The global transition toward a sustainable and low-carbon economy has intensified the demand for green skills as a critical component of future workforce development. As governments, industries, and educational institutions increasingly prioritize sustainability, scholarly interest in green skills has expanded rapidly across multiple disciplines. However, the growing body of literature remains fragmented, limiting a comprehensive understanding of its intellectual structure, thematic development, and future research directions. This study aims to systematically map the evolution of green skills and future workforce research through a bibliometric analysis of publications indexed in the Scopus database between 2015 and 2025. A total of 323 peer-reviewed publications were analyzed using Biblioshiny and VOSviewer to examine publication trends, influential sources, intellectual structures, thematic evolution, and emerging research themes. The findings reveal a substantial increase in research output, particularly after 2020, reflecting the growing strategic importance of green skills in sustainability transitions. Keyword co-occurrence analysis identifies five major research clusters related to sustainability competencies, employability, green jobs, vocational education, and Green Human Resource Management. The thematic analysis highlights the emergence of digitalization as a central research theme, indicating an increasing convergence between green and digital competencies within the context of the twin transition. The study contributes to the literature by providing a comprehensive overview of the field, identifying critical research gaps, and proposing an integrated future research agenda linking human capital development, organizational capability, digital transformation, and sustainable workforce competitiveness.
Rieka Mustika, R. Hurriyati, Juliana Juliana et al.· Human Resources Management a...· 0 citations
Digital maturity is increasingly recognized as an important condition for organizational transformation; however, it is still frequently assessed primarily through technological readiness, digital infrastructure, and process digitalization. This perspective provides limited guidance for higher education institutions, where digital transformation depends substantially on workforce capability, leadership readiness, organizational learning, and adaptive culture. This study examines the evolution and dimensional structure of digital maturity research and repositions digital maturity as a strategic human resource management capability for higher education. A hybrid systematic literature review and bibliometric analysis was conducted using 333 peer-reviewed journal articles indexed in Scopus and published between 2018 and November 2025. The analysis maps publication trends, thematic evolution, geographic and sectoral patterns, and the dimensional structure of 18 digital maturity models. The findings show that digital maturity research has expanded rapidly and evolved from a predominantly technology-centred orientation towards a broader capability-based perspective. Technology and Strategy are the most consistently represented dimensions, while People and Organization/Culture are essential for translating digital investments into institutional capability. Sustainability, Security, and Integration remain comparatively underrepresented. Based on the literature synthesis, the study proposes an HRM-oriented conceptual framework linking digital maturity dimensions with competency development, strategic workforce planning, digital leadership, organizational learning, and participatory change management. The framework is intended as an analytically grounded conceptual guide rather than an empirically validated causal model. The study contributes to HRM scholarship by clarifying how universities can integrate digital maturity assessment with people-centred capability development and institutional transformation.
Herman Herman, Juliana Juliana, Asep Miftahuddin et al.· Human Resources Management a...· 0 citations
The blind box phenomenon has created a complex digital conversation ecosystem on Platform X (formerly Twitter), where collector communities exchange information, unboxing experiences, and social validation. This study maps the digital conversation network structure of blind box collector communities on Platform X and traces product information diffusion patterns within it. Data were collected via the SocialX platform using the keywords “blind box” AND (“collector” OR “collection” OR “unboxing” OR “trading”), yielding 995 tweets from 716 unique accounts (January 15 to June 14, 2026), predominantly in English (77.8%) and Indonesian (11.3%). Five analytical methods were integrated: Social Network Analysis (SNA), Dynamic Network Analysis, Trend Analysis, Sentiment Analysis, and Text Network Analysis. The findings reveal a highly fragmented mention network divided into numerous small isolated clusters with content-resharing accounts (such as @youtube) and niche marketplace accounts (such as @chimpershq) emerging as the two dominant hubs. Dynamic network analysis confirmed that both hubs persisted consistently over time, indicating centralized information diffusion concentrated among a small number of actors. Trend analysis identified 11 conversation spikes concentrated in January to February 2026, followed by a significant decline in March to April, before recovering in June 2026. Sentiment analysis showed that community conversations were dominated by positive sentiment (42.71%), followed by neutral (37.59%) and negative (19.70%). Text network analysis revealed that unboxing, collection, series, and secret were the central concepts organizing community discourse. These findings contribute empirically to understanding how niche collector communities form and disseminate information on social media, while offering practical implications for digital marketing strategies targeting collectible product communities.
