Pricing strategies remain one of the most critical levers for business performance, particularly in rapidly growing emerging markets where consumer heterogeneity, income disparities, and evolving digital ecosystems shape demand in unpredictable ways. This paper investigates how big data analytics can be applied to predict and optimize pricing strategies in such markets. By integrating regression analysis, analysis of variance (ANOVA), and correlation methods, the study demonstrates how large-scale data provides actionable insights into consumer price sensitivity and elasticity. The analysis, conducted on a representative dataset of pricing and sales variables, reveals a strong negative relationship between discounted price and sales volume, confirming the theoretical expectations of demand elasticity. Furthermore, ANOVA results illustrate significant differences in sales outcomes across discount levels, underscoring the importance of predictive discounting strategies. Beyond statistical results, this study contributes to the theoretical discourse on big data-driven pricing by emphasizing its value in contexts characterized by market volatility and limited traditional infrastructure. Unlike static models that often fail in diverse markets, predictive analytics offers firms the ability to adjust prices dynamically, test discount scenarios, and anticipate consumer reactions in near real time. For practitioners, the findings provide evidence-based guidance on implementing big data techniques to achieve higher profitability, enhanced customer satisfaction, and stronger competitive positioning in emerging economies. For scholars, the research enriches the growing body of knowledge on predictive pricing by situating it within data-constrained yet opportunity-rich environments.

The field of sentiment analysis has advanced rapidly with machine-learning and deep-learning approaches, yet practitioners continue to face significant operational and conceptual challenges. This study seeks to identify and categorise these perceived challenges from the viewpoint of professionals engaged in analytics. A questionnaire comprising 17 statements were administered to 342 participants and exploratory factor analysis (EFA) was applied. The results reveal seven latent dimensions: Model Trustworthiness, Adaptive Handling, Linguistic Responsiveness, Nuanced Ethical Recognition, Negation & Bias Navigation, Emotional Depth & Balance, and Comprehensive Performance. Together these factors explain approximately 79.8 % of the variance. The factors highlight that sentiment-analysis obstacles are less about raw accuracy and more about trust, context-adaptation, language nuance, ethics and evaluation frameworks. Theoretically, the study contributes an empirical challenge-framework for sentiment analysis. Practically and in policy terms, the findings point to the need for more transparent, adaptable and ethically-aware sentiment systems.

This bibliometric study explores the evolving landscape of green marketing research, focusing on cross-cultural and regional trends over the past two decades. By analysing a comprehensive dataset of scholarly publications from SCOPUS and Web of Science, this research identifies key themes, influential authors, and geographic patterns in the field. The study employs co-citation analysis, keyword co-occurrence, and thematic mapping to uncover the intellectual structure and emerging areas of interest. Findings reveal significant variations in green marketing adoption and research focus across different cultural and regional contexts, with western economies emphasizing consumer behaviour and sustainability, while emerging economies prioritize regulatory frameworks and eco-innovation. The analysis also highlights the growing interdisciplinary nature of green marketing, integrating insights from environmental science, psychology, and economics. This study contributes to the literature by providing a holistic view of the field’s evolution, identifying research gaps, and offering directions for future studies. The insights generated are particularly valuable for policymakers, marketers, and researchers aiming to align green marketing strategies with cultural and regional nuances to foster sustainable consumption.

This research investigates the relationship between investments in human capital and employee brand advocacy at Tata Consultancy Services (TCS) over the period of 2020-2025. Drawing on Stakeholder, Social Exchange, and Signalling Theories, a mixed-methods approach was taken, consisting of secondary data extracted from TCS Annual Reports and Sustainability Reports, along with qualitative data obtained from organizational traineeship initiatives. Overall findings showed the training participation rates, engagement scores, and advocacy levels grew vigorously throughout commerce from 2020-2025. Regression analysis supported employee engagement as a mediating variable along with digital platforms acting in a moderator role to enhance advocacy behavior. Qualitative data, including the #TCSSpirit project and leadership-led initiatives corroborated the findings. In conclusion, investments in structured human capital, along with continued learning, digital enablement, and leadership engagement can sustainably support employee advocacy; strengthen the employer brand; provide competitive advantage to IT service organizations in an era of digital services.

