Somnuk Aujirapongpan

This study investigates the influence of digital transformation capability and strategic learning capability on strategic agility as well as competitive and innovative performance of Thai hotels. The sample consisted of 303 4–5-star hotels, selected through simple random sampling from a total population of 2,079 hotels nationwide. Data were collected through questionnaires and analyzed using structural equation modeling. The results revealed that digital transformation capability significantly influences strategic agility (β = 0.249, t = 5.182). Strategic learning capability, which encompasses strategic knowledge generation (β = 0.309, t = 5.759), strategic knowledge interpretation (β = 0.118, t = 2.325), strategic knowledge implementation (β = 0.266, t = 5.561), and strategic knowledge database (β = 0.106, t = 3.395), also has a positive impact on strategic agility. Furthermore, strategic agility positively affects competitive and innovative performance (β = 0.313, t = 4.984). It also serves as a mediator in the relationships between digital transformation capability (β = 0.078, t = 3.834), strategic knowledge generation (β = 0.097, t = 3.671), strategic knowledge interpretation (β = 0.037, t = 2.015), strategic knowledge implementation (β = 0.083, t = 3.704), and strategic knowledge database (β = 0.033, t = 2.651) on competitive and innovative performance. The findings offer hotel operators valuable insights into the importance of developing digital transformation capabilities and strategic learning capabilities to enhance strategic agility, which in turn leads to improved competitive and innovative performance, particularly within a volatile and uncertain business environment.

Acknowledgments
The authors declared that this study complied with ethical guidelines by the Institutional Review Board of the Human Research Ethics Committee of Walailak University (WUEC-23-264-01), Thailand. Dr. Kanokwan Meesook is also a co-first author of this article.

Type of the article: Research Article

Abstract
Digital transformation is central to customs modernization, yet empirical evidence on how regulatory digitization translates into employees’ job proficiency through capability-building remains limited in Peru. This study aims to test the relationships among digital customs regulations, digital transformation, professional competencies, and job proficiency in Peruvian customs agencies, including the mediating role of professional competencies, using PLS-SEM. A quantitative explanatory–predictive, cross-sectional design was applied. Data were collected via a five-point online survey of 104 employees in Peruvian customs agencies (Lima–Callao) in October–November 2025, recruited through WhatsApp-based convenience/snowball sampling. The model was estimated in ADANCO 2.4.1 with a two-stage approach for the higher-order digital transformation construct and bootstrap inference. Digital customs regulations strongly predicted digital transformation (β = 0.872, p < 0.001) and generated a sizeable total indirect effect on job proficiency (β = 0.757, p < 0.001). Digital transformation increased professional competencies (β = 0.853, p < 0.001) and had a direct effect on job proficiency (β = 0.464, p = 0.026), while professional competencies also enhanced job proficiency (β = 0.473, p = 0.023). Mediation was supported for the pathway digital transformation → competencies → job proficiency (β_ind = 0.403, p = 0.034), yielding a total digital transformation effect of β = 0.867. Explanatory power was high (R²: DT = 0.761; competencies = 0.725; job proficiency = 0.814; SRMR = 0.041). The findings indicate that regulatory-driven digitization improves work proficiency primarily when accompanied by systematic competency development, highlighting training and institutional enablers as priorities in customs reform.

Acknowledgments
A la Dirección de Investigación de la Universidad Peruana de Ciencias Aplicadas por el apoyo brindado para la realización de este trabajo de investigación a través del incentivo UPC-EXPOST-2026-1. [We would like to thank the Research Directorate of the Universidad Peruana de Ciencias Aplicadas for their support in carrying out this research through the UPC-EXPOST-2026-1 grant.]