N. Herliana, E. Surachman, Asep Miftahuddin· Apollo· 0 citations
This study examined the consumers' decisions on how to purchase eyeshadow products from Twitter/X conversations using Sentiment Analysis and Social Network Analysis (SNA). The research aimed to investigate the sentiment of consumers, interaction, influence of influential people, and communication structures of eyeshadow products in the social media marketing and the social media communication. We employed data collected from Twitter/X through SocialX as a quantitative computational social science approach to the research. The dataset comprised 218 records between January 1, 2026, and April 30, 2026, with eyeshadow, e.g., eye-shadow, eye-shadow review, eye-shadow recommendation, and eye-shadow discussion. We combined sentiment analysis, emotion analysis, text network analysis, trend analysis, and social network analysis to investigate consumers’ interactions and information sharing. We find that Twitter/X discussions regarding eyeshadow products are dominated by suggestions, product reviews, and information sharing. As a result, the sentiment analysis showed that neutral and positive sentiment dominated the discussion and the emotional representation was the most dominant emotion. The Social Network Analysis identified several key actors who are in the network and were involved in connecting discussion clusters and communicating cosmetic information. The findings show that the social media interactions were a major factor in the understanding of consumers’ decision to purchase eyeshadow products. The recommendations, positive perception of the product, and the well-connected digital communication structures of Twitter/X have shown that Twitter/X is a very effective source to exchange product information and to shape cosmetic purchasing in beauty online communities.
Auliya Nur Afifah, Vanessa Gaffar, Asep Miftahuddin· Apollo· 0 citations
Corporate universities have become a recurrent reference point in debates about how organizations build human capital, yet the term carries two largely disconnected meanings: a firm-operated learning-and-development (L&D) institution and a critical shorthand for the corporatized, managerialist transformation of higher education. This ambiguity fragments the evidence base on which human resource management (HRM) and human resource development (HRD) scholars rely. This review asks how scholarly output on corporate universities evolved from 2010 to 2026, what conceptual meanings coexist in the literature, and what themes, theories, and methods characterize each. Following the PRISMA 2020 guidelines, a single Scopus search (June 8, 2026) identified 69 journal articles, of which 59 met the eligibility criteria and were synthesized. Bibliometric mapping in Biblioshiny and VOSviewer complemented the thematic synthesis. The corpus grew at an average annual rate of 9.05%, was highly dispersed across 62 sources with no dominant outlet, and was citationally skewed (mean, 13.3; median, 4 citations). Two strands emerged: Strand A frames the corporate university as an instrument of strategic human capital development (n = 22), whereas Strand B treats it as an object of critique within higher education (n = 37). These two strands rarely cite each other and rest on different theoretical foundations. By naming and mapping this conceptual split, the review clarifies which evidence is usable for HRM/HRD theory building and argues that the L&D strand, though smaller and less cited, is where the field's most actionable contributions are concentrated.
Keywords: corporate learning; corporate academy; learning organization; talent development; bibliometric analysis; PRISMA
F. Sembiring, J. Sojanah, Juliana et al.· Human Resources Management a...· 0 citations
As AI technologies rapidly progress, privacy and surveillance, cybersecurity, and governance have become increasingly pressing concerns that raise questions about how the narratives of risk and AI influence the market's perception of new technologies. As a component of the public discourse, it is becoming more and more a sign of trust or distrust in technology and a source of legitimation in the digital world. This study utilized a Social Network Analysis (SNA) and Text based analytical method to analyze the perception of the market on AI by analyzing the AI risk narratives in the online public discourse. Data were gathered from X (formerly Twitter) using the SocialX platform over the first quarter of 2026 (1st January-31st March 2026) and found to be 2,883 public posts. The analysis combined trend analysis, sentiment analysis, temporal word analysis, text network analysis, BERTopic topic modeling, zero-shot classification, and SNA. The results showed an attitude of caution, with neutral (57.86%) and negative sentiment (35.93%) dominating the AI risk discourse, suggesting that the public isn't entirely positive about AI. Most prevalent data privacy issues were Data Privacy Risk (43.81%), Surveillance and Control Risk (21.19%) and Cybersecurity Risk (11.24%). Text network analysis further identified data, training, and surveillance as central themes within the discourse. This study contributes theoretically by integrating Framing Theory, Perceived Risk Theory, and market legitimacy perspectives to explain AI risk narratives as indicators of market perception. In practical terms, the results offer insights for trust-building in AI, responsible communication, and technology branding strategies.
Kirana Labbaika, V. Gaffar, Asep Miftahuddin· Apollo· 0 citations
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 distribution of consumer sentiment is analyzed, key actors in interaction networks are identified, and the extent to which Twitter-based data can complement the evaluation of fragrance co-branding strategy is explored.
Fida Adzkiyatunnida, V. Gaffar, Asep Miftahuddin· Apollo· 0 citations
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