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Journal articles on the topic 'Driven Strategies'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Hasan, Rakibul, Syeda Farjana Farabi, Md Kamruzzaman, Md Khokan BHUYAN, Sadia Islam Nilima, and Atia Shahana. "AI-Driven Strategies for Reducing Deforestation." American Journal of Engineering and Technology 6, no. 6 (2024): 6–20. http://dx.doi.org/10.37547/tajet/volume06issue06-02.

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Recent advancements in data science, coupled with the revolution in digital and satellite technology, have catalyzed the potential for artificial intelligence (AI) applications in forestry and wildlife sectors. Recognizing the critical importance of addressing land degradation and promoting regeneration for climate regulation, ecosystem services, and population well-being, there is a pressing need for effective land use planning and interventions. Traditional regression approaches often fail to capture underlying drivers' complexity and nonlinearity. In response, this research investigates the

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2

Keiser, Thomas C., and Douglas A. Smith. "Customer‐driven Strategies:." Managing Service Quality: An International Journal 4, no. 2 (1994): 5–9. http://dx.doi.org/10.1108/09604529410796134.

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3

Kaye, Michael, and Marilyn Dyason. "Customer value-driven strategies." Total Quality Management 10, no. 4-5 (1999): 594–601. http://dx.doi.org/10.1080/0954412997578.

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4

Cravens, David W., Nigel F. Piercy, and Ashley Prentice. "Developing market‐driven product strategies." Journal of Product & Brand Management 9, no. 6 (2000): 369–88. http://dx.doi.org/10.1108/10610420010356975.

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5

Durán, Francisco, Manuel Roldán, and Antonio Vallecillo. "Invariant-Driven Strategies for Maude." Electronic Notes in Theoretical Computer Science 124, no. 2 (2005): 17–28. http://dx.doi.org/10.1016/j.entcs.2004.11.018.

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6

Kruger, Corinne, and Nigel Cross. "Solution driven versus problem driven design: strategies and outcomes." Design Studies 27, no. 5 (2006): 527–48. http://dx.doi.org/10.1016/j.destud.2006.01.001.

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7

Srivastava Manish Singh, Sarthak. "Implementing AI - Driven Strategies in DevSecOps for Enhanced Cloud Security." International Journal of Science and Research (IJSR) 13, no. 2 (2024): 1281–85. http://dx.doi.org/10.21275/sr24216023228.

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8

Famoti, Oluwakemi, Chikezie Paul-Mikki Ewim, Okiomah Eloho, et al. "Revolutionizing Customer Experience Management through Data-Driven Strategies in Financial Services." International Journal of Advanced Multidisciplinary Research and Studies 5, no. 1 (2025): 948–57. https://doi.org/10.62225/2583049x.2025.5.1.3748.

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In today's digital age, financial services institutions are increasingly turning to data-driven strategies to revolutionize customer experience management (CEM). This Review explores how these strategies are reshaping the industry landscape, focusing on the key trends, challenges, and opportunities. The financial services sector is undergoing a significant transformation driven by technological advancements and changing customer expectations. Data-driven strategies are at the forefront of this transformation, enabling institutions to gain deeper insights into customer behavior, preferences, an

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9

Wang, Caibo. "IoT-Driven Smart City Environmental Design Strategies." Industry Science and Engineering 1, no. 6 (2024): 55–60. https://doi.org/10.62381/i245608.

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In response to accelerating urbanization and rapid technological advancements, smart cities have emerged as a new model for urban development. This paper explores how IoT technology drives environmental design strategies in smart cities. Utilizing literature review and theoretical analysis from a humanities and social sciences perspective, the study systematically examines IoT applications in smart cities and their impact on modern urban design. By reviewing existing smart city development theories, the fundamental concepts and core characteristics are clarified. The paper then discusses key I

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Andreasen, Alan R., Dean C. Coddington, and Keith D. Moore. "Market-Driven Strategies in Health Care." Journal of Marketing 53, no. 2 (1989): 132. http://dx.doi.org/10.2307/1251422.

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11

Choudaha, Rahul. "International Student Enrollment: Evidence-Driven Strategies." International Higher Education, no. 79 (January 1, 2015): 20–21. http://dx.doi.org/10.6017/ihe.2015.79.5845.

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Higher education institutions often underestimate the importance of research in deepening the understanding of international student decision-making processes and developing enrollment strategies. Institutions must recognize the complexity, criticality and volatility of international student decision-making processes, and should invest in developing data-driven international enrollment strategies by proactively assessing needs, behaviors, and profiles of international students during difference stages of application process.

