Leveraging clustering techniques to drive sustainable economic innovation in the India–Gulf interchange

Abstract

The collaboration between India and the Gulf regions presents a promising opportunity for sustainable economic innovation amidst global challenges. However, there is a notable research gap in understanding how machine learning techniques, particularly clustering, can drive such innovation effectively in this context. Existing literature lacks tailored models for the India–Gulf interchange’s specific needs. This study aims to fill this gap by investigating the application of machine learning clustering models to identify factors and opportunities for sustainable economic innovation. Specifically, it seeks to leverage these techniques to foster strategic partnerships and address environmental, social, and governance factors. Through SWOT analysis and clustering, the study identifies integration elements and proposes a forward-looking Paradigm for Future Development. The findings advocate for strategic collaborations and offer a model methodology for sustainable development, with broader policy implications. The study reveals that Current Saudi Arabia’s progress is linked to strategies akin to India’s, suggesting India as a model for Gulf countries.

Keywords:

• Clustering analysis
• India–Gulf interchange
• sustainable economic
• ESG (environmental, social, governance)

REVIEWING EDITOR:

• Armando Aliu, Faculty of International and Political Studies, Jagiellonian University, Krakow, Poland

SUBJECTS:

• Sustainable Development
• Economics and Development
• Environment & the Developing World
• Environmental Economics

1. Introduction

1.1. Overview

The India–Gulf interchange presents a unique opportunity for fostering sustainable economic innovation through collaboration. As both regions strive for economic growth and development, there is an increasing recognition of the need to leverage technology and strategic partnerships to address challenges and capitalize on opportunities.

The study underscores the pivotal role of sharing experiences and best practices between India and the Gulf regions. This collaboration aims to enhance competitive advantages by addressing weaknesses prevalent in the Gulf. The exchange of strategies and opportunities between these regions is instrumental in achieving sustainable development goals. The choice of focusing on the Gulf regions is driven by its relevance to key variables, emphasizing the need for specific data. This work aims to establish a robust link between India and the Gulf, leveraging their respective strengths for mutual sustainable economic growth. The proposed model emphasizes overcoming challenges through collaborative efforts, promoting a resilient sustainable development approach. The interplay of experiences and information exchange is envisioned to propel both regions towards a prosperous and eco-friendly future.

A comparable scenario is evident in the research conducted by Arif and Aldosary (2023) GCC member states have witnessed significant advancements in their smart cities. Each nation, post-British rule, has its urban planning authority overseeing growth. This research stands out for its in-depth cross-border analysis, shedding light on urban planning dynamics within the Gulf Cooperation Council. It aims to scrutinize national spatial strategies and vision plans, utilizing the SWOT method to evaluate achievements, weaknesses, opportunities, and threats. While highlighting successful outcomes and suggesting oil dependency strengthening, it emphasizes capitalizing on tourism opportunities and managing threats for sustainable urban development. The study suggests executing ministry-outlined programs for efficient spatial expansion management by municipal authorities, serving as valuable lessons for comprehensive national strategic planning in GCC countries. According to Arif et al. (2019) in recent decades, urban settlements, particularly in the Burdwan area, have witnessed significant growth, resulting in challenges like socio-spatial segregation and informal development. This study explores these issues using livelihood asset and quality of life indices (Malancha, 2021). Five years after the adoption of the 2030 Agenda for Sustainable Development, the COVID-19 pandemic has disrupted global dynamics. The severe impact on jobs, livelihoods, and sustainable development necessitates a reevaluation of India’s economic diplomacy for the next decade.

The exchange of experiences and best practices between India and the Gulf regions is crucial for several reasons as explored in Ashwarya (2023) and Kumar (2020). Firstly, by interchanging the best problem-solving practices and continuously improving approaches, both regions can attain greater competitive advantages. By learning from the powers of India and the Gulf regions, we can address the weaknesses and threats predominant in the Gulf regions. This familiarity transfer will help optimize strategies and influence the best practices for sustainable development. Additionally, by adapting and interchanging the strongest strategies and opportunities between India and the Gulf regions, we can realize the shared goal of sustainable development. India’s expertise in various sectors and the Gulf region’s resources and economic stability generate a rich ground for mutually beneficial collaboration. By optimizing the employment of resources, adopting sustainable practices, and exploiting on economic opportunities, we can drive sustainable economic growth in both regions.

