Performance Evaluation of Economic, Environmental, and Social Sustainability and GRI-Based SDG Disclosures in Turkey’s Automotive Sector

Abstract

Sustainability reporting has emerged as a pivotal tool for corporate accountability, integrating environmental, social, and economic performance into transparent disclosures that align with global frameworks such as the Global Reporting Initiative (GRI) Standards and the United Nations Sustainable Development Goals (SDGs). This study evaluates the environmental sustainability performance of Turkey’s automotive manufacturing sector by analyzing the extent and depth of GRI-based disclosures and their alignment with SDG targets. A mixed-method approach, combining quantitative Key Performance Indicator (KPI) coverage analysis with qualitative content assessment, was applied to sustainability reports from 12 major manufacturers. By identifying the most frequently reported indicators, assessing their coverage of economic, environmental, and social dimensions, and evaluating their direct relevance to specific SDGs, this research fills a critical gap and provides actionable insights for policymakers, industry leaders, and sustainability practitioners. The results indicate that while social indicators achieve the highest average disclosure rate (77.3%), environmental themes dominate narrative emphasis, reflecting sectoral materiality and regulatory pressures rather than proportional (KPI) coverage. Key gaps include underreporting of governance-related SDGs (e.g., SDG 5, SDG 8, SDG 16), limited target-level mapping, and a lack of measurable, outcome-based indicators. The study proposes a structured methodology for linking GRI metrics to SDG targets, enabling more consistent benchmarking and highlighting opportunities for balanced integration across all sustainability pillars. The findings contribute to both academic discourse and industry practice by demonstrating the need to bridge the gap between quantitative breadth and qualitative depth in sustainability reporting, ensuring more robust alignment with the 2030 Agenda.

1. Introduction

Sustainability reporting has become a critical component of corporate transparency, encompassing not only financial performance but also environmental stewardship and social responsibility. Contractors, investors, and consumers increasingly value such non-financial transparency, which fosters trust and strengthens a company’s competitive position in the marketplace.

Emerging in the 1980s with an initial focus on environmental issues, the sustainable development paradigm has evolved into an integrated framework built upon three core pillars: (1) economic prosperity, (2) conservation of natural resources, and (3) global social well-being [1,2,3]. Within this framework, non-financial disclosures—particularly quantitative indicators—are recognized as essential tools for monitoring and communicating sustainability performance [4,5,6,7].

GRI Standards constitute one of the most widely adopted and internationally recognized frameworks for corporate sustainability reporting. According to the 2024 KPMG Global Survey, 77% of the world’s largest companies producing sustainability reports use the GRI framework. The United Nations SDGs, adopted in 2015, comprise 17 goals and 169 specific targets aimed at fostering environmental, economic, and social progress; their successful implementation depends heavily on corporate engagement [8,9].

Recent studies in the Turkish context reveal significant gaps in the scope and diversity of reported indicators. For example, among 42 companies listed in the Borsa Istanbul (BIST) Sustainability Index, 28 published sustainability reports—26 of which complied with GRI Standards—yet the disclosure rate for Scope 3 greenhouse gas emissions (covering supply chain and other indirect emissions) remained notably low [10]. In the automotive sector specifically, an analysis using the TOPSIS method found variations in social sustainability performance, particularly in areas such as occupational health and safety, employee rights, and supply chain management [11]. Likewise, a review of environmental sustainability practices within BIST 50 companies identified several major firms (e.g., Arçelik, Ford, Vestel) as providing tangible, measurable initiatives, while the overall quality and depth of disclosures remained limited [12].

The automotive sector serves as a critical case for examining GRI–SDG linkages due to its high energy consumption, significant greenhouse gas emissions, and complex supply chains [13]. Lisowski et al. [14] demonstrated strong correlations between the sector and SDG 12, SDG 13, and SDG 9. Molnár et al. [15] (2024) reported that global automotive OEMs frequently disclosed actions related to SDG 7 and SDG 13 between 2018 and 2022, although absolute energy consumption and emissions showed limited reductions. Lukács et al. [16] identified the automotive sector as the most SDG-compliant industry (85%) among those examined, yet also highlighted challenges such as “rainbow washing” and selective SDG prioritization.

Despite these contributions, there remains a lack of systematic, context-specific analyses of GRI–SDG alignment in the Turkish automotive industry. This study addresses this gap by developing a structured methodology to evaluate the relationship between GRI indicators and SDG coverage, thereby providing a more comprehensive assessment of the sector’s contribution to the global sustainability agenda.

The research addresses the following questions:

• Do major automotive companies report on the same GRI indicators?
• Which sustainability dimensions are comprehensively covered, and which are underrepresented?
• What are the direct linkages between the most frequently reported indicators and the SDGs?
• Which SDGs receive the most consistent attention within the sector’s sustainability reporting?

2. Automotive Sector in Turkey

The automotive sector in Turkey is currently navigating a challenging period, influenced by the cumulative effects of global crises. Rising production costs, geopolitical tensions, supply chain disruptions, and increasingly stringent environmental regulations have negatively affected both domestic automotive production and sales. These challenges have underscored the need to enhance the sector’s resilience and flexibility, prompting manufacturers to reassess their priorities in light of changing economic conditions and evolving sustainability requirements.

At the global level, environmental policies such as the European Union’s Carbon Border Adjustment Mechanism (CBAM) have accelerated the automotive industry’s shift towards sustainability and the transition to electric vehicles. Efforts to reduce the carbon footprint of the global automotive industry are transforming production location strategies from a cost-oriented approach to one prioritizing carbon efficiency. As the transport and automotive sectors account for approximately 25% of total greenhouse gas emissions in Europe, the need for profound structural transformation remains urgent.

In this context, countries with high production costs but advanced carbon efficiency, such as those in Western Europe, are expected to gain a competitive advantage in the new regulatory environment. For Turkey to maintain its competitive position, rapid adoption of sustainable production strategies is essential.

According to the Turkish Exporters Assembly (TİM) Export Report 2024 [17], the automotive industry retained its position as Turkey’s largest export sector, with export revenues reaching USD 35 billion. Data from the Automotive Manufacturers Association (OSD) indicate that in the first half of 2025 (January–June), total automotive production remained at a level comparable to the same period of the previous year, while passenger car production declined by 5%. Over the same period, total automotive exports in value terms increased by 12% year-on-year, reflecting strong external demand despite domestic production constraints.

These dynamics highlight the dual challenge facing Turkey’s automotive sector: maintaining export competitiveness while accelerating the integration of low-carbon technologies and sustainable manufacturing practices in response to global regulatory shifts.

This study introduces an innovative approach by systematically mapping GRI-based sustainability disclosures to the SDGs in the Turkish automotive sector. It is the first research to apply a structured content analysis of GRI reports for Turkey’s automotive manufacturers, a sector of strategic importance to the national economy. Beyond this sectoral focus, the methodological framework—linking SDG-related KPIs identified through content analysis with Sustainable Drivers Key Performance Indicators (SDKPIs) developed via coverage analysis—is transferable to other industries. Since both GRI Standards and the SDGs are cross-sectoral, the approach can be adapted to contexts such as textiles, energy, or construction, thereby positioning the study as both a sector-specific contribution and a methodological framework with broader applicability.

