The Effects of Digital Transformation, IT Innovation, and Sustainability Strategies on Firms’ Performances: An Empirical Study

Sustainability, Год журнала: 2025, Номер 17(3), С. 823 - 823

Опубликована: Янв. 21, 2025

This paper examines the intertwined dynamics among digital transformation, IT innovation, and sustainability their collective influence on firm performance in response to evolving business landscape characterized by digitalization, concerns. The study investigates how these factors collectively impact analyzing a panel dataset of 1510 global companies from 2013–2023. model utilizes multiple linear regression analysis incorporate scores as dependent variable. At same time, are independent variables, alongside firm-level control variables. results reveal that transformation positively influences innovation strategic (BM) development, confirming its direct performance. Additionally, firms with simpler younger structures achieve better outcomes than larger more established ones. However, has limitations, it is based spanning 11 years; extending different longer period could provide insights into nature which inherently dynamic. groundbreaking exploring factors, offering unique perspective through an 11-year focus assessing dynamic models.

Язык: Английский

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Machine learning software for optimizing SME social media marketing campaigns

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(7), С. 1634 - 1647

Опубликована: Июль 25, 2024

This review paper explores the transformative role of machine learning in optimizing social media marketing strategies for small and medium-sized enterprises (SMEs). It begins by highlighting significance SMEs, outlining historical context traditional strategies, examining current trends emerging applications. The delves into technical challenges implementing learning, such as data quality, algorithm complexity, system integration, well ethical concerns surrounding privacy algorithmic bias. SME-specific limitations are also discussed, including budget constraints lack expertise. Future directions focus on technologies like deep reinforcement offering practical recommendations SMEs to leverage these advancements effectively. conclusion emphasizes importance embracing achieve sustainable growth competitive advantage digital marketplace. Keywords: Machine Learning, Social Media Marketing, Data Privacy, Audience Targeting.

Язык: Английский

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Circular economy integration in traditional business models: Strategies and outcomes

Finance & Accounting Research Journal, Год журнала: 2024, Номер 6(6), С. 1105 - 1123

Опубликована: Июнь 25, 2024

This study embarks on a critical examination of the integration circular economy (CE) strategies into traditional business models, pivotal transition in quest for sustainable development. The purpose is to elucidate barriers hindering effective adoption CE principles and propose actionable recommendations overcoming these obstacles. Employing comprehensive methodological framework, synthesizes findings from broad array literature, augmented by empirical data, provide nuanced understanding challenges opportunities inherent implementation. Key reveal that insufficient resources, resistance change, complexity integrating existing structures are major impediments. These dissected uncover underlying causes, such as inadequate funding, stakeholder inertia, logistical material recovery recycling. concludes addressing issues requires multifaceted approach, including development unified conceptual frameworks, increased financial technical support, enhanced engagement. Furthermore, it emphasizes role consumer behavior success initiatives, advocating more research attitudes promotion consumption practices. presented aim guide businesses policymakers fostering an environment conducive CE, thereby accelerating towards resilient economic model. Keywords: Circular Economy, Business Models, Sustainable Development, Resource Efficiency, Consumer Behavior, Implementation Barriers.

Язык: Английский

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Enhancing trade policy education: A review of pedagogical approaches in public administration programs

International Journal of Applied Research in Social Sciences, Год журнала: 2024, Номер 6(6), С. 1253 - 1273