The proposed work highlights intensive efforts to overcome faults and pressures by leveraging the strengths and strategies of India and the Gulf regions. This exchange of experiences and information will lead to a more healthy and resilient sustainable development model. By combining the best practices, optimizing resources, and capitalizing on opportunities, we can effectively achieve the goal of a sustainable paradigm for future development. The interchange of experiences between India and the Gulf regions will stand-in cross-regional learning, synergy, and progress towards a sustainable future. Through this collaborative approach, we can unlock the full possible of both regions and pave the way for long-term economic prosperity and eco-friendly well-being.

1.2. Motivation

The collaboration between India and the Gulf regions holds immense potential for driving sustainable economic innovation. With the global economy facing unprecedented challenges, including the impact of the COVID-19 pandemic, there is a growing urgency to develop resilient and eco-friendly solutions that promote long-term prosperity.

1.3. Research gap

Despite the growing interest in collaboration between India and the Gulf regions, there remains a significant research gap in understanding how machine learning models-Clustering can be effectively utilized to drive sustainable economic innovation in this context. Existing literature often lacks comprehensive models and methodologies tailored to the specific needs and challenges of the India–Gulf interchange.

1.4. Research question

This study seeks to address this gap by investigating the application of machine learning Models-Clustering to identify key factors and opportunities for sustainable economic innovation in the India–Gulf interchange. Specifically, we aim to answer the following research question: How can machine learning techniques be leveraged to drive sustainable economic innovation and foster strategic partnerships between India and the Gulf regions?

