The Impact of Blockchain Technology on Sustainable Environmental Performance: The Moderating Role of Environmental Management Accounting

Abstract

This study explores the impact of blockchain technology (BT) implementation on sustainable environmental performance (SEP). Further, the study explores the moderating role of environmental management accounting (EMA) on the BT–SEP relationship. The sample comprises 415 managers in an Egyptian industrial firm. Data were analyzed using Smart-PLS 4 software. The results revealed a positive and significant impact of BT on SEP. Moreover, EMA showed a significant moderating role as it strengthens the relationship between BT and SEP. These results hold significant implications for policymakers, investors, regulators and corporate executives, underlining the importance of BT implementation and EMA strategies and techniques in shaping SEP, particularly within developing markets such as Egypt. This study makes a distinguished added value to the accounting literature by highlighting the valuable consequences of BT, and EMA on SEP in a unique unexplored context. This study highlights the critical role that EMA plays in moderating the BT–SEP relationship, in contrast to early studies in the literature that focused on examining the direct impact of BT or EMA on SEP.

1. Introduction

In today’s dynamic economic settings, there has been an overhaul of the role of business organizations due to the mounting pressures from the environment, such as the prevalent use of ineffective energy resources, global warming, depletion of natural resources, and rising carbon emissions [1,2]. In this regard, the performance of firms is no longer assessed using the conventional method of evaluation based on procedures related to profitability, but there is an increasing interest in their capability to be able to deliver sustainable environmental performance (SEP) [3].

According to Nishitani et al. [4] environmental performance is the capability of the firm to be able to mitigate and react to the various negative impacts caused to the environment, such as pollution, emission of greenhouse gases, environmental waste generation, and the consumption of energy resources. Akhimien and Adekunle [5] mentioned that sustainable performance is the capability of the firm to achieve financial benefits in parallel with enhancing social welfare while minimizing negative environmental impacts.

Therefore, the significance and applicability of SEP have gained paramount and ingrained importance [6]. It has also been found that the costs to the environment can be reduced, efficiency related to resources can be improved, stakeholders’ confidence can be increased, companies can be highly likely to be equally compatible with the relevant authorities related to the environment, and therefore, a competitive advantage is available to a firm by using an effective framework of the method related to the deployment of environmental performance [6,7].

These challenges are especially prevalent in emerging economies, where the pace of industrialization and increasing resource utilization combine with environmental pressures and increasing stakeholder expectations in terms of sustainability [8,9]. In terms of the Egyptian economy, industrialization has been linked with various environmental challenges, including air and water pollution, resource depletion, and greenhouse gas emissions. Nevertheless, recent economic and environmental reforms in Egypt have placed sustainability, CSR, and environmental protection at the forefront of the country’s economic and environmental policy landscape [9]. This provides a focal area for the examination of challenges and opportunities in terms of SEP.

As a response to rising environmental problems, there is literature that has placed prominence on the role of digital innovation as a critical driver in working towards sustainability transformations [10,11]. Moreover, Hanifah et al. [12] argue that the quick pace of innovation in technology has a critical role in transforming accounting practices. Blockchain technology (BT) has received considerable academic and business interest within emerging digital technologies [13].

BT provides decentralized recording of transactions, which ensures the prevention of data manipulation and increases stakeholder trust [14]. Recently blockchain is considered as a fundamental digital infrastructure that can be used in auditing, accounting systems, supply chain management, and sustainability reporting [15,16,17]. Hence, blockchain optimizes the value of firms by processing, verification, and dissemination of environmental data to ensure effective decision-making [18,19,20,21].

Building on these advantages, prior empirical evidence documents that blockchain adoption can enhance environmental efficiency and reduce carbon emissions, for example in large U.S. listed firms and European airports, where BT-based applications improve operational and environmental performance [21,22]. However, these studies are largely concentrated in developed economies with advanced digital infrastructure and mature regulatory systems, which may limit the generalizability of their findings to emerging markets such as Egypt [18]. There is still scant firm-level evidence on whether BT adoption can similarly support sustainable environmental performance in Egyptian firms operating under different institutional, technological, and governance conditions [9,16].

While empirical evidence remains limited in emerging markets, several theoretical arguments have further expanded the debate on how blockchain adoption affects SEP [23]. Some researchers mentioned that there are negative effects on applying BT such as technical complexity level, privacy issues regarding data, the possibility of losing or damaging the data, and the cost involved in the technologies, especially in SMEs [24,25]. On the other hand, there are alternative perspectives supporting the importance of blockchain and its contribution to environmental sustainability, supply chain, improving efficiency, and increasing the monitoring of resources, while considering that superiority in technology is not sufficient [26,27,28].

In this context, environmental management accounting (EMA) is recognized as the critical tool that synchronizes and integrates financial and environmental information and makes a major contribution towards improvement in environmental performance [29]. EMA focuses on measuring, valuing, and interpreting environmental information concerning resource usage, waste generation, and environment-related costs, ultimately aiming at supporting informed environment-related decision-making [1,9].

Even though it is widely acknowledged that EMA is an effective way of promoting sustainable environmental practices, it has not been evenly implemented in emerging and developing economies. According to the literature, there are some firms where EMA is yet to be implemented because of a lack of understanding of environmental issues, data infrastructure, and integration of accounting and EMA [1,6,9]. This is precisely why it is highly important for EMA to integrate with advanced technologies.

