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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue III, March 2026

Leveraging Text Analytics to Evaluate ESG Metrics' Influence on

Corporate Sustainability Frameworks

Dhirendra Kumar Jena*

Dept. Of MBA, Balasore College of Engineering & Technology, Sergarh, Balasore, Odisha

*Corresponding Author

DOI:

https://doi.org/10.51583/IJLTEMAS.2026.150300083

Received: 27 March 2026; Accepted: 02 April 2026; Published: 17 April 2026

ABSTRACT

Companies achieving sustainable business practices through Environmental Social and Governance (ESG)

metrics integration now drive transparency and stakeholder involvement effectively. Electing qualitative

research methods allows this investigation to study ESG metrics' effects on corporate sustainability strategy

development through text analysis performed using both Latent Dirichlet Allocation (LDA) and Correspondence

Analysis (CA) on ESG reports, regulatory texts, and academic publications. ESG metrics demonstrate essential

importance in both corporate governance structures and regulatory conformity, as well as stakeholder

commitment and financial planning applications. Future sustainability trends, together with corporate

accountability, social impacts, and risk management, formed ten main themes that emerged from this analysis.

The remaining themes were environmental practices with credibility, ESG reporting standardization, strategic

ESG initiatives, and ESG disclosure communication and investor influence, followed by regulatory compliance

and climate risk management and financial reporting with ESG risk analysis. The research objectives align well

with the identified themes according to thematic mapping and CA results, which together create an extensive

framework for ESG metric assessment in corporate sustainability strategies. A thorough analysis demonstrates

that organizations must prioritize disclosure of ESG metrics together with sound governance systems while

allowing investors to play a role and follow regulations in order to advance sustainability. Corporate decision-

makers need to understand the essential implications that emerge from these findings because they demonstrate

why structured ESG implementation methods are vital. Research must continue to analyze the developing ESG

reporting environment and emerging regulatory changes and technological advancements that improve corporate

accountability and governance transparency.

Keywords: ESG metrics, Corporate sustainability strategies, ESG reporting, Regulatory compliance, Text

analytics, Text analysis, Text mining

INTRODUCTION

Businesses use Environmental Social Governance (ESG) metrics to develop sustainable strategies because

environmental challenges meet social responsibility standards, and governance requires strict oversight. ESG

metrics function as essential indicators to evaluate corporate effectiveness, and they affect investor faith and

regulatory needs while promoting extended worth creation. The integration of ESG principles into corporate

decision-making represents both a strategic corporate requirement and a powerful mechanism to accomplish

sustainable ethical business expansion.

Multiple theoretical models have directed academic studies about ESG metrics affecting corporate sustainability

approaches. Stakeholder theory (Freeman, 1984) reinforced business accountability by revealing shareholders

were accompanied by multiple stakeholder groups such as employees, customers, regulators, and communities,

thus leading to ESG integration in corporate decision-making. According to legitimacy theory (Suchman, 1995),

organizations chose ESG practices because they needed to match societal expectations, boost transparency, and

maintain public trust, especially when facing regulatory oversight. Organizations adopt ESG norms through

institutional pressures, which include coercive, mimetic, and normative elements to secure future sustainability

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and market leadership. Resource-based view (RBV) theory (Barney, 1991) demonstrated that ESG practices

operate as strategic assets because they generate distinctive capabilities, which include better brand reputation,

stronger risk management, and increased stakeholder devotion. Through the Signaling theory (Spence, 1973),

firms disclosed ESG information to demonstrate their dedication to sustainability, which helped them obtain

investors while decreasing market financial uncertainty. The merger of various theories highlights the essential

role that ESG metrics play in developing sustainability strategies and increasing business survivability while

generating lasting value.

ESG reporting systems started to receive increased oversight from regulators as different jurisdictions adopted

standardized reporting methods. The Corporate Sustainability Reporting Directive (CSRD) of the EU, together

with the International Sustainability Standards Board (ISSB), established formatted reporting conditions that

drive ESG reporting compliance (Shakeri, 2025; Bruhati, 2024). The implementation of AI with blockchain

technologies developed proper ESG data acquisition methods, which produced accurate results while providing

more transparency between companies and investors (Iris Business, 2025). ESG metrics became complicated

because rating providers did not use standardized criteria, which resulted in inconsistent evaluation methods

(McKinsey, n.d.). Businesses faced the dual task of meeting stakeholder needs alongside regulatory compliance

requirements as one of their major hurdles (Greenmyna, 2024). The collection and quality maintenance of ESG

data remained problematic because well-organized reporting platforms were not available to guarantee accurate

data consistency (Greenmyna, 2024). The enforcement of ESG regulations presented a major challenge for

businesses because they needed to adjust their operations to complex evolving rules, which required extensive

time and financial investments (Bedford Consulting, 2023).

ESG metrics have become increasingly important globally for companies, yet organizations face substantial

difficulties when it comes to incorporating them into operational decision-making. The goal of ESG frameworks

is to increase clear reporting, sustainable operations, and long-term performance, but measurement standards

alongside data reliability and compliance requirements act as barriers to complete implementation. Numerous

companies encounter difficulties in linking ESG reporting to their strategic sustainability goals because they face

challenges, including greenwashing stakeholder doubts and regulatory differences. The absence of a

standardized ESG measure leads to different opinions about corporate sustainability performance, which makes

it hard for investors and policymakers to determine the effectiveness of sustainable impact measures. This

research investigates the degree to which ESG metrics impact business sustainability approaches together with

executive choices and sustainable value generation because regulators, investors, and consumers demand real

ESG commitments from companies. This study works to solve these obstacles in order to offer business insights

about ESG metrics as strategic sustainability tools and risk management instruments and competitive advantages

that lead to both academic understanding and corporate governance enhancements.

Objective of the study

Following are objectives of the study

 To explore ESG metrics in corporate sustainability strategies using text analytics.

 To analyze stakeholder narratives on ESG decisions through text analysis.

 To investigate regulatory challenges in ESG reporting using text mining.

 To examine technological innovation in ESG-related corporate communications.