2. Literature review

The India-Gulf interchange has appeared as an important driver of economic growth and innovation. This research works review aims to study the role of machine clustering models in promoting sustainable economic innovation within the environment of the India–Gulf interchange. It also highlights the position of considering environmental, social, and governance (ESG) factors in the clustering analysis for expansion sustainable development. Xu and Tian (2015), provides a complete overview of various clustering algorithms used in machine learning, helping to establish a foundation for exploring the application of clustering models in the context of the India–Gulf interchange. In the previous work (Zhou et al., 2018), explores the existing literature on clustering analysis in the field of regional science and highlights the important of clustering for understanding economic innovation and development. Considering the existing literature similar to Shannaq et al. (2019), the research work based on the methodical use of an integration method comprising an information system and prediction model to improve the accuracy of Quantity Survey (QS) calculation. The proposed study was related to the concept of the green economy as it contributes to optimizing the accuracy of QS calculation. By building projects can better plan and allocate resources, and this could minimize waste and promoting sustainable practices. The improved prediction and classification, can lead to efficient resource utilization and reduced environmental impact. Supporting with the values of the green economy. Building upon prior investigations as in Kumar (2016), the studies proposes a sustainable development model for India’s economic growth, emphasizing the need for integrating sustainability considerations into economic policies and practices. Shannaq et al. (2012), the study focuses on filtering a database to identify instructors who use non-electronic teaching styles and incorporate a green instructional system into their curriculum. The main goal was to highlight the advantages of using green education and its potential impact on sustainable development. Linking this to the green economy and sustainable development, the adoption of green education practices aligns with the principles of sustainability. By integrating green instructional systems into curricula, educational institutions can improve the process of environmental awareness, promote sustainable practices, and equip students with the knowledge and skills needed for a green and sustainable future. Such approach not only enhances the quality of education but also contributes to the development of a workforce that is conscious of environmental challenges and capable of driving sustainable development in various sectors. By incorporating green education, Governments can build a more sustainable society and advance towards their sustainable development goals. In accordance with previous studies (Al-Shamsi & Shannaq, 2020), the study aimed to develop a visual tree and classification model to categorize 30 different types of businesses. The results indicated that 61.1753% of the instances were correctly classified using this approach. Several certain business types, such as sewing reusable masks, medical services, new delivery services, production of antiseptics, and software and automation, would play a dominant role in driving the global business economy in the future. Linking this to the green economy, the identified dominant business types align with sustainable practices and contribute to the development of a greener and more sustainable economy. By the development of sewing reusable masks supports the reduction of waste from single-use masks and promotes sustainable consumption. Medical services are essential for providing healthcare solutions, including sustainable healthcare practices and technologies. New delivery services can focus on sustainable logistics and transportation methods, could minimize carbon emissions. The development of antiseptics can incorporate eco-friendly ingredients and packaging. Software and automation can drive efficiency and sustainability in various sectors, including energy, agriculture, and manufacturing. Overall, the identified business types reflect the potential for green and sustainable practices to shape the future global business economy, highlighting the importance of integrating sustainability principles into business strategies and operations. In accordance with previous studies (Al-Shamsi et al., 2023), in this comparative analysis, the service quality of telecommunication services provided by both public and private companies was examined. The research work aims to understand the differences and similarities in service quality between these two sectors. The outcomes highlight the importance of service quality in shaping customer satisfaction and loyalty in the telecommunications industry. Linking this analysis to the future sustainable development with a green economy. It is crucial to consider the role of telecommunications in driving sustainability and green initiatives. As the world becomes increasingly connected, telecommunication services play a vital role in supporting sustainable development goals. Efficient and reliable communication networks enable remote working and reduce the need for physical commuting, thereby reducing carbon emissions and contributing to a greener economy. Furthermore, sustainable telecommunication practices involve using renewable energy sources to power communication infrastructure, minimizing electronic waste through responsible disposal and recycling. And promoting digital literacy to bridge the digital divide and ensure equal access to communication services. Building upon prior investigations (Chandran & Karunakaran, 2018; Maqbool & Bakr, 2019), this research’s examine the relationship between ESG performance and firm financial performance in India, emphasizing the importance of incorporating ESG factors in economic analysis and decision-making processes. According to Niazi and Salama (2020), they explores the applications of clustering techniques in sustainable energy systems, providing insights into how clustering models can be utilized in the context of promoting sustainable economic innovation. Drawing from earlier scholarly works found in Environmental Sciences Europe (2023), Emerald Insight (2023) and ScienceDirect (2023), the reviews examine the nexus between economic growth and environmental degradation in India, highlighting the need for sustainable economic practices to mitigate environmental challenges. According to Maher and Andersson (2000), the review focuses on the relationship between governance and economic growth in emerging markets. Emphasizing the significance of good governance for sustainable economic development. Aligned with existing literature (Ghaffour et al., 2015; Panigrahi et al., 2020; Sadriwala et al., 2020, 2023; Segumpan & McAlaney, 2023; Shannaq et al., 2023; Shannaq & Al Shamsi, 2023), the studies discuss the challenges and prospects of sustainable urban development in gulf regions, Oman and India, similar on the role in utilization of machine learning (ML) in particular clustering models holds immense potential for promoting sustainable economic innovation within the India–Gulf interchange.

According to Sahoo and Sahoo (2022), this study analyzes the interplay between renewable and non-renewable energy consumption and CO₂ emissions in India using disaggregated data from 1965 to 2018. Employing the ARDL bound testing approach, we assess the long-run elasticity. Toda–Yamamoto Granger causality test explores variable causality. Results show a positive but insignificant impact of hydro energy on CO₂ emissions. Conversely, nuclear energy exhibits a negative effect on CO₂ emissions, while all non-renewable sources significantly contribute to CO₂ emissions.

From Sahoo et al. (2023), the research spanning 2000 to 2018, analyzes corruption control, green energy, trade, innovation, natural resources, and ICT impact on CO₂ emissions in developing economies. Results reveal corruption control increases CO₂ emissions, while the interaction with natural resources exacerbates it. Conversely, corruption control and green energy reduce environmental impact. Evidence supports the Environmental Kuznets Curve hypothesis. Bootstrap quantile regression confirms corruption control, natural resource depletion, and non-renewable energy usage contribute to increased CO₂ emissions. Green energy, innovation, and ICT drive environmental sustainability growth in developing countries, emphasizing increased investment for SDGs achievement. According to Sahoo et al. (2021), this paper explores CO₂ emissions, electricity consumption, financial development, economic growth, and ICT from 1990 to 2018 in India. The study suggests positive contributions of electricity consumption and negative impacts of ICT on environmental sustainability. Financial development shows a negative relation to CO₂ emissions, supporting the Environmental Kuznets Curve. The findings recommend stringent policies in electricity production and increased investment in the renewable energy sector for environmental preservation.

