The Journal of Strategic Business Research (JSBR) is a peer-reviewed scholarly publication dedicated to advancing knowledge and practice in the field of strategic management, business innovation, and organizational development. It publishes original research articles, case studies, and reviews that address contemporary challenges in business strategy, corporate governance, entrepreneurship, marketing, finance, and global business trends. The journal aims to bridge the gap between academic theory and practical application, providing insights for researchers, practitioners, policymakers, and educators. JSBR welcomes multidisciplinary perspectives and promotes the dissemination of high-quality research that supports strategic decision-making in dynamic and competitive business environments.
Trusted Multi-Agent Generative AI for Real-Time Defense of U.S. Digital Payments: A Privacy-Preserving Governance Framework for Critical and Emerging Financial Technologies
The proliferation of autonomous, LLM-based multi-agent systems in financial services introduces critical challenges in verifying authenticity, intent, and overall system integrity, particularly within decentralized, trustless environments where emergent behaviors and opaque decision-making undermine regulatory compliance and operational safety. This study addresses the observability and control gap inherent in such systems by proposing, implementing, and empirically validating a novel Runtime Governance Framework predicated on the architectural separation of agent cognition from external policy enforcement. The framework operates through a non-bypassable governance layer that intercepts all agent actions, applies dynamic constraint-based controls, mandates cryptographic audit logging of chain-of-thought reasoning artifacts, and continuously monitors system behavior using real-time deviation scoring to enable runtime intervention and targeted machine unlearning. Empirical evaluation was conducted within a high-fidelity simulation environment replicating financial crime compliance workflows, comparing governed and ungoverned configurations across nine performance dimensions. Results demonstrate that the governed system achieves transformative improvements: regulatory action violations decrease by over eighty percent, decision traceability surges from negligible to near-perfect coverage, adversarial prompt success rates fall by eighty percent, hallucination rates drop by nearly eighty percent, anomaly detection latency improves sevenfold, and return on security investment exceeds four to one—indicating that every dollar invested in governance yields over four dollars in avoided losses and operational savings. While the framework introduces a predictable latency overhead, this trade-off is acceptable for asynchronous compliance workflows and is substantially outweighed by the operational efficiencies, regulatory safeguards, interpretability gains, and system stability achieved. This research provides a validated architectural blueprint for the secure, trustworthy, and compliant deployment of autonomous agentic AI in regulated financial environments, establishing that effective governance must be external, enforceable, and runtime-adaptive rather than static and pre-deployment focused.
Copyright (c) 2026 Md sajedul karim chy (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Evaluating the Challenges and Opportunities of Implementing ESG (Environmental, Social, Governance) Metrics in Corporate Financial Strategies
The integration of Environmental, Social, and Governance (ESG) factors into corporate financial strategies has gained increasing importance as firms and investors seek to align financial performance with sustainability objectives. This study empirically investigates the impact of ESG performance on corporate financial outcomes, market valuation, and risk characteristics using a mixed-methods experimental framework that combines panel econometric analysis with machine learning techniques. Drawing on firm-level data from OECD economies, the results reveal a robust positive relationship between ESG performance and key financial indicators, including return on assets, return on equity, and Tobin’s Q. The findings further demonstrate that higher ESG scores are associated with lower firm-level risk and volatility, highlighting the risk-mitigating role of sustainable business practices. Governance quality is identified as a dominant driver of financial stability, while regulatory stringency significantly strengthens the ESG–financial performance nexus. Sectoral analysis confirms heterogeneous effects across industries, with sustainability-oriented gains being more pronounced in technology and manufacturing sectors. The application of machine learning models enhances predictive accuracy and captures non-linear relationships between ESG dimensions and financial outcomes, offering methodological advancements over conventional approaches. Robustness analyses confirm the consistency of results across alternative specifications. Overall, the study provides compelling evidence that ESG integration contributes to sustainable value creation, improved risk management, and long-term corporate competitiveness, offering important insights for policymakers, investors, and corporate decision-makers in the evolving landscape of sustainable finance.
Copyright (c) 2025 https://creativecommons.org/licenses/by-nc-nd/4.0
Assessing the Impact of Blockchain Technology on Financial Transparency and Fraud Prevention in the Banking Sector
This study empirically examines the impact of blockchain technology on financial transparency and fraud prevention in the banking sector using a mixed-method experimental research design. By integrating quantitative panel data analysis with qualitative institutional insights, the study evaluates how blockchain adoption influences fraud incidence, audit efficiency, regulatory compliance, and operational performance. The quantitative results reveal a significant inverse relationship between blockchain adoption intensity and fraud occurrence, alongside measurable reductions in audit duration and operational costs. Banks utilizing blockchain-based systems demonstrate higher compliance scores and improved transaction integrity due to the immutability, decentralization, and cryptographic security inherent in distributed ledger technology. Graphical and tabular analyses further confirm that real-time visibility and automated verification mechanisms enhance fraud detection speed and reduce reporting errors. Qualitative findings support the empirical results by highlighting improved governance, accountability, and audit reliability in blockchain-enabled banking environments. Overall, the study finds that blockchain technology substantially strengthens financial transparency, mitigates fraud risks, and enhances trust in banking systems. These findings provide strong evidence that blockchain adoption can deliver both operational and regulatory benefits, making it a critical enabler of secure and transparent digital finance. The study contributes to the growing body of literature by offering empirical validation of blockchain’s role in modern banking and providing practical insights for policymakers, regulators, and financial institutions.
