Conformity assessment is defined by ISO/IEC 17000:2020 as “a demonstration that specified requirements related to a product, process, system, person, or body are fulfilled” [7]. This process encompasses testing, inspection, and certification, which are essential for verifying that products and services adhere to regulatory and customer standards. Conformity assessment is crucial for establishing consumer trust and promoting international trade by confirming compliance with established standards (ISO, 2020). Several research studies highlight the importance of conformity assessment in diverse sectors. [8] state that conformity assessment is crucial in ensuring the safety and safety and reliability of products and services, thereby enhancing the reliability of operations and fostering mutual recognition. The National Institute of Standards and Technology (NIST) points out that conformity assessment is essential for the efficient functioning of markets, as it fosters trust between buyers and sellers regarding the products exchanged [9]. Conformity assessment is a fundamental element in the transformative era of Industry 4.0, where technological developments are reshaping manufacturing and industrial landscapes, ensuring quality, compliance, and supporting innovation [10].

Few studies in the Gulf region have thoroughly examined conformity assessment, despite its crucial importance in improving product quality, ensuring consumer safety, and facilitating intra-GCC trade [11]. indicate that the GSO has made significant progress by launching the Regional Conformity Assessment Scheme project in November 2005. This initiative by GSO seeks to advance the objectives of the GCC through the coordination, integration, and establishment of standardization frameworks and quality infrastructure within the member states. Additionally, the Saudi Standards, Metrology and Quality Organization (SASO) establishes Saudi standards in all required fields such as goods, products and services, and measurement and implements procedures for conformity assessment and certification. In the Sultanate of Oman, the MoCIIP established the Technical Regulation of the Conformity Scheme under Ministerial Decision No. 190/2021 to provide a uniform national framework for guaranteeing that products fulfill national obligations. The legislation defines economic operators’ obligations, describes conformity assessment procedures, and establishes standards for the DGSM’s notification and supervision of CABs. It also specifies the legal basis for granting conformity certificates, conducting market surveillance, and enforcing compliance measures to ensure consumer safety and product quality.

The rule was published in Official Gazette No. 1419 on 5 December 2021 and entered into force six months later, establishing the basis of the Omani Conformity Scheme and its subsequent progressive implementation across regulated product categories [12].

Supply chain management (SCM) is the process of coordinating and managing the intricate network of relationships designed to supply a suitable product to the end-user or consumer [13]. Green SCM signifies the integration of environmental factors into SCM (SCM) [14]. GSCM involves the implementation of a proactive strategy aimed at enhancing the environmental performance of its processes and products to comply with environmental regulatory requirements [15]. [16] examine the role of standards and certifications as critical tools for assessing and enhancing environmental and sustainable supply chain performance. [17] investigate the motivations and advantages of adopting certification schemes in apparel supply chains, emphasizing the potential of these certifications to improve sustainability practices in the industry. The study by [18] analyzes the coordination between tradable white certificate (TWC) and tradable green certificate (TGC) markets in energy supply chains, highlighting the effects of reward-penalty mechanisms on sustainable energy generation. [19] examine how institutional forces, including legislation and customer expectations, promote the implementation of GSCM practices and green certifications. [19] argue that leadership and senior management support are crucial for the effective implementation of GSCM and for guaranteeing compliance via conformity assessment.

[20] analyze the influence of GSCM on organizational performance, positing that environmental certification significantly enhances both ecological and economic outcomes. [21] stated that quality management serves as a precursor to maturity in environmental management, which impacts the implementation of GSCM practices and overall performance. [22] provide an extensive overview of the literature on GSCM, highlighting the incorporation of environmental criteria into supply chain practices and the significance of certification for compliance assurance.

[23] investigate the correlation between GSCM approaches and environmental performance within the electronics sector in Taiwan region, demonstrating that con-formity assessment via certifications aids companies in adhering to environmen-tal standards. [24] examine the impact of environmental regulations on European companies, suggesting that eco-labeling and other conformity assessment meth-ods are crucial for compliance.