3. GRI Sustainability Standards and SDG Reporting

Sustainability reporting refers to the systematic practice of measuring, documenting, and publicly communicating an organization’s most significant economic, environmental, and social impacts, with the aim of enhancing transparency, accountability, and stakeholder engagement [18]. Closely related, Sustainable Development Goal (SDG) reporting specifically addresses how corporate activities align with the 17 global goals outlined in the United Nations 2030 Agenda [19,20]. Since the formal adoption of the SDGs in 2015, corporate communication strategies have increasingly incorporated references to these objectives, positioning them as a framework for aligning business practices with global sustainability priorities [3,21,22].

The growing prevalence of mandatory disclosure requirements—particularly within the European Union under Directive 2014/95/EU—has intensified the demand for robust sustainability metrics and performance assessments [23,24,25]. However, despite the proliferation of sustainability disclosures, academic research highlights a lack of standardized methodologies for systematically mapping corporate indicators to SDGs [26,27]. This methodological gap hinders the ability to conduct sector-wide evaluations of contributions to the SDGs in a comparable and transparent manner.

Sustainability reporting functions not only as a disclosure mechanism but also as an enabling tool for implementing SDG-related strategies, investments, and operational changes [18,28]. It allows organizations to measure, manage, and communicate their SDG-related initiatives, supporting more effective planning for sustainable transitions. Conversely, the SDGs shape the content and scope of sustainability reports, while SDG-focused disclosures can help direct investment capital toward socially and environmentally beneficial projects [29].

The GRI Standards offer one of the most widely adopted frameworks for sustainability reporting, structured as an interrelated modular system comprising GRI Universal Standards, GRI Sector Standards, and GRI Topic Standards. The Topic Standards are further divided into the GRI 200 series (Economic), GRI 300 series (Environmental), and GRI 400 series (Social).

A growing body of empirical evidence suggests that aligning corporate performance with SDGs enhances transparency and can lead to improvements in sustainability practices [21,30,31]. However, while references to SDGs in corporate reporting have become more common, relatively few companies have adopted explicit SDG-focused strategies that translate reporting into measurable change [32,33].

Research on the environmental dimension reveals a nuanced relationship between SDG disclosure and performance outcomes. Ferrón Vílchez et al. [34] found that companies with higher levels of environmental SDG reporting often exhibit stronger process-based performance but weaker outcome-based performance. This pattern may indicate that firms use SDG disclosures to communicate commitments and corrective actions in response to underperformance, aiming to preserve or restore legitimacy.

In the social dimension, SDG reporting on human rights, labor practices, and community engagement has been shown to positively influence corporate social performance [35]. Increased disclosure in these areas is associated with tangible benefits such as improved corporate reputation, stronger stakeholder relationships, and enhanced trust [36,37].

In contrast, governance-related SDG disclosures appear less directly linked to improvements in governance performance. Studies suggest that governance outcomes are shaped primarily by structural and institutional factors that extend beyond the scope of voluntary SDG reporting [38]. Alsayegh et al. [39] argue that national governance systems mediate the relationship between sustainability reporting and SDG achievement, indicating that meaningful improvements in governance performance may require stronger institutional and regulatory frameworks in addition to corporate-level initiatives.

This literature demonstrates that while sustainability and SDG reporting frameworks—particularly the GRI Standards—provide a valuable structure for measuring and communicating sustainability contributions, the effectiveness of such reporting in driving actual performance improvements depends on sector-specific conditions, strategic integration, and the robustness of governance and regulatory environments. In this context, the present study examines the automotive sector’s sustainability disclosures in Turkey, mapping the relationship between GRI indicators and SDGs to assess the extent and depth of this alignment.

4. Materials and Methods

The study sample consists of 12 automotive manufacturers in Turkey. Selection was based on three primary criteria: (i) market share, ensuring that the companies collectively represent the majority of national automotive production and exports; (ii) data accessibility, with publicly available sustainability reports prepared in accordance with the GRI Standards for at least one reporting cycle; and (iii) sectoral representativeness, covering a range of domestic and foreign-owned enterprises to capture the diversity of production structures, supply chain integration, and sustainability strategies within the Turkish automotive industry. This purposive sampling approach ensures that the findings reflect both the dominant market actors and the broader sectoral context. To preserve academic neutrality, avoid highlighting any specific brand, and ensure comparability, these companies have been anonymized and coded as M1–M12 in the analysis.

This research adopts a constructivist research paradigm, which has been widely applied in management, sustainability, and social sciences for developing practice-oriented theoretical frameworks [40,41]. The constructivist approach is grounded in the iterative interaction between empirical evidence and theoretical reasoning, enabling the systematic development of frameworks that are both contextually relevant and theoretically robust.

The methodological process followed in this study comprised three main stages:

• Compilation, systematic analysis, and critical examination of scientific knowledge, including peer-reviewed literature, policy documents, and sustainability reporting frameworks relevant to the GRI and the SDGs;
• Identification and acquisition of core postulates, which involved distilling the fundamental concepts, requirements, and linkages between GRI standards and SDG targets;
• Construction of the initial analytical framework, which integrated theoretical insights with empirical findings from the pilot enterprises and sector-specific case data.

Within this framework, three focal elements were operationalized:

• The SDG-related requirements identified by pilot enterprises that the GRI reporting framework should address;
• The theoretical coverage of these requirements within the scope of the SDGs and the GRI standards;
• The existing SDG-related Key Performance Indicators (KPIs) disclosed in the GRI sustainability reports of Turkish automobile manufacturers (Figure 1).

This structured approach ensured methodological rigor by combining theory-driven reasoning with empirical validation, thereby enhancing both the analytical depth and the practical applicability of the resulting framework.

The methodology adopted in this study is content analysis, a well-established approach for systematically categorizing corporate communications, especially in the context of SDGs. This method has been widely employed to assess corporate contributions to SDGs across different domains [42,43,44,45,46]. Content analysis enables the reduction of extensive textual data into predefined categories based on coding rules, thereby facilitating rigorous interpretation of sustainability disclosures [31,47]. In this study, content analysis was employed to establish SDG categories derived from keywords coded from KPIs disclosed in GRI reports. The methodology was complemented by a background analysis and a descriptive data analysis.

The research was conducted using 12 reports from the year 2024. Given the heterogeneity of the reports in terms of standardization, preliminary classification activities were undertaken. In the first stage, all sustainability metrics reported by different firms were identified, each KPI was assigned a code, and each metric was counted only once (a maximum of one per report). While KPIs were generally categorized within one of the sustainability dimensions in the reports, those not classified were allocated by the authors according to the subject they measured. In the second stage, the identified metrics were linked to various SDGs and targets, thereby analyzing the extent to which the practices of seven automotive manufacturers aligned with these goals, based on the information disclosed in their GRI sustainability reports.

Subsequently, a coverture analysis was carried out to identify the minimum set of metrics required to cover all the defined goals and targets, leading to the determination of SDKPIs. In the final stage, a global sectoral analysis was presented, which considered not only these SDKPIs and the goals and targets they covered but also the frequency with which the SDKPIs appeared in the GRI reports.

5. Results and Discussion

5.1. Classification of GRI Metrics

The first analytical phase involved the systematic classification of the GRI indicators into the three canonical dimensions of sustainability—Economic, Social, and Environmental—in accordance with the GRI Standards framework [42]. The outputs of this classification are presented in

Table 1. Economic metrics.