Investigating the Role of Artificial Intelligence in Predicting Financial Crises and Enhancing Risk Management in Global Markets
The increasing complexity, interconnectedness, and volatility of global financial markets have exposed the limitations of traditional risk management and crisis prediction approaches. This study investigates the effectiveness of artificial intelligence–driven models in enhancing financial risk forecasting and stability through an experimental mixed-method framework. Using large-scale financial, macroeconomic, and market-based datasets, multiple machine learning and deep learning models were developed, trained, and evaluated under identical experimental conditions. The empirical results demonstrate that AI-based models consistently outperform conventional statistical techniques in terms of predictive accuracy, robustness, and adaptability, particularly in capturing non-linear dependencies and emerging vulnerabilities within financial systems. The findings further reveal that AI-powered real-time risk monitoring significantly reduces anomaly detection time, thereby improving responsiveness during periods of market stress. Comparative analysis across nine performance tables and twelve complex visualizations confirms the reliability and generalizability of the proposed framework across diverse risk scenarios. Despite these performance gains, the study identifies key implementation challenges, including model interpretability, data governance, and integration with existing financial infrastructures. Overall, the results confirm that artificial intelligence represents a transformative tool for proactive financial risk management and crisis prevention, offering substantial improvements in decision accuracy, resilience, and regulatory effectiveness. The study provides valuable empirical insights for financial institutions, regulators, and policymakers seeking to harness AI for sustainable financial stability.
Analyzing the Impact of Trade Wars on Financial Stability and Investment Strategies in International Markets
This study empirically investigates the impact of trade wars on global financial stability and investment strategies using a comprehensive mixed-methods framework and advanced econometric techniques. Employing global financial market data, trade policy uncertainty indices, and sectoral investment indicators, the analysis captures both volatility dynamics and cross-market spillover effects associated with trade war episodes. The results reveal that trade wars significantly increase financial market volatility, reduce equity returns, and disrupt cross-border capital flows, with particularly strong effects observed in emerging and export-dependent economies. GARCH-based estimations confirm persistent volatility clustering following trade-related policy shocks, while Quantile Vector Autoregression results highlight pronounced asymmetric effects across different market conditions, especially during bearish regimes. Wavelet coherence analysis further demonstrates strong short- and long-term co-movements between trade policy uncertainty and financial market instability. Sectoral and firm-level evidence indicates that heightened uncertainty discourages irreversible investments, particularly in manufacturing and renewable energy sectors. Overall, the findings suggest that trade wars act as powerful external shocks that reshape global investment behavior, intensify risk aversion, and challenge macro-financial stability. The study offers important insights for policymakers and investors by emphasizing the need for transparent trade policies, robust institutions, and coordinated international strategies to mitigate the adverse financial consequences of escalating trade conflicts.
The Role of Behavioral Economics in Shaping Investment Decisions in Emerging Financial Markets
This study investigates the role of behavioral economics in shaping investment decision-making in emerging financial markets, with a particular focus on the interaction between behavioral biases, digital finance adoption, financial literacy, and machine learning applications. Using a mixed-methods experimental approach, the study integrates investor-level behavioral data, market performance indicators, sentiment measures, and computational modeling techniques. The results reveal that behavioral biases such as herding, loss aversion, and overconfidence significantly influence investment outcomes, contributing to return volatility and suboptimal portfolio decisions. Digital adoption is found to improve investment performance on average, yet it does not fully mitigate behavioral distortions, especially under heightened market sentiment. Financial literacy plays a crucial moderating role, reducing bias-driven inefficiencies and stabilizing returns. Furthermore, machine learning models augmented with behavioral and sentiment variables demonstrate superior predictive accuracy compared to traditional finance-based models, underscoring the value of behavior-aware computational frameworks. Despite these gains, the findings highlight persistent challenges related to data limitations and model interpretability in emerging markets. Overall, the study provides strong empirical support for integrating behavioral insights with advanced analytical techniques to improve investment prediction, policy design, and financial decision-making in emerging economies.
Cybersecurity Risks and Their Implications for Financial Technology Firms
The digital-first nature of financial technology (fintech) firms has accelerated innovation in payments, lending, asset management, and blockchain-based services, but it has simultaneously heightened their exposure to cybersecurity risks. This study investigates the nature and implications of these risks by employing a mixed-method approach that integrates quantitative analyses of cybersecurity incident datasets with qualitative case studies of prominent fintech breaches. The findings reveal that fintech firms face growing threats from phishing, ransomware, social engineering, and cloud vulnerabilities, with financial losses, regulatory fines, and reputational damages disproportionately affecting smaller, innovation-driven firms. Regression models demonstrate that the probability and impact of breaches increase with higher digital interconnectedness and reliance on third-party providers, while qualitative insights underscore the crucial roles of consumer trust, governance, and compliance. The results show that breaches lead to customer attrition, longer recovery times, and heightened compliance costs, while cross-border inconsistencies in regulation exacerbate systemic risks. The discussion highlights that cybersecurity in fintech is not simply a technical challenge but a strategic imperative, where strong governance and proportionate regulation are required to mitigate vulnerabilities. The study concludes that effective cybersecurity frameworks, when combined with regulatory cooperation and consumer education, can transform risks into opportunities for resilience and competitiveness. By reframing cybersecurity as both a defense mechanism and a driver of trust, fintech firms can strengthen their role in a secure, inclusive, and sustainable financial ecosystem.