[25] defined green practices within the supply chain into two categories of environmental activities: environmental cooperation and environmental monitoring. [21] defined external GSCM practices as “Cooperation with Customers” (CC) and “Green Purchasing” (GP). [26] examined green purchasing practices, eco-design practices, reverse logistics practices, and the impact of legalization and regulation. Green supply chain practices are assessed through three variables: green transportation, green distribution, and green purchasing [27]. [14] identify GSCM practices as encompassing green procurement, green manufacturing, green distribution, and green logistics. Consensus was reached with the findings of [28] as well as [13]. Green supply chain practices were evaluated using five variables: green manufacturing, green purchasing, green information systems, information systems cooperation with customers, and eco-design [29]. Accordingly, this research relies on the dimensions of green practices of the supply chain, represented in eco-design, green distribution, green purchasing, green manufacturing, and green reverse logistics.

The EER program is part of the Oman Conformity Scheme implemented by the Directorate General for Standards and Metrology (DGSM). It aims to reduce overall energy consumption and ensure products in the Omani market comply with established energy efficiency regulations. Standards are often established via law or regulatory frameworks and are frequently revised to incorporate technological advancements and enhancements in energy efficiency. Energy-efficient appliances are essential for decreasing household energy usage and fostering sustainable living practices. The importance of these appliances is paramount as the globe faces the challenges of climate change and energy sustainability [30]. The energy efficiency label offers consumers environmental and energy information regarding home appliances, facilitating the comparison and selection of more energy-efficient items. The label is generally represented through a numerical value or letter grade, with elevated ratings indicating superior energy performance and lower energy use. Energy-efficient appliances frequently employ sophisticated technology, such variable speed compressors in freezers and heat pumps in water heaters, to attain elevated efficiency levels [31]-[32]. The energy efficiency label is a widely utilized tool for lowering the energy consumption of household appliances in several places globally [33].

Numerous studies point out the global significance of energy efficiency ratings. In the European Union, the Energy Labelling Scheme has facilitated a reduction in energy use by providing clear ratings for equipment such as refrigerators and washing machines (European Commission, 2020). Recent Eurobarometer studies indicate that the energy label is well recognized among citizens, with 93% of consumers acknowledging it and 75% utilizing it to guide their purchases (European Commission, 2020). The Energy Star program in the United States has substantially aided energy conservation by offering ratings for diverse products, such as appliances and electronics (U.S. Environmental Protection Agency, 2019).In 2018, ENERGY STAR certified products enabled consumers to conserve approximately 200 billion kilowatt-hours of power, circumvent $20 billion in energy expenses, and realize a reduction of 150 million metric tons of greenhouse gas emissions.

[34] investigated the characteristics of existing labels in European developed countries. [35] identified key elements and practices in implementing building energy codes in 22 countries. Mills and Schleich (2010) demonstrate that when customers are unaware of energy efficiency labels, significant discrepancies may arise in estimating the utilization rates of energy-saving equipment and their potential determinants. Weissman (2024) states that the U.S. Department of Energy’s Appliance and Equipment Standards Program encompasses over 70 products, representing over 90% of residential energy use, 70% in commercial structures, and 30% in industrial sectors. These standards resulted in an expected savings of $105 billion for American consumers in 2024, with the average household saving approximately $576 compared to a scenario devoid of efficiency measures. [26] developed a hedonic pricing model for a metropolitan region in Atlanta, U.S., to elucidate the economic worth of energy-efficiency labels, revealing that homes with energy certificates commanded a sale price premium of 11.7%. [36] developed a systematic methodology for examining the variances between the projected and actual energy consumption of 21 faculty buildings at the University of Zaragoza campus. A study conducted in Germany investigated the impact of replacing old age refrigerators with energy-efficient models. The findings of the research indicated that homes that replaced their old refrigerators with energy-efficient models saved up to 50% on refrigeration energy costs. The analysis showed that households could save between €100 and €150 each year. The results further indicated that the newly developed energy-efficient refrigerators exhibited a payback period ranging from 3 to 5 years, positioning them as a financially viable option for households [37].