According to Gupta et al. (2022), rapid economic growth in Bangladesh increases human demand for natural resources, impacting climate change and environmental hazards. This study explores determinants of ecological footprint and PM2.5 between 1990 and 2016, supporting EKC hypothesis with policy implications for environmental sustainability.

According to Rout et al. (2022), over the past three decades, BRICS countries have experienced significant economic activities, technological innovation, and environmental deterioration. This study analyzes the impact of innovation, energy consumption, and financial development on ecological footprint in BRICS nations from 1990 to 2018. Results support the EKC hypothesis and advocate for promoting technological innovation and renewable energy for environmental sustainability.

From Ali et al. (2023), this study investigates the impact of economic structural changes on carbon emissions in Pakistan from 1971 to 2018. Findings suggest that economic expansion and agro production reduce emissions, while urbanization increases carbon dioxide release. Policymakers should promote renewable energy and rural development for environmental sustainability.

According to Villanthenkodath et al. (2021), the findings show a U-shaped impact of economic growth on environmental quality. Urbanization reduces environmental degradation.

The outcomes from this literature review prove that clustering algorithms can provide valuable insights into economic patterns, regional development, and resource allocation. By incorporating ESG factors into the clustering analysis, decision-makers can foster sustainable development practices that consider the environmental, social, and governance dimensions. Overall, the application of machine learning ML in particular clustering models, alongside the consideration of ESG factors, can drive sustainable economic innovation within the India–Gulf interchange. By realizing these models, Decision Makers can improve economic growth, promote sustainable practices, and foster innovation for a more prosperous and sustainable future.

3. Method and results

A comprehensive SWOT analysis allows businesses to identify market opportunities they might have missed otherwise that can be capitalized upon to enhance sustainable economic innovation within the India–Gulf interchange. Lastly, the threats to the interchange’s sustainable economic innovation are analyzed through the SWOT process. These threats may arise from economic, environmental factors that could hinder progress or pose risks to the project’s success. Figure 1 visually represents the integration of the SWOT analysis within the context of sustainable economic innovation through the India–Gulf interchange. The proposed strategic tool in this work enables a systematic evaluation of internal and external factors, guiding decision-making processes and identifying areas for improvement, ultimately fostering a more sustainable and innovative economic landscape within the region.

Figure 1. Proposed SWOT for India–Gulf Interchange.

According to Shannaq et al. (2023), SWOT analysis is a strategic instrument that methodically evaluates Strengths, Weaknesses, Opportunities, and Threats within a context. Its rationality lies in assessing internal factors (Strengths and Weaknesses) and external factors (Opportunities and Threats) to inform decision-making. In our research, SWOT analysis recognizes opportunities and threats for sustainable economic innovation in the India–Gulf interchange, offering strategic insights for enhancing regional development. Summary findings guide recommendations for leveraging strengths, addressing weaknesses, capitalizing on opportunities, and mitigating threats to foster a more sustainable economic landscape.

3.1. The clustering process involves the following three steps

• Develop a dissimilarity matrix (Dm): The Dm is created by determining the dissimilarity or distance between each pair of objects in the dataset. This matrix serves as the basis for subsequent clustering steps.

• Select clustering method: Once the Dm is established, the next step is to choose an appropriate clustering method. There are various clustering algorithms available, each with its own strengths and limitations. Different methods, such as hierarchical clustering, k-means clustering, may be considered based on the specific requirements of the analysis.

• Assessment of clusters: In this step we assess the quality and validity of the resulting clusters. Cluster evaluation involves analyzing the internal cohesion and separation of clusters, as well as examining the stability and reliability of the clustering results. Various evaluation measures, such as silhouette coefficient, Dunn index, or cluster validation indices, can be employed to assess the effectiveness and appropriateness of the clustering solution.

By following these methodology steps, the clustering process can be carried out systematically, ensuring the reliability and accuracy of the clustering results. The construction of a dissimilarity matrix lays the groundwork, followed by the selection of an appropriate clustering method, and finally, the evaluation of the obtained clusters to determine their quality and suitability for the given dataset.