Copyright (c) 2025 Imran Khalid, Rabia Ahmed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Relationship Between Digital Currencies and Traditional Banking Systems
The rapid development of digital currencies—including cryptocurrencies, stablecoins, and central bank digital currencies (CBDCs)—is transforming the global financial landscape and redefining the role of traditional banking institutions. This study investigates the complex relationship between digital currencies and banking systems through a mixed-method research design, integrating econometric modeling with qualitative case studies. Quantitative analyses reveal that digital currencies exert measurable impacts on deposit structures, lending activity, profitability, and liquidity ratios, while qualitative evidence highlights the importance of regulatory frameworks, institutional capacity, and consumer trust in shaping adoption outcomes. Results show that CBDCs, when carefully designed, can complement rather than replace bank deposits, enabling financial inclusion and efficiency gains while minimizing risks of disintermediation. Conversely, stablecoins pose challenges to monetary sovereignty and financial stability if not adequately regulated. Comparative case studies demonstrate that the effects of digital currencies are highly context-dependent, with advanced economies often benefiting from digital integration while emerging markets face adoption hurdles. The study concludes that digital currencies will not eliminate banks but compel them to evolve as custodians, intermediaries, and compliance facilitators within a hybrid financial ecosystem. The findings underscore that successful integration depends on striking a balance between innovation, regulatory oversight, and societal needs, ultimately shaping a more resilient and inclusive global financial system.
Copyright (c) 2025 Ali Hassan, Sana Qureshi (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Impact of Mobile Payment Systems on Consumer Financial Behavior
The rise of mobile payment systems has fundamentally reshaped consumer financial behavior by altering spending patterns, savings practices, and perceptions of security and convenience. This study employed a mixed-methods approach, combining quantitative transaction data with qualitative insights, to examine how mobile payment adoption influences financial decision-making across demographics. Results demonstrated that mobile payment platforms significantly increase transaction frequency and average expenditure due to their ease of use and accessibility. However, while some consumers benefited from in-app budgeting and savings tools, others reported heightened impulse spending facilitated by frictionless transactions. The analysis also revealed marked regional and demographic disparities: higher-income and financially literate users leveraged mobile payments for structured financial management and investment, while less literate groups were more prone to overspending and exhibited greater concerns about security. Trust in the system emerged as a decisive factor, with consumers perceiving higher levels of security engaging more actively and with larger transaction volumes. Visualizations further confirmed the multidimensional links between convenience, trust, and adoption, while tables highlighted correlations between literacy, income, and financial behavior. Collectively, the findings indicate that mobile payments represent both a tool for financial inclusion and a risk factor for overspending, depending on user characteristics and contextual factors. For policymakers and financial institutions, the results emphasize the need to enhance digital financial literacy, strengthen consumer protection frameworks, and design secure, inclusive platforms to maximize benefits while mitigating risks.
Copyright (c) 2025 Fahad Mahmood, Hina Riaz (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Blockchain in Enhancing Transparency in Financial Transactions
Blockchain technology has emerged as a transformative solution to persistent challenges in financial transparency, offering immutable audit trails, verifiable transactions, and decentralized verification mechanisms. This study employed a mixed-methods experimental framework integrating quantitative transaction simulations with qualitative stakeholder analyses to assess blockchain’s effectiveness in enhancing transparency in financial transactions. Results demonstrated that blockchain-based systems significantly outperformed traditional centralized models by reducing error rates, improving transaction validation efficiency, and preventing security breaches. Transparency index scores revealed consistent improvements, with Proof-of-Stake and hybrid consensus mechanisms offering a balance between scalability and auditability, whereas Proof-of-Work models showed efficiency limitations. Visual analyses confirmed strong correlations between blockchain adoption, transparency, and institutional trust, with measurable gains in accountability across financial institutions. Qualitative findings highlighted that blockchain fosters stakeholder confidence through verifiable records, but also raised concerns regarding privacy, regulatory alignment, and scalability. The study concludes that blockchain enhances transparency not only through technical features but also by enabling institutional trust and regulatory accountability. However, its long-term success depends on the evolution of sustainable consensus mechanisms, privacy-preserving innovations, and supportive governance frameworks. Together, these results establish blockchain as a paradigm-shifting infrastructure capable of aligning financial systems with the demands of transparency, trust, and accountability in a digital economy.
Copyright (c) 2025 Usman Qamar, Sadia Riaz (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Employee Empowerment and Its Link to Innovation in Organizations
Employee empowerment has become a central focus in organizational research as firms seek to sustain competitiveness through continuous innovation. This study employed a mixed-methods experimental design to examine the relationship between empowerment practices and organizational innovation outcomes. Quantitative findings demonstrated a strong positive correlation between empowerment levels and innovation indicators, with empowered employees reporting higher rates of idea generation, engagement, and successful implementation of new initiatives. Regression and structural equation modeling confirmed that empowerment significantly predicts innovation, with leadership support and organizational culture acting as critical moderating variables. Experimental interventions, such as decentralization of decision-making and enhanced autonomy, led to measurable improvements in innovation adoption, particularly in industries emphasizing knowledge-sharing and collaborative practices. Qualitative insights further revealed that empowered employees expressed greater willingness to take risks, challenge existing processes, and contribute to radical innovations, especially when supported by psychological safety and transformational leadership. However, the results also indicated that excessive autonomy without accountability created potential inefficiencies, underscoring the importance of balance between empowerment and organizational control. Moreover, digital empowerment emerged as a critical enabler in hybrid and remote work contexts, facilitating innovation through technology-enabled collaboration. Collectively, these findings suggest that empowerment is not merely a management tool but a strategic lever for innovation, with its effectiveness shaped by leadership, culture, and digital infrastructure. The study concludes that organizations investing in empowerment practices are more likely to cultivate employee creativity, sustain innovation, and achieve long-term competitive advantage.
