The Role of Artificial Intelligence and Blockchain Technology in Crisis Management, Startup Growth, and Sustainable Future

This study examines the impact of artificial intelligence (AI) and blockchain technology on crisis management, startup growth, and sustainability in the Indian business landscape. Using a quantitative, cross-sectional research design, data was collected from 123 research and development (R&D) employees across various enterprises. The study employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze relationships between key constructs. The results indicate that AI plays a crucial role in enhancing crisis management and business resilience (β = 0.553, p = 0.000), while effective crisis management positively influences long-term sustainability (β = 0.272, p = 0.000). Additionally, blockchain technology is a key driver of startup growth (β = 0.684, p = 0.000), and growing startups significantly contribute to a sustainable future (β = 0.689, p = 0.000). The findings highlight the transformative potential of AI and blockchain in navigating business uncertainties, fostering innovation, and driving sustainable development. The study offers practical implications for business leaders, policymakers, and entrepreneurs in leveraging emerging technologies for long-term resilience and success

Transforming Export Competitiveness: Technological Upgradation and Digitalization in the Indian Heating, Ventilation, and Air Conditioning Industry

This study investigates the impact of technological upgradation and digitalization on the export competitiveness of India’s Heating, Ventilation, and Air Conditioning (HVAC) industry. Drawing on a 23-year panel dataset from 51 low-and-lower-middle-income countries, the research employs econometric analysis using high-tech exports and broadband subscriptions as proxies. The findings reveal that technological upgradation—measured through medium and high-tech exports—has a statistically significant positive impact on export competitiveness. In contrast, digitalization, proxied by broadband subscriptions, shows no significant effect, suggesting that mere infrastructure is insufficient without deeper operational integration. The Indian HVAC sector, though poised for growth amid global demand and sustainability mandates, faces challenges such as limited R&D investment, inadequate digital adoption, and scale inefficiencies. The study proposes a theoretical framework linking technological advancement and digital readiness with competitive export performance, offering insights for policymakers and industry stakeholders. It underscores the need for strategic investments in innovation, sector-specific digital tools, and workforce development. By aligning macroeconomic data with sectoral realities, the research contributes to a nuanced understanding of how emerging economies like India can leverage technological transformation to boost global trade competitiveness

The Moderating Role of Emotional Intelligence in the Relationship Between Employee Resilience, Perceived Organizational Support, and Work Engagement: A Multi-Sector Study in Saudi Arabia

Employee engagement plays a crucial role in organizational success, influencing productivity, retention, and overall workplace performance. This study examines the impact of employee resilience and perceived organizational support (POS) on work engagement, with emotional intelligence (EI) as a moderating factor, across multiple sectors in Saudi Arabia. Grounded in the Job Demands-Resources (JD-R) model, the study hypothesizes that resilience and POS positively influence engagement, while EI moderates these relationships by enhancing employees’ ability to leverage resilience and support effectively. A quantitative research approach was employed, using a structured survey distributed to 450 full-time employees across industries such as healthcare, education, finance, manufacturing, and IT. Data were analyzed through structural equation modeling (SEM) to assess the relationships among the variables. The findings confirm that employee resilience and POS significantly enhance work engagement, supporting the direct effects. Additionally, EI moderates these relationships, indicating that employees with higher emotional intelligence are better equipped to utilize resilience and organizational support to sustain engagement. These findings contribute to Saudi Vision 2030, emphasizing workforce development and employee well-being. The study provides practical insights for HR professionals on fostering engagement through resilience training, supportive workplace policies, and emotional intelligence development programs

Business Model Innovation in the Trading Card Grading Industry: Cross-National Insights from Pokémon Trading Card Game and Non-fungible Tokens