3.2. Data collection

The source data for ESG (Environmental, Social, Governance) for selected gulf countries and India have been collected from: (Worldeconomics.Com - Rankings ESG, n.d.). All relevant data descriptions and information can be accessed from the provided link. Table 1 visually presents the information regarding the variables used in the collected dataset. A total of 21 variables have been selected for analysis, encompassing both string and numeric data types.

Table 1. Data set variable details.

Variables	Type
Country	String
GRADE_E	Numeric
WORLDECONOMICSEMISSIONSINDEX	Numeric
CARBONEMISSIONSTOTAL	Numeric
METHANEEMISSIONSTOTAL	Numeric
AIRQUALITYPM25	Numeric
WATERACCESSOFPOP	Numeric
GRADE_S	Numeric
WORLDECONOMICSSOCIALINDEX	Numeric
LIFEEXPECTANCY	Numeric
MEDIANAGE	Numeric
YEARSOFSHOOLINGAVERAGE	Numeric
EDUCATIONSPENDOFgdp	Numeric
POPULATIONEMPLOYMENTINWORK	Numeric
POVERTYINPOVERTY	Numeric
GRADE_G	Numeric
WORLDECONOMICSGOVERNANCE	Numeric
CORRUPTIONLEVELSINDEX	Numeric
RULEOFLAWINDEX	Numeric
PRESSFREEDOMINDEX	Numeric
POLITICALRIGHTSINDEX	Numeric

Table 2 provides a sample of the collected data pertaining to ESG factors, namely Environmental, Social, and Governance, for the countries in the Gulf region as well as India. ESG, denoting Environment, Social, and Governance, encapsulates a corporate development strategy emphasizing transparency, environmental stewardship, and social responsibility. Originating in 2004, proposed by Kofi Annan during his tenure as UN Secretary-General, ESG gained traction globally. The "Who Cares Wins" initiative urged CEOs to integrate these principles, a movement widely adopted over the past two decades. ESG principles serve diverse purposes, attracting investment, shaping PR strategies, fostering customer loyalty, and enhancing employer branding. In practice, ESG involves ecological considerations like zero-waste production, social aspects such as fair treatment of employees, and governance elements like transparency and anti-corruption policies.

Table 2. Sample of dataset about ESG.

Country	GRADE_E	WORLD ECONOMICS EMISSIONS INDEX	CARBONE MISSIONS TOTAL	METHANE EMISSIONS TOTAL	AIR QUALITY PM25	WATER ACCESS OF POP	GRADE_S	WORLD ECONOMICS SOCIAL INDEX	LIFE EXPECTANCY	MEDIAN AGE
UNITED ARAB EMIRATES	65	97.00	204.08	50.95	42.00	100.00	100	94.70	82.00	29.00
BAHRAIN	75	99.10	39.02	18.55	52.00	98.00	85	84.80	79.00	33.00
QATAR	65	98.70	95.67	22.21	59.00	100.00	85	81.20	79.00	33.00
OMAN	65	98.80	80.97	21.26	35.00	100.00	85	80.10	73.00	29.00
KUWAIT	65	98.50	106.15	25.41	64.00	100.00	75	74.40	79.00	38.00
SAUDI ARABIA	50	92.40	672.38	113.80	57.00	56.00	65	64.40	77.00	30.00
INDIA	50	60.60	2709.67	668.84	50.00	99.00	65	51.30	67.00	28.00

1. ESG Principles in Corporate Concerns:

   • Create awareness of environmental sustainability in their operations.

   • Evaluating organization based on ESG principles, encompassing environmental, social, and governance aspects.

2. Definition of ESG:

   • ESG as the practice of evaluating significant environmental, social, and governance issues during the investment process.

   • ESG aims to enhance financial returns while considering positive social/environmental performance and governance practices.

3. Increasing Media Coverage and Public Awareness:

   • Companies are striving to align with sustainable practices, contributing to increased media coverage of green initiatives.

   • A growing desire for sustainable investments is evident, with global investors applying ESG principles to a significant portion of their portfolios.

4. Evaluation of ESG Criteria:

   • Environmental criteria assess a company’s energy use, waste management, pollution, and conservation efforts.