Employee retention has emerged as a critical challenge for India’s IT sector, particularly among firms listed in the Nifty 50 index that employ a large and diverse workforce. This study examines employee retention practices and gender-wise retention trends across five leading IT companies—Tata Consultancy Services, Infosys Technologies Ltd., Wipro Ltd., Tech Mahindra Ltd., and HCL Technologies Ltd.—during the period 2020–2025. The research adopts a descriptive and analytical design, relying exclusively on secondary data collected from annual reports, HR disclosures, and industry publications. Descriptive statistics and trend analysis were applied to evaluate gender-wise and overall retention rates, while a Two-Way ANOVA without replication tested the significance of retention variations across companies and years. The findings reveal notable fluctuations in retention rates, with sharp declines during the post-pandemic period (2021–2023), reflecting the impact of the “Great Resignation” and intensified global competition for digital talent. TCS demonstrated relative stability, Infosys and HCL showed strong recovery in later years, while Wipro and Tech Mahindra exhibited inconsistent patterns. Gender-wise analysis indicates that while male and female retention trends generally moved in parallel, female employees experienced sharper declines in certain years. Statistical results, however, indicate that differences across years and companies were not significant, suggesting that broader industry-wide factors shaped retention more than firm-specific policies. The study contributes to the literature by providing a comparative, gender-sensitive, and statistically validated analysis of retention in top Indian IT firms. Practical implications highlight the need for consistent, long-term retention strategies that go beyond reactive measures, focusing on employee engagement, flexible work models, and inclusive policies to sustain workforce stability.

Over the past decade India has embarked on one of the largest consolidations of labour legislation in the world, merging 29 central laws into four comprehensive labour codes: the Code on Wages, 2019; the Industrial Relations Code, 2020; the Occupational Safety, Health and Working Conditions Code, 2020; and the Code on Social Security, 2020. The reforms promise administrative simplification, clearer definitions, and wider social protection, alongside a more predictable framework for enterprises and investors. Yet, full implementation remains pending in October 2025, primarily because both the Union and the states must notify rules and a common commencement date under India’s federal scheme. This paper situates the labour codes within the broader literature that links legal reform to development, explains the codes’ major design choices, examines their likely socioeconomic effects and distributional consequences, and analyses the principal obstacles that have slowed their roll-out. It shows how the same features touted as business-friendly simplifications may, if poorly sequenced or weakly enforced, undercut worker voice and dilute substantive protections in practice. The paper concludes with pragmatic recommendations to bridge centre–state gaps, strengthen inspection and data systems, ring-fence social security for unorganized and platform workers, and align the codes with India’s human-capital and inclusion agenda.

The blistering development of social media has changed the digital marketing environment and shifted the emphasis to micro-influencers with limited following but with a high engagement level. The following research paper, The Power of Micro-Influencers: Rethinking Digital Marketing ROI, discusses how micro-influencers redefine the concept of return on investment (ROI) by means of authenticity, trust, and community-specific interactions. Based on the recent research on marketing analytics, theory of consumer behaviour and case study in the industries, the research proposes to explore how micro-influencers are more effective than traditional celebrity endorsements in delivering meaningful consumer interactions and long-term brand loyalty. The paper sheds light on the mechanisms involved in ensuring that micro-influencers create value namely the relevance of the content, the perceived credibility, and the communication anchored on relationships. It also looks at the way digital marketers can successfully track non-traditional ROI metrics, including the quality of engagement, sentiment analysis, and consistency of conversion, as opposed to reach and impressions. It has been found out that although macro-influencers provide a wide reach, micro-influencers offer better engagement rates and also genuine consumer relations, especially in niche markets. The research also determines the major determinants of successful campaigns, which are influencer-brand compatibility, trust in the influencer, and cohesion in the stories. In qualitative and quantitative terms, the paper reveals that investment in smaller influencer marketing can be more effective in cost terms and sustainable brand promotion than the giant influencer relationships. Finally, this study will help expand the knowledge base of digital marketing strategy, locating micro-influencers as the key resources in the construction of credible and human-oriented brand ecosystems. It concludes that in a digital world that is already overcrowded, authenticity and the power of community is more important to help achieve higher ROI than the size of the audience, which necessitates re-evaluation of established marketing metrics to capture the actual value of digital interaction.