In line with this need for technological integration, recent studies in emerging economies like Malaysia and in Asia and the Middle East have found that EMA enhances corporate environmental performance and mediates/moderates the relationship between environmental strategies and green competencies and environmental outcomes [8]. In Egypt, EMA enhances the relationship between green intellectual capital and corporate environmental performance in industrial firms, thus serving as a strategic tool for converting environmental information into better corporate environmental performance [16,30]. However, these studies have not examined the relationship between EMA and BT, thus raising questions about the potential contribution of EMA in assisting Egyptian firms in leveraging BT-based environmental information for better SEP [30,31].

Recent studies show that BT has the prospective to improve EMA by providing valid, credible, timely, and authentic information regarding the environment. In accordance, Nguyen et al. [32] mentioned that while blockchain raises the quantity and quality of environmental information, EMA creates an enabling infrastructure for capitalizing on these efforts. As a result, firms with well-developed EMA are poised to effectively capitalize on blockchain environmental information, hence realizing superior environmental sustainability performance [24,33,34].

From this foundation, recent evidence shows that EMA plays a twofold role, as it not only positively impacts environmental performance but also moderates and shapes the relationship between BT and SEP [35]. Where firms with well-structured EMA systems achieve more benefits from environmental information provided through blockchain and turn it into meaningful insights for managers and then incorporate it into organizational decision-making processes [32,36].

Although there has been an increase in the literature about BT, environmental performance, and management accounting systems independently, some research gaps still exist. First, previous research papers have mainly concentrated on the direct impacts caused by blockchain on environmental performance with minimal focus on the accounting processes that moderate these impacts [26,34]. Second, the role of EMA as a moderating variable within an emerging digital era background, particularly within developing nations, still requires further research focus and exploration [1,9,30].

Third, most prior BT–environment studies have been carried out in developed economies and highly digitalized industries, with very limited evidence from emerging-markets and almost none from the Egyptian industrial sector [21,22]. Given the recent evolution of CSR regulations, sustainability initiatives, and EMA practices in Egypt, focusing on Egyptian firms, provide an opportunity to extend existing theory and offer context-specific insights into how BT adoption, combined with EMA, can drive SEP in an emerging market setting [8]. This study therefore positions Egypt as a pertinent and underexplored context to examine the moderating role of EMA in the BT–SEP relationship [37].

Furthermore, this study focuses on Egyptian firms because Egypt is a major emerging economy that is simultaneously implementing sustainability and environmental reforms while its industrial sector still faces significant environmental pressures [8,9]. Industrial and listed firms in Egypt are therefore a suitable setting to examine the BT–EMA–SEP nexus, as they operate in resource-intensive, environmentally sensitive activities under growing regulatory and stakeholder pressures; yet prior empirical evidence on blockchain and environmental outcomes in the Egyptian market remains almost nonexistent [9,22].

The current study attempts to respond to the literature gaps by replying to the two main research questions: how the moderating factor of EMA contributes to sustainable environmental outcomes after the adoption of BT, and how BT affects SEP. The remainder of this paper is structured as follows. Section 2 presents the theoretical framework. Section 3 investigates the current literature and develops a hypothesis. Section 4 explains the research design and variable measurements. Section 5 presents the study results. Section 6 and Section 7 include discussions of the findings, conclusions, limitations, and directions for future research.

2. Theoretical Framework

The recent study applied a multi-theoretical approach because of the complex and technology-intensive phenomenon of environmentally sustainable practices facilitated by blockchain and responding to calls for a more inclusive integration of several theories for a more comprehensive examination of environmental strategy and performance [7,38].

The variations in SEP generated out of blockchain innovation cannot be explained using one theory because of the belief that no single theory can be globally applicable for digital technologies, environmental strategies, and accounting techniques [39,40]. The appropriate theory for this study would be one that brings together several theories. Information processing (IP) theory explains that because of environmental uncertainty, a company needs to have better information processing abilities [41].

The Resource-Based View (RBV) and Natural Resource-Based View (NRBV) theories give importance to the structure of resources and natural resources, and they give importance to firms with better capabilities and competitive advantages in environmental performance [7,42]. The Knowledge-Based View (KBV) explains that environmental performance depends entirely on management systems in firms and considers the system as a main asset [43,44]. Dynamic Capabilities (DC) theory explains that to effectively deal with environmental changes brought out by advancements in technology, companies use and restructure their existing resources [38].

Lastly, ecological modernization theory explains that firms use modern technology for environmental protection while preserving economic advancement [45]. From a multi-theoretical view, comprehensive insights help explain the techniques through which blockchain and EMA affect variations in firms’ SEP.

From a Resource-Based View (RBV) literature perspective, firm performance is based on its ability to control and utilize resources that are significant, scarce, imitable, and non-substitutable [39,46]. BT can be considered a salient information technology resource because of amplified internal integration capabilities and traceability [18,47]. Consistent with the Resource-Based View, BT helps firms reduce ineffective resource use and enhance environmental efficiency by supporting competitive capabilities that help firms to achieve differential sustainable performance [48,49].

The information processing (IP) theory is considered a complement to the RBV theory because IP theory focuses more on information processing requirements driven by environmental complexity and uncertainty and shows that firms can improve performance by enhancing their information quality and processing capability [21,41]. The use of BT improves information processing capability, since the acquisition and processing of data occur in an efficient and complete manner [48]. In relation to the performance of sustainability and environment, the use of the technology can be seen to overcome the problem of information asymmetry, which is related to the environment, such that the technology will improve the efficiency of environment-related decision-making, providing superior sustainable environment performance [26,50].