   • Social criteria analyze business relationships, community contributions, and employee well-being.

   • Governance criteria focus on transparent accounting, shareholder involvement, and ethical business practices.

5. Prioritization and Challenges:

   • Investors have to prioritize ESG factors based on individual values and preferences.

   • Set ESG criteria priorities, avoiding companies engaged in unsustainable practices.

6. Pros and Cons of ESG Criteria:

   • Historically, limitations existed on eligible companies for investment, impacting potential profits.

   • ESG criteria gain practical significance, helping investors avoid risks and reputational damage associated with ethical lapses.

7. Success Stories and Brand Recognition:

   • Brands adopting sustainable practices receive positive ESG ratings.

8. Exclusions Based on ESG Ratings:

   • Some Industries may struggle to achieve high ESG ratings.

3.3. Experiment setting

The proposed work utilize the Hierarchical Cluster Analysis as investigated by Shannaq et al. (2020) and Shannaq et al. (2019) was performed with the Centroid clustering method. The Euclidean distance (ED) interval have been utilized to measure the dissimilarity between data points. Additionally, to ensure consistency and comparability, the data was standardized using a range of −1 to 1. This standardization process facilitated the rescaling of the data to a more manageable range of 0–1.

3.4. Experiment output

Figure 2 demonstrates the Dm, this matrix provides an overview of the dissimilarities or distances between every pair of data points within the database. It serves as a an important foundation for conducting the clustering analysis, allowing for the identification of patterns and relationships among the data.

Figure 2. Dissimilarity matrix.

Based on the dissimilarity matrix, the cluster membership cases have been generated, assigning each data point to a specific cluster. Figures 3 and 4 visually represents the outcomes obtained from this clustering process, providing a clear visualization of the clustered data points and their corresponding memberships.

Figure 3. The generated cluster membership.

Figure 4. Number of clusters per country.

The dissimilarity matrix (Dm) shows the variations or dissimilarities among particular data within the dataset. Figure 4 shows that India and Saudi Arabia exhibit a level of proximity, suggesting similarities in their environmental, social, and

Governance factors: On the other hand, Oman, Qatar, and Kuwait show a strong correlation in their ESG characteristics, indicating shared sustainable practices. Bahrain and the United Arab Emirates form distinct clusters, signifying unique ESG profiles compared to the other countries examined in the analysis. The outcomes of experiment include the following:

Calculation of the Dissimilarity Matrix: We successfully computed the dissimilarity matrix, which serves as the Foundation for the clustering process. This matrix captures the dissimilarities or distances between each pair of data points in the dataset. Exploration of Agglomerative Hierarchical Clustering Methods: We experimented with agglomerative method of hierarchical clustering. This approach allowed us to merge or split clusters iteratively based on their similarity or dissimilarity, resulting in a hierarchical structure of clusters.

3.5. The framework from the experiments for advance sustainable economic

Figure 5 illustrates the newly devised framework for future development, which strives to advance sustainable economic innovation through the India–Gulf interchange.

Figure 5. The proposed framework for advance sustainable economic innovation through the India–Gulf interchange.

The Eco-Wellness Hub prioritizes the development of various sustainable initiatives, including the establishment of Green Health Centers, fostering Green Culture & Religions, and creating Green Research and Education Centers. These efforts are geared towards promoting holistic well-being, environmental consciousness, and knowledge advancement in sustainable practices. Green Health Centers within the Eco-Wellness Hub focus on providing healthcare services that prioritize environmental sustainability. These centers aim to incorporate eco-friendly practices, such as energy efficiency, waste reduction, and the use of environmentally safe materials, to ensure both patient well-being and ecological harmony. In calculation, the Eco-Wellness Hub seats standing on promotion Green Culture & Religions. This involves encouraging environmental awareness, conservation ethics, and sustainable values within cultural and religious contexts. By integrating green philosophies into cultural and religious practices, the Eco-Wellness Hub aims to encourage a collective awareness of environmental accountability and encourage sustainable behaviors. When public are prepared with knowledge and thoughtful, they are more likely to involve in eco-friendly practices, such as energy conservation, waste reduction, and responsible consumption.