 To develop a framework for assessing ESG metrics from textual data.

Studies connected to ESG metrics and their effects on corporate sustainability planning require in-depth

knowledge about current standards, together with emerging patterns and operational obstacles. The research

must establish its position within academic and industry discussions about ESG reporting, qualitative data

analysis, and corporate decision-making because text analytics tools increasingly process sustainability

disclosures and stakeholder and regulatory texts. A literature review analyzes fundamental theoretical bases and

existing investigations regarding ESG execution methods and evaluation, as well as technological advancements

in sustainability research assessment. The review provides an essential theoretical background that helps

contextualize the exploratory design of the study and directs both the identification of research gaps and the

development of the methodology.

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LITERATURE REVIEW

ESG metrics serve as vital aspects of corporate sustainability reports because they allow organizations to show

their sustainable business practices and accountability, foster transparency to regulators and investors, and help

manage operational risks (Suttipun et al., 2025). Standardization issues persist, along with accuracy and

comparability difficulties when it comes to ESG disclosures, because ESG reporting does not have a globally

standardized framework like financial reporting standards like GAAP or IFRS (Rahman et al., 2025).

The global disclosure frameworks GRI, TCFD, and ESRS have developed to increase consistency, yet structural

differences among them continue to be a critical issue, according to Magli and Amaduzzi (2025). ESG metrics

provide sustainability benchmarks through which organizations measure their performance in environmental

aspects and social factors and governance elements that include board composition and anti-corruption measures

(Suttipun et al., 2025). ESG metrics, which appear in corporate sustainability reports, establish both investor

transparency and ethical interest through the rising utilization of blockchain technology in preventing

greenwashing and validating ESG disclosure contents (Emmanuel, 2025).

Evidence indicates that organizations with higher ESG scores receive increased sustainable investor interest

while lowering their risk profile (Suta et al., 2025). Strategic ESG reporting enables organizations to achieve

better internal control systems, which concurrently enhances financial governance and speeds up the completion

of audit reports (Jizi & Thomas, 2025). The EU's CSRD regulation, together with similar rules like the CSRD,

force companies to reveal sustainability-related risks while presenting opportunities resulting in advanced and

transparent disclosure practices (Rana et al., 2025; Jarboui et al., 2025).

Future ESG reporting will incorporate NLP and AI methodologies for better data evaluation. At the same time,

fintech solutions will help standardize datasets and expand their accessibility (Roy & Vasa, 2025; Sahu & Debata,

2025). Companies need standard ESG reporting criteria to improve both corporate responsibility and sustainable

business practices despite the advancement of ESG disclosures toward transparency and compliance objectives.

ESG metrics function as essential elements in corporate sustainability reports to show sustainable business

practice dedication as well as transparency and accountability while providing vital risk management tools for

companies and investors and regulatory compliance frameworks (Suttipun et al., 2025). Many experts debate the

accuracy and standardization issues of ESG reporting because it operates without a standard framework like

financial reporting systems that utilize GAAP or IFRS (Rahman et al., 2025). The GRI TCF, D, and ESRS

frameworks serve as global ESG disclosure systems that resolve the current reporting issues while enhancing

comparability between companies (Magli & Amaduzzi, 2025).

The ESG metrics serve as performance evaluation standards for sustainability assessments, which combine

environmental results with social practices alongside governance systems (Suttipun et al., 2025). Companies add

sustainability metrics to their reports for better transparency and earn ethical investors through enhanced

disclosure reliability by using blockchain technology, which reduces potential greenwashing occurrences

(Emmanuel, 2025). Studies show that that ESG disclosure activities produce positive financial outcomes because

organizations that display superior ESG performance records deliver better return on assets (ROA) together with

enhanced stock market performance (Suta et al., 2025). Sustainability reporting enhances financial governance

systems and establishes strong internal controls, which shortens audit reporting periods, leading to higher

organizational transparency (Jizi & Thomas, 2025).

International governments perform stringent sustainability reporting requirements which alter ESG disclosures

through mandates like the EU's CSRD that compel businesses to reveal sustainability-based risks and

opportunities, thus resulting in more exposed and transparent reporting (Rana et al., 2025; Jarboui et al., 2025).

The upcoming era of ESG reporting will receive its direction from AI and NLP-enabled data analysis systems

combined with fintech improvements for data consistency and better analytics of climate risks across

organizations (Roy & Vasa, 2025; Sahu & Debata, 2025).

Businesses now make ESG strategies fundamental to their corporate stories because these strategies help

improve their reputation while reducing risks and generating lasting economic value (Jamil & Wahyuni, 2024).

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ESG narratives center on transparency and accountability because organizations use direct sustainability

communication to show their goals and performance measurements and risk evaluations to build trust and

credibility (Whelan, Eckerle, & Tomlinson, 2020). The practice of clear ESG disclosure creates trust with

investors and social groups by fighting against greenwashing practices (Jamil & Wahyuni, 2024). The discussion

on ESG emphasizes risk management and organizational resilience through which companies use their ESG

initiatives to face financial, rational, and reputational threats, particularly when dealing with climate-related

financial risks (Biswas, Das, & Mitra, 2024).

Firms that implement properly organized ESG strategies demonstrate better financial performance, which

indicates that ESG compliance operates as both a regulatory obligation and a performance-enhancing element

(Rana et al., 2024). The theme of ESG-driven innovation emphasizes the business use of ESG principles to create

sustainable financial approaches with green tech and moral supply chains that boost operational outcomes while

setting organizations apart from the competition and attracting investors (Bonfanti, 2024; Sahu & Debata, 2025).

Stakeholder engagement, along with social responsibility, operate as essential components of ESG narratives

through which businesses present sustainability initiatives as joint projects that generate shared worth for

workers, customers, investors, and local communities (Ani & Solissa, 2024).