In an era where environmental consciousness increasingly influences purchasing decisions, corporations are compelled to integrate sustainability into their brand narratives. This has precipitated a proliferation of eco-marketing, a landscape simultaneously populated by genuine, substantiated initiatives and the phenomenon of "greenwashing"—where environmental claims are misleading, unsubstantiated, or deceptive. This research paper examines the critical dichotomy between authentic sustainability and greenwashing, with a specific focus on its impact on consumer trust. We argue that the erosion of trust due to perceived greenwashing creates a significant market barrier, not only for the offending firms but for the entire sector, fostering consumer cynicism and skepticism. The paper proposes a conceptual framework for measuring consumer trust, positing that it is a multi-faceted construct influenced by the transparency, specificity, and third-party verification of environmental claims, as well as the perceived consistency between a corporation's marketing and its tangible operational practices. By synthesizing contemporary literature, this analysis aims to provide a metric for discerning credible sustainability communication and to offer strategic insights for businesses seeking to build and maintain authentic, trust-based relationships with the environmentally modern consumer.

One of the most innovative tools for promoting businesses is digital marketing. Their widespread use and deep penetration into human civilization can be attributed to the readily available internet and reasonably priced smart phones. The COVID-19 pandemic has also accelerated the field's growth. Nonetheless, there is still a very low level of public knowledge of digital marketing options and their ability to offer new business opportunities and better promote already-existing ones. The goal of the current study is to comprehend how digital marketing encourages people to start their own businesses. The basic data gathered from India's Telangana region served as the study's foundation. The survey is conducted by gathering responses from around 451 local business owners in order to comprehend their attitudes towards and usage patterns of digital marketing. A conclusion is reached after determining the number of entrepreneurs who succeeded with the aid of digital marketing.

Artificial Intelligence (AI) as an addition to the Human Resource (HR) practice is transforming how things are done in an organization to bring about superior efficiency, predictive analytics, and decision-making. Despite possible beneficial results, the implementation of AI in HR is associated with severe challenges because of organizational preparedness and change management solution, as well as employee resistance. The paper examines a relationship between these two variables with the consideration of determining the determinants that drive or hinder the successful adoption of AI in HR functions. According to the mixed-methods approach, quantitative data were noted in the form of survey among HR specialists representing different industries, and were complemented by qualitative interviews so that some hidden perceptions and experiences could be identified. The findings reveal that the primary reasons which contribute towards employee resistance are job displacement, distrust towards AI systems as well as perceived complexity. It was found that the organizational preparedness, technological infrastructure and leadership support, and competency development programs became a highly significant facilitator of adoption. In addition, change management practices such as open communication, involvement of the stakeholders and on-going training are also proactive and can help to reduce the resistance levels and promote the preparedness. The paper highlights the need to integrate the organizational culture with technological programs and approaches that are human-focused in order to facilitate effective integration of AI. The practical implications on the HR leaders are that it is necessary to evaluate the readiness of the organization, design the change management interventions, and create an adaptive learning environment that promotes the AI processes in the organization. This study helps to add to the body of research on digital transformation in HR, implying practical implications of the study to organizations that want to utilize AI without losing employee engagement and organizational cohesion.

Autonomy in AI can improve trust, scalability, efficiency, and responsiveness. This is particularly pertinent in claims processing and policy servicing, where labour needs are diminishing but demand peaks are increasing. An insurance technology platform that uses agentic AI to automate these activ- ities would enhance the speed, quality, and efficiency of service delivery. If these autonomous systems are made trustworthy, their deployment would not only satisfy current labour shortages but also improve user sentiment in engagements that have traditionally been painful, frustrating, and expensive to manage. Acting on behalf of insurance companies, agentic AI would decide whether a claim should be settled or lead to escalation for further assessment. In the course of a policy life, agentic AI would address servicing requirements such as endorsements, renewals, and compliance checks, adjusting pricing in real time as new information becomes available. These transformations would benefit insurers whose investment in agentic AI remains aligned with the appropriate architectural paradigms—modular architecture focused on business goals, privacy-by-design data architecture, and decision-making frameworks that establish certifiability boundaries in low-risk domains such as claims and servicing. The links between claims processing, policy servicing, and architectural paradigms are further explored in the corre- sponding sections. Index Terms—Agentic Artificial Intelligence, Autonomy, Trust- worthy AI, Insurance Technology, Claims Processing, Policy Ser- vicing, Scalability, Efficiency, Responsiveness, Labour Shortages, Service Automation, Decision-Making Frameworks, Privacy-by- Design, Modular Architecture, Real-Time Pricing, Compliance Checks, User Experience, Certifiability Boundaries, Low-Risk Domains, Digital Transformation.