Опубликована: Июнь 24, 2024

This literature review rigorously examines pedagogical approaches in trade policy education within public administration programs, with the goal of enhancing educational strategies for future administrators context global trade. Recognizing vital role economic development, international relations, and governance, explores evolution, current state, challenges education. The scope includes an analysis traditional lectures, case studies, experiential learning, interdisciplinary teaching, technology modernizing practices. Using a qualitative methodology, synthesizes insights from reviews, comparative analyses curricula across various programs. Findings indicate that while lectures provide essential theoretical knowledge, their effectiveness is significantly enhanced by studies learning methods, such as simulations role-playing exercises. These methods foster practical application critical thinking, which are crucial comprehending complex policies. integration technology, including online courses digital simulations, further improves outcomes making more interactive accessible. Interdisciplinary incorporates perspectives economics, law, political science, enriches experience prepares students multifaceted nature policy. concludes balanced approach, combining innovative effective It recommends incorporating active strategies, continuous assessment, professional development educators. Additionally, fostering collaboration leveraging technological advancements curriculum. aim to equip comprehensive knowledge skills necessary navigate complexities trade, thereby contributing informed policymaking. Keywords: Trade Policy Education, Public Administration, Pedagogical Approaches, Experiential Learning, Teaching, Technology Integration.

Язык: Английский

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Real-Time Data Governance and Compliance in Cloud-Native Robotics Systems

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

This study investigates the frameworks and challenges of real-time data governance compliance in cloud-native robotics systems, focusing on integrity, cloud security, regulatory adherence, cybersecurity risks. Using extensive datasets from Amazon AWS Open Data Registry, EU GDPR Enforcement Tracker, Kaggle's IoT dataset, analysis explores systems' accuracy, governance. were extracted through a standardized process: performance metrics, including latency error rates, gathered to assess system efficiency, violation records analyzed Tracker understand trends, volume metrics dataset correlated identify challenges. Together, these sources provide comprehensive insights into how systems can be optimized for realtime operations. The highlights security benefits advantages inherent frameworks, such as monitoring, automated threat detection, encryption, which collectively reduce unauthorized access risks while supporting operational efficiency. Findings indicate high accuracy (0.51% rate) low (mean 48.96 ms) across systems; however, processing time variability (standard deviation 28.61 signals need further optimization time-sensitive environments. regression violations reveals substantial penalty increase €53,789.41 per violation, emphasizing financial non-compliance. Correlation (r = 0.083 failures) suggests that external threats have greater impact than internal underscoring importance adaptive support both integrity systems.

Язык: Английский

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AI and Risk Forecasting

Advances in computational intelligence and robotics book series, Год журнала: 2025, Номер unknown, С. 307 - 334

Опубликована: Апрель 8, 2025

This chapter examines the transformative potential of Artificial Intelligence (AI) in risk forecasting, emphasizing its critical role predicting and mitigating risks across industries domains. By leveraging AI techniques such as machine learning, natural language processing, neural networks, organizations can proactively identify emerging risks, optimize decision-making, enhance resilience. The explores various applications including financial prediction, disaster management, cybersecurity threats, supply chain disruptions. Through real-world case studies, it highlights how assessment methodologies enable to act preemptively volatile uncertain environments. Furthermore, addresses challenges like data privacy, algorithmic bias, ethical implications while proposing actionable solutions future directions for integrating into comprehensive management frameworks.

Язык: Английский

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The evolution of trade and industrial policies: Lessons from Cameroon

International Journal of Advanced Economics, Год журнала: 2024, Номер 6(7), С. 319 - 339

Опубликована: Июль 24, 2024

This study meticulously examines the intricacies of trade and industrial policy implementation, focusing on identifying strategic opportunities for enhancement deriving actionable recommendations. Anchored in a qualitative framework employing thematic analysis, research evaluates relevance, fidelity, effectiveness. Through detailed comparative analysis policies across different nations, highlights successes challenges inherent current practices. The findings reveal that while certain have achieved economic growth, others faltered due to implementation gaps insufficient adaptability emerging socio-economic challenges. concludes robust monitoring evaluation frameworks are crucial success policies. Furthermore, integration advanced analytical techniques is recommended enhance precision reliability assessments. Policymakers urged prioritize flexibility resilience design, ensuring can adapt dynamic conditions. advocates enhanced collaboration between government agencies, private sector entities, academic institutions foster holistic approach development. These insights provide foundation future initiatives aimed at fostering sustainable growth Keywords: Trade Policy, Industrial Policy Implementation, Qualitative Analysis, Stakeholder Engagement, Economic Growth.