Many companies exhibit Corporate Social Responsibility (CSR) initiatives with diversity, equity and inclusion

programs which they showcase through their ESG commitments (Wang & Phillips-Fein, 2023). ESG disclosure

frameworks like the Global Reporting Initiative (GRI) and Task Force on Climate-related Financial Disclosures

(TCFD), together with European Sustainability Reporting Standards (ESRS), receive top priority from

companies within regulatory compliance (Jang & Kang, 2023). ESG strategies receive mostly positive attention,

but ongoing challenges like greenwashing and ESG doubt exist, and certain businesses encounter criticism for

empty ESG statements (Jamil & Wahyuni, 2024). Unjustified ESG statements threaten corporate trustworthiness,

thus prompting regulators to monitor companies, which requires companies to implement transparent ESG

reporting systems that maintain stakeholder honesty (Tan et al., 2025).

Corporate communications now focus on ESG initiatives because companies use stakeholder perceptions to

build reputation while linking sustainability and ethical governance to their strategies (McCall, 2024).

Stakeholder trust relies heavily on transparent ESG reporting because it enables public disclosure verification to

prevent sustainability-related skepticism and avoid or reduce misrepresentation of environmental efforts

(Usman, 2024). Some organizations present their ESG successes to the public but conceal their difficulties,

which creates credibility gaps (Casalegno, Chiaudano, & Tamiazzo, 2024). The ESG initiatives of companies

receive distinct interpretations from investors who assess them as risk management while consumers focus on

ESG messaging and social-environmental outcomes (Koch, 2025; Hartwig, 2024). Strong ESG credentials

enable firms to draw sustainable investments because ESG factors have become important factors in financial

decision-making, according to Beckert & Koch (2025).

Social platforms have become essential for ESG communication because companies can use them to connect

with stakeholders, deliver updates, and address concerns; interactive ESG content on these platforms enhances

brand support and organizational responsibility (Sung, Tao, & Lee, 2025). The failure of influencer partnerships

to match corporate ESG principles creates enduring risks of misinformation, which frequently results in

stakeholder backlash, according to Zhang, Xu, and Chen (2024). ESG communication influences internal

stakeholders through effective messaging, which improves employee commitment and business partnership

commitment (Theron, Cant, & Wiid, 2024).

The perception of ESG initiatives remains uncertain because these programs seem superficial or do not match

company policies, particularly in terms of diversity and inclusion (Moyeen & Mehjabeen, 2024). The rising

focus on ESG reporting creates obstacles for companies to connect with multiple stakeholders, including

emerging market participants, because ESG messages are viewed as deceptive public relations instead of

authentic sustainability promises (Badr, Ibrahim, & Hussainey, 2024; Dadhich & Saini, 2024). The solution lies

in businesses needing to prove their tangible ESG advancement with sustained sustainability messaging since

this creates enduring trust from their stakeholders.

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ESG commitments now form the core element of sustainability narratives that direct business interactions with

stakeholders who participate in shaping corporate strategy development and stakeholder perception (Ahmaro,

Aljebrini, & Dogruyol, 2025). ESG discourse puts continuous emphasis on transparency and trust because

stakeholders need to verify ESG information in order to understand corporate sustainability initiatives

effectively, and data-driven transparency enhances stakeholder confidence (McCall, 2024; Junaedi, 2024).

Through social media, companies can now spread information quickly while molding public discussions about

ESG topics, but such practices create potential reputational hazards when corporate ESG statements do not match

actual operational results (Jayadatta, 2023; Zhang, Xu, & Chen, 2024). The discussion about ESG relies heavily

on ethical standards and corporate responsibility because stakeholders push for standardized reporting to

maintain ethical conduct while impact investors evaluate corporate legitimacy through ESG dialogue (Yunus &

Nanda, 2024; Lehner & Harrer, 2019).

Employee and social activist groups now recognize diversity equity and inclusion (DEI) as a vital ESG

commitment component because they want ESG strategies to contain DEI principles to build inclusive workplace

environments (Amanifar & Rahat, 2024). Stakeholders form their opinions about ESG commitments based on

evolving regulatory frameworks as companies modify their strategies to comply with changing standards,

according to Nielsen & Villadsen, 2023, and Mbhalati and Masehela, 2024. Businesses encounter substantial

difficulties from greenwashing when their sustainability promises do not match real operations, which leads

stakeholders to distrust them. This problem shows how important it is for companies to showcase ESG

performance through tangible verified actions to gain public confidence (Crosby, 2024).

ESG information disclosure has become mandatory for companies through regulation, but organizations face

difficulties stemming from inconsistent ESG standards and changing rules, as well as the challenges of text

analysis when producing ESG reports (Suta et al., 2025). Organizations face various regulatory requirements

that include GRI reporting TCF, D guidelines, and ESRS standards, which cause ESG disclosure inconsistencies

(Amanifar & Rahat, 2024). Businesses within the Central and Eastern European region experience difficulties

meeting ESRS standards because text analytics reported numerous shortcomings in sustainability disclosure,

according to Suta et al. (2025). ESG reports face two main compliance challenges:e complicated language that

creates barriers to understanding between stakeholders, and some sustainability statements are vague enough to

risk being classified as greenwashing (Parfentieva, 2024).

The evaluation of ESG disclosure clarity heavily depends on text analysis because many companies do not

supply measurable indicators to support their sustainability promises (Amanifar & Rahat, 2024). Sentiment

analysis enables ESG disclosure assessment by identifying optimistic statements that attract regulatory attention

and neutral language in mandatory reports that promote better compliance acceptance (Suta et al., 2025). ESG

data verification represents a key problem because many reports lack either independent audits or external

verification checks, which makes text analysis powered by AI essential to finding inconsistent findings while

enhancing report reliability (Amanifar & Rahat, 2024).

Companies solve ESG compliance problems by adopting automated text analysis and natural language

processing tools, enabling them to monitor compliance and create better readings of ESG material and

regulatory-aligned messaging, according to Parfentieva (2024). The accuracy of ESG claims is enhanced by the

application of AI-driven data validation technology, which guarantees that sustainable corporate reports meet

current compliance requirements (Suta et al., 2025).