This study examines how firms in the Pokémon Trading Card Game (PTCG) grading industry adapt their business models in response to digital disruption. We employ a qualitative multiple-case design, investigating three leading grading companies – PSA (United States), CCIC (China), and SQC (Thailand) – through 30 in-depth interviews and supplemental document analysis. The findings reveal divergent strategies shaped by both dynamic capabilities and institutional contexts. PSA leverages scale and AI technology to enhance efficiency, CCIC focuses on legitimacy and incremental improvements under regulatory constraints, and SQC pursues exploratory digital initiatives (e.g., NFT-linked trials) to co- create value with its community. These patterns highlight the ambidexterity required for business model innovation in a digitizing niche service sector. The study contributes to business model innovation and digital transformation literature by demonstrating how national institutions and customer engagement influence innovation paths. Practical implications include lessons for balancing core business sustainability with transformative innovation in different regulatory environments

Factors Influencing Consumer Purchase Behavior of Saudi Dates

This study examines the factors influencing consumer behavior toward Saudi dates, focusing on the roles of hedonic values, utilitarian values, purchase intention, and actual purchase behavior. A cross-sectional study design was employed, with data collected through an online survey from 271 consumers who include dates as part of their dietary plan. The questionnaire, translated into Arabic, was pilot-tested with 35 participants to ensure the validity and reliability of the measurement scales. Data analysis was conducted using structural equation modeling to explore the relationships between the constructs. The findings reveal that both hedonic values and utilitarian values significantly influence purchase intention, which in turn strongly predicts actual purchase behavior. The study demonstrates that consumers who derive pleasure and practical benefits from Saudi dates are more likely to intend to purchase them, and these intentions strongly translate into actual purchasing behavior. Additionally, the mediating role of purchase intention highlights its importance in linking hedonic and utilitarian values to actual behavior. By addressing both emotional and practical aspects of consumer behavior, businesses can create compelling marketing strategies that enhance purchase intentions and drive actual sales

Strengthening Artificial Intelligence Governance through Ethical Handling of Sensitive Data: An Applied Study on Text Classification and Differential Privacy

This research develops a comprehensive hybrid framework to enhance Artificial Intelligence governance by ethically managing sensitive textual data through advanced classification techniques. Focusing on natural language processing (NLP) applications, the study integrates rule-based systems, logistic regression, and transformer-based models, notably BERT, to address the challenges of identifying and handling sensitive information within complex and ambiguous linguistic contexts. Experimental results demonstrate that the hybrid model attains an overall classification accuracy of 91%, with precision and recall scores of 89% and 94%, respectively, achieving an F1-score of 92%. These metrics reflect the model’s robustness in real-world scenarios where explicit textual indicators are often lacking. Individually, the rule-based approach excels in precision (98.6%) for clearly identifiable sensitive content, logistic regression ensures perfect recall (100%), capturing all sensitive instances albeit with increased false positives, and the BERT model achieves perfect precision, effectively minimizing false alarms. The hybrid approach synergizes these strengths, resulting in a balanced and reliable classification system. The study further explores the integration of differential privacy via a differentially private logistic regression model using the diffprivlib library, assessing privacy-utility trade-offs at varying privacy budgets (ε = 3, 5, 6). Results reveal that stronger privacy guarantees (lower ε) reduce classification accuracy (78% at ε=3), while looser privacy constraints (ε=6) approach non-private model performance (97% accuracy). These findings underscore the potential of combining hybrid NLP models with differential privacy to deliver scalable, trustworthy, and privacy-preserving AI systems. The proposed framework holds significant relevance for sensitive domains such as healthcare, public administration, and corporate governance, where balancing data privacy and AI performance is critical. Future research should extend these findings by exploring additional privacy configurations and validating the approach against diverse real-world datasets to optimize the equilibrium between privacy protection and analytical effectiveness

Human Capital Perception in Hybrid Work Environments: A Qualitative Exploration of Artificial Intelligence Integration