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12

Meinert, T. S., and G. D. Taylor. "Robustness of capacity driven design strategies." International Journal of Production Research 36, no. 8 (1998): 2145–66. http://dx.doi.org/10.1080/002075498192823.

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13

Charles, Christina, Philip Clements, and Daniel E. Furst. "Systemic sclerosis: hypothesis-driven treatment strategies." Lancet 367, no. 9523 (2006): 1683–91. http://dx.doi.org/10.1016/s0140-6736(06)68737-0.

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14

Cravens, David W., and Shannon H. Shipp. "Market-driven strategies for competitive advantage." Business Horizons 34, no. 1 (1991): 53–61. http://dx.doi.org/10.1016/0007-6813(91)90082-7.

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15

Jacobsen, S. C., H. Ko, E. K. Iversen, and C. C. Davis. "Control strategies for tendon-driven manipulators." IEEE Control Systems Magazine 10, no. 2 (1990): 23–28. http://dx.doi.org/10.1109/37.45790.

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16

Won, Bo Yeong, and Weiwei Zhang. "Search Strategies Modulate Memory-Driven Capture." Journal of Vision 22, no. 14 (2022): 3269. http://dx.doi.org/10.1167/jov.22.14.3269.

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17

Burkett, Holly. "Data driven strategies that add value." Performance Improvement 50, no. 5 (2011): 2. http://dx.doi.org/10.1002/pfi.20215.

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18

Chioma Susan Nwaimo, Ayodeji Enoch Adegbola, and Mayokun Daniel Adegbola. "Data-driven strategies for enhancing user engagement in digital platforms." International Journal of Management & Entrepreneurship Research 6, no. 6 (2024): 1854–68. http://dx.doi.org/10.51594/ijmer.v6i6.1170.

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User engagement is a critical metric for success in digital platforms, influencing everything from customer retention to revenue generation. This paper explores data-driven strategies aimed at enhancing user engagement. By leveraging insights from user data, businesses can better understand user behavior, personalize experiences, and optimize interactions. Techniques such as A/B testing, gamification, and social proof can be employed to drive engagement and foster a sense of community. Feedback mechanisms enable continuous improvement, while predictive analytics empower proactive engagement st

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19

qizi, Parpiyeva Mohinur Baxtiyor. "Strategic Forecasting: Competency-Driven Approaches and Technological Tools." International Journal of Pedagogics 5, no. 5 (2025): 325–27. https://doi.org/10.37547/ijp/volume05issue05-84.

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This article explores the modern methodologies and technologies utilized in the effective organization of strategic forecasting practices through the mobilization of professional competencies. Emphasis is placed on the integration of competency-based approaches with digital tools to enhance decision-making and predictive capabilities in dynamic environments. The study analyzes educational and organizational settings where such strategies are implemented, highlighting the role of innovative technologies in fostering analytical thinking, adaptability, and strategic planning. The findings suggest

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20

Sunday, Stephen Adebowale. "Data-Driven Partial Differential Equations for Simulating Epidemic Spread and Containment Strategies." International Journal of Research Publication and Reviews 6, no. 5 (2025): 412–35. https://doi.org/10.55248/gengpi.6.0525.1990.

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21

Gonzalez-Jimenez, David, Jon del-Olmo, Javier Poza, Fernando Garramiola, and Patxi Madina. "Data-Driven Fault Diagnosis for Electric Drives: A Review." Sensors 21, no. 12 (2021): 4024. http://dx.doi.org/10.3390/s21124024.

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The need to manufacture more competitive equipment, together with the emergence of the digital technologies from the so-called Industry 4.0, have changed many paradigms of the industrial sector. Presently, the trend has shifted to massively acquire operational data, which can be processed to extract really valuable information with the help of Machine Learning or Deep Learning techniques. As a result, classical Condition Monitoring methodologies, such as model- and signal-based ones are being overcome by data-driven approaches. Therefore, the current paper provides a review of these data-drive

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22

Worapol, Pinit Somsak Amornsiripong Somboon Sirisunhirun Phut Ploywan Thanansak Borwornnuntakul Chalermchai Kittisaknawin. "Driven Strategies of Community Justice Administration in Thai Society." Multicultural Education 7, no. 8 (2021): 583. https://doi.org/10.5281/zenodo.5270625.