A deliberate relationship between the role of BT and SEP could be supported with the assistance of ecological modernization theory [23]. This theory asserts that technological innovation is central to the concept of ecological modernization and helps to offset any tensions between economic growth and environmental security in terms of lower emissions and cleaner production [45]. Ecological modernization theory also addressed varying possible environmental outcomes using technological innovations. Applying BT may lead to adverse environmental effects; hence, ecological modernization theory underpins the point of view that well-designed BT can enhance SEP while pointing out other measures, such as EMA practices, geared towards better environmental sustainability.

Hart [7] mentioned that the Natural Resource-Based View (NRBV) theory represents a further extension of the Resource-Based View (RBV) theory, where natural environment factors are considered for strategic analysis purposes. The NRBV illustrates that a company may achieve sustained competitive advantage based on a capability that leverages environmental elements while maintaining economic viability [40,51]. BT can strengthen the capabilities of NRBV by providing life cycle data regarding material usage, energy usage, and waste to firms for organic environmental risk spotting and environmental requirements for firms’ environmental enforcement needs in managing the wider scope of the supply chain, and assisting in green innovation strategies [18,52].

The Knowledge-Based View (KBV) theory adds more richness to the multi-theoretical framework by emphasizing knowledge instead of physical and financial assets as the most vital strategic resource for a firm [44]. Knowledge is an intangible asset that is specific to a particular environment and extremely hard to duplicate [53,54]. A KBV points out that for any corporation to be successful and efficient, efficient creation, acquisition, safeguarding, transfer, and use of such knowledge within a particular environment would be vitally important. EMA has assumed a critical role as a KBV tool in dealing with physical and monetary data about environmental management practices and contents for management professionals [1,55,56]. From the KBV point of view, BT and EMA create a mutually reinforcing configuration.

Dynamic Capabilities (DC) theory brings a processual, forward-looking perspective supplement to the RBV, NRBV, and KBV theories. Jain and Sharma [57] defined Dynamic Capabilities as the firm’s ability to cope with environmental rapid transformation by combining and restructuring internal and external capabilities. Recent studies stated that there is a link between EMA, environmental strategies, and dynamic capabilities [8,58]. The Dynamic Capability theory argues that the importance of a blockchain to an organization will rise if the organization has dynamic capabilities constructed by identifying and aligning its capabilities in response to rapid environmental changes [59]. Hence, the effect of BT on SEP is expected to be more significant in firms that have well-developed and structured EMA [60].

The application of a multi-theoretical framework leads to the understanding of how and why some firms can capitalize upon the benefits gained by applying BT to enhance their sustainable environmental practices effectively, while others cannot [61]. Firms that implement the blockchain in their operations along with effective EMA are in a favorable position to tap into the benefits of pollution prevention and efficiency in the utilization of natural resources, process and analyze complex environmental information, and dynamically adjust their environmental strategies and processes based upon Dynamic Capabilities theory.

3. Literature Review

3.1. BT Impact on SEP

One of the most groundbreaking technology innovations redefining contemporary organizational systems is BT. Increasingly, it has been perceived as a key driver of transparency, traceability, and secure information exchange in decentralized systems [34,62,63]. In line with the IP theory, BT has significantly improved the information processing activities of organizations because of reduced information asymmetry and efficiency in data verification [64]. Additionally, environmental uncertainties can be reduced using data processing and collecting via BT [21,32,65,66,67].

According to the RBV, BT is a competitive advantage tool that enhances resource management and sustainability reporting practices [68]. There is additional reasoning for combining a focus on a sustainable environment and BT, according to the NRBV [69]. This view suggests that the adoption of blockchain can improve environment capabilities and therefore contribute to a reduction in carbon emissions and waste [21,22,68]. There is also a proposed positive impact of BT on energy optimization and improvements in monitoring and supply chain transparency [21,63].

By analyzing two case studies, Park and Li [22] revealed that BT plays a vital role in enhancing sustainable performance in the supply chain. Moreover, Tawiah et al. [70] using a sample of 103 large US-listed firms from 2015 to 2019 proved that BT has a positive effect on sustainable economic performance. Additionally, using a sample of 152 firms and 11 industries from 2014 to 2023, Tijjani and Yahaya [68] stated that blockchain technology has a positive influence on improving overall environmental performance.

BT is associated with positive aspects of reduced waste of natural resources, mitigating unsustainable sourcing practices through the tracking of supply chain product precision and adherence to overall environmental protection regulations [69,71,72,73]. Other studies also suggest that BT promotes positive environmental disclosure by preventing manipulation of sustainability data and promotes immediate auditing of data [74]. Across 33 European airports from 2010 to 2023, Chomachaei [21] proved that applying BT leads to substantial improvements in operational outcomes and environmental performance.

However, some empirical findings suggest that blockchain implementation can also involve high costs of implementation and require certain technical knowledge that is not available for some firms, especially those in emerging markets such as Iraq [75]. A vast majority of evidence indicates that blockchain has a positive effect on environmental performance in terms of increased transparency, monitoring, and use of resources. Therefore, and in line with IP theory, RBV, and NRBV, we articulate our initial hypothesis as follows:

H1. 

BT is positively associated with SEP.

3.2. EMA and SEP

EMA has been broadly recognized as a critical management tool that adds value to an organization’s capabilities for identifying, measuring, and controlling environmental costs, hence, enhancing sustainable performance [8,55,76,77]. Also, Mohammed et al. [78] argued that management accounting enhances the decision-making process to deal with environmental difficulties. Management accounting enhances firms’ environmental performance by determining environmental costs and analyzing eco-efficiency [79,80].