Background: Clinical decision-making is a cornerstone of effective patient care, shaped by evolving research, technological advancements, and practitioner expertise. Evidence-Based Practice (EBP) enhances this process by incorporating the recent evidence with clinical judgment and patient preferences. Despite its proven benefits, EBP adoption remains inconsistent across healthcare settings due to structural, educational, and financial barriers. Objective: This review explores the crucial role of Evidence-Based Medicine (EBM) in strengthening clinical decision-making through the structured five-step model. It examines the primary factors influencing the adoption of EBP among healthcare professionals and evaluates current educational strategies that support its integration into clinical settings. Methods: This is a narrative review. Relevant literature was collected using a triangulation method across multiple electronic databases, including Google Scholar, JSTOR, ScienceDirect, and PubMed. Key findings were synthesized to identify patterns, gaps, and emerging trends. Results: The analysis identified the five-step EBM model such as formulating clinical questions, locating reliable results, critical analysis, application in practice, and evaluation of outcomes as a foundational framework for integrating research into healthcare delivery. Factors influencing the utilisation of EBP include clinician competency, institutional support, access to technology, and time constraints. The review also highlighted gaps in EBP education across healthcare disciplines, underscoring the need for targeted training and capacity-building initiatives. Rapid developments in decision-making tools and practices suggest that the current synthesis reflects a temporal snapshot rather than a comprehensive account. Conclusions: Integrating EBP into clinical decision-making requires a multifaceted approach involving workforce development, strategic financial planning, and institutional commitment. The inclusion of experienced mentors and flexible learning formats can enhance practitioner engagement. Addressing these barriers can enhance the consistency and impact of evidence-informed care. Future research should focus on interdisciplinary comparisons, digital decision-support tools, and longitudinal trends in clinical judgment.

Influencer marketing has rapidly evolved from just another tactic to one of the most dominant forces in advertising and public relations. Its power lies in relatability: The audience these days feel that the influencers are their friends and or kith and kins, which makes them believe that anything that is endorsed is more personal and clumsy than corporate,directed and shot. However, this ecosystem is under scrutiny now and the very building block is being questioned which was Trust. Today’s Gen-Z and Millennials are now increasingly recognising that all of this was well planted with the help of planned PR Strategies, revealing the persuasion techniques. This is now fueling skepticism, a critical lens through which audiences now evaluate digital content. We can now notice the pattern of counter-movement: de-influencing. No it is not just any random social trend, de-influencing has now started shaping brains and becoming a usual phenomenon, especially with the youth like Gen-Z and Millenials, these natives demand authenticity, transparency and facts in whatever data they are consuming. This entire concept of de-influencing is discouraging youth from purchasing products, analyse campaigns better. While positioned as resistance, de-influencing often functions as a subtle redirection of consumer attention, perpetuating the cycle of persuasion in new guises. This research studies the complex relationship between PR Practices, consumer skepticism, and the rise of de-influencing on social media. The study is based on a majorly qualitative research design also incorporating a thematic analysis of 300 de-influencing posts on Instagram and semi-structured interviews with 15 influencers, the paper examines how consumers being skeptical is reshaping PR. Findings suggest that skepticism does not dismantle influencer marketing; rather, it fuels its transformation, forcing practitioners to innovate in authenticity and transparency. Ultimately, this paper argues that consumer skepticism is no longer the enemy of PR—it is its newest collaborator, giving rise to strategies that thrive on reflexivity and critique.

