Defly Compass Trend Analysis Methodology: Quantifying Trend Detection to Improve Foresight in Strategic Decision Making
| dc.contributor.affiliation | Departamento de Comunicación Audiovisual, Documentación e Historia del Arte | |
| dc.contributor.affiliation | Facultad de Administración y Dirección de Empresas | |
| dc.contributor.affiliation | Departamento de Matemática Aplicada | |
| dc.contributor.affiliation | Instituto Universitario de Matemática Pura y Aplicada | |
| dc.contributor.affiliation | Escuela Técnica Superior de Ingeniería de Caminos, Canales y Puertos | |
| dc.contributor.author | López Bordao, Mabel | es_ES |
| dc.contributor.author | Ferrer Sapena, Antonia | |
| dc.contributor.author | Reyes Pérez, Carlos A. | es_ES |
| dc.contributor.author | Sánchez Pérez, Enrique Alfonso | |
| dc.contributor.funder | Generalitat Valenciana | es_ES |
| dc.date.accessioned | 2026-05-28T10:55:50Z | |
| dc.date.available | 2026-05-28T10:55:50Z | |
| dc.date.issued | 2025-07-14 | es_ES |
| dc.description.abstract | [EN] We present a new method for trend analysis that integrates traditional foresight techniques with advanced data processing and artificial intelligence. It addresses the challenge of analyzing large volumes of information while preserving expert insight. The hybrid methodology combines computational analysis with expert validation across four phases: literature review, information systematization, trend identification, and analysis. Tools like Voyant Tools 2.6.18 and NotebookLMare used for semantic and statistical exploration. Among them, we highlight the use of the Defly Compass tool, a natural language processing tool based on semantic projections and developed by our team. The method produces mixed results, including both conceptual conclusions and quantifiable, reproducible outcomes adaptable to diverse contexts. Comparative case studies in agriculture, education, and public health identified key patterns within and across sectors. Cross-domain validation revealed universal trends such as digital infrastructure, data integration, and equity. Designed for accessibility, the method enables small, non-specialized teams to combine computational tools with expert knowledge for strategic decision making in complex environments. | es_ES |
| dc.description.accrualMethod | S | es_ES |
| dc.description.bibliographicCitation | López Bordao, M.; Ferrer Sapena, Antonia; Reyes Pérez, CA.; Sánchez Pérez, Enrique Alfonso (2025). Defly Compass Trend Analysis Methodology: Quantifying Trend Detection to Improve Foresight in Strategic Decision Making. Information. 16(7). https://doi.org/10.3390/info16070605 | es_ES |
| dc.description.issue | 7 | es_ES |
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| dc.description.sponsorship | This research was funded by Generalitat Valenciana (Spain), grant number PROMETEO 2024 CIPROM/2023/32. | es_ES |
| dc.description.volume | 16 | es_ES |
| dc.identifier.doi | 10.3390/info16070605 | es_ES |
| dc.identifier.eissn | 2078-2489 | es_ES |
| dc.identifier.uri | https://riunet.upv.es/handle/10251/235487 | |
| dc.language | Inglés | es_ES |
| dc.publisher | MDPI AG | es_ES |
| dc.relation.ispartof | Information | es_ES |
| dc.relation.pasarela | S\559909 | es_ES |
| dc.relation.projectID | info:eu-repo/grantAgreement/GVA//CIPROM%2F2023%2F32/ | es_ES |
| dc.relation.publisherversion | https://doi.org/10.3390/info16070605 | es_ES |
| dc.rights | Reconocimiento (by) | es_ES |
| dc.rights.accessRights | Abierto | es_ES |
| dc.subject | Trend | es_ES |
| dc.subject | Forecasting | es_ES |
| dc.subject | Futures | es_ES |
| dc.subject | NLP | es_ES |
| dc.subject | Defly Compass | es_ES |
| dc.subject | Semantic projection | es_ES |
| dc.title | Defly Compass Trend Analysis Methodology: Quantifying Trend Detection to Improve Foresight in Strategic Decision Making | es_ES |
| dc.type | Artículo | es_ES |
| dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
| dspace.entity.type | Publication | |
| person.identifier | 211340 | |
| person.identifier | 1735 | |
| person.identifier.orcid | 0000-0001-6432-917X | |
| person.identifier.orcid | 0000-0001-8854-3154 | |
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