In line with IP theory, EMA aims to improve internal information processing systems by including environmental information in traditional accounting approaches. This inclusion of environmental information reduces uncertainties as well as enhances the quality of environmental sustainability reporting [81,82]. In addition, EMA is considered a specific implementation of NRBV theory, elucidating how firms can utilize natural resources to overcome pollution, and aid product management and sustainable development [83]. Based on a sample of 298 Egyptian employees, Alnaim and Metwally’s [30] study finds that EMA improves sustainable performance and mediates the relationship between green intellectual capital and environmental performance.

Previous studies have demonstrated that EMA has a positive association with SEP. Moreover, Al-Baghdadi et al. [84] found that the approach to management accounting has shifted to be more comprehensive, including financial and non-financial aspects. Also, Cosma et al. [85] noted that EMA raises awareness of unknown environmental costs, thereby enhancing environmental management practices and, in turn, leading to more transparent and reliable sustainable financial reporting. Additionally, the study of Bresciani et al. [86] demonstrated the positive effect of EMA on environmental performance by collecting data from the textile, chemical, and automotive industries in Pakistan. Furthermore, EMA is associated with greater environmental disclosure practices and higher stakeholder trust in environmental management disclosure practices [78,87].

Despite the existence of supporting empirical evidence, there are some obstacles that continue to exist. Firms in emerging markets usually face an insufficient amount of environmental knowledge, a scarcity of personnel with knowledge of EMA, and a lack of funds for the application of environmental accounting systems [78,88]. However, most literature robustly suggests a positive relationship between EMA and SEP [12]. Therefore, from the KBV, NRBV, and RBV theories, it has been proposed that:

H2. 

EMA is positively associated with SEP.

3.3. Moderation Effect of EMA

The moderating role of EMA has received growing interest among sustainability studies, particularly in relation to digital transformation [32,89,90]. EMA impacts the extent to which BT enhances SEP. Based on IP theory, EMA is considered a sophisticated form of information processing technique that helps firms in understanding, processing, and leveraging environmental data from BT in an effective way [91]. Therefore, EMA has the potential to optimize performance gains from effectively adopting BT by using timely and reliable environmental data that a blockchain provides [12,92].

Based on the RBV, KBV, and DC theories, EMA has a complementation role in BT [93]. EMA offers interpretation capabilities that ease understanding blockchain data concerning analysis related to sustainability insights [55,79,94]. In addition, defining and reformulating environmental practices, especially concerning transparency and automation, are enabled by BT [8,95]. Taken together, all theories imply that EMA takes a role in functioning as a dynamic capability in organizations that moderate between BT and sustainability performance.

Based on empirical evidence, implementation of best practices in EMA plays a vital role in positively promoting the conversion of digital technologies into superior sustainability performances [12,96]. Moreover, there is an indication that EMA plays a moderating role within the relationship between digital technologies and environmental performance, and its role can be seen as promoting superior interpretive abilities, better compliance, and additional value created by data analysis relating to the environment, as suggested by Latan et al. [56]. EMA is seen as making a positive contribution towards making reports more accurate, traceable, and capable within blockchain-based monitoring systems [8,97]. Although there have been numerous studies done on BT and literature related to EMA, some prominent gaps are still present. First, relatively few studies considered in a comprehensive model the impact of BT and EMA together to identify their effects on SEP in emerging economies. Second, very little research has been implemented to identify how BT can provide better sustainable results by taking into consideration EMA as a moderating factor. Third, despite theoretical interpretations that associate BT with various theories like IP, RBV, KBV, NRBV, and DC, relatively little research has a multi-theoretical framework.

By addressing an existing gap, this study enhances the literature with original insights in multiple perspectives: it provides a model that combines blockchain, EMA, and environmental performance, which is relatively rare in the literature; it provides a test of a theoretical model that is comprehensive in that it encompasses six different theories of environmental performance, rather than merely testing a model consistent with a specific theoretical perspective; it fills a significant void in this literature in that it examines the moderating role of EMA; it contributes to the literature in that it provides evidence in a developing economy in which environmental management systems using technology are in their development stages.

Although the theoretical model developed in this study focuses on the direct effect of BT on SEP and the moderating role of EMA, the real-world sustainability context is undoubtedly more complex, as environmental performance is also influenced by institutional pressures, corporate environmental strategies, governance mechanisms and other organizational capabilities [8,9,18]. In this paper, we deliberately adopt a parsimonious baseline model centered on BT, EMA and SEP to provide a clear and tractable test of how blockchain and EMA jointly shape environmental outcomes in an emerging-market context, in line with prior studies that recommend starting from focused models before incorporating additional layers of complexity in future research [22,31]. Based on these theoretical and supportive considerations, we have formulated our hypothesis as follows:

H3. 

EMA moderates the relationship between BT and SEP.

The study’s methodological framework, which incorporates the research variables and proposed linkages in a logical structure, is shown in Figure 1. Sustainable environmental performance (SEP) is the dependent variable, while blockchain technology (BT) is the independent variable. The moderating variable that influences the direction and strength of this connection is environmental management accounting (EMA). Additionally, the framework outlines the moderating interaction effect (H3), the direct effect (H1), and the impact of EMA on SEP (H2). A thorough foundation for the empirical assessment of the study hypotheses is provided by this integrated structure.

4. Research Methodology

In order to provide a comprehensive analysis of the connections between blockchain technology, environmental management accounting, and sustainable environmental performance, the methodological approach used in this study—which is based on the research framework depicted in Figure 2—integrates the research design, data collection procedures, measurement of variables, and data analysis techniques.