The financial sector that is now present is known as Decentralized Finance (DeFi) and is a result of the high rate of blockchain development and lacks any middlemen, such as a bank or clearing house. DeFi is based on smart contracts and decentralized networks, which facilitate peer-to-peer transactions, lending, and asset management and, thus, reinvent the architecture of traditional banking systems. This analytical essay explores how DeFi can revolutionize the whole world of finance with reference to the opportunities it can promise and the systemic risks involved. It discusses how the open-source protocols of the DeFi technology help to make transactions more transparent, reduce transaction costs and include financial inclusion, in particular in the underbanked regions. Also, consequences of adoption of DeFi in regulatory systems, monetary policy and financial stability will be discussed in the paper. The paper reveals the opportunities of a democratic access to capital in the comparison of the models of centrally and decentrally financed ones and tells about the gaps in the securities, governance and scalability, to which DeFi is likely to be susceptible. It will also reveal the issue of whether DeFi is the complementary system to the conventional banking system or a disruptive alternative by a multidisciplinary approach that will consider the financial theory, technological innovation, and policy analysis. The findings show that although DeFi is effective and open, the potential of its future realization with the world banking system is relative to the establishment of effective regulatory frameworks and compatibility between chains. The paper concludes that DeFi is not a new technological phenomenon, but it is the paradigm shift that could potentially substitute the trust, control, and the distribution of values across the global financial system.

This study explores the vital role of budgetary practices and public finance in promoting the Sustainable Development Goals (SDGs), with a focus on social spending and developmental outcomes in developing countries. By combining theoretical frameworks with comparative analyses, the research shows how transparent and accountable fiscal systems can improve SDG alignment and resilience to external shocks like the COVID-19 pandemic. Evidence from Sri Lanka and Bangladesh reveals notable changes in domestic tax revenues, highlighting both vulnerabilities and adaptive capacities of national budgets during crises. The findings emphasize the need for strong, participatory, and integrated public finance strategies and policy reforms to boost the developmental impact of fiscal priorities. Recommendations include encouraging inclusive budget processes, utilizing digital tools, and strengthening international cooperation to support sustainable and predictable progress toward SDGs.

A diverse workforce is increasingly recognized as crucial for enhancing a firm's performance and has become a necessity that organizations can no longer ignore. It is now widely acknowledged that diversity brings both tangible and intangible benefits, even if it involves addressing associated challenges and costs. Organizational practices related to inclusion have been examined in areas such as recruitment and selection, training and development, and social activities. The present study is based on the secondary information collected from various published sources. The main objective of the study is to analyse the DEIB practices of selected Indian companies. The data were retrieved from the official websites of the selected companies. Diversity is realized through inclusion, which requires that employees feel valued and integrated within an organization. This involves both recognizing and overcoming differences, while appreciating the diverse backgrounds and perspectives of individuals. At the heart of the diversity conversation is the principle of fairness and justice. People have a fundamental need to belong, to be valued, to be treated equitably, and to have their identities recognized. When organizations invest in diversity, they benefit not only in visible and financial ways but also through subtler forms of increased loyalty, enhanced well-being, and the respect they earn in the process. Hence it is very important to study the significant role of DEIB strategies in the workplace in the current scenario.

Since the early 2000s, India has progressively liberalized foreign direct investment (FDI) rules for the insurance sector to attract capital, technology, and global expertise. This dissertation explores how FDI has influenced the structure and functioning of India’s insurance market, using secondary (published) data from IRDAI (insurance statistics), DPIIT (FDI trends), and industry reports (PwC, GIC, Swiss Re, etc.). The work is descriptive and non-technical: it highlights how the market has grown in premium volumes, how insurance penetration has changed, the rising share of private insurers, and the influence of foreign partnerships on products and service quality. Key findings: As of FY2023–24, India’s insurance market collected ₹11.19 trillion in total gross premiums, with non-life premium alone at ₹2.90 lakh crore. The insurance penetration in FY2023–24 was 3.7% of GDP. Private insurers now dominate non-life business (~63% share), while LIC still holds ~64% share in life insurance. FDI policy steps (26% in early 2000s, 49% in 2015, and 74% in 2021) created confidence for foreign partners, leading to improvements in product variety (health insurance, digital offerings, microinsurance), distribution (bank tie-ups, online platforms), and customer service (faster claims). However, challenges remain in reaching rural areas, ensuring governance and fair pricing with foreign investors, and aligning growth with inclusion. This simpler version offers policy guidance: maintain clear and stable FDI rules, require foreign entrants to commit to rural expansion and tech transfer, strengthen IRDAI’s oversight, and improve data transparency (particularly on insurance-specific FDI). The study contributes by weaving together authoritative published figures and industry narratives into a readable, structured story of transformation.

