{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T02:46:24Z","timestamp":1782355584666,"version":"3.54.5"},"reference-count":127,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T00:00:00Z","timestamp":1782259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Behavioral Sciences"],"abstract":"<jats:p>Learning agility has become an essential capability for employees working in technology-driven environments characterized by rapid change and uncertainty. Despite increasing attention on learning agility, limited empirical research has examined how different levels of cognitive abilities contribute to its development, particularly among Generation Z employees. This study investigates the cognitive determinants of learning agility by distinguishing between basic cognitive abilities and high-level cognitive abilities and examining their roles across established and start-up companies. A total of 270 Generation Z employees in Indonesia participated in the study, consisting of 135 employees from established companies and 135 from start-up companies. Cognitive abilities were assessed using objective psychometric instruments, where basic cognitive abilities (reasoning, memory, attention, coordination, and perception) were measured using CogniFit, while high-level cognitive abilities were assessed through the Divergent Association Task (DAT) for creativity, the Watson\u2013Glaser Critical Thinking Appraisal for critical thinking, and the FourSight framework for problem-solving. Learning agility was measured using a multidimensional behavioral scale. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that higher-order cognitive abilities play a more prominent role in shaping learning agility than basic cognitive abilities. Creativity and problem solving consistently demonstrate significant positive relationships with learning agility across organizational contexts, while reasoning, critical thinking, and perception show context-dependent effects across organizational environments. These findings suggest that learning agility is primarily driven by generative and evaluative cognitive processes rather than by basic cognitive efficiency alone. The study contributes to a deeper understanding of the cognitive architecture of learning agility and provides insights for organizations seeking to develop adaptive talent in rapidly evolving technological environments.<\/jats:p>","DOI":"10.3390\/bs16071053","type":"journal-article","created":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T01:03:56Z","timestamp":1782349436000},"page":"1053","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["The Influence of Different Cognitive Skills on Learning Agility Among Gen Z in Established and Start-Up Companies"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7942-5607","authenticated-orcid":false,"given":"Dian Palupi","family":"Restuputri","sequence":"first","affiliation":[{"name":"Department of Industrial Engineering, Bandung Institute of Technology, Bandung 40132, Indonesia"},{"name":"Industrial Engineering, Universitas Muhammadiyah Malang, Malang 65144, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"family":"Yassierli","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, Bandung Institute of Technology, Bandung 40132, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ari","family":"Widyanti","sequence":"additional","affiliation":[{"name":"Department of Industrial Engineering, Bandung Institute of Technology, Bandung 40132, Indonesia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1037\/0096-3445.131.4.567","article-title":"Individual differences in working memory within a nomological network of cognitive and perceptual speed abilities","volume":"131","author":"Ackerman","year":"2002","journal-title":"Journal of Experimental Psychology: General"},{"key":"ref_2","first-page":"1","article-title":"Critical thinking: Components, skills, and strategies","volume":"30","year":"2021","journal-title":"Revista Argentina de Cl\u00ednica Psicol\u00f3gica"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Alkhatib, O. 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