4.1. Data Collection and Survey Design

A questionnaire was employed to collect primary data applying the survey approach. The survey instrument was created in accordance with the study framework in order to capture the relationships between independent, dependent, and moderating variables. The study’s participants included manufacturing companies listed on the Egyptian Stock Exchange (ESE). The manufacturing sector was selected due to its substantial environmental effect, risks related to this, and the environmental issues these firms frequently face [98]. This emphasizes how important BT and EMA implementation are for industrial firms in Egypt [6,9,37,67,78,99].

In this study, we distributed 600 surveys to the manager in an Egyptian industrial firm based on their knowledge and experience in accounting and the application of BT and EMA. Convenience sampling was used to choose managers, with an emphasis on those who could offer trustworthy and knowledgeable answers about the study constructs. And the survey was conducted via both manual and web-based methods.

In this research, we used questionnaires with a 5-point Likert scale (ranging from 1 “totally disagree” to 5 “absolutely agree”) to evaluate and measure the participants’ responses to the survey items. We started collecting data in November 2025. After four months a response rate of 69.2% (resulting in 415 valid responses) was obtained from the 600 surveys that were issued, which is considered satisfactory for survey research in organizational settings, particularly in emerging economies [86,100]. In

Table 1. Profiles of sample (n = 415).

		Freq.	%
Gender	Female	92	22.2
	Male	323	77.8
Total		415	100
Years of experience	1–5 years	12	2.9
	6–10 years	78	18.8
	11–15 years	110	26.5
	More than 15 years	215	51.8
Total		415	100
Educational Level	Bachelor	118	28.4
	Masters	205	49.4
	PhD	92	22.2
Total		415	100
Industry	Food, Beverages, and Tobacco	70	16.9
	Industrial Goods, Services and Automobiles	77	18.5
	Basic Resources	68	16.4
	Healthcare & Pharmaceuticals	75	18.1
	Textile & Durables	40	9.6
	Building Materials	85	20.5
Total		415	100

we display the demographic profile of the managers depicted.

4.2. Measures and Scale Development

Measurement scales (BT, EMA, and SEP) were created to operationalize the research framework’s elements. In our study, the questionnaire consists of three sections that were carefully designed to meet the specific requirements of this study. We relied on the previous studies to develop information that is used in the measurement of our study variables (BT, EMA, and SEP). The first step is to get the participants’ informed consent, in which the objective is to get the participants to agree to participate in the study. After that, we gathered the respondents’ demographic information.

Then, the questionnaire includes 5 items to measure the degree of support for adopting BT based on research by Aljumah [99], Khan et al. [101], and Mohammed et al. [78]. After that, the questionnaire had questions about EMA and SEP. Whereas all six items of measurement for SEP were adopted from [31,67,79,102], the five items of measurement for EMA were evaluated using a methodology from [6,9,79,103,104]. We presented a detailed list of all items on the scale (

Table 2. Measurement Model.

Scale Variables and Items	Outer Loading	Alpha	CR	AVE
Blockchain Technology (BT)		0.887	0.914	0.678
BT is used by our company to improve sustainability reporting and environmental data transparency.	0.822
Data on compliance and environmental performance are safely recorded using blockchain systems.	0.826
BT enhances raw material traceability and facilitates supply chain environmental effect monitoring.	0.862
Blockchain-supported smart contracts make it easier to adhere to environmental laws and norms.	0.858
Stakeholder trust in environmental practices and sustainability efforts is increased by BT.	0.736
Environmental Management Accounting (EMA)		0.821	0.869	0.568
Our company’s accounting system carefully records and captures all physical inputs and outputs, including materials, energy, water, wastes, and emissions.	0.754
Product inventory analysis, product improvement evaluations, and product environmental impact assessments are all possible with our company’s accounting system.	0.769
The accounting system of our business is able to recognize, categorize, and project environmental costs and liabilities.	0.750
The ability to generate and utilize environment-related expense accounts is part of our company’s accounting system.	0.751
The accounting system of our business is able to allocate environmental charges to individual items.	0.736
Sustainable Environmental Performance (SEP)		0.895	0.921	0.658
Our company has reduced waste and pollution in the air.	0.737
The energy and water consumption of our company has decreased.	0.710
Our organization now purchases fewer non-renewable resources, chemicals, and components.	0.840
At our company, environmental mishaps have become less frequent.	0.833
Our company has improved its environmental position by following environmental regulations.	0.911
Our company provides environmental education to its employees as well as the general public.	0.805

).

4.3. The Common Method Bias (CMB)

To evaluate the presence of CMB in the survey data, we used two techniques supported by Podsakoff and Organ [105]. The first method is Harman’s single factor which determines if a certain factor is responsible for most of the data’s variation, and for this analysis to be considered valid, the total variance must not exceed 50% [106]. The outcomes of the Harman single factor analysis indicate that CMB was not present in the study, as the total variance was 22.3%. Furthermore, the second method is full collinearity, since studies show that if the value of the variance inflation factor (VIF) is less than 3.3, CMB is not troublesome [107]. The findings of full collinearity demonstrate that there are no issues with CMB as the VIF value is less than 3.3.

4.4. Data Analysis Methods

The data analysis was conducted in accordance with the proposed framework. Specifically, the PLS-SEM analysis was performed using SmartPLS statistical software (Version 4) to evaluate the hypotheses. The SmartPLS-4 statistical software was chosen as the primary data analysis tool for this analysis because of its ability to handle complex structural equation modeling (SEM). This decision was made after it became clear that SmartPLS’s flexibility and ease of use are particularly beneficial in exploratory research [108].