The high demand from stakeholders for transparent ESG information has driven companies to use AI with big

data analytics and blockchain, as well as digital platforms to improve their sustainability report transparency,

according to Magli and Amaduzzi (2025). AI and big data analytics systems help improve ESG reporting through

instant data collection and emotional analysis and sustainability report inconsistency detection, which results in

better disclosure reliability and consistency (Li & Zhang, 2024; Faccia & Petratos, 2024). Blockchain technology

represents a crucial instrument that verifies ESG data by establishing immovable records while stopping data

tampering to enhance business reputation through "GPT4ESG" and its related AI-based blockchain model

(Makridis, Beck, & Louca, 2025; Lin et al., 2024). Through digital communication of ESG metrics, stakeholders

now engage with companies through corporate sites and social media platforms as well as interactive dashboards,

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which improves regulatory compliance and ensures transparency, according to Carabelli (2025) and Dathe

(2024). AI and automated systems for ESG monitoring help businesses monitor regulatory changes while

ensuring global reporting standards, thus reducing compliance risks and enhancing transparency (Rajput,

Sharma, & Garg, 2024; Chen, 2024). Green innovation represents a major technological advancement in ESG

disclosures because it allows companies to use digitalization to incorporate green technologies into their ESG

strategies, which strengthens their environmental commitments while drawing investors who invest in

sustainable and social responsibility (Ijomah et al., 2024; Nodhiva et al., 2024). ESG data integrity will continue

to benefit from advancing technological solutions as regulatory developments occur, thus creating better

compliance and sustainable business practices.

Corporates adopt Emerging technologies to improve Environmental Social Governance disclosure through

transparency enhancements com, appliance management, and stakeholder relationships by leveraging Artificial

intelligence and Big data analytics together with Digital platforms to gain better ESG reporting, er greenwashing

exposure, and build investor trust (Veloso, 2024). The analysis of ESG disclosures through AI natural language

processing (NLP) enables companies to achieve regulatory compliance, and the AI sentiment analysis allows

them to monitor public discussions to adjust their ESG communication properly (Veloso, 2024). AI scoring

systems help investors implement data-based investments via the examination of financial data and corporate

reports and social media interaction, which diminishes subjectivity in sustainability assessment procedures. The

secure blockchain database preserves unalterable sustainability records, which allows for the real-time review

of supply chains, carbon tracking, and ethical procurement practices to protect against sustainability fraud

(Veloso, 2024). The analysis of large data volumes helps businesses monitor ESG metrics in real time and predict

sustainability risks through the presentation of performance data (Veloso, 2024). The digitalization of platforms

through sustainability dashboards and investor communication portals enables demonstrative ESG stakeholder

engagement because companies present ESG information honestly and enhance public and investor

empowerment through interactive sustainability metrics (Veloso, 2024). The tightening of ESG disclosure

standards by regulatory authorities depends on technology that uses AI fact-checkers to expose ESG report

inconsistencies while blockchain keeps data from being manipulated (Veloso, 2024). Businesses benefit from

automated compliance tools together with ESG software, which aids in standard alignment and risk reduction

for accurate sustainability reporting (Veloso, 2024). Efforts to develop ESG compliance software together with

ESRS and TCFD standards improve decision-making transparency and provide better-reporting integrity to

fulfill investor demands regarding sustainable business operations.

The evaluation of Environmental Social Governance (ESG) performance necessitates numerical objective

assessment points from carbon emissions to diversity ratios along with governance scores combined with

interpretive textual data about corporate sustainability declarations (Sun & Long, 2024). The evaluation of ESG

narratives and stakeholder perceptions, together with transparency levels, is done through Natural language

processing (NLP) sen, timing analysis, and discourse analysis tools. The analysis of emotional content in

corporate ESG performance relies on automated text analysis of sustainability reports and investor briefings, and

social media and news ESG-related passages to spot ESG communication inconsistencies versus public reactions

and identify greenwashing risks (Sun & Long, 2024).

Studies show that transparent ESG information disclosure manifests as simple text with straightforward

language, which leads to clear accountability, yet difficult language tends to hide weak sustainability results (Sun

& Long, 2024). The analysis of ESG textual information allows investors to identify main sustainability topics

like carbon neutrality and diversity and inclusion together with governance integrity, which helps differentiate

meaningful ESG promises from empty gestures, but authentic sustainability engagement demonstrates

companies using specific targets and progress metrics (Sun & Long, 2024). The analysis of stakeholder discourse

provides qualitative information through monitoring social media inv, ester calls emp, employee reviews, and

regulatory reports, which enables investors and analysts to evaluate sustainability risks and regulatory scrutiny

(Sun & Long, 2024). The use of different ESG-related words throughout reports indicates deep sustainability

commitment since detailed descriptions accompany extensive terminology usage (Sun & Long, 2024). The

assessment of corporate ESG performance receives additional support through advanced NLP techniques

because these methods track relevant ESG narrative patterns and extract meaningful keywords to produce more

accurate sustainability assessments.

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METHODOLOGY

Research Design

This study employs a qualitative research design to explore the role of Environmental, Social, and Governance

(ESG) metrics in shaping corporate sustainability strategies. Given the complexity and multidimensional nature

of ESG metrics, a qualitative approach allows for an in-depth examination of existing literature, corporate

disclosures, and regulatory frameworks. The study focuses on thematic analysis using topic modeling to uncover

latent themes within ESG discourse, providing structured insights into how these metrics guide corporate

decision-making.

Research Approach

A qualitative, exploratory approach is adopted to analyze textual data from ESG reports, regulatory documents,

and academic literature. This approach enables a comprehensive understanding of ESG frameworks, stakeholder

narratives, and regulatory challenges. By leveraging natural language processing (NLP) techniques, specifically

Latent Dirichlet Allocation (LDA), the study systematically extracts and categorizes key themes in ESG-related

discourse. Correspondence Analysis (CA) is further employed to visualize term relationships, reinforcing the

robustness of topic modeling findings.

Research Philosophy

The research is grounded in an interpretive philosophy, emphasizing the subjective and evolving nature of ESG

discourse. Interpretivism allows for a nuanced analysis of corporate sustainability strategies by recognizing the

contextual influences of regulatory developments, investor expectations, and corporate governance practices.