Язык: Английский

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Comprehensive analysis of the economic, environmental and social impacts of large-scale renewable energy integration

International Journal of Applied Research in Social Sciences, Год журнала: 2024, Номер 6(8), С. 1706 - 1724

Опубликована: Авг. 21, 2024

This review paper offers a comprehensive analysis of the economic, environmental, and social impacts large-scale renewable energy integration, aiming to illuminate multifaceted benefits challenges inherent in transitioning sustainable systems. By exhaustively reviewing current literature empirical data, examines key economic advantages, including job creation, cost reduction, diversification. These underscore sector's potential foster stability growth. Environmental are highlighted by significant reductions greenhouse gas emissions, enhanced air quality, promotion practices through circular economy. Furthermore, reveals that projects can improve access, bolster community resilience, cohesion, addressing critical issues equitable benefit distribution involvement. Looking future, investigation identifies advancements storage technologies, digitalization systems, development hybrid systems as pivotal overcoming integration optimizing energy. innovations essential for ensuring reliable efficient supply, enhancing grid stability, reducing operational costs. The concludes holistic approach—integrating supportive policies, cutting-edge inclusive practices—is vital maximizing It recommends continued investment research development, implementation effective policy frameworks, active engagement ensure just transition. connecting these recommendations with paper's findings, conclusion provides clear path forward. Overall, this contributes valuable insights broader discourse on offering guidance policymakers, industry stakeholders, researchers committed advancing integration. interconnected elements, underscores transformative achieving global sustainability goals. Keywords: Renewable Energy Integration, Economic Impact, Benefits, Social Cohesion, Storage Technologies, Sustainable Development.

Язык: Английский

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Modernizing the Charitable Sector through Artificial Intelligence: Enhancing Efficiency and Impact

Journal of Ecohumanism, Год журнала: 2024, Номер 3(4), С. 3426 - 3443

Опубликована: Авг. 28, 2024

The proposed research explores the transformative potential of artificial intelligence (AI) in modernizing charitable sector. Initiative aims to address critical gaps program delivery, resource allocation, and impact assessment, ultimately enhancing efficiency effectiveness humanitarian aid. study argues that AI can revolutionize disaster response by predicting natural disasters, improve educational outcomes through personalized learning platforms, enhance public health monitoring forecasting disease outbreaks. Furthermore, optimize food distribution systems, reducing waste ensuring timely delivery. also emphasizes urgent need develop a digital safety framework protect children youth from online risks, exacerbated rapid proliferation technologies. methodology includes comprehensive data collection various sectors, followed development testing models tailored specific needs, such as prediction education. involves stakeholder engagement ensure practical applicability ethical implementation solutions. Expected results include use, improved impact, safer environment for vulnerable populations. project set precedent integration

Язык: Английский

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The role of data science in transforming business operations: Case studies from enterprises

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(8), С. 2026 - 2039

Опубликована: Авг. 31, 2024

Data science has emerged as a pivotal force in transforming business operations across various industries, driving innovation, operational efficiency, and strategic decision-making. This review paper explores the multifaceted role of data business, examining key concepts, historical integration, advantages. It discusses application diverse domains, highlighting techniques such predictive analytics, sentiment analysis, optimization that have revolutionized marketing, supply chain management, finance, customer service. The further analyzes science's tangible intangible benefits, including cost reduction, improved experience, enhanced productivity, which collectively contribute to competitive edge market. reflects on emerging trends like artificial intelligence, machine learning, ethical practices, integration blockchain IoT, are set shape future data-driven operations. offers recommendations for businesses prepare this evolving landscape, emphasizing importance data-centric culture, robust infrastructure, collaboration. concludes by underscoring critical fostering sustained success an increasingly world. Keywords: Science, Business Transformation, Predictive Analytics, Operational Efficiency, Artificial Intelligence, Strategic Decision-Making.

Язык: Английский

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