Copyright (c) 2025 Noman Farooq, Sadia Khan (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Consumer Attitudes Toward Corporate Social Responsibility Initiatives
This paper discusses the consumer attitude towards the corporate social responsibility (CSR) initiatives using a mixed-method experimental design, a quantitative survey and a qualitative interview. CSR campaign based and centered around environment, social, philanthropic campaign or control as well as in-depth interview were used to treat one thousand two hundred respondents of which 25 participants were in-depth interviewed to provide their responses on CSR campaigns. In the quantitative analysis results obtained through regression, ANOVA and mediation models, CSR authenticity has been demonstrated to be a strong enhancer of purchase intention and loyalty with consumer trust acting as a major mediator. The results further reveal important cultural and demographic differences. In Europe, the respondents were more oriented on the environment and the Asian customers were inclined to social and more community-oriented CSR. The generation gaps were high, and Gen Z and Millennials were the most CSR-focusing buyers, and women were more CSR-aware than men were.The qualitative research supported these findings with the inclusion of such themes as authenticity, CSR-firm congruence, and consumer skepticism. Numbers and tables demonstrated that environmental activities generated the most positive consumer responses and incongruent CSR activity generated training. The findings synthesized are inclined to the fact that CSR performance is conditional upon culture congruence, generational expectations and authenticity. The study contributes to the body of literature about CSR because it demonstrates the mediating interest of the trust, and moderating role of cultural context and gives the managerial implications of the development of the localised transparent and authentic CSR strategies. Companies can attain brand equity in the long-term and can build sustainable consumer trust by taking the extra steps of ensuring that the authenticity is put to practice.
Copyright (c) 2024 Ayesha Zafar, Bilal Rehman (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Customer Experience in Driving Brand Advocacy
This study investigates the role of customer experience (CX) in driving brand advocacy, employing a mixed-methods experimental design that integrates quantitative survey analysis with qualitative interviews. A sample of 600 survey respondents and 30 in-depth interviewees across retail, hospitality, and digital service industries was analyzed using structural equation modeling (SEM) and thematic coding. The results demonstrate that customer experience significantly influences advocacy intentions, with emotional and relational dimensions exerting the strongest effects. Satisfaction and trust emerged as dual mediators, strengthening the relationship between CX and advocacy. Reliability and validity checks confirmed the robustness of measurement models, while bootstrapping tests validated mediation and moderation effects. Visual analyses using line, bar, pie, scatter, and hybrid plots highlighted generational and technological differences, with younger, digitally active customers showing higher advocacy potential. Qualitative findings reinforced the importance of personalization, ethical practices, and sustainability as key elements of advocacy-enhancing experiences. The study concludes that customer experience is not merely an antecedent of satisfaction but a transformative driver of customer advocacy. Managerial implications emphasize the need for firms to invest in emotional engagement, technological personalization, and value-driven strategies to cultivate loyal and vocal advocates. This research contributes theoretically by extending service-dominant logic and practically by offering actionable insights for experience management in dynamic and global markets.
Copyright (c) 2024 Sania Rehman, Hamza Ali (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Price Sensitivity and Its Impact on Brand Switching Behavior
This study investigates the impact of price sensitivity on brand switching behavior by employing a mixed-methods experimental design that integrates quantitative surveys and qualitative interviews. A structured survey of 500 consumers across multiple retail categories, complemented by 30 in-depth interviews, provides robust evidence on how price-related factors shape switching intentions. The quantitative findings reveal that price sensitivity exerts a significant positive influence on brand switching, as confirmed by regression and structural equation modeling, while brand loyalty demonstrates a moderating effect that dampens sensitivity-driven defection. Perceived value emerges as a critical mediator, with consumers perceiving low value more likely to abandon established brands even at marginal price differences. The results further indicate that demographic characteristics strongly influence sensitivity, with younger and lower-income consumers displaying higher switching rates than older or more affluent segments.Visual analyses from twelve figures and nine data tables underscore the robustness of these relationships, showing consistent patterns across consumer segments and product categories. Time-series and hybrid plots highlight the role of discounts and promotional strategies in amplifying switching, while scatter and correlation analyses confirm the interactive influence of loyalty and perceived value. The thematic analysis of interviews enriches these findings, revealing psychological underpinnings such as loss aversion, fairness perceptions, and reference pricing that shape switching behavior.Theoretically, this study contributes to the literature by integrating behavioral economics with marketing models to explain the dynamics of price sensitivity. Managerially, the findings suggest that while competitive pricing and promotions can attract high-sensitivity consumers, long-term loyalty requires value-added strategies, emotional branding, and trust-building. In an era of sustainability awareness, firms that effectively balance pricing with authentic ethical attributes can reduce sensitivity and foster durable brand relationships.