The study also integrates aspects of constructivism, acknowledging that ESG narratives are shaped by

stakeholder interactions, regulatory shifts, and evolving sustainability frameworks.

Data Collection

The study relies on secondary data sources, including ESG reports from corporations across various industries,

Regulatory guidelines and sustainability disclosure frameworks (e.g., GRI, TCFD, CSRD, ISSB), Academic

literature on ESG integration, corporate governance, and sustainability metrics, Industry reports and white papers

analyzing ESG trends and regulatory developments. These textual datasets provide a rich source of qualitative

information, enabling the identification of key themes and patterns in ESG-related decision-making. Text mining

techniques are applied to extract relevant ESG terms, corporate commitments, and sustainability performance

indicators.

Data Analysis Methods

The study employs a combination of Latent Dirichlet Allocation (LDA) and Correspondence Analysis (CA) to

analyze the collected data:

Latent Dirichlet Allocation (LDA): LDA is used to uncover latent topics within ESG reports and sustainability

literature. It enables the identification of recurring themes, such as governance integrity, environmental

responsibility, and social impact. Dynamic topic modeling allows for the exploration of evolving ESG discourse,

particularly trends projected for 2025 and beyond.

Correspondence Analysis (CA): CA provides a visual representation of term associations within ESG

discourse. It highlights the relationships between key ESG terms, differentiating core sustainability themes from

emerging topics. The method enhances topic modeling results by validating clusters of ESG-related terms and

identifying gaps or synergies in corporate sustainability strategies. By integrating LDA and CA, the study ensures

a comprehensive and systematic examination of ESG narratives, enhancing the understanding of how

corporations leverage ESG metrics for sustainability-driven decision-making.

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RESULT

Topic modelling using LDA

Fig 1: Topic modelling

The interpretation of topic modeling data shows excellent compatibility with the research topic while

demonstrating different ways ESG metrics affect corporate sustainability strategies. The future sustainability

trends center on transparency development of leadership and diversity because they demonstrate how ESG

metrics direct business adaptation toward 2025 and beyond. The role of ESG in promoting corporate integrity

becomes stronger through corporate governance and accountability systems that emphasize transparency and

risk reduction related to greenwashing. ESG demonstrates its importance through social performance

measurement and risk management, together with innovation development. Companies achieve better investor

relationships by sharing ESG information because ESG disclosures guide the way both investors view businesses

and corporations make their strategic decisions.

The section focuses on corporate environmental initiatives while investigating decision-making frameworks

through which ESG drives enhanced credibility. ESG reporting, along with standardized procedures and carbon

footprint assessment tools, strives to achieve precise measurement of sustainability as well as direct stakeholder

collaboration and carbon footprint assessment precision for maintaining sustainability assessment consistency.

The implementation of Strategic ESG initiatives and internal performance tracking systems enable accessibility

to organizational sustainability programs and internal performance measurement across corporate operations.

This research field studies investor actions after structured ESG disclosure release as well as their effects on

business financial outcomes. The necessity of ESG in compliance becomes evident through regulatory

compliance and climate risk because it shows how ESG regulations and climate-related disclosures interact with

policy frameworks. Financial reporting and ESG risk analysis show how ESG elements get incorporated into

financial documentation while improving their importance in financial evaluations. The research's practical and

forward-looking evaluation of ESG metrics for sustainability strategies receives support from the complete set

of topics, which cover governance, social impact, environmental performance, reporting, investor engagement,

and regulatory compliance.

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ESG metrics for sustainability strategies.

Fig 2: ESG metrics for sustainability strategies

The thematic map shows in an easy-to-understand format which of the ten topics affect your main research

inquiry about "The Role of ESG Metrics in Shaping Corporate Sustainability Strategies." Through the use of

purple-colored trends, the map demonstrates future sustainability practices that focus on transparency alongside

leadership and diversity, highlighting the essential function of ESG metrics in corporate governance and

greenwashing prevention (Green). ESG metrics link to three essential areas, which include social impact and

risk management alongside innovation (Pink), investor communication with transparency (Black), and

environmental practices and credibility (Light Blue). The implementation of ESG reporting standards and carbon

measurement and related practical uses (Orange) appear together with benefits for strategic sustainability plans

and internal organization development (Light Green). The integration of ESG disclosures along with investor

influence forms a vital connection that shows structured reporting has an impact on financial outcomes (Yellow).

The regulatory and financial aspects of ESG metrics find support through themes that encompass regulatory

compliance and two specific disclosure types related to climate (Pink) and financial risk assessment (Dark Blue).

The thematic map proves through visual evidence that the research title perfectly matches key themes, presenting

a structured and easily understood framework that displays how ESG metrics affect corporate sustainability

strategies.

Correspondence Analysis (CA)

Fig 3: Correspondence Analysis

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Research investigators use Correspondence Analysis (CA) as a statistical tool to create visual representations of

categorical variable relationships, which reveal the associations among ESG-related terms throughout the

research framework. The X-axis dimension holds 33.16% of the total variance, followed by the Y-axis at 22.61%,

and color coding at 12.35%, which explains 68.12% of the total variability. The ESG discourse shows strong

connections between its main concepts, "governance," "environmental," "compliance," and "investors," since

these terms appear in the central area of the analysis. The peripheral terms "metrics," "2025," "risk," and

"commitments" represent specialized aspects within the data set. The central ESG concepts group together in

Cluster 4, while other clusters separate reporting from strategy and stakeholder interaction and regulatory

requirements. The research indicates that practical ESG aspects used for reporting purposes appear on the right

side X-axis, whereas strategic themes exist on the left side X-axis. Similarly, data-driven analysis resides at the

top Y-axis, while implementation-focused engagement lies at the bottom Y-axis. The structured distribution

system demonstrates that the study effectively reveals how ESG metrics affect sustainability strategy

development by focusing on governance, risk, stakeholder influence, reporting, and strategic decision-making.