In our study, we used the Partial Least Squares Structural Equation Modeling (PLS-SEM) method because it is well-suited to complex models with many independent and dependent variables that require causal analysis. It also works well for studies using complex theoretical models and those looking for links between underlying variables, particularly when moderating influences are included in the study model, like in EMA [109]. Additionally, PLS-SEM is well-suited to the data set used in the current investigation since it is resilient in managing very small to medium sample numbers and does not require tight assumptions regarding data normality. In order to provide thorough model evaluation, it also permits the concurrent evaluation of the measurement model (construct validity and reliability) and the structural model (hypothesized connections).

Overall, the methodological approach offers a comprehensive analysis of the study hypotheses by connecting the conceptual framework, measurement model, and empirical analysis in a logical and cohesive manner. The empirical findings from using the above-described methodological approach are presented in the next section.

5. Main Results

5.1. Measurement Model Assessment

To verify the validity and reliability of the data collected via the survey, we evaluated convergent and discriminant validity tests. To determine the degree of agreement among many indicators of the same construct, the CV (convergent validity) method is utilized. The findings shown in Table 2 demonstrate that all factor loading was above 0.70 (ranged from 0.710 to 0.911), average variance extracted value (AVE) value was higher than 0.50 (ranged from 0.568 to 0.678) and composite reliability (CR) was 0.70 or higher (ranged from 0.869 to 0.921), which are all essential conditions for the assumption of CV [109]. Furthermore, to assess the discriminant validity of the measurements we used both Fornell–Larcker and HTMT—Heterotrait–Monotrait ratios. The Fornell–Larcker criterion was additionally satisfied by the diagonal values of all constructs being more significant than the predetermined threshold (below 0.90) [110].

Table 3. Discriminant validity measures of scales.

	Fornell–Larcker			HTMT
	BT	EMA	SEP	BT	EMA	SEP
1. BT	0.822
2. EMA	0.598	0.752		0.660
3. SEP	0.731	0.639	0.809	0.821	0.708

shows that each construct’s values are less than 0.90. According to

Table 4. Cross-loading indicators.

	BT	EMA	SEP
BT-1	0.822	0.466	0.510
BT-2	0.826	0.411	0.527
BT-3	0.862	0.519	0.452
BT-4	0.858	0.508	0.468
BT-5	0.736	0.469	0.516
EMA-1	0.282	0.754	0.325
EMA-2	0.391	0.769	0.442
EMA-3	0.369	0.750	0.384
EMA-4	0.523	0.751	0.552
EMA-5	0.508	0.736	0.517
SEP-1	0.541	0.460	0.737
SEP-2	0.534	0.521	0.710
SEP-3	0.470	0.453	0.840
SEP-4	0.522	0.504	0.833
SEP-5	0.486	0.526	0.911
SEP-6	0.504	0.518	0.805

’s findings, outer-loadings considerably outnumbered cross-loadings for every latent variable, indicating strong convergent validity.

5.2. Hypotheses Testing

Firm value and CCD have a positive correlation, according to Hypothesis 1. The regression findings from Model 1 in

Table 5. Structural parameter estimates.

Hypotheses		Beta (β)	T-Statistics	p-Values	Results
H-1	BT -> SEP	0.590 ***	14.622	0.000	Accepted
H-2	EMA -> SEP	0.195 ***	5.339	0.000	Accepted
H-3	BT × EMA -> SEP	0.217 ***	7.411	0.000	Accepted

Note: *** p < 0.01.

show a strong positive association between CCD.

The results shown in Table 5 and Figure 3 provide a thorough examination of the moderating hypotheses (H3) and direct-influencing hypotheses (H1 and H2) examined in this study, highlighting the connections between the variables under investigation. The beta coefficients, t-values, and p-values in Table 5 offer important information about the relevance and strength of these associations. The validity of a hypothesis depends on the significance of path coefficients (β); when the values of these coefficients are statistically significant, the hypothesis is accepted. A hypothesis is considered accepted in PLS-SEM if the t-value is more than 1.96, which is comparable to p < 0.05.

The results of this study indicate that BT has a favorable and significant association with SEP for direct-influencing hypotheses. While the p-values show their statistical significance, the beta-values and t-values show how strong and significant these correlations are. The results show that BT significantly and favorably affects SEP, with a beta-value of 0.590, a t-value of 14.622, and a p-value of 0.000. The thorough research carried out in this study supports the direct-influencing hypothesis (H1), confirming the significant and favorable correlations between the variables being examined.

Furthermore, the results of the study corroborate the direct-influencing hypotheses that EMA has a favorable and significant relationship with SEP; the p-values indicate the statistical significance of these relationships, while the beta-values and t-values demonstrate their strength and significance. The findings show that EMA significantly and favorably affects SEP, with a beta-value of 0.195, a t-value of 5.339, and a p-value of 0.000. The direct-influencing hypothesis is supported by these results (H2).

Additionally, the results confirmed that (H3) was supported which investigated EMA’s moderating effect on the relationship between BT and SEP. Regarding the moderating effect of the interaction between BT and EMA on SEP (H3), the results were positive and statistically significant (a beta-value of 0.217, a t-value of 7.411, and a p-value of 0.000), as Figure 4 shows that EMA increased the relationship between BT and SEP. Figure 4 indicates that EMA enhanced the association between BT and SEP. The line is steeper for high EMA indicating that the impact of BT on SEP is much larger at high EMA than it is at low EMA. The model’s strong explanatory percentage and quality are indicated by the computed R2 value of 77.4%, which implies that the model accounts for 77.4% of the variation in endogenous constructs.