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<em>The research study aims to formulate strategies to drive community justice administration to be effective and appropriate in accordance with the context of Thai society. The objectives are as follow: Firstly,to study the fundamental information and to analyze the environment of community justice administration in Thai society. Secondly, to compile the concept of creating a strategy to drive community justice administration in Thai society. Thirdly, to synthesize the concept of creating a strategy to drive community justice administration in Thai society. The research study used mix methods

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23

Veselica Celić, Rozana. "INNOVATION STRATEGIES AND ORGANIZATIONAL COMPETITIVENESS." DIEM: Dubrovnik International Economic Meeting 10, no. 1 (2025): 109–18. https://doi.org/10.17818/diem/2025/1.10.

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Organizational innovation is a crucial factor for the competitiveness and performance of a company as it enables adaptability, efficiency and long-term market success. The paper examines the role of innovation strategies in shaping the competitive position of firms, focusing on organizational innovation, structural change and strategic flexibility. A qualitative research approach was used, incorporating a systematic literature review and comparative analysis, to examine the impact of leadership, organizational culture, and external market dynamics on innovation-driven competitiveness. The resu

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24

Ranjith, Engu, and Vakkalanka Sairam. "Mitigation strategies to Major challenges Faced in Market Driven Development Scenario." International Journal of Software Engineering & Applications (IJSEA) 3, no. 5 (2020): 63–79. https://doi.org/10.5281/zenodo.3967103.

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This report explains about three major challenges that are faced in market driven requirement engineering with feasible solutions. Also, discusses the circumstances and implications organizations face due to these challenges. Validation and analysis of the solutions is provided with our own experiences from industry and literature study, discussing the merits and demerits.

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25

Akbari, Mohsen, Mehdi Naderi Nasab, and Seyyed Abbas Biniaz. "Entrepreneurial Strategies in Ai-Enhanced Sports Marketing Platforms." Management Strategies and Engineering Sciences 6, no. 2 (2024): 59–67. https://doi.org/10.61838/msesj.6.2.7.

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Artificial intelligence (AI) is transforming sports marketing by enabling more personalized fan experiences, enhancing customer engagement, and optimizing marketing operations. AI technologies such as machine learning, predictive analytics, and chatbots are widely used to drive innovation and create new revenue models in the sports industry. However, despite the benefits, the integration of AI in sports marketing comes with challenges related to technical implementation, economic risks, and ethical concerns. This article aims to review entrepreneurial strategies in AI-enhanced sports marketing

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26

Pollice, Robert, Gabriel dos Passos Gomes, Matteo Aldeghi, et al. "Data-Driven Strategies for Accelerated Materials Design." Accounts of Chemical Research 54, no. 4 (2021): 849–60. http://dx.doi.org/10.1021/acs.accounts.0c00785.

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27

Bowton, Erica, Sarah Collier, Xiaoming Wang, et al. "Phenotype-Driven Plasma Biobanking Strategies and Methods." Journal of Personalized Medicine 5, no. 2 (2015): 140–52. http://dx.doi.org/10.3390/jpm5020140.

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28

Yap, Timothy A., and Jordi Rodon. "Development of Molecularly Driven Targeted Combination Strategies." Oncologist 22, no. 12 (2017): 1421–23. http://dx.doi.org/10.1634/theoncologist.2017-0402.

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29

von Ah, Roman. "Liability-Driven Investment Strategies for Pension Funds." CFA Institute Conference Proceedings Quarterly 25, no. 4 (2008): 39–46. http://dx.doi.org/10.2469/cp.v25.n4.7.

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30

Raza Naqvi, Muhammad, Muhammad Waseem Iqbal, Muhammad Usman Ashraf, et al. "Ontology Driven Testing Strategies for IoT Applications." Computers, Materials & Continua 70, no. 3 (2022): 5855–69. http://dx.doi.org/10.32604/cmc.2022.019188.

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31

Rounds, Jay. "Strategies for the Curiosity-Driven Museum Visitor." Curator: The Museum Journal 47, no. 4 (2004): 389–412. http://dx.doi.org/10.1111/j.2151-6952.2004.tb00135.x.

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32

So, Byunggyu, Yongsu Jang, and Yeonjae Oh. "Certification-Driven Strategies for Enhancing Generative AI." International Journal on Advanced Science, Engineering and Information Technology 14, no. 6 (2024): 1836–41. https://doi.org/10.18517/ijaseit.14.6.20447.