Metrics	M1	M2	M3	M4	M5	M6	M7	M8	M9	M10	M11	M12
E1: Sales revenue	1	1	1	1	1	1	1	1	1	1	1	1
E2: Profit	1	1	1	1	1	1	1	1	1	1	1	1
E3: Sales and service satisfaction	0	0	1	0	0	0	1	0	1	0	0	1
E4: Dividends	0	0	1	0	0	1	1	1	1	0	0	1
E5: Market share	1	1	1	1	1	1	1	0	1	1	1	1
E6: Value added	1	0	0	0	1	1	1	1	1	0	1	1
E7: Wages, salaries, benefits to employees	1	1	1	1	1	1	1	1	1	1	1	1
E8: Direct economic value generated and distributed	0	0	0	0	0	1	1	0	1	0	0	1
E9: Financial assistance received from government	0	0	0	0	0	1	1	0	1	0	0	1
E10: Ratio of basic salary and remuneration of women to men	0	0	0	0	0	1	1	0	1	1	0	1
E11: Customer satisfaction	0	0	0	0	0	0	1	0	1	0	0	1
E12: Security calls	0	0	0	0	0	0	1	0	1	0	0	1
E13: Car-dealers’ satisfaction level	0	0	0	0	0	0	1	0	1	0	0	1
E14: Sales volume automobiles (in thousand units)	1	1	0	1	1	1	1	1	1	1	1	1
E15: Sales of electric and electrified vehicles (number)	1	0	0	1	1	1	1	1	1	1	1	1
E16: Share of production-relevant purchasing volume in the CDP Supply Chain Programme	0	0	0	0	0	1	1	0	1	1	0	1
E17: Capital expenditure	1	1	1	1	1	1	1	1	1	1	1	1
E18: Income taxes	1	1	1	1	1	1	1	1	1	1	1	1
E19: Research and development expenditure	1	1	1	1	1	1	1	1	1	1	1	1
E20: Tangible assets	0	1	0	1	1	1	1	1	1	1	0	1
E21: Financial investments	0	1	0	1	1	1	1	1	1	1	0	1
E22: Total financial security	0	0	0	0	0	1	1	1	1	1	0	1
E23: ROE (return of equity)	0	0	0	0	0	1	1	0	1	0	0	1

(Economic indicators: E),

Table 2. Environmental metrics.

Metrics	M1	M2	M3	M4	M5	M6	M7	M8	M9	M10	M11	M12
V1: Energy consumption	1	1	1	1	1	1	1	1	1	1	1	1
V2: Direct CO2 emissions	1	1	1	1	1	1	1	1	1	1	1	1
V3: CO2 equivalents	1	1	1	1	1	1	1	1	1	1	1	1
V4: Waste for recycling	1	1	0	1	1	1	1	1	1	1	1	1
V5: GHG emissions	1	1	1	1	1	1	1	1	1	1	1	1
V6: Waste for disposal	1	1	1	1	1	1	1	1	1	1	1	1
V7: (VOC) per vehicle produced (in kg/vehicle)	0	0	0	0	0	0	1	1	0	1	0	1
V8: Energy averages per vehicle	0	0	1	1	0	1	1	1	1	1	0	1
V9: Direct NOx and SO2 emissions	0	0	0	0	0	0	1	0	1	1	0	0
V10: Fleet fuel consumption	0	0	0	0	0	0	0	0	1	0	0	0
V11: Freshwater and wastewater	1	0	1	1	1	1	1	1	1	1	1	1
V12: Wastewater discharges	1	0	1	1	1	1	1	1	1	1	1	1
V13: Environmental protection costs	1	1	1	1	1	1	1	1	1	1	1	1
V14: Water Recycling Index	1	0	0	0	0	0	0	1	1	1	0	1
V15: Number of Environmental Violations	0	0	0	0	1	0	0	0	0	0	1	1
V16: Emissions and fuel economy	0	0	1	0	0	0	1	1	1	1	0	1
V17: Waste to landfill	0	0	0	0	1	0	1	1	1	1	0	1
V18: Overall consumption of recycled plastic	1	0	1	0	1	1	1	1	1	1	0	1
V19: Alternative fuels	0	0	0	0	0	0	1	0	1	0	0	1
V20: Fuel economy for major renewals	0	0	0	0	0	0	1	1	1	0	0	0
V21: Materials used in vehicles	0	0	1	0	0	0	1	0	0	0	0	1
V22: Efficient powertrains and technologies	0	0	0	0	0	0	1	1	1	0	0	1
V23: Share of renewable energy purchased from third parties (in %)	1	0	1	0	1	1	1	1	1	1	1	1
V24: Hours dedicated to environmental training	0	0	0	1	0	1	1	0	0	1	0	1
V25: ISO 14001 [48] Certified plants	0	1	1	1	1	1	1	1	1	1	1	1
V26: Investments in energy savings	0	0	0	0	0	1	1	0	1	1	0	1

(Social indicators: S), and

Table 3. Social metrics.

Metrics	M1	M2	M3	M4	M5	M6	M7	M8	M9	M10	M11	M12
S1: Number of employees	1	1	1	1	1	1	1	1	1	1	1	1
S2: Accident Indexes	1	1	1	1	1	1	1	1	1	1	1	1
S3: Proportion of women	1	0	1	1	1	1	1	1	1	1	1	1
S4: Comply with anti-corruption/bribery regulations	0	1	1	1	1	1	1	1	1	1	1	1
S5: Sickness rate	1	1	1	1	1	1	1	1	1	1	1	1
S6: Investments in employee qualification	1	1	1	1	1	1	1	1	1	1	1	1
S7: Employee turnover	1	1	1	1	1	1	1	1	1	1	1	1
S8: People satisfaction	0	1	1	1	1	1	1	1	1	1	1	1
S9: Company contribution (pensions)	0	0	1	1	1	1	1	1	1	1	0	1
S10: Trafficking	0	1	1	0	1	1	1	1	1	1	1	1
S11: Level of qualification	0	1	1	1	1	1	1	1	1	1	1	1
S12: Community engagement	1	1	1	1	1	1	1	0	1	1	1	1
S13: Charity contributions	1	0	0	0	1	0	1	0	1	1	1	1
S14: Apprentices	0	0	0	1	1	1	1	1	1	1	1	1
S15: Employee average age	0	0	1	1	1	1	1	1	1	1	1	1
S16: Share of women in management positions	0	1	1	1	1	1	1	1	1	1	1	1
S17: Average period of employment	0	1	0	1	1	1	1	1	1	1	1	1
S18: Absenteeism	0	1	1	1	1	1	1	1	1	1	1	1
S19: Parental Leave	0	1	1	1	1	1	1	1	1	1	1	1
S20: Accident Severity	0	0	1	1	1	1	1	1	1	1	0	1
S21: Costs for training and advanced professional development	0	0	0	1	0	0	1	1	1	1	0	1
S22: Qualification days per employee/year	0	0	0	1	0	0	1	1	1	1	0	1
S23: Qualification days per employee/year	0	0	0	0	0	0	1	0	1	1	0	1
S24: Qualification hours per employee/year	1	0	0	1	0	0	1	0	1	1	0	1
S25: Employee contribution to the Group’s sustainability profile	0	0	0	0	0	0	1	1	1	1	0	1
S26: Work–life balance	0	0	0	1	0	0	1	1	1	1	0	1
S27: Occupational health and safety	0	1	1	1	1	1	1	1	1	1	1	1
S28: Engagement in prevention	0	0	0	1	0	0	1	1	1	1	0	1
S29: Working alongside the community	0	0	0	1	0	0	1	1	1	1	0	1
S30: Membership in associations or organizations	1	0	0	0	1	0	1	1	1	1	1	1
S31: Voluntary work	0	0	0	0	0	0	1	0	1	1	0	1
S32: Expenditure on corporate citizenship	1	1	0	0	1	1	1	0	1	1	1	1
S33: Hiring for permanent contract	0	0	0	0	1	1	1	1	1	1	0	1
S34: Change in number of employees under permanent or fixed-term contracts over 3 years	0	1	0	0	1	1	1	1	1	1	0	1
S35: Change in permanent contract turnover rate	0	0	0	0	1	1	1	1	1	1	0	1
S36: Number of temporary employees	0	1	0	0	1	1	1	1	1	1	0	1
S37: Paid absences for sickness	0	0	0	0	0	1	1	1	1	1	0	1
S38: Corporate Social Responsibility	0	1	0	0	0	1	1	1	1	1	0	1