The European Parliament and Council’s Directive 2009/125/EC created a common set of rules to set eco-design requirements for energy-related products, with the goal of making sure they are environmentally friendly throughout their entire lifecycle. As defined by Regulation (EU) 2017/1369, the energy label shall represent updated performance categories (A to G). The 2021 International Energy Conservation Code (IECC) requires builders to implement superior thermal insulation and improve window efficiency to significantly decrease energy usage in residential and commercial buildings. As reported by the GCC Standardization Organization (2021), an agreement was established on April 1, 2021, with the Ministry of Industry, Commerce, and Tourism of the Kingdom of Bahrain to facilitate services concerning the operation and advancement of the Bahraini Energy Efficiency Labeling System. The Emirates Authority for Standardization and Metrology (ESMA, 2022) indicates that the UAE has established compulsory energy efficiency labeling initiatives for household appliances, including air conditioners, refrigerators, and washing machines, aimed at fostering sustainable energy use and minimizing environmental effects. The Saudi Standards, Metrology and Quality Organization (SASO, 2023) mandates that the Energy Efficiency Label for electric dishwashers necessitate the registration of the requisite conformity certificate to facilitate the issuance of the shipment certificate via the SABER electronic platform.

The Directorate General for Standards and Metrology (DGSM) announced on June 8, 2023, that Phase 2 of the Omani Conformity Scheme, outlined in Royal Decree No. 190/2021, has commenced. This phase requires energy efficiency (EE) labelling for an expanded range of household products. The Guidance on Conformity Assessment Procedures (CAP) for the Oman Energy Efficiency Labelling Scheme (Directorate General for Standards and Metrology [DGSM], 2023) explains that the Energy Efficiency and Regulation (EER) program is based on several important factors, including the obligations of economic operators, energy labelling, safety and minimum energy performance requirements, the HAZM platform, market surveillance, mandatory products, and harmonized standards.

Energy efficiency is essential for reaching sustainability objectives by decreasing resource usage and lowering carbon emissions throughout the supply chain. Fernando et al. (2018) illustrated the effects of energy management methods on renewable energy supply chains. [38] emphasize that energy-efficient supply chains are crucial for achieving sustainability. Minimizing carbon emissions safeguards the environment and is essential for promoting environmental sustainability. [39] point out that including energy consumption into SCM can enhance energy efficiency in processes from a systemic perspective. [32] discovered that the digitization of supply chains plays a crucial role in enhancing corporate energy efficiency by leveraging green technology innovation. [40] emphasized that the green supply chain is increasingly recognized as a vital strategy for numerous industries and enterprises, as it fosters low energy consumption and mitigates environmental and air pollution. The ISO 50001:2018 standard serves as a globally acknowledged energy management system (EMS) designed to assist organizations across various sectors in enhancing energy efficiency through a Plan-Do-Check-Act (PDCA) continual improvement framework (International Organization for Standardization, 2018). [41] examine the essential function of energy efficiency in improving environmental performance in the context of GSCM, with a specific focus on the Chinese automobile industry. [42] emphasize that the adoption of energy-efficient practices in the supply chain of the manufacturing sector is crucial for attaining sustainability and enhancing energy performance. [38] highlight that green supply chain practices demonstrate a marked superiority over traditional models in their ability to decrease energy consumption and mitigate environmental damage. [43] discovered that energy efficiency labels in China significantly contribute to the promotion of technological innovation among manufacturers, thereby enhancing sustainable supply chain practices. Zu and Zeng (2020) illustrate that energy efficiency standards set by the government have a considerable impact on the decisions made by manufacturers and retailers, promoting investments in energy-saving measures throughout the supply chain. Based on the above discussion, the following research hypothesis is proposed:

Green supply chain practices have a significant impact on the Energy Efficiency Program. Figure 1 illustrates the structure of the proposed research model and reflected the Main hypothesis.

