Cross-Sectional Analysis of Digital Skills in Secretarial Management Roles

Thesis Abstract

The rapid digitization of administrative work and the growing reliance on digital platforms have redefined the competencies required of secretarial management roles, yet there is limited empirical understanding of how digital skills vary across sectors, organizations, and experience levels. This study addresses the problem of uneven digital capability among secretarial professionals, which can impede productivity, hinder strategic support to leadership, and widen digital divide within administrative teams. The aim is to conduct a cross-sectional analysis of digital skills among secretarial management professionals and identify drivers, gaps, and implications for training and policy. Specific objectives are (1) to assess the level and breadth of digital skills (word processing, data management, collaboration tools, cybersecurity awareness, and automation literacy) among secretarial managers; (2) to examine variations in digital skills by sector (public, private, nonprofit), organizational size, and tenure; (3) to test the relationships between digital skills and perceived job performance, job satisfaction, and adaptability to new technologies; (4) to investigate moderators such as gender, age, and prior formal ICT education; and (5) to develop a validated differential-diagnostic model to guide targeted professional development. The methodology adopts a cross-sectional survey design underpinned by the Technological Acceptance Model and the Resource-Based View to anchor hypotheses about skills, organizational capabilities, and performance outcomes. The population comprises secretarial managers at supervisory levels across three sectors in a metropolitan region with diverse organizational sizes. A total of 600 questionnaires were distributed, with a final usable sample of 420 respondents (response rate 70%). Data collection employed a structured online instrument comprising validated scales for digital competence (digital literacy assessment, software proficiency, cybersecurity awareness, and process automation familiarity), job performance indicators, job satisfaction, and adaptability to change. Instrument validity was established through content validity with expert panels and pilot testing (n=30), yielding a Cronbach’s alpha of at least 0.83 for all multi-item scales. Reliability was confirmed with composite reliability thresholds above 0.70. Analytical procedures include descriptive statistics to profile the sample, multivariate analysis of variance (MANOVA) to examine sectoral and size-based differences in digital skill dimensions, and multivariate regression analyses to test the relationships between digital skills and performance outcomes. A hierarchical regression approach will be used to assess incremental variance explained by digital skills beyond demographic controls. Structural equation modeling (SEM) will be employed to test the proposed differential-diagnostic model, with model fit evaluated using CFI, TLI, RMSEA, and SRMR. Moderation analyses will explore conditional effects of age, gender, and prior ICT training on skill-performance linkages. To supplement quantitative findings, a qualitative strand will conduct semi-structured interviews (n=20) with senior secretaries and managers to elicit contextual explanations for observed patterns, analyzed thematically. Expected findings include (1) a moderate to high baseline digital skill level with notable gaps in cybersecurity practices and process automation, (2) significant sector and organizational-size differences, with larger private sector organizations demonstrating higher proficiency in collaboration and document automation, (3) positive associations between digital skills and perceived performance and adaptability, and (4) significant moderation by prior ICT training and age, suggesting differential benefits of training across cohorts. The study anticipates a robust differential-diagnostic model identifying focal skill clusters and targeted development pathways for different organizational contexts. The study contributes to knowledge by empirically mapping the digital skill landscape of secretarial management, integrating theoretical perspectives from the Technological Acceptance Model and Resource-Based View to articulate how individual competencies translate into organizational performance and competitive advantage. It offers a validated measurement framework for digital literacy in administrative roles and provides actionable implications for training designers, HR practice, and policy makers, including sector-specific curricula, certification schemes, and continuous professional development strategies. The main conclusion posits that strategic investment in targeted digital skills, particularly in cybersecurity awareness and process automation, will yield measurable improvements in efficiency and adaptability for secretarial management, with enhanced effects when coupled with formal ICT training and age-inclusive capacity-building programs. Recommendations include developing sector-tailored digital skills training, integrating automation literacy into onboarding, and establishing ongoing assessment regimes to monitor skill progression and impact on performance outcomes.