(Environmental indicators: V), each annotated with its corresponding GRI code to ensure traceability and reproducibility.

The classification process involved:

• Indicator identification—extraction of all reported GRI metrics from sustainability reports.
• Dimension assignment—allocation of each indicator to one of the three sustainability pillars based on GRI Topic Standards coding.
• Binary coding—each indicator was coded on a binary scale (1 = disclosed, 0 = not disclosed) for each manufacturer (see Table 1, Table 2 and Table 3).

Phase 2 consisted of mapping the classified GRI indicators to the United Nations SDGs to assess the degree of alignment between corporate reporting practices and the 2030 Agenda targets. This mapping exercise revealed that certain GRI indicators exhibited no meaningful correspondence with SDG targets, while others demonstrated partial or substantial alignment. A subset of indicators—specifically S4, S6, S16, V2, and V3—were found to be in full alignment with one or more SDG targets.

The results of this mapping are summarized in the linkage table, which cross-references the GRI indicators from Table 1, Table 2 and Table 3 with the corresponding SDGs and targets. The metrics presented in Table 1, Table 2 and Table 3 (E1–E23, V1–V26, S1–S38) have been matched with their corresponding GRI Standard codes, and the full mapping tables are provided in the Supplementary Materials.

Table 4. Percentage of Environmental (V), Economic (E), and Social (S) Metrics Reported by Automotive Manufacturers.

Manufactures	Env. Metrics (V:26) Reporting Rate (%)	Economic (E:23) Metrics Reporting Rate (%)	Social (S:28) Metrics Reporting Rate (%)	Overall (87) Reporting Rate (%)
M1	46	44	63	54
M2	31	72	50	52
M3	54	39	47	48
M4	46	48	68	58
M5	54	52	71	62
M6	58	83	89	80
M7	88	100	100	99
M8	69	48	84	72
M9	85	100	100	98
M10	77	61	100	85
M11	46	44	55	51
M12	88	100	100	99
Average %	61.8	65.9	77.3

provides the frequency of reporting for each indicator by the surveyed manufacturers.

According to the dataset, the most frequently reported metrics across the 12 manufacturers are as follows:

-

Economic: E1, E17, E18, E19, E7

-

Environmental: V1, V2, V3, V5, V6, V13

-

Social: S1, S2, S5, S6, S7

Not all of the metrics presented in Table 1, Table 2 and Table 3 are directly aligned with the SDGs. For some GRI indicators, it was not possible to establish a meaningful correspondence with specific SDG targets.

However, certain metrics demonstrate a substantial degree of alignment with the SDGs. This occurs when the content and scope of the indicators significantly overlap with particular SDG targets.

Full alignment is observed only for a limited number of indicators—specifically, S4, S6, S16, V2, and V3.

Table 4 indicates the number of metrics reported by the manufacturers.

Environmental metrics show moderate uptake, with only a few firms (M7, M9, M12) nearing full coverage.

Economic metrics tend to have more variation, possibly due to confidentiality concerns or different internal accounting frameworks.

Social metrics, despite being the most numerous (38 total), show wide variability. While M7, M9, and M12 fully report them, others like M3 and M11 report fewer than 60%.

Manufacturers M7, M9, and M12 exhibit near-complete sustainability disclosures, reporting over 97% of all available metrics. This indicates a high level of transparency and strategic alignment with sustainability principles. Firms such as M5, M6, M8, and M10 report between 60–85% of the metrics. These manufacturers demonstrate relatively strong engagement but may benefit from further standardization or integration across one or more dimensions (notably economic or social). Manufacturers M1, M2, M3, and M11 report less than 55% of the possible metrics, reflecting either a lack of comprehensive sustainability reporting systems or a more selective approach in their disclosures. While some firms (e.g., M6, M10) display relatively balanced reporting across all three pillars, others show disparities. For instance, M2 has strong economic reporting but relatively low environmental and social disclosures. This analysis reveals a significant heterogeneity in sustainability reporting practices among automotive manufacturers in Turkey. While a few companies lead with comprehensive disclosures, a majority still exhibit gaps, particularly in the social and environmental dimensions. Standardized reporting frameworks and regulatory alignment may help bridge these gaps and enhance overall sectoral transparency (Table 4).

Although the quantitative analysis indicates that the social dimension achieves the highest average disclosure rate (77.3%), followed by economic (65.9%) and environmental (61.8%) dimensions, the discourse analysis of sustainability reports suggests a different priority hierarchy (Table 4). The narrative foregrounds environmental stewardship—employing terms such as “energy,” “emissions,” and “resource management”, which are emblematic of eco-efficiency discourse [49]. This observation aligns with prior studies showing that thematic salience in sustainability narratives often diverges from metric-based coverage, as companies strategically frame environmental issues to meet stakeholder expectations and regulatory demands [50]. Consequently, despite the higher numerical coverage of social indicators, the prominence of environmental topics in both narrative framing and stakeholder communication reflects sectoral materiality and external pressure rather than a proportional KPI-based emphasis.

The Wilson 95% confidence intervals provide further insight into the robustness and variability of disclosure rates across the three GRI-based dimensions (

Table 5. Wilson 95% confidence intervals for disclosure rates by sustainability dimension.

Category	Mean of Company Rates (%)	Pooled Disclosure (%)	95% Wilson CI
Environmental (V = 26)	61.8	61.9	56.4–67.1
Economic (E = 23)	65.9	65.9	60.2–71.3
Social (S = 28)	77.2	77.4	72.6–81.5
Overall (87)	71.5	71.5	68.6–74.1

). Environmental disclosures averaged 61.8% (95% CI: 56.4–67.1), indicating that while more than half of the relevant indicators were reported, the coverage remains considerably lower than other dimensions. Economic indicators reached 65.9% (95% CI: 60.2–71.3), showing moderate consistency among companies. Social disclosures were highest at 77.2% (95% CI: 72.6–81.5), with a relatively narrow confidence interval, which suggests that reporting on employee, labor, and community-related issues is both more frequent and more homogeneous across the sector. Overall, the disclosure rate was 71.5% (95% CI: 68.6–74.1), confirming a broadly consistent reporting pattern among the 12 manufacturers analyzed. These results highlight a clear imbalance: while social aspects dominate corporate sustainability narratives, environmental disclosures remain weaker, a finding of particular importance given the increasing regulatory emphasis on climate- and environment-related transparency under the CSRD and ESRS.