Copyright (c) 2024 Nadia Shah, Adeel Khan (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Effect of Packaging Design on Consumer Preferences
This study investigates the effect of packaging design on consumer preferences through a mixed-methods experimental approach that integrates quantitative surveys, neuromarketing techniques, and qualitative interviews. A sample of 500 participants was exposed to packaging prototypes varying in visual design, structural features, and sustainability cues. Quantitative analysis employed conjoint modeling, regression, and structural equation modeling, while eye-tracking and EEG technologies captured subconscious responses. Results revealed that sustainability cues were the strongest predictors of consumer preference, significantly enhancing willingness-to-pay and emotional engagement. Structural features such as resealable and ergonomic designs further improved perceptions of convenience and trust, while visual design elements such as color and typography influenced brand recall and impulse purchase behaviors. Eye-tracking confirmed that eco-labels and logos attracted the most visual attention, whereas EEG data validated heightened neural responses to sustainable packaging. Qualitative findings enriched these insights by highlighting consumer narratives around environmental responsibility and brand authenticity. Demographic analysis showed that younger consumers consistently prioritized eco-friendly designs, whereas older groups favored clarity and readability. The study advances theoretical understanding of packaging design as a multidimensional construct operating across rational, emotional, and subconscious domains. Managerially, the results underscore the importance of balancing sustainability, functionality, and aesthetics to appeal to diverse consumer segments. Limitations include the controlled laboratory context and limited cultural scope, suggesting future research should explore real-world retail settings and cross-market comparisons. Overall, the findings affirm that packaging design is not merely a protective layer but a strategic tool that significantly shapes consumer preferences, brand loyalty, and market competitiveness.
Copyright (c) 2024 Hira Malik, Zain Ahmed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Social Media Influencers in Shaping Buying Behavior
This study examines the role of social media influencers in shaping consumer buying behavior using a mixed-methods experimental design. Drawing on survey data from 600 participants and 30 qualitative interviews, the research integrates quantitative analysis through regression and structural equation modeling with thematic coding of consumer narratives. Results demonstrate that influencer credibility, authenticity, and engagement are the strongest predictors of purchase intention. Micro-influencers, despite smaller follower counts, were shown to generate higher levels of trust and loyalty, while macro-influencers provided broader reach but weaker intimacy with audiences. Transparency in sponsorship disclosure emerged as critical, with explicit disclosures enhancing trust and mitigating skepticism, whereas ambiguous disclosure undermined authenticity. Cultural and demographic differences also moderated outcomes, with younger consumers and collectivist societies showing heightened susceptibility to influencer endorsements compared to older cohorts and individualistic contexts. The findings suggest that influencer-brand congruence, authenticity, and cultural alignment are central to driving effective campaigns. Managerially, the study highlights that influencer marketing can yield higher return on investment than traditional advertising when strategically executed. Nevertheless, challenges such as influencer fraud, content oversaturation, and regulatory scrutiny persist. This research contributes to academic theory by extending understanding of persuasive mechanisms in digital contexts and offers practical implications for businesses seeking to optimize influencer collaborations in competitive markets.
Copyright (c) 2024 Sana Iftikhar, Owais Qureshi (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Consumer Perceptions of Green Marketing Practices
In the current research, the invigilance of consumer attitudes toward green marketing practices is addressed with a mix-method design, which combines quantitative surveys, experimental vignettes, and qualitative interviews. The sample size used (n=600 respondents, n=30 in-depth interviews) was used to evaluate the effects of green trust, eco-label credibility and green skepticism on purchase intentions. The findings of the descriptive statistics, structural equation modeling and experimental analysis indicate that trust and credibility of eco-label positively influence purchase intentions and skepticism acts as a negative mediator between the two. Moreover, the analysis of the clusters provided specific consumer segments between eco-enthusiasts and eco-skeptics with the emphasis on the heterogeneity of sustainable consumption patterns. Experiment findings indicated that advertisements whose eco-labels were credible and whose messages were emotionally framed had a greater impact on intention as compared to ambiguous or unspecified statements. The significance of authenticity, transparency, and correspondence with consumer identity in forming perceptions of green marketing campaigns, was supported by qualitative results. The findings taken together support the presence of attitude-behavior gap, in which positive attitudes towards sustainability do not always translate into purchasing behavior. This study adds to the theory as it has incorporated the Theory of Planned Behavior (TPB) and Value-Belief- Norm (VBN) models to explain green consumerism. In practical matters, the results indicate the need to implement transparent, verifiable, and consumer-focused communication methods by firms. Standardization of eco-labeling structures and consumer education are some of the policies which are being encouraged to enhance trust and reduce skepticism towards greenwashing. In general, the research contributes to the scholarship of consumer psychology in sustainability marketing and offers practical information to scholars, professionals and authorities that are striving to achieve the shift to sustainable consumption.
Copyright (c) 2024 Amina Tariq, Bilal Khan (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Impact of Digital Marketing on Consumer Decision-Making
This study investigates the impact of digital marketing on consumer decision-making, focusing on personalization, social media influence, influencer credibility, and AI-enabled interactivity. Using a mixed-methods experimental design, data were collected from 600 survey respondents, supplemented by interviews, focus groups, and digital analytics. Quantitative analysis using regression and structural equation modeling revealed that personalization and influencer credibility significantly enhance purchase intention and brand loyalty, while qualitative insights highlighted the role of authenticity and trust in shaping consumer choices. Results from nine tables and twelve figures demonstrated that social media platforms such as Instagram and TikTok outperform traditional channels in driving engagement and conversions, and that immersive technologies like augmented reality reduce perceived risk and strengthen purchase confidence. However, consumer skepticism surrounding fake reviews, AI-generated content, and privacy concerns emerged as critical challenges. The study concludes that digital marketing strategies must integrate personalization and technological innovation with transparent practices to sustain long-term trust. These findings contribute to digital marketing theory by integrating technographic and psychographic perspectives into consumer decision-making models and offer practical guidance for firms seeking to enhance consumer engagement in evolving digital environments.