Financial inclusion is central to India’s development agenda, with the Digital India Programme serving as a transformative driver in extending digital financial services to citizens. This research delves into the effects of Digital India on financial inclusion in Karnataka, specifically looking at demographic variables, awareness, adoption, use and obstacles. A total of 175 participants filled out a structured survey, and the results were evaluated using several statistical methods, including t-tests, binomial tests, chi-square tests, and correlation analysis. Findings reveal moderate awareness of Digital India initiatives (52%), though awareness did not significantly influence adoption. The shift to online banking greatly enhanced the availability of financial systems, but had little effect on the management of personal finances and the elimination of cash. There was no discernible correlation between adoption and demographic variables like gender, age, or income, and no notable hurdles were identified in terms of technical difficulties, cybersecurity worries, or educational attainment. To guarantee effective citizen empowerment, the report stresses the necessity of better digital infrastructure, greater financial literacy initiatives, and increased awareness campaigns. When it comes to changing people's financial habits, Digital India has increased access, but it needs long-term policy and institutional backing to really shine.

A study is conducted to find out the relationship between emotional intelligence and its impact on job satisfaction, motivation and level of stress among the private Banking sector employees. Private banks employees have been taken as population for the study. Total of 340 sample respondents have provided the feedback. Emotional Intelligence is measured by Wong and law emotional intelligence scale (WLESI) developed by Wong and law (2002) and the Minnesota satisfaction questionnaire (MSQ) scale is used to measure job satisfaction and for occupational job stress self-made questionnaire has been used. Pearson’s correlation, ANOVA and levene's independent sample-T test and factor analysis has been used as statistical tests for data analysis. The conclusion states that there is a significant relationship between emotional intelligence, job satisfaction and motivation. However, emotional intelligence is negatively correlated with stress. It is also concluded that there is significant difference in the dimensions of emotional intelligence with respect to job satisfaction, motivation and stress. Leven’s Independent T-Test results states that Job satisfaction is equivalent between male and female employees of banking sector but there is significant difference in the motivation level and stress between both groups.

The rise of digital media has significantly transformed the dissemination of healthcare information. While the proliferation of online platforms has democratized access to medical knowledge, it has simultaneously amplified the spread of disinformation, posing serious threats to public health. In India, where health literacy varies widely and internet penetration is rapidly increasing, misinformation regarding vaccines, treatments, and disease outbreaks has led to adverse health outcomes and eroded trust in medical institutions. This study explores the current landscape of health journalism in India, identifying the sources, channels, and mechanisms through which healthcare disinformation spreads. Drawing on a mixed-methods approach with a sample of 500 healthcare news articles, social media posts, and public surveys, the research examines the role of traditional media, digital platforms, and journalistic ethics in mitigating misinformation. A conceptual framework is proposed that integrates media literacy, journalistic responsibility, and regulatory mechanisms as foundational pillars for strengthening health journalism. The findings reveal that proactive fact-checking, training in evidence-based reporting, and collaboration between media professionals and healthcare experts are critical for curbing disinformation. The paper concludes with policy recommendations and practical strategies for enhancing credibility, accountability, and effectiveness in health journalism across India.

The fast-changing nature of supply chains across the world has made it more complicated, uncertain, and vulnerable to disruption, and thus real-time visibility and active risk management are vital to sustainable operations. The Internet of Things (IoT) has become a disruptive technology able to solve these issues by facilitating smooth connectivity, data collection, and automation of processes throughout supply chains networks. The paper provides insights into how the IoT can be used to improve supply chain visibility and reduce risks by combining smart sensors, cloud-based applications, and sophisticated analytics. IoT-created data streams in real-time facilitate inventory, transportation, and production follow-up to enable firms to spot deviations, predict bottlenecks, and react to threats more swiftly. Moreover, predictive insights with the help of IoT enhance decision-making in demand forecasting, quality control, and supplier performance management. The paper identifies resilient supply chains as one way through which organizations can harness the power of IoT to create supply chains that can adapt to dynamic market environments, environmental uncertainty and geopolitical interruptions. Industrial evidence of the use of IoT in manufacturing, logistics, and retail industries shows that the integration of IoT can significantly decrease lead times, enhance traceability, and compliance with regulations. Other challenges like cybersecurity threats, data integration problems, and high implementation costs that should be considered to maximize the potential of IoT are also highlighted in the discussion. In general, the results indicate that the IoT-based supply chain visibility is the solution that can not only benefit operational efficiency but also reinforce the risk management strategies, thus ensuring a competitive edge in any unstable global markets.