Data related to the impact of the green supply chain on the EER program were collected from Ten Economical Operators in the Sultanate of Oman. This research targeted managers at the senior and middle levels, as they are responsible for

Figure 1. Research model.

formulating organizational strategies and determining corporate policies. Nineteen (19) managers were selected as a sample using purposive sampling. The research questionnaire was sent to them via email, and they were asked to return it within one week. Moreover, it was emphasized that the questionnaires would be treated with strict confidentiality. It was found that 68.4% of respondents were male, while 31.6% were female. In terms of age, the majority of respondents 47.4% fell within the category “25 - 34,” followed by 36.8% in the category “35 - 44,” and finally 15.8% of those in the category “45 and above.

According to the study aims, a model was developed that contains an independent variable, the GSC, and a dependent variable, the Energy Efficiency Program. To collect the data needed for the analysis, a self-administered questionnaire was created electronically using Google Forms. This survey’s elements were initially prepared in English. This questionnaire included a section to determine the demographic characteristics of the research sample (gender, age, organization name, job title, and department), which were categorical variables, as well as two sections dedicated to the main research variables, with responses determined using a five-point Likert scale. Determined using a five-point Likert scale. Developed in English. The elements of this measure were adapted from the Guidance on Conformity Assessment Procedures (CAP) for the Oman Energy Efficiency Labelling Scheme issued by the Directorate General for Standards and Metrology (DGSM).

Green supply chain: This characteristic was measured using 22 items adopted from Khan et al. (2022). This scale was developed to examine respondents’ impressions of economical operators implementing green supply chain approaches in the Sultanate of Oman. Developed in English. The green supply chain was examined as a second-order architecture subdivided into six first-order constructs. Four indicators are used to evaluate ecological design, for example: “The company strives to design products that can be recycled and recover their materials and components.” Green distribution was measured using five items, for example: “The company uses recyclable cartons when distributing products in the market”. Green purchasing was measured using four items, for example:” The company focuses on environmental audit procedures to assess and manage supplier relationships”. Green manufacturing was measured using four items, for example: “The company emphasizes an operational strategy that minimizes waste and optimizes resource investment”. Green reverse logistics was measured using five items, for example: “The company follows a policy of collecting used products for recycling or proper disposal”.

To ensure the accuracy, reliability, and credibility of the measurement instrument used in this study, a validation process was conducted prior to hypothesis testing. Validation is essential in empirical research to confirm that the data collection instrument adequately measures the intended constructs and produces consistent results. Accordingly, several statistical techniques were employed to assess the reliability and validity of the study variables. The following Table 1 showed the Cronbach’s Alpha (α) results the measure the validation.

Table 1. Validation.

The table results indicate the internal consistency reliability of the study constructs as measured by Cronbach’s Alpha (α). All constructs demonstrate acceptable to excellent reliability, as Cronbach’s Alpha values exceed the commonly accepted threshold of 0.70, indicating strong internal consistency among the measurement items.

Table 2 presents the Chi-square goodness-of-fit statistics for the proposed structural model compared with the saturated and independence models.

The default model yields a Chi-square value of 31.207 with 2 degrees of freedom, which is statistically significant (p < 0.001). This result indicates that the hypothesized model does not adequately reproduce the observed covariance matrix. Furthermore, the CMIN/DF ratio is 15.603, which far exceeds the recommended threshold (≤ 3 or ≤ 5), providing strong evidence of poor model fit.

Table 2. CMIN.

The saturated model, as expected, demonstrates a perfect fit (CMIN = 0) because it exactly reproduces the observed data. In contrast, the independence model shows a very poor fit (CMIN = 109.464, DF = 15, p < 0.001; CMIN/DF = 7.298), confirming that the observed variables are not independent.

Although the default model fits the data better than the independence model, its fit remains statistically unacceptable. These findings suggest that the current model specification is inadequate and requires re-specification or structural modification to improve overall goodness of fit.

