Sürdürülebilir Kalkınma Amaçları
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- MakaleAçık Erişim2026Scopus SJRQ4Semantic Architecture and Knowledge Evolution of Endoscopic Submucosal Dissection Research: A Computational Bibliometric Analysis
Demir, Huseyin; Akar, Tuncay; Mertoglu, Suleyman; Tekinarslan, Merve
Aim: The overarching intellectual structure, dominant thematic clusters, and longitudinal evolution of the endoscopic submucosal dissection (ESD) literature have yet to be systematically mapped. This study aims to characterize the semantic and thematic architecture of ESD research through computational text analytics and to reveal latent structural patterns and temporal dynamics within this domain. Methods: A corpus of 1,000 peer-reviewed publications was processed through an eight-stage computational pipeline that incorporated word embedding-based semantic analysis, unsupervised clustering, Latent Dirichlet Allocation (LDA) topic modeling, inter-topic network analysis, and temporal trend modeling. The primary outcome was characterization of the semantic architecture of ESD research, whereas secondary outcomes included topic relationships, temporal evolution, and model performance metrics. Results: Semantic analysis revealed two dominant clusters: a technically oriented domain encompassing device innovation and procedural optimization and a clinically oriented domain addressing therapeutic outcomes, organ-specific protocols, and adverse event management. Topic modeling identified nine coherent thematic categories, with limited integration between technical and clinical research trajectories. Temporal analysis revealed a pronounced post-2024 shift toward upper-gastrointestinal applications, particularly esophageal and gastric ESD, with relative stagnation in colorectal investigations. The optimal semantic clustering solution achieved a silhouette score of 0.215, while the nine-topic LDA model demonstrated a coherence score of 0.39. Conclusion: This study provides the first data-driven macro-structural characterization of the ESD literature, revealing a persistent bifurcation between technical innovation and clinical application streams. These findings offer a strategic framework to help clinicians, investigators, and curriculum developers identify priority areas for advancement in therapeutic endoscopy.
- MakaleYalnız künye2025Prioritisation of Human Resource Strategies in the Digital Transformation Process of SMEs
Olubiyi, Timilehin Olasoji; Longe, Olumide Babatope; Susela Devi, K. Suppiah; Sinha, Mudita; Şimşek, Tuğçe; Şimşek, Ahmet Bahadır; Olubiyi, TO; Longe, OB; Devi, KSS; Sinha, M
This chapter focuses on the importance of human resource (HR) management strategies in the digital business strategy for small- and medium-sized enterprises (SMEs). With the increasing influence of digital transformation that alters organisational structures and implements new technologies, SMEs have no other choice but to evolve. However, due to the scarcity of resources, it becomes very important for SMEs to allocate its HR appropriately and effectively. To support decision-making on strategies like employee reskilling, recruitment of digital talent, leadership development, and promoting a digital culture, this chapter presents a multi-criteria decision analysis (MCDA) framework. The prioritisation is crucial because not all the strategies can be executed at once, and SMEs should target the most effective ones in the long run, affordable, and relevant to their digital transformation agenda. This chapter illustrates methods for how SMEs can use the proposed prioritisation framework effectively. The hypothetical case study demonstrates the real challenges faced by SMEs during digital transformation and how MCDA assists leaders in selecting the most beneficial HR strategies. The case highlights the necessity of fitting strategies to organisational challenges to allow the customisation of training and leadership to align with business demands and maximise effectiveness while minimising costs. Upon use, this framework enables SMEs to comprehend and direct their digital transformation path more effectively.