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This paper highlights the critical need for national functional certifications designed explicitly for generative AI ogy, addressing the challenges its rapid advancement poses. The current educational and accreditation systems are struggling to keep pace with the fast-evolving demands of the AI field, resulting in a gap between the skills required by industries and those possessed by the workforce. To close this gap, the paper proposes a structured certification program that aligns educational curricula with industry needs, ensuring that professionals gain both theoretical knowledge and practi

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33

Zahaib Nabeel, Muhammad. "Big Data Analytics-Driven Project Management Strategies." Journal of Science & Technology 5, no. 1 (2024): 117–63. http://dx.doi.org/10.55662/jst.2024.5104.

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The integration of Artificial Intelligence (AI) and Big Data Analytics (BDA) in project management has become a critical enabler of efficiency in managing large-scale, complex projects. This research paper delves into how AI-driven big data analytics can revolutionize traditional project management methodologies by introducing dynamic scheduling, real-time risk prediction, and automated task prioritization strategies. These advanced techniques, which leverage machine learning (ML) models and extensive historical project data, enable a shift from reactive to proactive project management, ensuri

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34

de Lissovoy, Gregory. "Book ReviewMarket-Driven Strategies in Health Care." New England Journal of Medicine 318, no. 7 (1988): 457–58. http://dx.doi.org/10.1056/nejm198802183180720.

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35

Harvey, Neal, and Reid Porter. "User-driven sampling strategies in image exploitation." Information Visualization 15, no. 1 (2014): 64–74. http://dx.doi.org/10.1177/1473871614557659.

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Both visual analytics and interactive machine learning try to leverage the complementary strengths of humans and machines to solve complex data exploitation tasks. These fields overlap most significantly when training is involved: the visualization or machine learning tool improves over time by exploiting observations of the human–computer interaction. This article focuses on one aspect of the human–computer interaction that we call user-driven sampling strategies. Unlike relevance feedback and active learning sampling strategies, where the computer selects which data to label at each iteratio

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36

Li, Yan, Bo Zheng, Ting-Ting Chen, and Xiong-Fei Jiang. "Fluctuation-driven price dynamics and investment strategies." PLOS ONE 12, no. 12 (2017): e0189274. http://dx.doi.org/10.1371/journal.pone.0189274.

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37

Mascarilla, Laurent, and Carl Frélicot. "Reject Strategies Driven Combination of Pattern Classifiers." Pattern Analysis & Applications 5, no. 2 (2002): 234–43. http://dx.doi.org/10.1007/s100440200021.

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38

Steudle, Kirk. "Data-Driven Strategies: Critical for Futureroadway Safety." Traffic Technology International 2023, no. 2 (2023): 63. http://dx.doi.org/10.12968/s1356-9252(23)40656-9.

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39

Huang, Ying, Qian Wen, Ying Xiong, et al. "Nanomaterials driven CRISPR/Cas-based biosensing strategies." Chemical Engineering Journal 474 (October 2023): 145615. http://dx.doi.org/10.1016/j.cej.2023.145615.

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40

Gao, Meng, Zhi Li, and Te Wu. "Evolutionary dynamics of friendship-driven reputation strategies." Chaos, Solitons & Fractals 175 (October 2023): 113987. http://dx.doi.org/10.1016/j.chaos.2023.113987.

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41

Rocha, Gabriel, Jonathas Gomes, Michel Leite, Nicolau B. da Cunha, and Fabricio Costa. "Epigenome-Driven Strategies for Personalized Cancer Immunotherapy." Cancer Management and Research Volume 15 (December 2023): 1351–67. http://dx.doi.org/10.2147/cmar.s272031.

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42

张, 艺涵. "Design of Data-Driven Optimal Travel Strategies." Advances in Applied Mathematics 14, no. 01 (2025): 41–53. https://doi.org/10.12677/aam.2025.141007.

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43

Vinay, M. "Transforming Investment Strategies: AI-Driven Portfolio Optimization." Journal of Research and Review in Digital Marketing and Communications 2, no. 1 (2024): 1–6. https://doi.org/10.5281/zenodo.13933431.

