationship between eco-efficiency and financial performance (−1.1471) in the industrial sector. That can be explained by the cost generated by environmental investments (Saidane & Ben Abdallah, 2021). The industrial sector tends to be enthusiastic, and companies within this sector show hesitancy. Complex factors constrain these firms’ green transition, including cost reduction strategies (Alarie, 2017), market perception (Delmas & Burbano, 2011), etc. However, we found a positive relationship between socio-efficiency and financial performance (21.510), which can be explained by many factors, such as employee productivity and well-being, social responsibility efforts (Haninun et al., 2018), positive impact on profitability (Hassan & Hassan, 2023), etc.

Furthermore, we found that the control variables affect financial performance. There is a negative relationship between assets and financial performance, which can be explained by firm size (Aldaarmi, 2023), and the same is true with debt, which can be explained by debt levels (Abeyrathne & Thilakerathne, 2016). Conversely, we found a positive relationship between inflation and financial performance, which can be justified by the threshold effect of inflation (Boyd & Smith, 1998).

For the European financial sector, the results show that past financial performance significantly negatively impacts current financial performance. This suggests that factors affecting profitability persist over time (Goddard et al., 2005). Furthermore, there is a negative relationship between socio-efficiency and financial performance. It can be attributed to increased social responsibility costs, potential inefficiencies in social initiatives, etc. However, we found a positive relationship between eco-efficiency and financial performance (29.955). This result can save costs through reduced resource consumption, energy efficiency, and waste reduction (Tiyas & Imronudin, 2025).

For control variables, we noted that only ln(debt) affects the financial performance of European companies.

The consumer goods and services results show a positive relationship between eco-efficiency, socio-efficiency, and financial performance.

For control variables, we noted the positive significance of firm size and inflation on financial performance. In contrast, we noted a negative relationship between debt levels and financial performance. Research on financial performance shows that debt is negatively related to FPS (Alvarez-Perez & Fuentes, 2024).

5. Conclusions and Suggestions

5.1. Conclusions

The present study investigates the influence of eco-efficiency and socio-efficiency on the financial performance of 180 European companies across the industrial, financial, and consumer goods and services sectors from 2010 to 2022. The findings indicate significant sector-specific variations. A negative relationship between eco-efficiency and financial performance was observed in the industrial sector, attributed to high environmental costs. In contrast, a positive relationship with socio-efficiency underscores the importance of social initiatives. Conversely, the financial sector exhibits a positive correlation between eco-efficiency and financial performance, driven by cost savings. Yet, a negative relationship with socio-efficiency suggests inefficiencies in social responsibility programs. The consumer goods sector demonstrates a positive relationship between eco-efficiency and socio-efficiency and financial performance, reflecting alignment with consumer demand for sustainable products. Control variables such as firm size and inflation positively influence financial performance, whereas higher debt levels tend to have a detrimental effect.

In light of these findings, companies should integrate eco–socio-efficiency into their strategic frameworks, allocate resources towards innovation, enhance transparency, engage with stakeholders, and align their objectives with the Sustainable Development Goals (SDGs). Implementing sector-specific strategies is essential: industrial firms should focus on cost-effective environmental initiatives, financial firms should optimize their social responsibility programs, and consumer goods companies should continue to weave sustainability into their operations. These recommendations provide a framework for harmonizing sustainability with financial performance, ensuring long-term business success alongside a positive societal impact.

The results of this study indicate the broader implications of integrating eco-efficiency and socio-efficiency into corporate strategies. These findings mainly address market reputation, investor attractiveness, and long-term competitiveness. For instance, the positive relationship between eco-efficiency and financial performance in the financial sector underscores the potential for cost savings and operational efficiencies, which can enhance a firm’s market position and appeal to environmentally conscious investors. This finding is consistent with the conclusions of Hassan and Hassan (2023), who demonstrated that firms with strong environmental performance are more likely to attract sustainable investment funds and achieve higher market valuations. Similarly, the industrial sector has shown evidence of a positive impact of socio-efficiency on financial performance, suggesting that social initiatives, such as employee welfare programs and community engagement, can enhance workforce productivity and stakeholder trust. Furthermore, Alvarez-Perez and Fuentes (2024) emphasize that companies with robust social responsibility practices are perceived as lower-risk investments, leading to improved access to capital and reduced financing costs. The findings underscore the strategic importance of sustainability as a driver of financial performance and market reputation, reinforcing the need for firms to align their operations with global sustainability trends and investor expectations.

However, this study has certain limitations that should be acknowledged. First, the sample size, while representative, is limited to 180 companies, which may affect the generalizability of the findings. Second, the study relies on secondary data from databases such as LSEG-Datastream and the World Bank, which may not capture all the nuances of sustainability performance. Third, the use of DEA, while robust, has limitations in analyzing dynamic phenomena over time, and future studies could explore alternative methods, such as stochastic frontier analysis (SFA), to complement the findings. Finally, the study focuses on European firms, and the results may not be fully applicable to other regions with different regulatory and economic contexts.

Future research could address these limitations by expanding the sample size, incorporating primary data to capture firm-specific sustainability practices, and using longitudinal analyses to assess the long-term impact of eco-efficiency and socio-efficiency on financial performance. In addition, comparative studies across regions could provide insights into how cultural, regulatory, and economic differences influence the relationship between sustainability and financial performance.

5.2. Suggestions

The findings suggest that companies should incorporate eco–socio-efficiency into their strategic frameworks, invest in innovative solutions to create sustainable products and processes, and improve transparency in reporting their environmental and social performance to foster stakeholder trust. Additionally, engaging stakeholders, prioritizing employee well-being, and aligning with the Sustainable Development Goals (SDGs) can strengthen sustainability initiatives. It is essential to implement sector-specific strategies: industrial firms should focus on cost-effective environmental practices while capitalizing on their strong social performance; financial firms need to optimize social responsibility programs to minimize inefficiencies; and consumer goods companies must continue embedding sustainability into their operations to align with consumer expectations. These recommendations provide a practical roadmap for enhancing sustainability without sacrificing financial viability, ensuring long-term business success and a positive societal impact.