DISCUSSION

The research utilized LDA as its primary method because it delivers essential capabilities for finding hidden

patterns, framework planning, and future trend tracking. The ten identified themes, including governance and

regulatory compliance, served as a system to explore ESG metrics. The dynamic nature of LDA allowed

researchers to visualize changes in ESG discourse because it supported tracking future trends with a specific

focus on 2025 projections. The selected approach delivered optimal results for exploring ESG metrics as well as

stakeholder narratives regarding regulatory challenges and framework development. The analysis tool

Correspondence Analysis (CA) acted alongside LDA to show relationships between terms, identify specific

versus fundamental themes, and support the LDA findings. The cluster patterns of terms "governance," "risk,"

and "investors" that came to light through CA analysis enabled researchers to determine if ESG strategies showed

overlapping points or distinct strategic areas. The approach helped detect emerging subjects together with

underprioritized topics within ESG dialogues, particularly "metrics" and "2025."

The research utilized LDA and CA in combination to provide a comprehensive understanding of the data. LDA

established thematic pillars through its usage, but CA functioned to analyze metric interactions with stakeholders

and regulatory elements and improve the framework development process. The analysis conducted by LDA

uncovered data-driven analysis as a technological innovation topic, while CA demonstrated that AI combined

with blockchain and carbon tracking technologies relate to ESG metrics. Through the application of CA, the

regulatory themes identified by LDA received additional definitions, which revealed that compliance and

greenwashing existed as opposing forces. The proposed research agenda involves using dynamic LDA for

monitoring ESG theme evolution imp, lamenting CA for stakeholder investigations, and conducting machine

learning assessments, which include sentiment analysis and network evaluation. The core method used for this

research was LDA because it matched the project goals, but the CA addition allowed further examination of term

connections and verification of LDA results. The combination of these methods created an extensive adaptable

system to evaluate ESG metrics effectively.

The analysis of Correspondence Analysis (CA) delivered different results to LDA since it examined term

relationships instead of discovering hidden themes. LDA organized ESG metrics into various topics, but CA

created visual clusters to show term interrelationships for analysis of ESG strategic gaps and synergies. The

analysis performed by LDA concentrated on ESG discourse classification, yet CA used its method to showcase

different types of topics that exposed new emerging concepts such as "metrics" and "2025." The team at CA used

topic cluster cross-checks to confirm the LDA analysis results and thus strengthen the thematic validity. The

LDA framework development and thematic evolution assessment functioned better than the CA method, which

delivered superior analysis for refining regulatory and stakeholder requirements through sequential term

associations and context-based relationships.

CONCLUSION

The research investigates how environmental social governance metrics impact corporate sustainability methods

through qualitative analysis, which uses latent Dirichlet Allocation (LDA) and correspondence analysis (CA).

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Company success depends heavily on ESG metrics because they drive corporate governance along with

regulatory compliance, stakeholder relationships, and financial procedures. Through extensive ESG disclosure

analysis, sustainability report evaluation, and thematic mapping research, it aims to fulfill its four objectives

about ESG metrics alongside stakeholder narratives and regulatory challenges alongside technological

innovations. According to the discussion, ESG transparency, governance integrity, investor influence, and

regulatory compliance have been shown to guide the creation of corporate sustainability strategies.

Managerial Implications

Through this research, corporate decision-makers gain important insights that stress the necessity of adopting an

organized approach to ESG implementation. Businesses need to embed ESG metrics across their prolonged

corporate planning to guarantee sustainability operations synchronize with market trends, investor demands, and

legal needs. ESG reporting that uses standards and clear transparency helps businesses build trustworthiness,

reduce greenwashing risks, and create investor trust. The integration of artificial intelligence with blockchain for

ESG disclosures extends information reliability while eliminating regulatory_floor_ issues and reinforcing

businesses' sustainability performance.

Research Implications

This study contributes information about corporate sustainability to academic research about ESG integration.

By using LDA and CA to analyze ESG discourse, researchers can confirm that analytical methods used for text

research successfully reveal underlying themes and validate classifying concepts. The research creates an

analytic linkage between human-based ESG stories and systematic thematic examination to establish a research

method for upcoming ESG discourse investigations. Scientists should adopt methods from machine learning to

analyze stakeholder opinions and regulatory progress through sentiment evaluation and network examination

systems.

Societal Implications

This research demonstrates how ESG integration affects society through business strategies. Companies that

prioritize ESG principles work to sustain the environment while promoting fair social practices and ethical

leadership, thus creating beneficial transformations in society. By increasing ESG disclosure transparency,

consumers and investors receive better information to choose businesses that practice accountability and

responsible business operations. According to the research, standards from regulatory bodies contribute to ESG

reporting consistency, which makes it possible to achieve quantifiable positive societal outcomes from corporate

sustainability promises.

Future Directions

The next phase of ESG reporting research should inspect how the new CSRD and ISSB framework standards

influence the current reporting practices. Dynamic topic modeling tracks the evolution of ESG discourse over

time, which helps organizations understand their sustainability strategy adjustments in response to regulatory

updates. The combination of sentiment analysis and stakeholder network analysis produces a better

understanding of both investor sentiment and ESG narrative contents. Future investigation should explore how

ESG metrics integrate with emerging sustainable reporting technology, including artificial intelligence for

sustainability analytics and blockchain-powered ESG verification platforms, to ensure greater firm

accountability standards.

REFERENCE

1. Ahmaro, M., Aljebrini, M., & Dogruyol, H. (2025). Corporate sustainability narratives and stakeholder

engagement: Shaping business strategies through ESG commitments. Journal of Business Strategy and

Sustainability, 19(2), 88–104.

Page 972

www.rsisinternational.org

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2. Amanifar, F., & Rahat, M. (2024). Challenges in ESG reporting: Addressing readability, compliance, and

verification through text analysis. Journal of Corporate Social Responsibility and Environmental

Management, 22(2), 115–130.

3. Ani, M., & Solissa, A. (2024). Stakeholder engagement and the creation of shared value in ESG

initiatives. Journal of Corporate Social Responsibility, 19(2), 233–245.