Hybrid work environments that blend human labor with artificial intelligence (AI) systems reconceptualize assumptions about identity, agency, and value creation within the firm. Grounded in the philosophical postulate that organizational reality is a social construct, this study analyses how human capital interprets AI integration in companies located in the Sierra de Zongolica, Veracruz. A phenomenological design was employed; twenty-five semi structured interviews and two focus groups were conducted with service, production, and administrative workers who interact daily with human–AI systems. Thematic coding revealed four interrelated constructs: AI as an operational enabler, perceived occupational well-being, enhanced professional autonomy, and holistic job satisfaction. Participants reported that AI lightens repetitive tasks, shortens cycle times, and broadens decision-making scope, thereby reducing stress and improving work–life balance. Concurrently, concerns arose regarding the loss of human interaction and job stability, particularly among longer-tenured employees. The findings indicate that AI functions as a contingent complement to human expertise; its value depends on transparent algorithms, upskilling programmes differentiated by age cohorts, and change management sensitive to the cultural context. The study concludes that corporate strategies and public policies must align technological efficiency with ethical governance so that digital transformation simultaneously fosters productivity and human development

Enhancing Market Reach and Profitability in the Indian Aquaculture Industry

The Indian aquaculture industry, a global leader, faces persistent challenges in marketing, pricing, and supply chain management that limit profitability and market expansion. This study investigates how marketing channels, pricing strategies, and supply chain practices influence commercial success, focusing on West Godavari (Andhra Pradesh), Hooghly (West Bengal), and Kollam (Kerala). Semi-structured interviews with 45 stakeholders, including farmers, marketers, and supply chain managers—reveal that using online platforms and targeting export markets significantly enhances reach and profitability. Value-based pricing improves margins by aligning prices with product quality and customer perception. Efficient supply chain management, particularly through blockchain and automation, is vital for maintaining product integrity and meeting market demands. However, high implementation costs, lack of technical expertise, and resistance to change hinder adoption, especially among smaller operators. The study concludes that sustainable growth requires integrating diversified marketing strategies, value-driven pricing, and tech-enabled logistics. Key recommendations include investing in digital tools, embracing innovation, and fostering stakeholder collaboration to address operational barriers and strengthen the industry’s economic impact

Strengthening ASEAN-Guangxi Trade Relations: Enhancing Regional Integration and Industrial Collaboration

A complex array of global disruptions—including the COVID-19 pandemic, the US-China trade war, the Russia-Ukraine conflict, retaliatory tariffs, economic stagflation, supply chain breakdowns, and the rise of artificial intelligence technologies—has significantly challenged the foundational structure of regional economic development. This study investigates the key barriers hindering ASEAN–Guangxi trade from achieving sustainable and accelerated economic growth. Trade data from 2019 to 2024 were analyzed, and empirical data were collected through structured questionnaires administered to 200 business practitioners and policymakers across ASEAN member states and Guangxi. The data were processed and validated using the Statistical Package for the Social Sciences (SPSS). The results indicate that enhanced regional integration and the presence of positive spillover effects are pivotal in promoting sustainable trade relations between ASEAN and Guangxi. These findings offer actionable insights for companies operating in the region and serve as a valuable reference for policymakers and future researchers seeking to strengthen regional economic cooperation. This study contributes to the literature by identifying integration and spillovers as critical drivers of resilient regional trade amid contemporary global uncertainties

Examining Determinants of Real Estate Appraisal Accuracy in Property Business

This study investigates the factors influencing real estate appraisal accuracy, focusing on market dynamics, technological integration, appraiser expertise, and the regulatory framework. The research aims to explore how these factors impact the accuracy of property valuations performed by real estate appraisers in Saudi Arabia. A cross-sectional survey was conducted with 161 licensed real estate appraisers, using a convenience sampling method. Data was collected through a structured questionnaire, and the responses were analyzed using structural equation modeling (SEM). The study found that market dynamics, technological integration, appraiser expertise, and regulatory frameworks significantly influence real estate appraisal accuracy. The findings highlight the importance of these factors in improving the reliability of property valuations, providing valuable insights for real estate professionals, regulators, and policymakers. The findings suggest that real estate appraisers should stay informed about market trends, enhance their technological skills, and continuously develop their expertise to improve appraisal accuracy. Regulatory bodies should strengthen guidelines and standards to ensure consistency in the appraisal process. Policymakers can use these insights to develop strategies that promote trust and stability in the real estate market