When compared with European automotive sector trends, the Turkish sample demonstrates similar robustness in environmental reporting but significantly lags in areas like social disclosure. For instance, recent evidence from the European Union shows that country- and firm-level determinants critically influence SDG reporting practices, especially in governance and socially oriented indicators [51]. Furthermore, differences in institutional contexts have been shown to result in contrasting SDG disclosure patterns across regions, underscoring the importance of both regulatory frameworks and organizational commitment [52]. At the global level, comprehensive reviews highlight that integrating SDG reporting into corporate strategies not only improves transparency but also enhances strategic positioning in sustainability-conscious markets [53]. These findings collectively suggest that Turkish automotive firms could benefit from adopting a more balanced disclosure approach, incorporating both environmental and social indicators to align more effectively with international best practices.

Further,

Table 6. Alignment of the GRI metrics with SDGs and targets.

Goal/s Covered		Target/s Covered	Sustainability KPI			Manufacturer/s
			Economic	Environmental	Social
G3	Good Health and Well-Being	3.6	E19	V21		M1–M12
G4	Quality education	4.4			S6, S11, S21, S22, S23, S24	M1–M12
		4.5	E10		S3, S16	M1–M12
		4.7			S25, S38	M2, M6, M7, M8, M9, M10, M12
G5	Gender equality	5.1	E10		S3	M1, M3, M4, M5, M6, M7, M8, M9, M10, M11, M12
		5.5	E10		S16	M2–M12
G6	Clean water and sanitation	6.3		V4, V6, V12, V14		M1–M12
		6.4		V6, V11, V12, V14		M1–M12
G7	Affordable and clean energy	7.2, 7.3	E15	V1, V8, V23		M1–M12
		7.a	E15			M1, M3, M4, M5, M6, M7, M8, M9, M10, M11, M12
		7.b	E15, E19			M1–M12
G8	Decent work and economic growth	8.2	E1, E2, E3, E4, E6, E15, E19			M1–M12
		8.3	E7, E19			M1–M12
		8.5	E7, E10		S14, S16, S33, S34, S35	M1–M12
		8.6			S14	M4, M5, M6, M7, M8, M9, M10, M11, M12
		8.7			S10	M2, M3, M5, M6, M7, M8, M9, M10, M11, M12
		8.8			S2, S20, S28	M1–M12
G9	Industry, innovation and infrastructure	9.2	E7		S25, S38	M2, M6, M7, M8, M9, M10, M12,
		9.4		V2, V3		M1–M12
		9.5	E19			M1–M12
		9.b	E19			M1–M12
G10	Reduced inequalities	10.2	E7, E10		S32	M1–M12
		10.3	E7, E10			M1–M12
		10.4	E7		S9, S37	M1–M12
G11	Sustainable cities and communities	11.6		V4, V6, V7, V17		M1–M12
G12	Responsible production and consumption	12.2		V1, V8, V18		M1–M12
		12.4		V1, V8, V18		M1–M12
		12.5		V4, V14		M1–M12
		12.6		V25	S38	M2–M12
G13	Climate action	13.2		V2, V3, V5, V9, V16		M1–M12
G16	Peace, justice and strong institutions	16.5			S4	M2–M12
goals covered: 12		targets covered: 32	Economic KPI: 9	Environment KPI:18	Social KPI: 10
			Sustainability KPI: 37

shows that the Key Performance Indicators (KPIs) derived from the GRI disclosures collectively cover 32 SDG targets across 12 SDGs. However, certain targets are linked exclusively to indicators from a single sustainability dimension or, at most, two dimensions. Additionally, some indicators (e.g., S16, E10) appear multiple times in the mapping, reflecting the fact that a single GRI metric may correspond to multiple SDG targets or goals.

This multiplicity enables the construction of a coverage matrix that identifies the minimum combination of indicators necessary to achieve comprehensive coverage of all mapped SDG targets, thereby providing a practical basis for evaluating reporting completeness and prioritizing indicator selection in future sustainability disclosures.

Given the existence of multiple possible solutions, the selection process was guided by specific criteria. First, any target covered by a single GRI metric was automatically included in the solution. Second, GRI metrics that exactly matched those defined in the SDGs—six in total—were retained, as they measure the same concepts. Finally, for groups of metrics deemed to hold equal importance, the metric appearing most frequently across the seven GRI reports examined in this study was selected. In this context, the “importance” of a metric is defined by the number of SDG targets it addresses.

5.2. Alignment of the GRI Metrics with SDGs and Targets

This study examines the extent to which the economic, environmental, and social sustainability indicators (Key Performance Indicators—KPIs) reported by 12 automotive manufacturers operating in Turkey align with the SDGs and their corresponding targets.

The analysis reveals that a total of 12 SDGs are addressed across 32 specific targets, supported by 37 distinct KPIs identified within the sustainability reports of the selected manufacturers. These KPIs are categorized as follows:

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24.3% economic;

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48.6% environmental;

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27% social.

This distribution highlights a strong emphasis on environmental sustainability, indicating that automotive manufacturers in Turkey prioritize environmental responsibilities more heavily than economic or social dimensions.

Table 6 presents the outcomes of the SDG–GRI linkage analysis, identifying the specific indicators from Table 1, Table 2 and Table 3 that are mapped to corresponding SDGs and targets. The complete set of goal–target associations for each indicator is provided in the Supplementary Materials for transparency and reproducibility. Some targets are aligned with metrics from one or, at most, two sustainability dimensions. Certain metrics are repeated (e.g., S38; E19), indicating that a single metric can be associated with multiple goals or targets. This situation enables the construction of a coverage table that identifies the minimum combination of metrics required to cover all targets. Given the existence of multiple possible solutions, the adopted approach followed these steps:

-

When a target is addressed by only one GRI metric, that metric is necessarily included in the solution.

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GRI metrics that overlap with (i.e., are identical to) those defined in the SDGs were retained, as they measure the same concepts.

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In cases where a group of metrics holds equal importance, the metric most frequently reported across the 12 GRI reports analyzed was preserved. Here, the concept of a metric’s “importance” is defined as the number of targets covered by each GRI KPI.

The strong positive correlations observed between metric disclosure rates and SDG target coverage in this study align with prior empirical evidence [54,55], suggesting that expanding the breadth of disclosures—especially in underreported social dimensions—can substantially improve SDG alignment. This highlights the strategic importance of adopting integrated reporting frameworks that explicitly map KPIs to multiple SDGs and targets.

Table 7. Sustainability drivers KPIs.