4. Badr, H., Ibrahim, M., & Hussainey, K. (2024). ESG communication challenges in emerging markets:

Perception management and stakeholder trust. International Journal of Emerging Markets, 9(1), 55–71.

5. Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1),

99-120. https://doi.org/10.1177/014920639101700108

6. Beckert, J., & Koch, D. (2025). ESG performance as a driver of sustainable investments: The role of

long-term financial stability. Sustainable Finance Journal, 12(2), 142–156.

7. Bedford Consulting. (2023). The 5 main challenges of ESG reporting and best practice. Retrieved

from https://bedfordconsulting.com/the-5-main-challenges-of-esg-reporting-and-best-practice/

8. Biswas, P., Das, S., & Mitra, S. (2024). Risk management and resilience: The role of ESG strategies in

mitigating climate-related financial challenges. Environmental Economics and Sustainability, 15(1), 98–

112.

9. Bonfanti, F. (2024). ESG-driven innovation: Advancing sustainable finance and green technology.

Journal of Sustainable Finance and Investment, 21(4), 287–303.

10. Bruhati. (2024). The rise of ESG metrics: Understanding the impact on corporate performance. LinkedIn

Pulse. Retrieved from https://www.linkedin.com/pulse/rise-esg-metrics-understanding-impact-

corporate-performance-bruhati-idnle

11. Carabelli, A. (2025). The digitalization of ESG communications: Using interactive platforms to improve

transparency and engagement. Sustainability and Governance Review, 19(3), 190–205.

12. Casalegno, M., Chiaudano, S., & Tamiazzo, F. (2024). Selective ESG disclosures and their impact on

corporate credibility. Corporate Governance and Sustainability Review, 23(4), 157–172.

13. Chen, X. (2024). Automated ESG monitoring systems: Enhancing compliance and reducing risks.

Journal of Regulatory Technology, 12(1), 80–92.

14. Crosby, R. (2024). Greenwashing and corporate sustainability: Eroding trust through inconsistency.

Journal of Business Ethics, 17(2), 89–103.

15. Dadhich, S., & Saini, S. (2024). Perceptions of ESG as impression management: Challenges in emerging

markets. Global Business and Organizational Excellence, 34(1), 45–60.

16. Dathe, L. (2024). Digital tools for ESG communication: Leveraging websites and social media for greater

accessibility and alignment. Corporate Communication Journal, 29(2), 135–147.

17. DiMaggio, P. J., & Powell, W. W. (1983). The iron cage revisited: Institutional isomorphism and

collective rationality in organizational fields. American Sociological Review, 48(2), 147-160.

https://doi.org/10.2307/2095101

18. Emmanuel, S. (2025). Blockchain technology and ESG disclosures: Enhancing credibility and mitigating

greenwashing. Journal of Corporate Sustainability, 34(2), 105–120.

19. Faccia, A., & Petratos, P. (2024). Big data analytics and AI in ESG reporting: Enhancing reporting

accuracy and regulatory alignment. International Journal of Business and Technology, 33(4), 244–259.

20. Freeman, R. E. (1984). Strategic management: A stakeholder approach. Pitman.

21. Greenmyna. (2024). Top Challenges in ESG Reporting and How to Overcome Them. Retrieved

from https://www.greenmyna.com/top-challenges-in-esg-reporting-and-how-to-overcome-them-1

22. Hartwig, A. (2024). The role of consumer priorities in shaping corporate ESG messaging. Journal of

Marketing and Consumer Behavior, 18(3), 134–148.

23. Ijomah, W., Nodhiva, M., & Makridis, G. (2024). Green innovation through digitalization: Leveraging

technology to enhance ESG disclosures. Sustainable Business Innovation Journal, 25(3), 167–182.

24. Iris Business. (2025). Top ESG Trends in 2025: Shaping the Future of Sustainability and Corporate

Responsibility. Retrieved from https://www.irisbusiness.com/top-esg-trends-to-watch-in-2025-to-the-

future-of-sustainability-and-corporate-responsibility/

25. Jamil, S., & Wahyuni, S. (2024). The role of transparency and accountability in ESG strategies. Journal

of Business Ethics, 28(3), 145–158.

26. Jang, Y., & Kang, D. (2023). Regulatory compliance and ESG disclosures: Aligning with global

standards. International Journal of Environmental Sustainability, 19(2), 211–224.

Page 973

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue III, March 2026

27. Jarboui, A., Rana, J., & Thomas, P. (2025). Regulatory frameworks and corporate sustainability: The role

of ESG disclosures. International Journal of Business Ethics, 42(3), 250–265.

28. Jayadatta, T. (2023). The transformation of ESG stakeholder engagement through social media. Journal

of Communication in Business, 26(4), 203–215.

29. Jizi, M. I., & Thomas, H. (2025). The impact of ESG reporting on financial governance and audit delays.

Journal of Business Ethics, 121(4), 310–325.

30. Junaedi, P. (2024). Transparency in ESG reporting: Strengthening stakeholder trust with clear

disclosures. Journal of Corporate Governance, 25(1), 38–52.

31. Koch, D. (2025). ESG factors in financial decision-making: The growing influence of sustainability on

investments. Journal of Finance and Sustainable Development, 19(1), 77–92.

32. Lehner, O., & Harrer, S. (2019). Corporate accountability and ethical expectations in ESG discussions.

Business Ethics Quarterly, 24(3), 215–231.

33. Lin, M., Beck, K., & Louca, L. (2024). Blockchain for ESG data verification: Enhancing credibility and

mitigating greenwashing risks. Journal of Digital Sustainability, 22(1), 75–88.

34. Magli, M., & Amaduzzi, A. (2025). Global disclosure frameworks: A comparative analysis of GRI,

TCFD, and ESRS. Sustainability Accounting, Management and Policy Journal, 17(1), 77–94.

35. Magli, M., & Amaduzzi, A. (2025). The impact of AI and blockchain on ESG reporting: Revolutionizing

transparency and compliance. International Journal of Environmental Sustainability, 14(2), 134–149.

