The expansion of cloud platforms, artificial intelligence (AI)-driven applications, and data center infrastructure has increased the need for workers and organizations that can operate, interpret, and govern complex digital ecosystems. However, research on human capital readiness for cloud–AI–data center ecosystems remains fragmented across technology adoption, digital skills, education, workforce development, and human resource management (HRM). This study maps the intellectual structure, thematic development, and research gaps of this field through a bibliometric review of 783 Scopus-indexed journal articles published between 2010 and 2025. Biblioshiny/R Bibliometrix and VOSviewer were used to conduct performance analysis and science mapping, including annual publication trends, keyword co-occurrence, thematic mapping, co-citation analysis, bibliographic coupling, and country collaboration analysis. The findings show that publication activity increased after 2019 and accelerated after 2023, indicating growing attention to digital workforce readiness in the AI era. The analyses reveal a divide between technology-oriented studies on AI, Industry 4.0, cloud computing, and digital transformation and human-centered studies on digital skills, literacy, competencies, and workforce readiness. Co-citation and bibliographic coupling results show that the field is shaped by technology adoption, behavioral readiness, strategic capability, future-of-work research, work psychology, and education-based digital competency development. Country collaboration patterns indicate that Asia-Pacific scholarship remains uneven despite the region’s growing role in digital infrastructure expansion. This study contributes by repositioning human capital readiness as a strategic HR capability linking digital talent development, HR analytics, and workforce planning.
Rinaldi Noor, Agus Rahayu, Ratih Hurriyati et al.· Human Resources Management a...· 0 citations
The rapid growth of the global fragrance industry has driven brands to adopt co-branding strategies to strengthen brand equity and expand market reach, yet consumer responses to these collaborations in digital spaces remain fragmented and difficult to predict. This study analyzes the distribution of consumer sentiment, identifies key actors in interaction networks, and explores the extent to which Twitter-based data can complement the evaluation of fragrance co-branding strategy. Using an exploratory social media analytics approach grounded in Digital Public Sphere theory and Social Network Theory, this study integrates Social Network Analysis with six computational modules, wordcloud analysis, sentiment analysis, text network analysis, emotion analysis, trend analysis, and zero-shot classification, applied to 300 public tweets collected via the SocialX platform during 1–12 January 2026 using fragrance and brand collaboration keywords. Results show that public discourse was lexically dominated by neutral sentiment (88%), while zero-shot classification of the same corpus yielded a positive-leaning distribution (82.33%); these are interpreted as two distinct constructs, evaluative polarity versus semantic stance, alongside a Sentiment Index of +0.28 and a dominant happy-emotion classification (92%). Network analysis identified a small number of actors occupying central or bridging positions in information dissemination, and trend analysis detected two major activity peaks on January 1–2, 2026, coinciding with the New Year transition. These findings offer theoretical implications for applying Digital Public Sphere and Social Network Theory jointly to fragrance co-branding discourse, and practical implications for brand managers seeking to monitor how collaboration discourse is expressed and circulates online.
Fida Adzkiyatunnida, V. Gaffar, Asep Miftahuddin· Apollo· 0 citations
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