4. Discussions

The research question "How can machine learning techniques be leveraged to drive sustainable economic innovation and foster strategic partnerships between India and the Gulf regions?" is addressed through the utilization of machine learning clustering techniques, specifically hierarchical clustering, within the SWOT analysis framework. Although the paper’s title initially suggested the exploration of machine learning models, the study employs a clustering approach due to its suitability for analyzing complex datasets and identifying patterns. The SWOT analysis identifies opportunities and threats for sustainable economic innovation, guiding strategic decision-making. By clustering countries based on ESG factors, the study reveals distinct patterns, highlighting similarities and differences in environmental, social, and governance practices. Through this approach, the research contributes to understanding the ESG landscape of the India–Gulf interchange, offering insights for future policy considerations and fostering sustainable development. The clustering methodology enables systematic analysis and interpretation of data, facilitating informed decision-making and promoting strategic collaborations for driving economic innovation and addressing regional challenges.

Our analysis reveals compelling indications of Saudi Arabia’s trajectory towards advancement, notably exemplified by its Vision 2030 initiative. The proposed tool as a strategic roadmap could identify objectives aimed at fostering economic diversification and catalyzing social transformation. Proposed an initiative to reduce the reliance on oil revenues, alongside concerted efforts to stimulate private sector expansion and bolster female workforce participation. Moreover, Saudi Arabia’s engagement in forging global tech replace and investment in burgeoning sectors like renewable energy, tourism, and entertainment underscores its commitment to modernization and economic evolution. Recent reports highlight a surge in foreign investment and the development of new economic zones, indicative of Saudi Arabia’s proactive stance in fostering a conducive business landscape and attracting international capital. Through these multifaceted endeavors, Saudi Arabia is poised to emerge as a pivotal regional player in innovation and economic progress, with the potential to rival, if not surpass, the economic prominence and diversification of UAE Dubai in the foreseeable future.

The study’s findings shed light on the untapped potential for sustainable economic innovation through collaboration between India and the Gulf regions. By leveraging machine learning clustering techniques, particularly in the context of SWOT analysis, the study identifies key factors and opportunities for driving sustainable development. These findings contribute to the existing body of knowledge by offering a tailored model methodology specifically designed for the India–Gulf interchange. Additionally, the study underscores the importance of strategic partnerships and addresses critical environmental, social, and governance factors. The proposed paradigm for future development offers a forward-looking approach to addressing these challenges and highlights the significance of cross-regional learning and collaboration in achieving long-term economic prosperity and environmental well-being. Through this collaborative approach, the study aims to empower entities and communities to move towards a more sustainable and fulfilling future.

The formation of new Green Research and Instruction Centers is maintained by evidence highlighting their important role in promoting a new and improved quality of life. By promotion research and education in sustainability, we can drive optimistic change, empower people and entities, and create a more environmentally responsive future for human occupancy. Inspiring tourists to involve in activities that deference and preserve the natural and cultural tradition of destinations aids to minimize negative effects on ecosystems and local communities. By promotion ecological tourism, we can contribute to the conservation of biodiversity, care local economies, and raise awareness about sustainable travel practices.

In general, the proposed model seeks to improve the excellence of life for the people by integrating strategies that focus on sustainable transportation, environmentally friendly construction, and the promotion of ecological tourism. By implementing these measures, we can move towards a more sustainable and fulfilling future for entities and communities alike.

The interchange of practices and best practices among India and the Gulf regions is vital for several reasons. Firstly, by interchanging the best problem-solving practices and always-refining approaches, both regions can reach greater competitive advantages. By learning from the strengths of India and the Gulf regions, we can discourse the weaknesses and threats predominant in the Gulf regions. This information transfer will help optimize strategies and control the best practices for sustainable development.

By combining the best practices, enhancing resources, and exploiting on opportunities, we can successfully achieve the goal of a sustainable paradigm for future development.

There is no doubt that the interchange of experiences amongst India and the Gulf regions will foster cross-regional learning, interaction, and growth towards a sustainable future. Through this collaborative approach, we can unlock the complete credible of both regions and cover the way for long-term economic wealth and environmental well-being.