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<em>AI has transformed the approach to delivering financial services significantly with its ease of decision-making and risk control. The paper investigates how AI influences portfolio management by analysing, practical data and distinct models such as support vector machines (SVM), artificial neural networks (ANN), and reinforcement learning (RL). The effectiveness of these models is assessed relative to typical approaches such as Mean-Variance Optimization (MVO) with measures including return on investment (ROI), Sharpe ratio and maximum loss. Findings reveal that AI-inspired models bring la

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44

Yan, Hao-Fang, Yong-Qiang Zhao, Jonathan Cheung-Wai Chan, Seong G. Kong, Nashwa EI-Bendary, and Mohamed Reda. "Hyperspectral and multispectral image fusion: When model-driven meet data-driven strategies." Information Fusion 116 (April 2025): 102803. http://dx.doi.org/10.1016/j.inffus.2024.102803.

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45

Findlay, Izac J., Geoffry N. De Iuliis, Ryan J. Duchatel, et al. "Pharmaco-proteogenomic profiling of pediatric diffuse midline glioma to inform future treatment strategies." Oncogene 41, no. 4 (2021): 461–75. http://dx.doi.org/10.1038/s41388-021-02102-y.

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AbstractDiffuse midline glioma (DMG) is a deadly pediatric and adolescent central nervous system (CNS) tumor localized along the midline structures of the brain atop the spinal cord. With a median overall survival (OS) of just 9–11-months, DMG is characterized by global hypomethylation of histone H3 at lysine 27 (H3K27me3), driven by recurring somatic mutations in H3 genes including, HIST1H3B/C (H3.1K27M) or H3F3A (H3.3K27M), or through overexpression of EZHIP in patients harboring wildtype H3. The recent World Health Organization’s 5th Classification of CNS Tumors now designates DMG as, ‘H3 K

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46

Shavkatovna, Yarieva Zarrina. "ENHANCING LEXICAL PROFICIENCY IN ASPIRING FOREIGN LANGUAGE EDUCATORS THROUGH MOTIVATIONALLY-DRIVEN PEDAGOGICAL STRATEGIES." International Journal of Pedagogics 4, no. 5 (2024): 61–65. http://dx.doi.org/10.37547/ijp/volume04issue05-13.

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This article investigates the implementation of motivationally-driven pedagogical strategies to enhance the lexical proficiency of aspiring foreign language educators. Recognizing the crucial role of vocabulary in language acquisition and teaching, this paper explores innovative approaches to motivate future teachers in developing their lexical competencies. Drawing upon theoretical frameworks and practical insights, this article proposes a comprehensive plan to integrate motivational techniques into pedagogical practices, aiming to empower educators with the lexical expertise necessary for ef

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47

Anand, Royana. "Enhancing Patient Care Pathways through AI-Driven Data Science and Program Management Strategies." International Journal of Media and Networks 2, no. 8 (2024): 01–06. http://dx.doi.org/10.33140/ijmn.02.08.04.

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The integration of Artificial Intelligence (AI) and data science into healthcare program management offers transformative potential for enhancing patient care pathways. By leveraging advanced algorithms and data analytics, healthcare organizations can streamline processes, personalize treatment, and improve outcomes. This research paper explores the application of AIdriven data science in optimizing patient care pathways, examines current strategies in program management, and provides recommendations for implementing these technologies to achieve more effective and efficient patient care.

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48

Javadov, Ilkin. "AI-Driven Cybersecurity Strategies for Educational Platforms: Toward Transparent and Resilient Learning Environments." International Journal of Science and Research (IJSR) 14, no. 5 (2025): 265–68. https://doi.org/10.21275/sr25502120520.

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49

PV, Dr Sanesh, and Aman Kumar. "Harnessing AI-Driven Advertising in Financial Markets: Transforming Investment Strategies and Investor Behaviour." International Journal of Research Publication and Reviews 6, no. 5 (2025): 7931–39. https://doi.org/10.55248/gengpi.6.0525.1805.

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Sowmya R. "Ai-Driven Consumer Behavior Analysis for Optimizing Marketing and Financial Strategies with Machine Learning." Journal of Information Systems Engineering and Management 10, no. 30s (2025): 357–63. https://doi.org/10.52783/jisem.v10i30s.4842.

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In the era of digital transformation, artificial intelligence (AI) and machine learning (ML) have revolutionized the way businesses analyze consumer behavior to refine marketing and financial strategies. AI-driven consumer behavior analysis enables organizations to leverage data-driven insights for personalized marketing, customer segmentation, demand forecasting, and financial decision-making. This paper explores the role of AI and ML in consumer behavior analysis, highlighting their impact on optimizing marketing campaigns and financial strategies. The study reviews existing literature, disc

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