6. Discussion

In what follows, the empirical findings are interpreted in light of the existing literature on blockchain technology, environmental management accounting, and sustainable environmental performance. The study shows that BT notably enhances SEP, aligning with previous research suggesting that BT is crucial for enabling the implementation of environmental strategies by boosting both financial and non-financial environmental data and confirming many early studies which claimed that BT enhances SEP [22,68,79]. The results also confirm many early study results which claimed that BT enhance SEP [22,68]. On the contrary, the study results came in consistent with studies that reported a negative impact [75]. Overall, these findings support prior literature emphasizing that blockchain improves transparency, traceability, and environmental monitoring, thereby enhancing sustainable environmental performance [34,62,63,69].

In particular, our evidence that BT improves SEP in Egyptian industrial firms is consistent with empirical studies that document a positive association between blockchain adoption and environmental efficiency or sustainable performance in other contexts, such as U.S. listed firms and global supply chains, while extending these findings to an emerging-market setting [22,68]. However, this finding contrasts with studies arguing that blockchain adoption may increase environmental burden due to energy-intensive infrastructure and implementation costs, thereby limiting sustainability gains [24,25]. Additionally, this finding supports RBV and NRBV arguments suggesting that blockchain functions as a strategic capability that enhances environmental resource management and sustainability performance [21,68,69].

From a theoretical perspective, these results confirm early claims of the IP theory, which states that BT has significantly improved the information processing activities of organizations because of reduced information asymmetry and efficiency in data verification. Additionally, environmental uncertainties can be reduced using data processing and collecting via BT [21,32,66,95]. Moreover, it also aligns with the NRBV claims that the adoption of BT is able to improve environment capabilities and therefore contributes to a reduction in carbon emissions and waste [21,22,68].

By showing that these theoretical arguments hold in the Egyptian context, the findings also refine ecological modernization perspectives that regard digital technologies as key levers for reconciling economic growth and environmental protection, which have so far been examined primarily in developed economies and specific industries such as airports and logistics [18,21].

Moreover, the study’s findings indicate that EMA has a positive and significant impact on SEP. This result is consistent with many studies that reported that EMA represents a critical management tool that adds value to an organization’s capabilities for identifying, measuring, and controlling environmental costs, hence, enhancing sustainable performance [8,55]. Moreover, this supports early findings by Mohammed et al. [78] who argued that EMA enhances the decision-making process to deal with environmental difficulties. EMA enhances firms’ environmental performance by determining environmental costs and analyzing eco-efficiency [79]. Having said this, the results confirm early claims that EMA enhances SEP [12,78,85,86]. However, this result differs from studies that reported an insignificant or weak relationship between EMA practices and environmental performance, particularly in contexts where EMA implementation remains limited or symbolic [56,111].

The results also go in line with the IP theory claims that EMA aims to improve internal information processing systems by including environmental information in traditional accounting approaches. This inclusion of environmental information reduces uncertainties as well as enhances the quality of environmental sustainability reporting [81]. In addition, EMA is considered a specific implementation of NRBV theory, elucidating how firms can utilize natural resources to overcome pollution, product management, and sustainable development [9,30,112]. Additionally, our evidence supports the view advanced in prior EMA studies that position EMA as a knowledge-intensive capability which enhances the processing, interpretation, and use of environmental information, thereby reinforcing KBV arguments that environmental knowledge embedded in accounting practices is a critical strategic resource [31,111].

Furthermore, the findings of the study suggest that the EMA functions as a moderator within the relationship between BT and SEP. Accordingly, organizations may improve their environmental performance through the implementation of both EMA and BT practices. This result especially represents one of the unique contributions of the current study. As it confirms early theoretical claims by the IP theory. These claims suggested that EMA is considered a sophisticated form of information processing technique that helps firms in understanding, processing, and leveraging environmental data from BT in an effective way [91]. Therefore, it is proved that EMA has the ability to optimize performance gains from effectively adopting BT by using timely and reliable environmental data that BT provides [12]. This moderating effect supports prior literature suggesting that EMA complements digital technologies by improving the interpretation and utilization of environmental information generated by blockchain [12,32,92].

This moderating effect adds to recent work in the digital transformation–sustainability literature, which has suggested—but rarely tested empirically—that management accounting and control systems can shape the extent to which digital technologies translate into improved environmental outcomes [8,56]. By documenting that EMA strengthens the BT–SEP relationship, our results provide direct evidence for this proposition in an emerging-market setting. Moreover, the results supported early theoretical claims by RBV, KBV, and DC theories that EMA plays a complementary role in BT implementation [93]. EMA offers interpretation capabilities that ease understanding BT data concerning analysis related to sustainability insights [55,79] in addition to defining and reformulating environmental practices, especially concerning transparency and automation enabled by BT [8,95]. Taken together, all theories imply that EMA takes a role in functioning as a dynamic capability in organizations that moderates the relationship between BT implementation and SEP. While prior studies examined blockchain and EMA independently, the current findings demonstrate that their joint implementation produces stronger sustainability outcomes, thereby extending the previous literature [22,78].