The results indicate a high level of organizational awareness and compliance with Energy Efficiency Rating (EER) requirements, legal obligations, international standards, and product safety, with most respondents agreeing or strongly agreeing across these areas. Strong adherence is evident in the use of accredited laboratories, third-party testing, market surveillance, and harmonized standards, reflecting effective quality control and alignment with global norms. However, responses reveal uncertainty in some areas, particularly MEPS compliance and the use and awareness of the HAZM platform, suggesting knowledge gaps and inconsistent application. Overall, while compliance and safety practices are robust, targeted training and clearer guidance are needed to strengthen MEPS implementation and HAZM utilization.

Table 3 shows that the mean values of all constructs range from 3.61 to 4.32, indicating that respondents generally agree to strongly agree with the statements measuring green supply chain practices and Energy Efficiency Rating (EER). EER records the highest mean (M = 4.32, SD = 0.64), reflecting a strong perceived level of compliance and effectiveness of energy efficiency practices. High mean scores

Table 3. Descriptive statistics and correlation.

are also observed for Green Manufacturing, Eco-design, Green Reverse Logistics, and Green Purchasing, demonstrating strong organizational commitment to environmentally responsible practices, while Green Distribution reports the lowest mean, suggesting moderate agreement. Overall, standard deviations below 1.1 indicate acceptable dispersion and relatively consistent perceptions among respondents.

The correlation analysis further reveals strong and statistically significant positive relationships among the green supply chain dimensions, highlighting a high level of integration in green practices. Eco-design is strongly correlated with Green Purchasing, Green Manufacturing, and Green Reverse Logistics, while Green Purchasing also shows strong associations with Green Manufacturing and Green Reverse Logistics. These results suggest that organizations adopting one green practice are likely to implement others, reflecting a coherent and synergistic approach to green supply chain management.

With respect to EER, the strongest positive relationship is observed with Green Manufacturing, followed by Green Purchasing and Eco-design, indicating that production-oriented and upstream environmental practices play a more influential role in enhancing energy efficiency performance. Green Reverse Logistics shows a modest association with EER, whereas Green Distribution demonstrates a negligible and non-significant relationship, suggesting a limited direct impact in this context. Overall, the findings indicate strong adoption and integration of green practices, meaningful associations with EER, and no immediate multicollinearity concerns, supporting the suitability of the data for further multivariate analysis such as regression or SEM.

In this study, AMOS software was used to test the hypotheses that included the impact of the green supply chain dimensions on EER of the Manufacturing industry in Oman. Figure 2 illustrates the structural model used to test the research hypotheses.

Figure 2. SEM for the impact of green supply chain on EER.

The structural model illustrates the relationships between green supply chain practices (Eco-design, Green Distribution, Green Purchasing, Green Manufacturing, and Green Reverse Logistics) and Energy Efficiency Rating (EER). The standardized path coefficients indicate that Green Purchasing (β = 0.87) has the strongest positive effect on EER, suggesting that environmentally responsible procurement practices contribute most substantially to improving energy efficiency performance. In contrast, Eco-design (β = −0.31) and Green Distribution (β = −0.45) exhibit negative effects on EER, while Green Manufacturing (β = 0.03) shows a very weak positive effect, and Green Reverse Logistics (β = −0.20) demonstrates a modest negative influence. These results indicate that not all green practices exert a direct positive impact on energy efficiency outcomes.

The model also shows strong correlations among the green supply chain constructs, confirming that these practices are highly interrelated and tend to be implemented collectively rather than independently. This high degree of intercorrelation suggests the presence of shared underlying dimensions of environmental management and may partially explain why several direct paths to EER are weak or non-significant when modeled simultaneously. Such overlap can reduce the unique explanatory power of individual constructs in the structural model.

Finally, the error term associated with EER (e1 = 0.27) indicates that a proportion of variance in energy efficiency performance remains unexplained by the included predictors. Combined with the previously reported poor model fit indices, the figure suggests that the current model may suffer from specification issues, such as multicollinearity among predictors or missing mediating variables. Overall, while green practices are strongly interconnected, their direct effects on EER appear limited, implying that their influence may be indirect or mediated through other organizational or regulatory factors.