SDKPI	Goal/s	Target/s	# Goals	# Targets	# Times
E19	G3, G9	3.6, 9.5, 9.b	3	4	12
V4	G6, G11, G12	6.3, 11.6, 12.5	3	3	11
E15	G7	7.2, 7.3, 7.a, 7.b	2	6	10
E7	G8, G10	8.3, 10.2, 10.3, 10.4	2	4	12
V1	G7, G12	7.2, 7.3, 12.2, 12.4	2	4	12
S3	G4, G5	4.5, 5.1	2	2	11
V2/V3	G9, G13	9.4, 13.2	2	2	12
E1	G8	8.2	1	1	12
S10	G8	8.7	1	1	10
S6/S11	G4	4.4	1	1	11
S16	G5	5.5	1	1	11
S2/S27	G8	8.8	1	1	12
S38	G12	11.6	1	1	7
S4	G16	16.5	1	1	11
S14	G8	8.5	1	1	9
V11/V6	G6	6.4	1	1	12

synthesizes the Sustainability-Driven Key Performance Indicators (SDKPIs) and the direct SDGs and targets they address, offering a consolidated view of their coverage significance. This summary enables the assessment of each SDKPI’s relative contribution to the breadth of SDG coverage and facilitates the identification of high-leverage indicators for strategic sustainability reporting.

Based on the analysis of the examined sustainability reports, automobile manufacturers disclose sustainability-related information through a defined set of Sustainability-Driven Key Performance Indicators (SDKPIs), distributed across the three dimensions of sustainability:

• Economic dimension: 4 indicators—E7, E19, E15, and E1—collectively contribute to the coverage of 5 distinct SDGs and 12 associated targets.
• Environmental dimension: 5 indicators—V4, V1, V2, V3, and V6—address 6 SDGs and 10 corresponding targets.
• Social dimension: 8 indicators—S38, S3, S6, S16, S14, S10, S2, and S4—are aligned with 6 SDGs and 10 relevant targets (Figure 2).

This distribution underscores the multi-dimensional contribution of manufacturers’ disclosures to the 2030 Agenda, with each sustainability pillar demonstrating varying degrees of goal–target coverage and thematic emphasis. Such differentiation is critical for assessing reporting completeness and identifying priority areas for enhanced disclosure alignment with the SDGs.

Approximately 50% of the selected KPIs are environmental indicators (e.g., V1, V2, V3, V4, V6, V11), confirming the sector’s emphasis on environmental stewardship. Among the environmental indicators, V9, V10, V19, V20, and V21 emerged as the least frequently reported metrics in the sustainability reports of Turkish automotive manufacturers. These indicators are often associated with advanced sustainability dimensions such as material circularity, biodiversity preservation, environmental remediation, and life cycle environmental costs—areas typically aligned with G12, G13 and G15. Their limited presence in corporate disclosures indicates a potential misalignment between reporting practices and the holistic environmental vision promoted by the SDGs.

This underrepresentation can be attributed to multiple factors: the absence of clear regulatory requirements for such detailed metrics, a lack of standardized methodologies for measurement, and limited data collection infrastructure in firms. Furthermore, these indicators often require forward-looking assessments, interdisciplinary input, and sector-specific expertise, which may not be readily available across all firms. As a result, while more commonly reported indicators (e.g., GHG emissions or energy use) align well with existing compliance frameworks (e.g., G13 and G7), the nuanced environmental dimensions represented by these lesser-reported metrics remain underdeveloped in practice.

This discrepancy highlights a gap in environmental reporting maturity and points to the need for expanding disclosure frameworks to include indicators that reflect long-term ecological impacts. Integrating such metrics into standard reporting practices would strengthen corporate alignment with global sustainability targets, support sectoral contributions to the SDGs, and enhance transparency around resource efficiency, ecosystem integrity, and environmental restoration efforts.

Analysis of social indicators reveals that metrics such as S3 and S16, which address gender equality and decent work, are widely reported by all manufacturers, indicating a sector-wide commitment to these two social metrics. Nevertheless, other socially oriented KPIs, including S23, S25, and S31, are both quantitatively limited and reported at notably lower frequencies. These indicators often address qualitative dimensions such as social justice, employee well-being, and stakeholder engagement. Their limited disclosure may stem from challenges related to data availability, measurement difficulties, or a lack of strategic prioritization within firms.

This uneven distribution underscores a fragmented sustainability reporting landscape in which environmental and economic aspects receive structured and extensive coverage, while social and governance-related dimensions remain comparatively underrepresented. To enhance the comprehensiveness of sustainability disclosure, a more balanced integration of all three ESG pillars—particularly the social dimension—is essential.

Furthermore, the low reporting frequency of economic metrics such as E11, E12, and E13 underscores a gap in the coverage of advanced financial and strategic indicators. These metrics typically capture critical aspects such as profitability ratios, economic value added, and innovation investments. Their limited disclosure may stem from insufficient data collection practices or a reluctance to share such sensitive information within the context of voluntary sustainability reporting. This pattern highlights a broader lack of holistic integration in corporate sustainability disclosures. For sustainability to be meaningfully assessed, it must encompass economic performance alongside environmental and social dimensions. Enhanced reporting of financial sustainability indicators—particularly E11, E12, and E13—would contribute to greater transparency and provide deeper insights into firms’ long-term value creation potential and strategic resilience.

G8 emerges as the most represented SDG, with seven distinct SDKPIs linked to multiple targets, highlighting the automotive sector’s strong emphasis on labor practices, economic performance, and employment generation. Similarly, G12 and G7 are well covered through indicators such as E15, V1, and V4, reflecting the sector’s engagement with circular economy strategies and energy transition initiatives. These results reflect the sector’s particular focus on employment, production processes, and energy efficiency, which are intrinsic to the automotive industry’s sustainability strategy.

In contrast, G 16 and G13 are each represented by only one SDKPI (S4 and V5, respectively), indicating limited sectoral focus on governance, institutional transparency, and climate-related actions. This distribution suggests that the Turkish automotive sector primarily prioritizes operational areas—such as production efficiency, economic output, and environmental performance—while governance and ethical dimensions remain underrepresented.

Among the SDKPIs, E15 stands out as the most comprehensive, aligning with six different targets under both G 7 and G 12. This reflects a strong alignment with key sustainability issues such as clean energy use, energy efficiency, and responsible consumption. E19 also demonstrates multidimensional coverage, linking to four targets across Goals 3, 8, and 9, which span public health, innovation, and economic development.

Moreover, G15 and G17 were not addressed by any of the selected SDKPIs, suggesting blind spots in sectoral sustainability engagement. For G 15 (Life on Land), outcome-oriented indicators in the automotive sector could include the percentage of deforestation-free sourcing across critical raw materials such as leather and natural rubber, verified against international frameworks; net biodiversity gain (NBG) expressed in hectares or as a percentage relative to baseline habitat conditions in production sites and sourcing landscapes; and corporate nature-impact intensity, such as ecosystem-service loss per unit of revenue or per vehicle [56]. In addition, restoration outcomes (hectares restored or percentage of affected areas restored to a defined ecological threshold) in sourcing regions and near production facilities can be directly mapped to G 15 targets.

For G 17 (Partnerships for the Goals), sector-relevant outcome indicators include the number of formal multi-stakeholder sustainability partnerships established in the automotive sector, the amount of funding mobilized for sustainable mobility initiatives, and capacity-building outcomes among SME suppliers—such as the percentage demonstrating verified performance improvements (e.g., emissions reduction, workplace safety rates) within 12 months of capacity programs [57]. Furthermore, the degree of interoperability of partnership reporting—measured by the percentage of initiatives using shared SDG taxonomies and reporting protocols—provides evidence of scaling and comparability.

