نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه خط و سازه، دانشکده مهندسی راه اهن، دانشگاه علم و صنعت ایران، تهران، ایران
2 گروه مهندسی حمل و نقل ریلی، دانشکده مهندسی راه اهن، دانشگاه علم و صنعت ایران، تهران، ایران
3 گروه ایمنی ریلی، دانشکده مهندسی راه اهن، دانشگاه علم و صنعت ایران، تهران، ایران
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Purpose: This study examines how scientometric methods can be used not only to analyze the structure and evolution of research activities in a specialized academic field but also to facilitate the development of scientific collaboration networks. While scientometrics traditionally focuses on evaluating research performance, identifying thematic trends, and mapping scientific structures, this study expands its scope to strategic networking among researchers. It analyzes the scientific output of the Faculty of Railway Engineering at Iran University of Science and Technology and compares its thematic orientation with international trends in railway engineering. Additionally, the study introduces an innovative software tool—certified at Technology Readiness Level 5 (TRL5) by Iran Tech Hub—designed to automatically extract researcher information from reputable journals and support the creation of targeted scientific networks.
Methodology: A comprehensive scientometric approach was applied using data extracted from the Scopus database for the period 2014–2025. A multi stage analytical framework guided the study. First, bibliometric indicators were used to assess research productivity and citation patterns. Next, co occurrence network analysis identified thematic clusters and mapped the intellectual structure of railway engineering research. Density maps were then employed to detect frequently studied areas and emerging topics. These analyses were conducted for two datasets: (1) articles affiliated with the Faculty of Railway Engineering, and (2) international articles published in leading journals in the field. This dual level comparison enabled an evaluation of the faculty’s research landscape relative to both institutional output and global scientific developments, offering insights into thematic alignment and research gaps. In the final stage, the developed software automatically extracted authors’ names, institutional affiliations, and email addresses from top journals, generating structured datasets that support the formation of scientific collaboration networks and enhance strategic engagement with the global research community.
Findings: The scientometric analysis revealed a significant mismatch between the thematic focus of the Faculty of Railway Engineering and prevailing national and international research trends. While global railway engineering research increasingly emphasizes advanced topics such as intelligent transportation systems, energy efficient operations, predictive maintenance, and data driven optimization, the thematic clusters in the faculty’s output were more traditional, less diverse, and slower to adapt to emerging scientific directions. Density maps further indicated that several internationally influential research areas were either weakly represented or entirely absent in the faculty’s scientific portfolio, highlighting potential gaps in research competitiveness and innovation capacity. The newly developed software successfully extracted structured datasets of leading researchers—including email addresses and institutional affiliations—enabling the creation of targeted scientific networks and facilitating collaboration with high impact scholars. The TRL5 certification confirms that the software has been validated in a real world environment and is ready for broader academic deployment. Overall, the findings suggest that scientometric tools can function not only as evaluative instruments but also as strategic drivers for scientific networking, research empowerment, alignment with global trends, and long term capacity building in specialized academic fields.
Conclusion: This study underscores the important role of scientometrics in guiding research development in specialized fields such as the railway sector. The integration of bibliometric indicators, co occurrence network analysis, and density mapping provides a clear understanding of strengths, weaknesses, and thematic gaps in the faculty’s scientific output. The observed inconsistencies with global trends highlight the need to reassess research priorities to maintain scientific competitiveness and relevance. The introduction of TRL5 certified software represents a significant practical contribution. By automating the extraction of researcher information, the tool supports the creation of scientific collaboration networks, helps address thematic gaps, and strengthens connections with the global research community.
کلیدواژهها [English]
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