Copyright (c) 2024 Sadia Hussain, Fahad Iqbal (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Cross-Cultural Consumer Behavior: A Comparative Study
This study investigates cross-cultural consumer behavior through a comparative analysis of Western, Asian, and Middle Eastern cultural clusters. Employing a mixed-method design, the research integrates quantitative survey data from 600 respondents with qualitative in-depth interviews of 45 participants. Quantitative analysis using regression and structural equation modeling revealed that collectivist cultures exhibit stronger brand loyalty and symbolic consumption patterns, while individualist cultures prioritize personal satisfaction and variety-seeking. The qualitative findings further highlighted cultural narratives shaping perceptions of global brands, digital adoption, and sustainability. Asian consumers were found to lead in mobile commerce and influencer-driven trust, Western consumers emphasized individuality and direct complaint behavior, while Middle Eastern consumers exhibited hybrid consumption orientations. Results from nine statistical tables and twelve figures confirmed significant cultural variations in purchase intention, loyalty, sustainability attitudes, and post-purchase satisfaction. The discussion connected these findings with global marketing theory, emphasizing the balance between standardization and adaptation. The study concludes that cultural values remain central to consumer behavior despite globalization, and firms must cultivate cultural intelligence to develop competitive, ethically resonant, and adaptive international strategies.
Copyright (c) 2024 Hina Farooq, Ali Raza (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Effect of Celebrity Endorsements on Consumer Purchase Intentions
This study investigates the effect of celebrity endorsements on consumer purchase intentions, adopting a mixed-method research design integrating experimental surveys (n = 500) and qualitative interviews (n = 20). Grounded in the source credibility and meaning transfer models, the research tested the impact of celebrity attributes—trustworthiness, expertise, and attractiveness—on purchase intentions, while examining mediating roles of brand trust and consumer attitude, and moderating roles of age, gender, and cultural context. Quantitative results from regression and structural equation modeling revealed that celebrity endorsements significantly enhance purchase intentions, with trust and attitude acting as key mediators. Qualitative insights further confirmed that congruence between celebrity image and brand identity strengthens consumer attachment. Results also showed that younger consumers and women are more responsive to endorsements, while local celebrities outperform global ones in domestic contexts, though global celebrities carry stronger international appeal. Graphical analyses reinforced these findings, highlighting correlations between attractiveness, expertise, and purchase behavior, as well as the positive impact of repeated exposure. The study concludes that while celebrity endorsements remain powerful tools for enhancing purchase intentions, their success depends on careful strategic alignment and ongoing reputation management. These findings contribute to academic literature on consumer behavior and provide actionable insights for practitioners in designing effective endorsement strategies in both traditional and digital environments.
Copyright (c) 2024 Sania Malik, Omer Shah (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Brand Equity in Driving Consumer Loyalty
This study examines the role of brand equity in driving consumer loyalty using a mixed-methods approach that integrates survey-based quantitative analysis with qualitative interviews. Drawing on responses from 600 consumers across retail, hospitality, and digital service industries, the research evaluates the impact of brand awareness, perceived quality, brand associations, and brand trust on loyalty outcomes. Structural equation modeling confirmed that perceived quality and trust are the most influential predictors of both attitudinal and behavioral loyalty, while awareness and associations contribute significantly when reinforced by credibility and emotional attachment. Thematic analysis of interviews further revealed that consumers increasingly value authenticity, sustainability, and social responsibility as components of equity that enhance long-term loyalty. Industry-level analysis indicated that hospitality brands outperformed retail and digital services in generating loyalty, largely due to experiential engagement. These findings extend traditional equity models by underscoring the centrality of trust and authenticity in loyalty-building and offer practical guidance for managers to strategically leverage brand equity in dynamic markets. The study contributes to both theory and practice by confirming that brand equity functions as a catalyst for consumer loyalty and as a protective mechanism during times of uncertainty.
Copyright (c) 2024 Ayesha Tariq, Bilal Ahmed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
AI-Driven Predictive Analytics for Enhancing Corporate Tax Compliance
This study investigates the role of artificial intelligence (AI)-driven predictive analytics in enhancing corporate tax compliance through a mixed-method experimental framework that integrates quantitative modeling, qualitative validation, and simulation-based analysis. Using a dataset comprising corporate financial statements, tax filings, and audit outcomes, multiple machine learning models—including logistic regression, random forests, gradient boosting, and neural networks—were developed and tested. Results demonstrate that ensemble methods consistently outperformed traditional techniques, achieving accuracy and AUC values above 90% in detecting potential noncompliance. Interpretability was ensured through SHAP analysis, which identified transfer pricing deviations, effective tax rates, and cash flow discrepancies as critical predictors. Monte Carlo simulations further validated the robustness of these models, showing that predictive analytics can reduce compliance costs by up to 30% while simultaneously improving risk detection. Complementary qualitative findings, drawn from case studies and practitioner insights, highlight that explainable AI enhances transparency and supports trust between corporations and regulators. The integration of these methods reveals not only efficiency gains but also the potential for AI to act as a governance mechanism that promotes fairness and accountability in taxation. The study contributes to the literature by bridging predictive accuracy with ethical oversight, demonstrating that AI systems can transform compliance frameworks when aligned with responsible governance practices. Overall, the findings underscore that AI-driven predictive analytics can strengthen regulatory effectiveness, lower corporate costs, and encourage voluntary compliance, while raising important considerations regarding algorithmic fairness, data governance, and cross-jurisdictional adaptability.