From a theoretical perspective, these findings advance the multi theoretical framework adopted in this study in several ways. First, by documenting a positive effect of BT on SEP in an emerging-market setting, the results extend RBV, NRBV and ecological modernization arguments that position advanced digital technologies as strategic resources for environmental performance, which have so far been validated mainly in developed economies and highly digitalized sectors [21,22]. Second, the evidence that EMA both directly enhances SEP and strengthens the BT–SEP relationship contributes to EMA research grounded in KBV, NRBV and DC theories by conceptualizing EMA as a dynamic capability that enables firms to convert blockchain-based environmental information into superior sustainable outcomes [8,9,31]. Third, by jointly mobilizing IP, RBV, NRBV, KBV and DC theories within a single empirical model, the study responds to recent calls for more integrative, multi theoretical explanations of how digital technologies and management accounting practices interact to shape environmental performance in emerging economies.

7. Conclusions, Limitations, and Future Research

Using a sample of 425 managers in the Egyptian industrial firm the present study explored the influence of BT implementation on SEP. Further, it investigated the moderating role of EMA in this relationship. The results revealed a positive and significant impact of BT on SEP. Moreover, EMA showed a significant moderating role as it strengthens the relationship between BT and SEP. All hypotheses, whether direct or indirect, are supported by empirical evidence.

Theoretically, this study contributes to the literature on blockchain and environmental performance by providing firm-level evidence from an under researched emerging economy, thereby extending prior findings that have predominantly focused on developed markets and specific industries such as U.S. listed firms and European airports [21,22]. It also enriches EMA research grounded in KBV, NRBV and DC theories by showing that EMA operates simultaneously as a direct driver of SEP and as a moderating capability that amplifies the environmental benefits of BT, in line with recent work that positions EMA as a strategic environmental management tool rather than a purely operational accounting technique [8,9,31]. In this way, the study responds to calls for more empirical research on the joint effects of digital technologies and environmental management accounting in emerging economies, and it clarifies the conditions under which BT can be successfully leveraged to improve sustainable environmental performance [37,67].

Building on these theoretical insights, the study recommends that policymakers improve EMA practices and promote employee participation in EMA to enhance ecological awareness in organizations. These findings support earlier research, which also showed that EMA positively affects SEP [55,79,111]. Moreover, the results align with existing literature in related fields, highlighting the significance of BT in improving SEP [79].

The study recommends that policymakers strategically prioritize investments in green management, viewing it as a way for firms to improve their reputation among stakeholders. As stakeholders become more environmentally conscious, there is increased demand for companies to implement eco-friendly practices. The research offers managerial insights, stressing the need to promote eco-friendly leadership behaviors within organizations to support the adoption of EMA practices. Additionally, the study highlights the strategic importance of EMA practices in developing an environmentally friendly organizational culture. Besides emphasizing EMA’s significance, the findings also point out its crucial role as a strategic asset that fosters an environmentally aware culture. The study concludes that integrating EMA into organizational structures can stimulate BT and provide a competitive edge for the firm.

This study offers several practical implications for managers in Egyptian industrial firms. First, the evidence that blockchain technology enhances sustainable environmental performance indicates that operations and plant managers should prioritize pilot blockchain projects in high impact areas such as supply chain traceability, energy intensive processes and emissions monitoring, rather than treating blockchain as a purely financial or experimental tool [22]. Second, our finding that EMA both improves SEP and strengthens the BT–SEP relationship suggests that management accountants and sustainability officers need to redesign EMA systems to capture blockchain generated data (for example, real time material, energy and waste flows) and translate them into decision-relevant cost and performance indicators that support eco-efficiency initiatives and green investment decisions [8,30,31]. Third, taken together, these results imply that senior executives should view BT and EMA as complementary strategic capabilities and integrate them into broader green management and digitalization programs, since investing in blockchain without upgrading EMA practices, or vice versa, is unlikely to deliver the full sustainability benefits observed in our study [32,34].

While this research offers valuable practical and theoretical insights, it also has limitations that suggest opportunities for future studies. The focus on survey data from Egyptian industrial firms restricts the ability to generalize findings to other industries. Future research could explore different sectors and industries, enabling comparative analyses and extension to other countries in the MENA region. A key limitation is the study’s cross-sectional design, with data collected at only one point in time. Since environmental outcomes tend to develop over the long term, longitudinal studies could better capture these changes over time. Additionally, relying solely on quantitative data may miss important insights found in qualitative responses. Combining both approaches in future research would provide a more comprehensive understanding of participants’ motivations. Moreover, since strategic management accounting (SMA) practices play a crucial role in fostering green behavior and improving SEP, future research could measure the direct impact of SMA on SEP.

Furthermore, the theoretical model adopted in this study is intentionally simplified, as it only incorporates BT, EMA and SEP and does not explicitly account for other important drivers of environmental performance such as institutional pressures, green innovation, corporate governance or broader digital transformation capabilities [8,9,22]. This parsimony represents an additional limitation and suggests that future research should develop and test more elaborate models that include these constructs, investigate more complex mediated and moderated relationships and examine potential reciprocal links among BT, EMA and different dimensions of sustainability performance [22,31]. Including control variables like gender, age, and education in the model could also reveal additional factors influencing environmental performance. Overall, these limitations and suggested research directions open new avenues for more comprehensive and diverse future studies.

The study’s focus on managers in Egyptian industrial enterprises may limit the findings’ applicability to other nations or industries because emerging economies have distinct institutional, regulatory, and technological features. As a result, when applying the results to other circumstances, caution should be exercised. To improve external validity, future research is urged to repeat the study in different nations and industries and include relevant control variables to enhance robustness and generalizability. Furthermore, future research is advised to utilize more comprehensive scales to properly depict the complex constructs of BT, EMA, and SEP. This study is limited by the relatively small number of items employed to measure these concepts, which may not fully capture all dimensions of these concepts.