36. Makridis, G., Beck, K., & Louca, L. (2025). Blockchain-integrated AI models for real-time ESG

monitoring. Journal of Corporate Governance and Innovation, 18(2), 99–113.

37. Mbhalati, M., & Masehela, I. (2024). Regulatory pressures and ESG transparency: Enhancing

stakeholder engagement. Journal of Business Law and Ethics, 12(2), 95–108.

38. McCall, T. (2024). Stakeholder perceptions and their impact on corporate ESG strategies. Corporate

Social Responsibility and Environmental Management, 22(3), 177–189.

39. McKinsey & Company. (n.d.). Does ESG really matter—and why? Retrieved

from https://www.mckinsey.com/capabilities/sustainability/our-insights/does-esg-really-matter-and-

why

40. Moyeen, S., & Mehjabeen, S. (2024). The influence of internal ESG communication on employee

engagement. Journal of Corporate Responsibility, 30(2), 142–156.

41. Nielsen, K., & Villadsen, A. (2023). ESG transparency and regulatory frameworks: Enhancing

stakeholder trust. Business Strategy and Environmental Policy, 31(1), 89–104.

42. Nodhiva, M., Ijomah, W., & Makridis, G. (2024). ESG reporting and green technologies: Advancing

sustainability and attracting socially responsible investments. Journal of Business Ethics and Innovation,

27(3), 201–215.

43. Parfentieva, M. (2024). The role of readability and accessibility in ESG compliance: Overcoming

greenwashing risks. Business and Environment Journal, 21(1), 57–70.

44. Rahman, S., Suta, D., & Debata, B. (2025). The challenges of standardizing ESG disclosures: A global

perspective. Journal of Financial Reporting and Accounting, 19(4), 439–455.

45. Rajput, M., Sharma, N., & Garg, A. (2024). AI and automated ESG monitoring: Tools for improving

compliance and governance. Corporate Regulation and Ethics Journal, 16(4), 202–218.

46. Rana, J., Jarboui, A., & Thomas, P. (2025). Regulatory compliance and its impact on ESG disclosures.

Corporate Social Responsibility and Environmental Management, 22(1), 58–75.

47. Roy, S., & Vasa, R. (2025). The role of AI and NLP in ESG reporting: Future trends in data analysis.

Journal of Technology in Business, 16(3), 212–227.

48. Sahu, R., & Debata, B. (2025). Fintech innovations and the future of ESG data standardization. Finance

and Technology Journal, 27(2), 180–198.

49. Shakeri. (2025). The Future of Sustainability: Key ESG Trends and Predictions for 2025. LinkedIn Pulse.

Retrieved from https://www.linkedin.com/pulse/future-sustainability-key-esg-trends-predictions-2025-

shakeri-dba-rlcrf

50. Spence, M. (1973). Job market signaling. Quarterly Journal of Economics, 87(3), 355-374.

https://doi.org/10.2307/1882010

51. Suchman, M. C. (1995). Managing legitimacy: Strategic and institutional approaches. Academy of

Management Review, 20(3), 571-610. https://doi.org/10.5465/amr.1995.9508080331

Page 974

www.rsisinternational.org

INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,

MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)

ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue III, March 2026

52. Sun, H., & Long, Y. (2024). Evaluating corporate ESG performance through quantitative and qualitative

measures: The role of natural language processing and sentiment analysis. Journal of Corporate

Sustainability and Innovation, 22(3), 145–160.

53. Sung, Y., Tao, C., & Lee, M. (2025). The role of social media in enhancing corporate ESG communication

and engagement. Journal of Public Relations and Corporate Communications, 17(2), 108–122.

54. Suta, D., Rahman, S., & Debata, B. (2025). The role of AI-driven text analysis in improving ESG

reporting compliance. Journal of Financial Reporting and Accounting, 19(4), 439–455.

55. Suta, D., Rahman, S., & Magli, M. (2025). The relationship between ESG scores and financial

performance: A global analysis. Financial Sustainability Review, 11(2), 102–115.

56. Sutta, D., Rahman, S., & Magli, M. (2025). The relationship between ESG scores and financial

performance: A global analysis. Financial Sustainability Review, 11(2), 102–115.

57. Suttipun, M., Emmanuel, S., & Suta, D. (2025). ESG metrics: Enhancing transparency and promoting

sustainability. Journal of Corporate Governance, 29(1), 50–63.

58. Tan, K., Wang, Y., & Phillips-Fein, L. (2025). Greenwashing and ESG skepticism: Addressing

unsubstantiated claims. Journal of Business Ethics, 30(1), 140–155.

59. Theron, R., Cant, M., & Wiid, J. (2024). The influence of internal ESG communication on employee

engagement. Journal of Business Communication, 41(1), 47–63.

60. Usman, A. (2024). Transparency in ESG reporting: Building stakeholder trust and mitigating

greenwashing risks. Sustainability and Governance Journal, 18(2), 144–160.

61. Veloso, C. (2024). Emerging technologies in ESG reporting: AI, blockchain, and big data analytics

transforming corporate sustainability. Journal of Corporate Sustainability, 24(2), 98–112.

62. Wang, Y., & Phillips-Fein, L. (2023). Diversity, equity, and inclusion initiatives within corporate ESG

frameworks. Journal of Corporate Social Responsibility, 17(4), 321–335.

63. Whelan, P., Eckerle, K., & Tomlinson, B. (2020). The importance of transparent ESG disclosures for

investor confidence. Journal of Financial Regulation and Compliance, 28(3), 110–121.

64. Yunus, M., & Nanda, S. (2024). The role of ethical expectations in ESG accountability. Business Ethics

and Corporate Responsibility, 28(3), 209–224.

65. Zhang, X., Xu, J., & Chen, L. (2024). Blockchain and big data in ESG transparency: Securing

sustainability claims. Journal of Corporate Innovation, 17(3), 145–160.

66. Zhang, Z., Xu, J., & Chen, L. (2024). Misinformation and reputational risks in ESG communication: The

role of influencer partnerships. Journal of Corporate Communication, 21(3), 186–200.