Copyright (c) 2023 Imran Razzak, Sadia Khan (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Leveraging Artificial Intelligence for Real-Time Fraud Detection in Financial Audits
This study investigates the role of artificial intelligence (AI) in enabling real-time fraud detection within financial audits. Using a mixed-method experimental design, quantitative models—including logistic regression, random forests, gradient boosting, convolutional neural networks, and recurrent neural networks—were trained and tested on large transactional datasets. Complementary qualitative insights from audit practitioners and regulators contextualized the interpretability and ethical implications of AI adoption. Results across nine tables and twelve figures demonstrate that AI models achieved superior accuracy, precision, recall, and F1-scores compared to traditional audit approaches, with ensemble and deep learning frameworks offering the strongest classification performance. Real-time deployment simulations confirmed that fraud detection could be achieved with minimal latency and high scalability, while explainable AI techniques such as SHAP and LIME ensured model transparency. Discussion of findings emphasizes that AI enhances, rather than replaces, auditor judgment by supporting professional skepticism and reducing the audit expectation gap. The study concludes that AI-driven fraud detection contributes to stronger investor confidence, improved audit quality, and enhanced regulatory compliance, while highlighting ongoing challenges concerning ethics, data governance, and regulatory frameworks. These findings suggest that AI adoption is a critical step in advancing the future of auditing and financial accountability.
Copyright (c) 2023 Usman Qamar, Hira Ahmed (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Sovereign Wealth Funds in Global Investment Portfolios
Based on the mixed methods research design that combines quantitative econometric modelling and qualitative thematic analysis, this paper concentrates on the location of international investment portfolio of SWFs. Using the largest SWF dataset, we report highly significant positive impacts of SWF on portfolio diversification and portfolio stability through allocation in: equities, bonds, real estate, infrastructure and alternative assets. Finally, the econometric results show that there is a positive and statistically significant relationship between SWF investment and portfolio return, in particular after diversification into the alternative asset classes. Secondly, the qualitative analysis highlights the strategic and geopolitical drivers of investment decision-making and there are common themes about governance, transparency and ESG integration as features of global investment practice. The estimates of the SWF's liquidity contribution also suggest the countercyclical role of the SWF during financial crises, during which the SWFs were the liquidity provider and long-run stabilizer of the global markets. Furthermore, the newly defined sustainability theme is re-affirming that the climate finance field is becoming even more pertinent, in the context of UN Sustainability Goals. However, the paper also touches on risks associated with political imperative, domestic centralisation of projects, and geopolitical risk - the risk of compromising longer-term financial sustainability. Overall, the evidence demonstrates that SWFs are not only stabilising financial agents, but transformational institutions, which are knitting together economic policy, global finance governance and sustainability into re-shaping the composition and resilience of global investment portfolios.
Copyright (c) 2023 Eatzaz Ahmad, Hafiz Pasha (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Foreign Direct Investment Trends and Their Effect on Local Stock Markets
This study investigates the trends in foreign direct investment (FDI) and their effect on local stock markets during the period 2020–2023, a time characterized by global volatility, pandemic-induced contractions, and shifting economic dynamics. Using a mixed-method approach that combines panel econometric models, Granger causality, and ARDL analysis with qualitative content evaluation of policy and market reports, the research identifies both the opportunities and risks that FDI presents for host-country stock markets. The findings reveal that sustained FDI inflows positively contribute to market capitalization, trading activity, and investor confidence, particularly in emerging economies where institutional frameworks are developing. Evidence also suggests that sectoral distribution matters, with technology-driven investments producing stronger long-term stability compared to resource-based FDI, which is more prone to external price shocks. However, the study also highlights vulnerabilities: abrupt reversals of foreign capital exacerbate market volatility, while macroeconomic instability—particularly inflation and exchange rate fluctuations—dampens the beneficial spillovers of FDI. Regional divergence is notable, as BRICS economies demonstrate stronger growth responses to FDI than advanced G7 markets, where institutional maturity moderates dependency on foreign inflows. Overall, the study concludes that FDI remains a double-edged driver of financial development: it strengthens stock markets when embedded in stable institutions and long-term policies but introduces fragility in the presence of global shocks and short-term capital flows. The results carry significant policy implications, emphasizing the need for strategies that attract sustainable, sectorally diversified investment while enhancing macroeconomic stability and institutional credibility to maximize long-term benefits.
Copyright (c) 2023 Naveed Hamid, Hina Riaz (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Venture Capital Financing and Its Impact on Entrepreneurial Growth
This paper explores the multidimensionality of the impact of the wealth of venture capital (VC) financing in entrepreneurial development along the lines of a mixed-method experimental research design that integrates the econometric analysis of panel data and qualitative interviews. According to the propensity score matching and regression models and difference-in-differences estimation in the international firm-level data, the results of the study show significantly greater growth in revenues, growth in employment and are more innovative in VC-backed firms compared with non-VC firms. Heterogeneous impacts are also reported in the sectoral and regional studies, indicating that the majority of the VC flows were to technology, healthcare, and green energy, and the rates of growth of post investments were higher in the developed regions as compared to the emerging markets. Qualitative data confirms these findings because the entrepreneurs too mention the significance of strategic direction, access to networks, and governance discipline as part of the topmost rank of non-financial services that the venture capitalists offer. Notably, the study also achieves the challenges amongst them selection bias, varied access to funding by varied demographics and valuation distortions in overheated markets. All these lessons suggest that despite the fact that VC is a key component in entrepreneurship success, there are still systemic inequities and risk factors. Quantitative rigor and qualitative narratives have been triangulated in a study which shows how effectively venture capital can be catalytic, and how inclusive policies are necessary to democratize access to funding, to achieve sustainable and equitable entrepreneurial eco systems.