4.1. Policy implications and recommendations

• Establishment of Green Research and Instruction Centers:

  The evidence supporting the crucial role of Green Research and Instruction Centers in enhancing the quality of life suggests the need for their widespread establishment. Governments and organizations should consider investing in and supporting the creation of such centers to promote research and education in sustainability.

• Promotion of Ecological Tourism:

  Encouraging tourists to engage in activities that respect and preserve the natural and cultural heritage of destinations is vital. Governments, tourism boards, and local communities should collaborate to promote ecological tourism, contributing to biodiversity conservation, supporting local economies, and fostering awareness of sustainable travel practices.

• Enhancing Sustainability through Interregional Collaboration:

  The interchange of practices and best practices between India and the Gulf regions is essential for sustainable development. Governments and stakeholders should focus on exchanging problem-solving practices, refining strategies, and optimizing resources. Collaborative efforts can lead to the development of a sustainable paradigm for the future, addressing challenges and leveraging the strengths of both regions.

These recommendations aim to guide decision-makers, governments, and organizations toward actions that foster sustainability, responsible governance, and positive environmental impact.

5. Conclusions

Our research findings unveil a compelling theoretical and logical inference: the observed progress in Saudi Arabia can be attributed, in part, to its alignment with certain developmental strategies akin to those employed by India. This parallel suggests that India may serve as a benchmark or "best practice" model for future development endeavors, particularly for other Gulf countries seeking similar advancements. Encouragingly, this implication underscores the potential for enhanced collaboration across various domains between India and other Gulf nations. By leveraging India’s successful strategies and fostering cross-regional partnerships, Gulf countries stand to gain valuable insights and synergies that can catalyze their own socio-economic progress and innovation.

After thorough examination of the experimental results, it is evident that distinct clustering patterns emerge based on the ESG factor among the countries under analysis. The results show that India and Saudi Arabia demonstrate similar activites in their ESG characteristics, indicating similarities in environmental, social, and governance practices. Similarly, Oman, Qatar, and Kuwait form a strong cluster, with shared ESG attributes within this group. Bahrain and the United Arab Emirates, however, exhibit individual clustering, signifying unique ESG profiles for each country.

These findings offer valuable insights into the ESG landscape of the analyzed countries, informing future research and policy considerations pertaining to sustainable development and responsible governance. The proposed framework for advancing sustainable economic innovation through the India–Gulf interchange holds promise in addressing the challenges faced by the emerging green economy.

To facilitate sustainable development, substantial investment on a larger scale than currently observed is imperative. It is likely that the financial sector will undergo various transformations, including the implementation of new regulations, standards, and requirements. Moreover, there will be increased emphasis on the historical origins, ethical considerations, and climate footprint of financial activities.

In summary, our study underscores the importance of understanding the ESG dynamics within the India–Gulf interchange for driving sustainable economic innovation. By leveraging these insights, stakeholders can make informed decisions that contribute to the advancement of responsible governance and environmentally sustainable practices. However, it is crucial to acknowledge the limitations of our study and encourage further research in this area to deepen our understanding and enhance the effectiveness of future policy interventions and business strategies.

Author’s Contributions

The main author Dr. Ibrahim Al shamsi and the co author Dr. Boumedyen perform all research work.

Institutional review board statement

The study did not require ethical approval.

Informed consent statement

The study did not involve humans.

Acknowledgments

I would like to express our heartfelt gratitude to the University of Buraimi and the College of Business for their unwavering support and motivation in our research publications. We are immensely grateful to the faculty members of the College of Business for their diligent efforts in reviewing and evaluating the proposed research work. Their valuable suggestions and comments have significantly enriched the outcome of this research. We extend our deepest appreciation for their guidance and encouragement throughout this endeavor.

Disclosure statement

The authors declare no conflict of interest.

Data availability statement

https://www.worldeconomics.com/Indicator-Data/ESG.

Additional information

Notes on contributors

Ibrahim Rashid Al-Shamsi

Dr. Ibrahim Rashid Al-Shamsi, University of Buraimi email at uob.edu.om. Dean of College of Business PhD, Associate Professor in Management and HRM. http://taerproject.com/. Smart MIS Demo http://aerstore-001-site2.itempurl.com/AACR.aspx.