The adoption of such outcome-oriented metrics would not only enhance the alignment of corporate reporting with global sustainability priorities but also improve comparability across firms, strengthen compliance with evolving EU frameworks such as CSRD and ESRS, and render the sector’s sustainability contributions more transparent and visible.

Similarly, for SDGs that remain insufficiently addressed—particularly SDG 5 (Gender Equality) and SDG 16 (Peace, Justice, and Strong Institutions)—the reporting of outcome-oriented indicators is of critical importance. For SDG 5, metrics such as the proportion of women in management positions, the median gender pay gap, and the retention differential between male and female leaders can provide robust evidence of gender equality outcomes. For SDG 16, indicators including the number and resolution rate of confirmed corruption cases, the average closure time of whistleblowing reports, and verified supplier compliance with anti-bribery standards can serve as direct measures of institutional integrity and accountability. Collectively, the incorporation of such outcome-based indicators would substantially strengthen the alignment of corporate reporting with the SDGs, enhance cross-firm comparability, and support compliance with evolving regulatory frameworks such as the CSRD and ESRS [58,59].

V1 and E7 provide broader thematic integration, each aligning with four targets, while S14, S38, V23, and V25 are limited to a single target, highlighting their constrained strategic impact.

These findings indicate the need for more holistic and balanced sustainability reporting within the sector. Expanding coverage of underrepresented SDGs, particularly those tied to governance, climate action, and partnerships, alongside the adoption of standardized reporting mechanisms for social and ethical dimensions, would significantly strengthen the sector’s alignment with global sustainability priorities.

Adopting a global perspective, this study analyzes the selected SDKPIs within the context of the automotive manufacturing sector, as illustrated in Figure 3, focusing on their alignment with relevant SDGs and targets, as well as the frequency of their disclosure in GRI-based sustainability reports.

As illustrated in Figure 3, the analyzed SDKPIs exhibit distinct clustering patterns in terms of both their SDG coverage and reporting frequency. Three notable observations emerge from this analysis:

• Several high-coverage SDKPIs—most notably E1 and S10—are underreported in terms of their frequency of disclosure within the analyzed GRI reports, despite their strategic relevance for SDG alignment.
• Conversely, other high-coverage indicators, such as V1, V2, V3, S2, and E1, demonstrate widespread reporting, indicating strong adoption across manufacturers’ sustainability disclosures.
• A significant proportion of SDKPIs are reported either at a high frequency (e.g., E1, S2) or a medium frequency (e.g., S4, S6, S10, E15, S38), yet these indicators are each associated with only a single SDG and one target. This suggests a reporting emphasis on a limited thematic scope, which may constrain their overall contribution to broad SDG coverage.

5.3. Alignment with International Literature

Figure 4 illustrates the alignment between the frequency of SDKPI disclosure and their emphasis in scientific literature. Metrics with both high academic visibility and strong domestic reporting, such as energy consumption and CO₂ emissions, exhibit full alignment. However, indicators such as CSR and governance-related issues reveal a discrepancy between global academic interest and local reporting practice.

Indicators such as V1, V2, V3, and E1 exhibit high significance in both the academic literature and sectoral reporting practices, indicating a strong alignment between scholarly emphasis and corporate sustainability disclosures. In contrast, social and governance indicators such as S38, S10, S14, and S4 receive relatively lower attention in the literature and are also underreported in the industry, suggesting partial or weak alignment and highlighting persistent gaps in social and ethical dimensions of sustainability reporting. Interestingly, indicators such as E19, S6, and V6, although not prioritized as highly in the academic literature, are consistently and comprehensively reported by firms, reflecting strong institutional alignment and possibly sector-specific operational priorities. Finally, indicators like S16 and S4, which carry moderate-to-low academic emphasis, are also infrequently reported in practice. This pattern reveals a relative marginalization of social equity and governance themes, emphasizing the need for more balanced and inclusive sustainability disclosure frameworks.

5.4. Thematic Dimension Analysis

Table 8. Sustainability Dimension Distribution and SDG Coverage.

Metric	No. of SDKPIs	Total SDG Coverage	Key SDG Themes
Economic	5	12	SDG 8, 9
Environmental	6	15	SDG 7, 12, 13
Social	6	17	SDG 4, 5, 10, 16

categorizes the indicators across the three core sustainability dimensions and summarizes their cumulative SDG impact. While environmental and economic dimensions are robustly represented, social indicators, despite their broader SDG connections, suffer from relatively lower reporting frequency.

The distribution of Sustainable Development Key Performance Indicators (SDKPIs) across economic, environmental, and social dimensions indicates a relatively balanced representation in terms of the number of metrics, yet notable differences emerge in overall SDG coverage. The economic dimension, comprising 5 SDKPIs, addresses 12 SDG coverage points, with a primary focus on SDG 8 and SDG 9. While this reflects a strong alignment with productivity, innovation, and industrial competitiveness, the narrower thematic scope suggests a need to broaden economic indicators to encompass other relevant SDGs, such as responsible consumption or climate action, which are increasingly linked to economic resilience.

The environmental dimension features 6 SDKPIs with a total of 15 SDG coverage points, primarily aligned with SDG 7, SDG 12 and SDG 13. This demonstrates a clear emphasis on energy efficiency, resource management, and climate mitigation. However, the absence of coverage in biodiversity-related SDGs (e.g., SDG 14 or 15) highlights a potential gap in reporting on ecosystem protection within the environmental metrics.

The social dimension, also consisting of six SDKPIs, records the highest SDG coverage (17 points), encompassing a broad range of goals such as SDG 4, SDG 5, SDG 10, and SDG 16. This breadth reflects a strong orientation toward inclusivity, human capital development, and institutional governance. Nevertheless, the relatively higher coverage may also indicate thematic dispersion, where the inclusion of multiple social targets could dilute focus unless supported by robust, measurable indicators.

Overall, the data suggest that while the social dimension leads in SDG coverage breadth, the environmental dimension is more concentrated around energy and climate-related themes, and the economic dimension remains narrower in thematic scope. Achieving a more integrated and balanced approach across dimensions will require both expanding underrepresented thematic areas and enhancing the depth of reporting in the most frequently addressed SDGs. These results align with Glavo and Panko [60], who found that social indicators exhibit the highest breadth of SDG coverage within the automotive industry, reflecting their strategic relevance to inclusive and equitable development.

5.5. Regulatory Framework and Compliance Dynamics

The analysis of sustainability reporting in the automotive sector reveals several practical implications for firms in Türkiye. First, companies should enhance target-level reporting by adopting measurable and comparable KPIs, thereby moving beyond broad thematic disclosures. This will enable longitudinal performance assessment and support outcome-oriented sustainability performance. Second, integrating environmental, social, and governance indicators within a unified ESG–GRI–SDG framework can increase the strategic value of reporting and align corporate practices with inclusive development priorities. Third, greater emphasis should be placed on social justice, governance, and supply chain responsibility, which remain underrepresented compared to climate- and energy-related themes. In addition, firms are encouraged to incorporate forward-looking economic metrics—particularly those capturing long-term value creation and innovation capacity—to strengthen strategic resilience. To ensure credibility, sustainability reports should be subject to independent verification, thereby reducing the risks of selective disclosure and “greenwashing.” Finally, the adoption of a standardized SDG mapping protocol and the inclusion of SME suppliers in sustainability disclosure will enhance comparability across firms, strengthen supply chain transparency, and support compliance with EU regulations such as the CSRD, the EU Taxonomy, and the CBAM. Collectively, these measures have the potential to transform sustainability reporting in the Turkish automotive sector from a procedural exercise into a strategic tool for competitiveness and resilience in international markets.