Copyright (c) 2023 Atif Ansar, Sana Iqbal (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Active vs. Passive Portfolio Management: A Comparative Study
This study conducts a comprehensive comparative analysis of active and passive portfolio management strategies using a mixed-methods approach that integrates quantitative measures such as Jensen’s alpha, Sharpe ratios, tracking error, and information ratios with qualitative insights derived from fund manager reports and investor narratives. The results indicate that passive funds consistently outperform active funds in terms of cost efficiency, risk-adjusted performance, and long-term stability, largely due to lower expense ratios and minimal tracking errors. However, active management retains relevance under specific conditions: in volatile or innovation-driven markets, in emerging economies with higher inefficiencies, and when integrating investor-specific objectives such as ESG considerations. While active strategies often suffer from higher costs and weaker persistence in alpha generation, their adaptability provides value during market turbulence and structural change. Overall, the findings suggest that passive management should serve as the portfolio core, but selective integration of active strategies can enhance resilience and flexibility. The study concludes that active and passive management are not mutually exclusive but should be viewed as complementary within modern investment frameworks.
Copyright (c) 2023 Sohail Ahmed, Maria Iqbal (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
The Role of Derivatives in Portfolio Risk Management Introduction
To address the question of the significance of derivatives in portfolio risk management, the paper discusses the mixed-method experimental approach to the topic using a quantitative model and qualitative lessons. The analysis is made on a multi asset portfolio data set, which compares the impact of futures, options and swaps on risk reduction, growth in performance and downside protection. Quantitative results indicate that adding of derivatives reduces significantly portfolio variance, enhances Value-at-Risk (VaR) and Conditional Value-at-Risk (CVaR) models, and improves Sharpe ratios compared with unhedged portfolios. The hedging (HE) measure defined that the higher the hedge ratios, the higher the risk reduction, and the Monte Carlo simulations further proved the stabilizing nature of derivatives in a stochastic market set-up. Besides these findings, qualitative information collected through portfolio managers emphasized the argument that derivatives may be applied not only with the benefits of hedging but also as a liquidity management and regulatory compliance instrument. The integration of results confirms that derivatives are significant when it comes to mitigating risks, facilitating performance, and capital efficiency particularly during a period of heightened market volatility. Overall, the research paper concludes that derivatives as applied in a rational manner can and should be regarded as essential tools to effective portfolio risk management and no longer as entirely speculative tools.
Copyright (c) 2023 Zahid Iqbal, Ayesha Riaz (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Sustainable Investing: The Role of Green Bonds in Portfolio Performance
This paper explores how green bonds can be used to improve portfolio performance using the mixed-method design, which combines quantitative econometric modeling and qualitative data analysis of the perceptions of investors. The research builds diversified portfolios with data on global green bond indices, traditional bond indices, equity indices, and macroeconomic factors in determining the relationship between risk and returns of sustainable investments. The descriptive statistics and correlation matrices indicate that the green bonds have moderate relations with equities and traditional bonds, which implies that the bonds have high benefits of diversification. The regression analyses support that green bond allocations have a positive and statistically significant effect on the portfolio returns even when macroeconomic shocks like interest rate fluctuations and inflation are considered. Mean-variance-based optimal portfolio optimization shows that the addition of green bonds always shifts the efficient frontier outward, which enhances the overall portfolio efficiency, particularly in times of volatility like the COVID-19 crisis.Risk-adjusted performance indicators, especially, Sharpe Ratios and Conditional Value at Risk (CVaR), reveal that the green-bond portfolio always outperforms traditional counterparts, particularly in the volatile environment. Robustness checks further validate these findings across different sub-periods. The qualitative review also presents increased investor confidence in sustainable fixed-income instruments, but worries about greenwashing and transparency remain. All the results highlight the point that the green bonds offer not only better financial performance but also substantial additions to the environmental goals, which supports the idea that they may serve two purposes: promoting the portfolio resilience agenda and the global sustainability agenda.
Copyright (c) 2023 Fawad Malik, Sara Imtiaz (Author) https://creativecommons.org/licenses/by-nc-nd/4.0
Impact of Inflation Hedging Strategies on Investment Portfolios
This study investigates the impact of inflation hedging strategies on investment portfolios through a mixed-methods approach, combining econometric modeling with qualitative insights from investors and portfolio managers. Using data on equities, bonds, real estate, commodities, and Treasury Inflation-Protected Securities (TIPS) spanning , the analysis employs regression, VAR, and GARCH models to examine the sensitivity of asset returns to inflation, while portfolio optimization frameworks incorporate inflation as a risk-adjusted constraint. The results reveal that commodities—particularly energy—and real estate consistently provide strong hedging benefits, whereas equities and traditional bonds exhibit weaker and regime-dependent inflation sensitivities. TIPS demonstrate reliable inflation protection but are constrained by interest rate risk and tax considerations. The inclusion of qualitative evidence highlights that investors continue to view real assets and infrastructure as stable long-term hedges, while skepticism surrounds cryptocurrencies due to volatility and speculative behavior. Figures further illustrate sector-specific equity dynamics, portfolio volatility under inflation regimes, and optimization frontiers with inflation constraints. Overall, the study concludes that effective inflation hedging requires a diversified and dynamic strategy, combining real assets, TIPS, and selective equities, supported by adaptive modeling and behavioral insights. These findings underscore that resilience against inflation is achieved not through a single instrument but through integrative portfolio construction capable of adapting to evolving macroeconomic conditions.
Copyright (c) 2023 Arslan Khan, Hina Qureshi (Author) https://creativecommons.org/licenses/by-nc-nd/4.0