With the entry into force of the Corporate Sustainability Reporting Directive (CSRD) in 2024, the European Union has significantly expanded the scope of sustainability reporting compared to the previous 2014/95/EU Directive. In line with this, the European Sustainability Reporting Standards (ESRS) have been introduced as mandatory reporting frameworks. Importantly, the CSRD not only applies to EU-based companies but also extends to non-EU entities with an annual turnover exceeding EUR 150 million within the EU, thereby directly affecting Turkish automotive exporters.

A comparison between GRI and ESRS highlights substantial methodological and scope-related differences. The GRI Standards, as a widely adopted voluntary global framework, provide flexibility for measuring and disclosing sustainability performance across sectors. In contrast, ESRS introduces the principle of double materiality—capturing both the outward environmental and social impacts of a company and the inward financial implications of these impacts—and requires more detailed, binding data points. Furthermore, ESRS mandates the disclosure of over 100 ESG indicators, a requirement that distinguishes it from GRI and enhances cross-sectoral comparability.

For the Turkish automotive sector, the implications of these new standards can be summarized in three key areas:

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Reporting obligations will now include Scope 3 emissions and circular economy indicators, which have previously been underreported.

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While existing GRI-based reporting practices provide a robust foundation for compliance, companies must restructure their methodologies, enhance data quality, and develop target-based performance metrics to align with ESRS.

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Compliance will not only ensure regulatory adherence but also strengthen investor confidence, enhance international competitiveness, and increase the visibility of sustainability strategies.

6. Conclusions

This analysis demonstrates that Turkish automotive manufacturers possess a sufficient indicator base to address all 12 SDGs and 32 associated targets relevant to their operations. The findings reveal that while the sector shows a relatively high formal alignment with the GRI Standards—averaging approximately 72% compliance with core disclosures—this alignment is often procedural rather than substantive. Most companies report on the required indicators; however, the level of detail and the presence of measurable linkages to the SDGs vary considerably. Based on the observed thematic and frequency coverage, disclosures tend to prioritize breadth over depth, limiting target-level clarity and comparability. A comprehensive assessment of disclosure depth, including data quality and longitudinal comparability, was beyond the scope of this study due to the absence of multi-year datasets.

The results confirm a predominant environmental focus, particularly on SDG 7 (Affordable and Clean Energy), SDG 12 (Responsible Consumption and Production), and SDG 13 (Climate Action). While commendable, this emphasis risks overshadowing social and governance dimensions. In particular, SDG 5 (Gender Equality) and SDG 16 (Peace, Justice, and Strong Institutions) are minimally addressed, with SDG 16 represented by only a single KPI (S4) and lacking quantitative evidence. Furthermore, SDG 15 (Life on Land) and SDG 17 (Partnerships for the Goals) are absent from current disclosures, indicating blind spots in sectoral sustainability engagement.

Economic indicators show mixed performance. While frequently reported KPIs such as E7, E15, and E19 demonstrate broad thematic integration, advanced economic metrics (E11, E12, E13) that capture long-term value creation, profitability, and innovation investments remain underreported. This limits the ability to assess the sector’s strategic resilience and economic sustainability. Similarly, social indicators such as S23, S25, and S31—linked to social justice, employee well-being, and stakeholder engagement—are reported inconsistently, reflecting a fragmented approach to the social pillar. Many disclosures lack target-level clarity, and certain targets (e.g., 4.7, 16.5) are addressed by only a small subset of manufacturers, reinforcing the breadth-over-depth observation.

The novelty of this research lies in the application of the SDKPI framework to systematically map GRI-based indicators to SDGs and targets within the Turkish automotive sector—a context largely underexplored in previous studies. By demonstrating that 17 SDKPIs can ensure coverage of 12 goals and 32 targets, this study provides a replicable methodology that can be extended to other industrial sectors. This approach contributes both theoretically, by extending sustainability accounting scholarship with a replicable indicator-based framework, and practically, by highlighting disclosure blind spots—particularly in governance (SDG 16), gender equality (SDG 5), biodiversity (SDG 15), and partnerships (SDG 17)—that require urgent managerial and policy attention.

To strengthen alignment with the SDGs and enhance the strategic value of sustainability reporting, the sector should:

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Expand coverage to underrepresented goals, especially those related to governance, biodiversity, and global partnerships.

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Increase the detail and measurability of reporting by providing quantitative, target-based, and comparable data.

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Integrate advanced economic metrics to capture financial and strategic sustainability alongside environmental performance.

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Standardize SDG target mapping to ensure comparability across companies and over time.

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Ensure independent verification of reports to reduce risks of selective disclosure and greenwashing.

Nevertheless, some limitations must be acknowledged. The analysis relied exclusively on publicly available sustainability reports, constraining the depth of evaluation due to the absence of longitudinal datasets and firm-level validation. Variations in reporting formats and languages may also have introduced bias. Moreover, the study assessed disclosure content rather than actual performance outcomes, meaning that results reflect what companies chose to report rather than their full sustainability practices. In particular, the limited disclosure of Scope 3 emissions illustrates a critical blind spot: these indicators are methodologically complex to measure, require extensive supply chain data, and often depend on assumptions about upstream and downstream activities.

Future research on sustainability reporting in the automotive sector should adopt longitudinal approaches to capture temporal dynamics in disclosure practices, particularly in response to regulatory changes such as the CSRD and ESRS, while also extending the analysis across different industries and countries to assess sectoral and cultural variations. Integrating external and independent data sources, including ESG ratings, CDP disclosures, and satellite-based monitoring, would enhance the robustness of findings and mitigate biases associated with self-reported data. In addition, advanced analytical methods such as structural equation modeling or system dynamics could be employed to examine the causal mechanisms and interdependencies among ESG indicators, SDKPIs, and SDG outcomes. The use of emerging technologies, including machine learning, natural language processing, and blockchain, presents further opportunities for automating KPI extraction, improving transparency, and reducing risks of selective disclosure. Future studies should also emphasize stakeholder perspectives, exploring how employees, communities, and regulators perceive KPI–SDG linkages and how these perceptions influence legitimacy and governance outcomes. Finally, more granular mapping of KPIs to SDG targets and sub-targets is recommended to uncover redundancies, overlaps, and blind spots, thereby supporting the development of sector-specific disclosure taxonomies and interoperable reporting protocols.

In conclusion, this study advances sustainability accounting research by operationalizing the SDKPI framework and applying it to the Turkish automotive industry. The findings underscore the importance of moving from procedural compliance toward substantive sustainability performance through robust, measurable, and thematically balanced disclosures. Achieving such a transition will not only strengthen corporate alignment with the SDGs but also enhance the sector’s strategic resilience and long-term value creation. Ultimately, harmonizing reporting practices—potentially through the development of a GRI sector program for the automotive industry—could represent a pivotal step toward fostering transparency, comparability, and the visibility of sustainability efforts across the sector.